Download-manuals-gis-gis methodology-manual

Government of India & Government of The Netherlands
DHV CONSULTANTS &
DELFT HYDRAULICS with
HALCROW, TAHAL, CES,
ORG & JPS
GIS – METHODOLOGY MANUAL
March 2001

March 2001 Page i
Table of Contents
1 Introduction 1
1.1 Hydrology Project 1
1.2 GIS in Hydrology 1
1.3 Why GIS 1
1.4 Objective 1
1.5 Scope 2
1.6 Methodology Overview and Schedule 2
1.7 Procurement Process 2
1.8 Scope and Organization of Manual 2
2 Directory of Spatial Data 5
2.1 Selection of Minimum Spatial Datasets 5
2.2 Inventory of Existing Spatial Data Sets and Fresh Generation Requirements 5
2.3 Database Organization 5
3 Land use/cover 12
3.1 Classification System 12
3.2 Input Data 12
3.3 Methodology 12
3.4 Output Products 13
4 Soils 16
4.1 Classification Scheme 16
4.2 Input Data 16
4.3 Methodology 16
5 Geology - Lithology 30
5.2 Input Data 30
5.3 Methodology 30
6 Geology - Structures 35
6.2 Input Data 35
6.3 Methodology 35
7 Geomorphology 37
7.2 Input Data 37
7.3 Methodology 37
8 Administrative Units 47
8.2 Input Data 47
8.3 Methodogy 47
9 Hydrologic Units 48
9.2 Input Data 48
9.3 Methodology 48

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10 Settlements 49
10.2 Input Data 49
10.3 Methodology 49
11 Transport Network 51
11.2 Input Data 51
11.3 Methodology 51
12 Drainage 53
12.2 Input Data 53
12.3 Methodology 53
13 Contours and Spot Heights 55
13.2 Input Data 55
13.3 Methodology 55
Annexure I: Classification and Mapping Accuracy 56
Annexure II: Standard Procedure for Digitization 58
Annexure III: Quality Control (QC)/Quality Assurance (QA) Strategy and Plan 59
Annexure IV: Format for Textual Report accompanying Digital Spatial Dataset 68

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1 Introduction
1.1 Hydrology Project
The Hydrology Project (HP) aims at assisting the Central Government and the participating eight state
water resources agencies in the development of valid, comprehensive, interactive, easily accessed,
and user friendly data bases covering al important aspects of the hydrological and meteorological
cycle; and to provide such data to all legitimate users involved in water resources management. The
participating States of Andhra Pradesh, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharashtra,
Orissa, and Tamil Nadu have improved and expanded the observation network, water quality
laboratories and computing facilities for collection, compilation, validation and archival of point
measurements of hydrometeorological and hydrological parameters.
Subsequent to the Mid Term Review of the project it is now proposed to enhance the component of
Geographic Information System (GIS) in HP.
1.2 GIS in Hydrology
Building GIS capability in Hydrology project covers
a) Hardware and GIS modules in surface and ground water data processing software in all
participating States, and stand-alone GIS systems in Andhra Pradesh, Maharashtra and Orissa
States
b) Generating minimum spatial data sets relevant to SW/GW hydrology
c) Georeferencing point measurements
d) Hydrometeorology/surface water/ground water measurements referenced to SOI map coordinates
and datum
e) Upgrading skill sets through training for managers and specialists
1.3 Why GIS
GIS will be used in:
Customised mapping
Individual layers or combination, specific area, and as per specified map specification (scale,
projection, legend, etc.)
Spatial analysis
Aggregation of point measurements over specified area unit, interpolation and contouring, inputs for
models, and theme overlaying
Querying – user specified
By theme, by spatial feature, by time period, and combination of above
1.4 Objective
To generate GIS data sets on select themes for integration in the Surface and Ground Water Data
Centres in 8 participating States, and in the National Data Centres

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1.5 Scope
a) State Ground Water agency will have responsibility within each state for generating and
distributing spatial data sets to State surface water agency and Central Water Commission and
Central Ground Water Board: State level Technical committee will be constituted to support the
activity
b) Surface water and ground water agencies in each state will integrate data in respective Data
Centres
c) Central Water Commission and Central Ground Water Board will integrate data in the National
Data Centres
d) Data to be generated through outsourcing as per standard methodology before March 2001
e) Spatial data sets will be in 1:50000 scale in 8 states covered by more than 2600 SOI toposheets;
Scale will be 1:250000 at national level
1.6 Methodology Overview and Schedule
The approach to generation of spatial data sets is shown in Fig.1.1 along with the proposed time
schedule.
1.7 Procurement Process
Five different procurement actions are involved in the generation of spatial datasets under HP (Table
1.1). The manual addresses only fresh generation of satellite derived digital thematic data and
digitization of existing thematic maps.
Data Set Procurement Process
Fresh generation of satellite derived thematic digital data Through the State RSA
Procurement of existing paper maps and digital data Direct procurement
Procurement of existing digital restricted topomap data Direct procurement from
SOI after clearance from
MOD
Digitization of existing paper maps (including SOI unrestricted
maps)
Through the State RSA
Digitization of restricted SOI maps Direct procurement from
SOI, after MOD
clearance
Table 1.1: Different procurement processes
1.8 Scope and Organization of Manual
It is proposed to procure services from a large number of vendors through the State Remote Sensing
agencies in the preparation of spatial data sets. The manual provides technical guidelines for
preparation of uniform and consistent spatial datasets by multiple vendors, by standardizing the
methodology and input and output products.
The second chapter provides an overview of spatial data sets: selected themes, input data, output
data, and generation methodology. This chapter also covers the spatial database organization
(including map tiles and TIC mark Ids) and data specifications in regard to scale, map projection,
digitization accuracy, and registration accuracy between layers. The subsequent theme-wise chapters
(3 – 13) cover the classification scheme, input data specifications, methodology flowchart, feature and

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attribute data coding standards, output file naming convention, internal QC and external QA, and
specification for deliverable product.
Annexure I: Classification and mapping accuracy
Annexure II: Standard procedure for digitization.
Annexure III: Quality Control/Quality Assurance Strategy and Plan.
Annexure IV: Format for Textural Report

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Figure 1.1: Approach to Generation of Spartial Data Sets
Select basic themes
Digital data
Inventory existing data and define fresh generation
requirements
Procure existing/suitable data
through direct contract Award of work to State Remote Sensing
Agencies (RSA) to prepare the digitised
sets
Methodology manual
Map data
External
QA
Delivery of products and acceptance
Integration in GIS environment at
Data Centre
Hydrologic analysis by HP agencies

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2 Directory of Spatial Data
2.1 Selection of Minimum Spatial Datasets
The selection of primary themes for minimum GIS data sets will be guided by the relevance and
commonality to both surface and ground water component of HP. Surface water analysis requires a
minimum set of thematic data on land use, soil, topography and drainage, while GW analysis will
additionally require spatial data on geology, geomorphology, structures, lineaments and
hydrogeomorphology. General supporting data cover settlements, transport network and
administrative boundaries. This only constitutes a minimum spatial data set, considering the time and
manpower constraints. For example data on irrigation command areas, canal network and other water
use sectors such as industries though useful will be difficult to generate within the balance period of
HP. It is envisaged that the minimum data set will be augmented by additional spatial data sets in
course of time.
The primary data layers are shown in Figure 2.1. The last six themes are digitized from existing
Survey of India maps ( and other maps such as AISLUS National Watershed Atlas and State survey
department maps) while the other 5 themes are derived from appropriate satellite data. The directory
of spatial data in Table 2.1 lists the themes, input and output data, and generation methodology.
2.2 Inventory of Existing Spatial Data Sets and Fresh Generation
Requirements
The extent of fresh data generation requirements shall be assessed based on the inventory of existing
data sets in map and digital format, generated under national and State programmes (Figure 2.2). The
existing data sets shall be reviewed under a set of standard criteria (level of thematic classification,
mapping and thematic accuracy, age of data, and availability –Table 2.2) for acceptance in HP.
Additional generation of data sets (thematic mapping and digitization, digitization of existing maps and
format conversion of existing digital data sets) shall be defined for each state. The preparation of
these data sets shall be as per the standard methodology proposed by HP, to ensure consistency and
uniformity amongst the participating States.
Inventory of existing data for possible use in HP shall be assisted by technical committees at central
and State level. The High Level Technical Group (HLTG) will approve selection of primary themes and
classification schemes, methodology manual, and integration of GIS data sets into National and State
Data Centres. The State level committee shall have representatives from State Ground Water
department, Surface Water agency, Central Water Commission, CGWB, Survey of India, GSI and
State Remote Sensing Centre. The committee shall support the State GWD in conducting inventory of
existing GIS data sets, defining fresh data generation requirements, external quality audit of data
products, and integration of GIS data sets into the State Data Centre.
2.3 Database Organization
The spatial database for each participating State will be organized with 15 minutes by 15 minutes
geographic area, corresponding to a SOI 1:50000 scale map sheet, as the basic map tile. Each map
tile will be assigned a unique number, The map tiles covering the state will be precisely identified by
superposing the 15 min by 15 min framework on the State map in a suitable scale. Thematic coverage
of any specific hydrologic or administrative unit will be generated by digitally mosaicing the map tiles.
Standard and unique TIC Ids will be created for each cross-section of latitude and longitude at 15
minutes interval. All maps will be digitized by taking TIC points at four corners of each 15-minute tile,
and the appropriate Id will be assigned. Additional registration points (permanent manmade features)

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will be digitized to enable co- registration of scanned maps without lat-long details. The registration
point Id will be the map tile number followed by a serial number.
All the map sheets (of each theme) in each State will be transformed to the polyconic projection using
the central latitude and longitude of projection origin of the State, by using the same *.prj file (text file
containing input and output parameters to be used in map projection).
The list and structure of primary data elements are shown in Table 2.3. The code for each primary
theme coverage as also the data structure of the Look Up Table (LUT) is listed in respective thematic
chapters. Each primary data coverage will be named as for example Landuse54j14 representing the
theme and SOI map sheet number, and all associate files will have this identification as the prefix.

March 2001 Page 7
Figure 2.1: Primary Data Layers
Land Use/Cover
Geomorphology (and
landforms)
Administrative boundary upto
block
Geology - structure
Geology – lithology / rock type
Soil
Hydrologic boundary upto
watershed
Drainage
Transport network
Settlements up to village
Elevation contours and spot
heights

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Figure 2.2: Data Inventory Modality
INVENTORY EXISTING DATA SETS
ASSESS EXISTING DATA SETS
COMPILE FRESH
REQUIREMENTS
LIST SUITABLE EXISTING DATA
SETS
HP DATA QUALITY
STANDARDS

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Primary Data Source of Data Fresh Generation
Process
Output data
1. Land Use/ Cover IRS Satellite
LISS III Sensor1
Visual interpretation
and digitization
Digital file of spatial data
and attribute data upto
Level III categories,
2. Soil IRS Satellite
LISS III Sensor
and digitization
and attribute data of soil
categories upto soil series
association
3. Geology – lithology IRS Satellite
LISS III Sensor
and digitization
lithologic units and local
macroscopic features
4. Geology - structure IRS Satellite
LISS III Sensor
and digitization
and attribute data as per
classification
5. Geomorphology IRS Satellite
LISS III Sensor
and digitization
and attribute data as per
classification
6. Administrative
boundary
SOI and State survey
map
Digitization Digital file of spatial data
block boundary
7. Hydrologic boundary Watershed Atlas of
India of AISLUS; SOI
map in 1:50000 scale
Interpretation and
Digitization
watershed boundary
8. Settlements SOI 1:50000 scale
map
village
9. Drainage SOI 1:50000 scale
map
and attribute data of all
drainage in SOI map
10. Transport network SOI 1:50000 scale
map
and attribute data of all
railroad and upto track road
11. Contours and spot
heights
1:50000 scale SOI
map
and attribute data of all 20
m contours and spot
heights in SOI map
Table 2.1: Spatial Data Directory
1
Preferable for fresh mapping of selected theme

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S. No. Item Specifications
1 Scale 1:50000
2 Projection Polyconic
3 Thematic accuracy
Minimum spatial unit
Classification accuracy
0.01 sq.km
95 percent
4 Mapping accuracy- Planimetric accuracy 25 m
5 Age of thematic map / level of detail
Land use (level III)
Geology (lithologic units/local macroscopic
structures)
Geomorphology (landforms)
Soil (soil series association)
Drainage (as in toposheet)
contour (20 m interval)
Settlements (upto villages)
Transport (upto village /cart roads)
Administrative boundaries (upto block)
Hydrologic boundaries (upto watershed)
5 years
10 years
10 years
10 years
20 years
as in SOI map
5 years (or as in SOI map)
5 years (as in SOI map)
Latest (as per State survey
Dept)
derived from AISLUS
Watershed Atlas & SOI map
6 Digital data specifications
Location reference to include lat-long and
permanent features
Data tile
Coordinate units
Registration accuracy between themes
Planimetric accuracy
Sliver polygon tolerance
Weed tolerance
Coordinate movement tolerance
corresponding to SOI map of
1:50000 scale
metre
12.5 m
12.5m
25 sq. m.
12.5 m
12.5 m
Table 2.2: Specifications for Spatial Data in Hydrology

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Feature Type Feature Class Feature Code Attribute Table
1. Land Use/ Cover Poly LU- Code LUSE. Lut
2. Soil Poly SOIL-Code SOIL.Lut
3. Geology – lithology Poly LITH-CODE LITH.Lut
4. Geology - structure Line STRU-Code STRU.Lut
5. Geomorphology Poly GU-Code GU.Lut
6. Administrative boundary Poly ADMIN-code ADMIN.LUT
7. Hydrologic boundary Poly WS-Code WS.Lut
8. Settlements
Location
Extent
Point
Poly
SettlP-Code
SettlA-Code
SettlP.Lut
SettlA.Lut
9. Drainage
Minor Streams
Major rivers
Line
Poly
DRNL-Code
DRNP-Code
DRNL.Lut
DRNP.Lut
10. Transport network
Road/ Rail Line TRNPT-Code TRNPT.Lut
11. Contours
Spot heights
Line
Point
-
-
-
-
Table 2.3: List and Structure of Primary Data Elements

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3 Land use/cover
3.1 Classification System
The land use / cover map shall be prepared as per the classification scheme in Table 3.1. Any
category unique to a geographic area and not included in the scheme will be labeled as ‘others –
Specific category”.
3.2 Input Data
− IRS LISS III geocoded False Colour Imagery (FCC) in 1:50000 scale of two time periods ( Kharif
and Rabi season)
− SOI map in 1:50000 scale
− Collateral data in the form of maps, area statistics, and reports
3.3 Methodology
The land use/cover categories shall be visually interpreted (based on interpretation key developed for
the area) into line maps; the mapped categories may vary from map sheet to map sheet depending on
ground conditions. The interpretation process shall involve reference to collateral data to enable
incorporation of features (such as forest boundaries from SOI map and from State Forest department
records) and establish consistency with existing maps and statistics (such as existing maps on land
use, wastelands and salinity affected lands and 7 fold land classification statistics of State Revenue
department). Delineation of Kharif and Rabi crop lands and discrimination of level II and III categories
shall require interpretation of two season satellite data. All surface waterbodies (reservoirs, lakes,
and tanks) shall be referenced to SOI map, and updated for recent constructions based on most
recent satellite data. The extent of waterspread shall be as in SOI map, and satellite data for new
constructions. The classified map shall have standard feature codes (Table 3.1).
Field visits shall be organized both for collection of ‘ground truth’ to aid and finalize interpretation, and
to estimate the classification accuracy. The interpretation process shall be continued till the
classification conforms to output data accuracy specifications (Table 2.2).
The overall classification accuracy shall be estimated through ‘Kappa Coefficient’, which is a measure
of agreement between the classified map and ground conditions at a specified number of sample sites
(Annexure I).
The classified map shall be scanned and digitized using an appropriate scanner following standard
procedure (Annexure II). The Arc/Info coverage shall be created and edited to remove digitization
errors, and the topology shall be built. The features shall be labeled and coded as defined in the
LUSE.Lut (Table 3.1 and 3.2). The coverage shall then be transformed into polyconic projection and
coordinate system in meters. The transformation process shall involve geometric rectification through
Ground Control Points (GCPs) identified on the input coverage and corresponding SOI map. The HP
data specification standards in Table 2.2 need to be conformed. The resulting GIS coverage shall be
backed up in CD and labeled with corresponding SOI map sheet number, theme, generating agency,
and generation date.
Internal quality control and external quality audit shall be at different critical stages of mapping and
digitization process (Annexure III).

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3.4 Output Products
Five copies of GIS coverage with appropriate file names and format (Annexure IV) in CD and two B/W
hardcopies of thematic map shall be delivered by the vendor, alongwith a report (Annexure IV) on
input data used, interpretation and digitization process, internal QC statement, and contact address
for clarifications.

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Level I Level II Level III LU-Code
1. Built-up land
1.1(towns and cities)
1.1 Rural settlements -
villages
01-00-00
01-01-00
01-02-00
2. Agricultural land
2.1 Crop land
2.2 Fallow
2.3 Plantations (includes
tea, coffee, rubber,
arecanut and others)
2.4 Aquaculture
2.1.1 Kharif cropped
2.1.2 Rabi cropped
2.1.3 Double cropped
02-00-00
02-01-00
02-01-01
02-01-02
02-01-03
02-02-00
02-03-00
02-04-00
3. Forest
3.1Evergreen/semieverg
reen
3.2 Deciduous
3.3 Scrub forest
3.4 Forest blanks
3.5 Forest plantations
3.6 Mangrove
3.1.1 Dense
3.1.2 Open
3.2.1 Dense
3.2.2 Open
03-00-00
03-01-00
03-01-01
03-01-02
03-02-00
03-02-01
03-02-02
03-03-00
03-04-00
03-05-00
03-06-00
4. Wastelands
4.1 Salt affected
4.2 Waterlogged
4.3 Marshy/swampy land
4.4 Gullied/ravinous land
4.5 Land with scrub
4.6 Land without scrub
4.7 Sandy area
4.8 Barren rocky/ stony
waste
4.9 Others
04-00-00
04-01-00
04-02-00
04-03-00
04-04-00
04-05-00
04-06-00
04-07-00
04-08-00
04-09-00
5. Water
5.1 River/stream
5.2 Reservoir/lake/tank
5.3 Canal
05-00-00
05-01-00
05-02-00
05-03-00
6. Others
6.1 Inland wetlands
6.2 Coastal wetlands
6.3 Grass land/grazing
land
6.4 Salt pans
06-00-00
06-01-00
06-02-00
06-03-00
06-04-00
Table 3.1: Land Use /Cover Classification Scheme/ Code (LUSE.LUT)

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Field Name Field Type Field Width Key
LU- Code I 8 Y
Lev 1 C 30 N
Lev 2 C 30 N
Lev 3 C 30 N
Table 3.2: Data Structure

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4 Soils
4.1 Classification Scheme
The soil categories of each SOI map sheet area shall be delineated and coded with reference to the
Order, sub-order, Great Group, sub-group, family and soil series and/or associations as per Keys to
Soil Taxonomy, Sixth Edition, 1994, USDA Soil Conservation Service. The coding scheme shall
follow NRIS standard developed by the Department of Space1
. The standard classification scheme
and code (SOIL.LUT) is shown for two sample soil units at order level, which can be extended to other
units and upto series level.
4.2 Input Data
− Geocoded IRS LISS III FCC imagery of summer scene with minimum vegetation cover; when
needed Kharif and Rabi season imagery may be used.
− Collateral information such as existing maps on soil, geology, geomorphology and land use, and
climatic data
4.3 Methodology
The interpretation key based on acquired satellite data and in reference to SOI topographic map and
existing geological and geomorphologic map and soil map (in any scale) shall be prepared.
Physiography units shall be delineated, and further stratified into possible soil scapes based on
variations in geology, landform, parent material, elevation, slope, aspect, natural vegetation, etc.
Sample strips shall be selected based on variability in landform, geology and image interpretation
elements. Detailed field investigations (soil profile, minipit and auguring) be conducted in sample
strips. Atleast 20 profiles shall be examined in a SOI toposheet area. The actual number of profiles
depend on the variability of terrain. Mini- pit and auger bore data shall supplement profile
investigations. An objective grid based observations may also be made to avoid bias. Typifying
pedons are selected and describes as per standard procedures. Horizon-wise soil samples are
collected and analyzed for physical and chemical properties for soil classification. Mineralogical class
is established using available information. Meteorological data is used in establishing soil
temperature, moisture regimes and preparation of ombrothermic diagrams. Locale specific
interpretation key is developed between the physiographic unit/ image interpretation and soil
categories based on study of sample strips.
Soil units are delineated by drawing boundaries based on interpretation key and auger bore checking.
The soil classes are randomly verified in the field. The legend is finalized on completion of
classification validation, and appropriate codes (Table 4.1) are assigned.
(Annexure I).
The classified map shall be scanned and digitized using an appropriate scanner (Annexure II). The
Arc/Info coverage shall be created and edited to remove digitization errors, and the topology shall be
1
National (Natural ) Resources Information System (NRIS) – Node Design and Standards, Doc. No.
SAC/RSA/NRIS-SIP/SD-01/97, Space Applications Centre, Ahmedabad, April 1997

March 2001 Page 17
built. The features shall be labeled as per codes/symbols defined in Table 4.1 and 4.2. The coverage
shall then be projected and transformed into polyconic projection and coordinate system in meters.
The transformation process involve geometric rectification through Ground Control Points (GCPs)
identified on the input coverage and corresponding SOI map. The HP data specification standards in
Table 2.2 need to be conformed. The resulting GIS coverage shall be backed up in CD and labeled
with corresponding SOI map sheet number, theme, generating agency, and generation date.
digitization process (Annexure III). Additional quality assurance shall include ensuring delineation of
all physiographic units at the pre-field stage, study of atleast one profile for each prominent soil series,
and post-classification validation over atleast 10 percent of the area using auger bore data and road-
cuts.
4.4 Output Products
for clarifications.

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Order Sub Order Great group Sub group Code
Alfisols Aqualfs Linthaqualfs Typic Plithaquaifs 01-01-01-01
Naatraqualfs Vertic Natraqualfs 01-01-02-01
Alabic Glossic Natraqualfs 01-01-02-02
Glossic Natraqualfs 01-01-02-03
Millic Natraqualfs 01-01-02-04
Typic Natraqualfs 01-01-02-05
Duraqualfs Typic Duraqualfs 01-01-03-01
Fragiaqualfs Aeric Fragiaqualfs 01-01-04-01
Plinthic Fragiaqualfs 01-01-04-02
Umbric Fragiaqualfs 01-01-04-03
Typic Fragiaqualfs 01-01-04-04
Kandiaqualfs Arenic Kandiaqualfs 01-01-05-01
Grossarenic Kandiaqualfs 01-01-05-02
Plinthic Kandiaqualfs 01-01-05-03
Plinthic Kandiaqualfs 01-01-05-04
Aeric Umbric Kandiaqualfs 01-01-05-05
Typic Kandiaqualfs 01-01-05-06
Glossaqualfs Arenic Glossaqualfs 01-01-06-01
Grossarenic Glossaqualfs 01-01-06-02
Aeric Glossaqualfs 01-01-06-03
Mollic Glossaqualfs 01-01-06-04
Typic Glossaqualfs 01-01-06-05
Albaqualfs Aeric Vertic Albaqualfs 01-01-07-01
Chromic Vertic Albaqualfs 01-01-07-02
Vertic Albaqualfs 01-01-07-03
Udollic Albaqualfs 01-01-07-04
Aeric Albaqualfs 01-01-07-05
Aquandic Albaqualfs 01-01-07-06
Mollic Albaqualfs 01-01-07-07
Durinodic Albaqualfs 01-01-07-08
Typic Albaqualfs 01-01-07-09
Umbraqualfs Aquandic Umbraqualfs 01-01-08-01
Arenic Umbraqualfs 01-01-08-02
Grossarenic Umbraqualfs 01-01-08-03
Ferrudalfic Umbraqualfs 01-01-08-04
Typic Umbraqualfs 01-01-08-05
Epiaqualfs Aeric Chromic Vertic Epiaqualfs 01-01-09-01
Aeric Vertic Epiaqualfs 01-01-09-02
Chromic Vertic Epiaqualfs 01-01-09-03
Vertic Epiaqualfs 01-01-09-04
Aquandic Epiaqualfs 01-01-09-05
Arenic Epiaqualfs 01-01-09-06
Grossarenic Epiaqualfs 01-01-09-07
Aeric Umbric Epiaqualfs 01-01-09-08
Udollic Epiaqualfs 01-01-09-09
Aeric Epiaqualfs 01-01-09-10
Mollic Epiaqualfs 01-01-09-11
Umbric Epiaqualfs 01-01-09-12

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Typic Epiaqualfs 01-01-09-13
Endoaqulfs Aquandic Endoaqualfs 01-01-10-01
Arenic Endoaquanlfs 01-01-10-02
Gossarenic Endoaqualfs 01-01-10-03
Udollic Endoaqualfs 01-01-10-04
Aeric Endoaqualfs 01-01-10-05
Molic Endoaqualfs 01-01-10-06
Umbric Endoaqualfs 01-01-10-07
Typic Endoaqualfs 01-01-10-08
Boralfs Paleboralfs Antic Paleboralfs 01-02-01-01
Vitrandic Paleboralfs 01-02-01-02
Aquic Paleboralfs 01-02-01-03
Oxyaquic Paleboralfs 01-02-01-04
Abruptic Paleboralfs 01-02-01-05
Mollic Paleboralfs 01-02-01-06
Typic Paleboralfs 01-02-01-07
Fragiboralfs Andic Fragiboralfs 01-02-02-01
Vitrandic Frgiboralfs 01-02-02-02
Aquic Frgiboralfs 01-02-02-03
Oxyquic Frgiboralfs 01-02-02-04
Typic Fragiboralfs 01-02-02-05
Natriboralfs Typic Natriboralfs 01-02-03-01
Cryoboralfs Lithic Mollic Cryoboralfs 01-02-04-01
Lithic Cryoboralfs 01-02-04-02
Vertic Cryobralfs 01-02-04-03
Aquic Cryoboralfs 01-02-04-04
Oxyaquic Cryoboralfs 01-02-04-05
Psammentic Cryoboralfs 01-02-04-06
Mollic Cryoboralfs 01-02-04-07
Glossic Cryoboralfs 01-02-04-08
Typic Cryoboralfs 01-02-04-09
Eutroboralfs Lithic Eutroboralfs 01-02-05-01
Vertic Eutroboralfs 01-02-05-02
Andic Eutroboralfs 01-02-05-03
Vitrandic Eutroboralfs 01-02-05-04
Aquic Arenic Eutroboralfs 01-02-05-05
Glossaquic Eutroboralfs 01-02-05-06
Aquic Arenic Eutroboralfs 01-02-05-07
Oxyaquic Eutroboralfs 01-02-05-08
Pasmmentic Eutroboralfs 01-02-05-09
Arenic Eutroboralfs 01-02-05-10
Mollic Eutroboralfs 01-02-05-11
Glossic Eutroboralfs 01-02-05-12
Typic Eutroboralfs 01-02-05-13
Glossoboralfs Lithic Glossoboralfs 01-02-06-01
Andic Glossoboralfs 01-02-06-02
Vitrandic Glossoboralfs 01-02-06-03
Aquic Glossoboralfs 01-02-06-04

March 2001 Page 20
Oxyaquic Glossoboralfs 01-02-06-05
Pasammentic Glossoboralfs 01-02-06-06
Eutric Glossoboralfs 01-02-06-07
Typic Glossoboralfs 01-02-06-08
Ustalfs Durustalfs Typic Durustalfs 01-03-01-01
Plinthustalfs Typic Plinthustalfs 01-03-02-01
Natrustalfs Vertic Natrustalfs 01-03-03-01
Grossarenic Natrustalfs 01-03-03-02
Aquic Arenic Natrustalfs 01-03-03-03
Aquic Natrustalfs 01-03-03-04
Arenic Natrustalfs 01-03-03-05
Petrocalcic Natrustalfs 01-03-03-06
Salidic Natrustalfs 01-03-03-07
Mollic Natrustalfs 01-03-03-08
Typic Natrustalfs 01-03-03-09
Kandiustalfs Grossarenic Kandiustalfs 01-03-04-01
Aquic Arenic Kandiustalfs 01-03-04-02
Plinthic Kandiustalfs 01-03-04-03
Aquic Kandiustalfs 01-03-04-04
Arenic Aridic Kandiustalfs 01-03-04-05
Arenic Kandiustalfs 01-03-04-06
Aridic Kandiustalfs 01-03-04-07
Udic Kandiustalfs 01-03-04-08
Rhodic Kandiustalfs 01-03-04-09
Typic Kandiustalfs 01-03-04-10
Kanhapulstalfs Lithic Kanhaplustalfs 01-03-05-01
Aquic Kanhaplustalfs 01-03-05-02
Aridic Kanhaplustalfs 01-03-05-03
Udic Kanhaplustalfs 01-03-05-04
Rhodic Kanhaplustalfs 01-03-05-05
Typic Kanhaplustalfs 01-03-05-06
Paleustalfs Aquertic Paleustalfs 01-03-06-01
Oxaquric Vertic aleustalfs 01-03-06-02
Udertic Pleustalfs 01-03-06-03
Vertif Paleustalfs 01-03-06-04
Psammentic Paleustalfs 01-03-06-05
Grossarenic Paleustalfs 01-03-06-06
Aquic Arenic Paleustalfs 01-03-06-07
Plinthic Paleustalfs 01-03-06-08
Aquic Arenic Paleustalfs 01-03-06-09
Oxyaquic Paleustalfs 01-03-06-10
Petrocalcic Paleustalfs 01-03-06-11
Arenic Aridic Paleustalfs 01-03-06-12
Arenic Paleustalfs 01-03-06-13
Calcidic Paleustalfs 01-03-06-14
Aridic Paleustalfs 01-03-06-15
Kandic Paleustalfs 01-03-06-16
Rhodic Paleustalfs 01-03-06-17

March 2001 Page 21
Ultic Paleustalfs 01-03-06-18
Udic Paleustalfs 01-03-06-19
Typic Paleustalfs 01-03-06-20
Rhodustalfs Lithic Rhodulstalfs 01-03-07-01
Kanhaplic Rhodustalfs 01-03-07-02
Udic Rhodustalfs 01-03-07-03
Typic Rhodustalfs 01-03-07-04
Haplustalfs Lithic Haplustalfs 01-03-08-01
Aquertic Haplustalfs 01-03-08-02
Oxyaquic Vertic Aplustalfs 01-03-08-03
Udertic Haplustalfs 01-03-08-04
Vertic Haplustalfs 01-03-08-05
Aquic Arenic Haplustalfs 01-03-08-06
Aquulitic Haplustalfs 01-03-08-07
Aquic Haplustalfs 01-03-08-08
Oxyaquic Haplustalfs 01-03-08-09
Psammentic Haplustalfs 01-03-08-10
Arenic Aridic Haplustalfs 01-03-08-11
Arenic Haplustalfs 01-03-08-12
Aridic Haplustalfs 01-03-08-13
Kanhaplic Haplustalfs 01-03-08-14
Ultic Haplustalfs 01-03-08-15
Udic Haplustalfs 01-03-08-16
Typic Haplustalfs 01-03-08-17
Xeralfs Durixeralfs Natric Durixeralfs 01-04-01-01
Vertic Durixeralfs 01-04-01-02
Aquic Durixeralfs 01-04-01-03
Abruptic Haplic Durixeralfs 01-04-01-04
Abruptic Durixeralfs 01-04-01-05
Haplic Durixeralfs 01-04-01-06
Typic Durixeralfs 01-04-01-07
Natrixeralfs Vertic Natrixeralfs 01-04-02-01
Aquic Natrixeralfs 01-04-02-02
Typic Natrixeralfs 01-04-02-03
Fragixeralfs Andic Fragixeralfs 01-04-03-01
Vitrandic Fragixeralfs 01-04-03-02
Mollic Fragixeralfs 01-04-03-03
Aquic Fragixeralfs 01-04-03-04
Ochreptic Freagixeralfs 01-04-03-05
Typic Fragixeralfs 01-04-03-06
Plinthoxeralfs Typic Plinthoxeralfs 01-04-04-01
Rhodoxeralfs Lithic Rhodoxeralfs 01-04-05-01
Petrocalcic Rhodoxeralfs 01-04-05-02
Calcic Rhodoxeralfs 01-04-05-03
Ochreptic Rhodoxeralfs 01-04-05-04
Typic Rhodoxeralfs 01-04-05-05
Palexeralfs Vertic Palexeralfs 01-04-06-01
Aquandic Palexeralfs 01-04-06-02

March 2001 Page 22
Andic Palexeralfs 01-04-06-03
Vitrandic Palexeralfs 01-04-06-04
Aquic Palexralfs 01-04-06-05
Petrocalcic Palexeralfs 01-04-06-06
Arenic Palexeralfs 01-04-06-07
Natric Palexeralfs 01-04-06-08
Calcic Palexeralfs 01-04-06-09
Plinthic Palexeralfs 01-04-06-10
Ultic Palexeralfs 01-04-06-11
Haplic Palexeralfs 01-04-06-12
Mollic Palexeralfs 01-04-06-13
Typic Palexeralfs 01-04-06-14
Haploxeralfs Lithic Mollic Haploxeralfs 01-04-07-01
Lithic Ruptic-Xerocherptic
Haploxeralfs
01-04-07-02
Lithic Haploxeralfs 01-04-07-03
Vertic Haploxeralfs 01-04-07-04
Aquandic Haploxeralfs 01-04-07-05
Andic Haploxeralfs 01-04-07-06
Vitrandic Haploxeralfs 01-04-07-07
Aquultic Haploxeralfs 01-04-07-08
Aquic Haploxeralfs 01-04-07-09
Natric Haploxeralfs 01-04-07-10
Psammentic Haploxeralfs 01-04-07-11
Plinthic Haploxeralfs 01-04-07-12
Calcic Haploxeralfs 01-04-07-13
Ultic Haploxeralfs 01-04-07-14
Mollic Haploxeralfs 01-04-07-15
Type Haploxeralfs 01-04-07-16
Udalfs Agrudlfs Typic Agrudalfs 01-05-01-01
Natrudalfs Vertic Natrudalfs 01-05-02-01
Glossic Natrudalfs 01-05-02-02
Mollic Natrudalfs 01-05-02-03
Typic Natrudalfs 01-05-02-04
Ferrudalfs Aquic Ferrudalfs 01-05-03-01
Typic Ferrudalfs 01-05-03-02
Glossudalfs Fragic Glossudalfs 01-05-04-01
Aquandic Glossudalfs 01-05-04-02
Andic Glossudalfs 01-05-04-03
Vitrandic glossudalfs 01-05-04-04
Oxyaquic Glossudalfs 01-05-04-05
Arenic Glossudalfs 01-05-04-06
Haplic Glossudalfs 01-05-04-07
Typic Glossudalfs 01-05-04-08
Fraglossudalfs Aquic Fraglossudalfs 01-05-05-01
Oxyaquic Fraglossudalfs 01-05-05-02
Typic Fraglossudalfs 01-05-05-03
Fragiudalfs Umbreptic Fragiudalfs 01-05-06-01

March 2001 Page 23
Mollic Fragiudalfs 01-05-06-02
Glossaquic Fragiudalfs 01-05-06-03
Aqueptic Fragiudalfs 01-05-06-04
Albaquic Fragiudalfs 01-05-06-05
Aquic Fragiudalfs 01-05-06-06
Oxyaquic Fraguidalfs 01-05-06-07
Glossic Fragiudalfs 01-05-06-08
Ochreptic Fragiudalfs 01-05-06-09
Typic Fragiudalfs 01-05-06-10
Kandiudalfs Plinthaquic Kandiudalfs 01-05-07-01
Aquic Kandiudalfs 01-05-07-02
Oxyaquic Kandiudalfs 01-05-07-03
Arenic Plinthic Kandiudalfs 01-05-07-04
Grossarenic Plinthic Kandiudalfs 01-05-07-05
Arenic Kandiudalfs 01-05-07-06
Grossarenic Kandiudalfs 01-05-07-07
Plinthic Kandiudalfs 01-05-07-08
Rhodic Kandiudalfs 01-05-07-09
Mollic Kandiudalfs 01-05-07-10
Typic Kandiudalfs 01-05-07-11
Kanhapludalfs Lithic Kanhapludalfs 01-05-08-01
Aquic Kanhapludalfs 01-05-08-02
Oxyaquic Kanhapludalfs 01-05-08-03
Rhodic Kanhapludalfs 01-05-08-04
Typic Kanhapludalfs 01-05-08-05
Paleudalfs Vertic Paleudalfs 01-05-09-01
Anthraquic Paleudalfs 01-05-09-02
Plinthquic Paleudalfs 01-05-09-03
Glossaquic Paleudalfs 01-05-09-04
Albaquic Paleudalfs 01-05-09-05
Aquic Paleudalfs 01-05-09-06
Oxyaquic Paleudalfs 01-05-09-07
Arenic Plinthic Paleudalfs 01-05-09-08
Grossarenic Plinthic Paleudalfs 01-05-09-09
Psammentic Paleudalfs 01-05-09-10
Arenic Paleudalfs 01-05-09-11
Grossarenic Paleudalfs 01-05-09-12
Plinthic Paleudalfs 01-05-09-13
Glossic Paleudalfs 01-05-09-14
Rhodic Paleudalfs 01-05-09-15
Mollic Paleudalfs 01-05-09-16
Typic Paleudalfs 01-05-09-17
Rhodudalfs Typic Rhodudlfs 01-05-10-01
Hapludalfs Aquic Lithic Hapludalfs 01-05-11-01
Lithic Hapludalfs 01-05-11-02
Aquertic Chromic Hapludalfs 01-05-11-03
Aquertic Hapludalfs 01-05-11-04
Oxyquic Vertic Hapludalfs 01-05-11-05

March 2001 Page 24
Chromic Vertic Hapludalfs 01-05-11-06
Vertic Hapludalfs 01-05-11-07
Andic Hapludalfs 01-05-11-08
Vitrandic Hapludalfs 01-05-11-09
Psammaquentic Hapludalfs 01-05-11-10
Psammantic Hapludalfs 01-05-11-11
Aquic Arenic Hapludalfs 01-05-11-12
Arenic Hapludalfs 01-05-11-13
Anthraquic Hapludalfs 01-05-11-14
Albaquultic Hapludalfs 01-05-11-15
Albaquic Hapludalfs 01-05-11-16
Glossaquic Hapludalfs 01-05-11-17
Aquultic Hapludalfs 01-05-11-18
Aquollic Hapludalfs 01-05-11-19
Aquic Hapludalfs 01-05-11-20
Oxyaquic Hapludalfs 01-05-11-21
Glossic Hapludalfs 01-05-11-22
Glossoboric Hapludalfs 01-05-11-23
Ultic Hapludalfs 01-05-11-24
Mollic Hapludalfs 01-05-11-25
Typic Hapludalfs 01-05-11-26
Andisols Aquands Cryaquands Lithic Cryaquands 02-01-01-01
Pergelic Cryaauands 02-01-01-02
Histic Cryaquands 02-01-01-03
Thaptic Cryaquands 02-01-01-04
Typic Cryaquands 02-01-01-05
Placaquands Lithic Placaquands 02-01-02-01
Duric Histic Placaquands 02-01-02-02
Duric Placaquands 02-01-02-03
Histic Placaquands 02-01-02-04
Thaptic Placaquands 02-01-02-05
Typic Placaquands 02-01-02-06
Duraquands Histic Duraquands 02-01-03-01
Acraquoxic Duraquands 02-01-03-02
Thaptic Duraquands 02-01-03-03
Typic Duraquands 02-01-03-04
Vitraquands Lithic Vitraquands 02-01-04-01
Duric Vitraquands 02-01-04-02
Histic Vitraquands 02-01-04-03
Thaptic Vitraquands 02-01-04-04
Melanaquands Lithic Melanaquands 02-01-05-01
Acraquoxic Melanaquands 02-01-05-02
Hydric Pachic Melanaquands 02-01-05-03
Hydric Melanaquands 02-01-05-04
Thaptic Melanaquands 02-01-05-05
Typic Melanaquands 02-01-05-06
Epiaquands Petroferric Epiaquands 02-01-06-01
Duric Epiaquands 02-01-06-02

March 2001 Page 25
Histic Epiaquands 02-01-06-03
Alic Epiaquands 02-01-06-04
Hydric Epiaquands 02-01-06-05
Thaptic Epiaquands 02-01-06-06
Typic Epiaquands 02-01-06-07
Ndoaquands Lithic Endoaquands 02-01-07-01
Petroferric Endoaquands 02-01-07-02
Duric Endoaquands 02-01-07-03
Histic Endoaquands 02-01-07-04
Alic Endoaquands 02-01-07-05
Hydric Endoaquands 02-01-07-06
Thaptic Endoaquands 02-01-07-07
Typic Endoaquands 02-01-07-08
Cryands Geliccryands Typic Gelicryands 02-02-01-01
Melanocryands Lithic Melanocryands 02-02-02-01
Alic Melanocryands 02-02-02-02
Vertic Melanocryands 02-02-02-03
Typic Melanocryands 02-02-02-04
Fluvicryands Lithic Fluvicryands 02-02-03-01
Vitric Fluvicryands 02-02-03-02
Typic Fluvicryands 02-02-03-03
Hydrocryands Lithic Hydrocryands 02-02-04-01
Placic Hydrocryands 02-02-04-02
Aquic Hydrocryands 02-02-04-03
Thaptic Hydrocryands 02-02-04-04
Typic Fluvicryands 02-02-04-05
Vitricryands Lithic Vitricryands 02-02-05-01
Aquic Vitricryands 02-02-05-02
Thaptic Vitricryands 02-02-05-03
Humic Xeric Vitricryands 02-02-05-05
Xeric Vitricryands 02-02-05-06
Ultic Vitricryands 02-02-05-07
Alfic Vitricryands 02-02-05-08
Humic Vitricryands 02-02-05-09
Typic Vitricryands 02-02-05-10
Haplocryands Lithic Haplocryands 02-02-06-01
Alic Haplocryands 02-02-06-02
Aquic Haplocryands 02-02-06-03
Acrudoxic Haplocryands 02-02-06-04
Vitric Haplocryands 02-02-06-05
Thaptic Haplocryands 02-02-06-06
Xeric Haplocryands 02-02-06-07
Typic Haplocryands 02-02-06-08
Torrands Vitritorrands Lithic Vitritorrands 02-03-01-01
Petrocalcic Vitritorrands 02-03-01-02
Duric Vitritorrands 02-03-01-03
Aquic Vitritorrands 02-03-01-04
Calcic Vitritorrands 02-03-01-05

March 2001 Page 26
Typic Vitritorrands 02-03-01-06
Xerands Vitrixerands Lithic Vitrixerands 02-04-01-01
Aquic Vitrixerands 02-04-01-02
Thaptic Vitrixerands 02-04-01-03
Alfic Humic Vitrixerands 02-04-01-04
Alfic Vitrixerands 02-04-01-05
Ultic Vitrixerands 02-04-01-06
Humic Vitrixerands 02-04-01-07
Typic Vitrixerands 02-04-01-08
Melanoxerands Pachic Melanoxerands 02-04-02-01
Typic Xelanoxerands 02-04-02-02
Haploxerands Lithic Haploxerands 02-04-03-01
Aquic Haploxerands 02-04-03-02
Thaptic Haploxerands 02-04-03-03
Calcic Haploxerands 02-04-03-04
Ultic Haploxerands 02-04-03-05
Alfic Humic Haploxerands 02-04-03-06
Alfic Haploxerands 02-04-03-07
Humic Haploxerands 02-04-03-08
Typic Haploxerands 02-04-03-09
Vitrands Ustivitrands Lithic Ustivitrands 02-05-01-01
Aquic Ustivitrands 02-05-01-02
Thaptic Ustivitrands 02-05-01-03
Calcic Ustivitrands 02-05-01-04
Humic Ustivitrands 02-05-01-05
Typic Ustivitrands 02-05-01-06
Udivitrands Lithic Udivitrands 02-05-02-01
Aquic Udivitrands 02-05-02-02
Thaptic Udivitrands 02-05-02-03
Ultic Udivitrands 02-05-02-04
Alfic Udivitrands 02-05-02-05
Humic Udivitrands 02-05-02-06
Typic Udivitrands 02-05-02-07
Ustands Durustands Aquic Durustands 02-06-01-01
Thaptic Durustands 02-06-01-02
Humic Durustands 02-06-01-03
Typic Durustands 02-06-01-04
02-06-01-05
Haplustands Lithic Haplustands 02-06-02-01
Aquic Haplustands 02-06-02-02
Dystric Vitric Haplustands 02-06-02-03
Vitric Haplustands 02-06-02-04
Pachic Haplustands 02-06-02-05
Thaptic Haplustands 02-06-02-06
Calcic Haplustands 02-06-02-07
Dystric Haplustands 02-06-02-08
Oxic Haplustands 02-06-02-09
Ultic Haplustands 02-06-02-10

March 2001 Page 27
Alfic Haplsutands 02-06-02-11
Humic Haplustands 02-06-02-12
Typic Haplustands 02-06-02-13
Udands Placudands Lithic Placudands 02-07-01-01
Aquic Placudands 02-07-01-02
Acrudoxic Hydric Placudands 02-07-01-03
Acrudoxic Placudands 02-07-01-04
Eutric Vitric Placudands 02-07-01-05
Vitric Placudands 02-07-01-06
Hydric Pachic Placudands 02-07-01-07
Pachic Placudands 02-07-01-08
Hydric Placudands 02-07-01-09
Thaptic Placudands 02-07-01-10
Eutric Placudands 02-07-01-11
Typic Placudands 02-07-01-12
Durudands Aquic Durudands 02-07-02-01
Acrudoxic Durudands 02-07-02-02
Hydric Pachic Durudands 02-07-02-03
Thaptic Durudands 02-07-02-04
Typic Durudands 02-07-02-05
Melanudands Lithic Melanudands 02-07-03-01
Anthraquic Melanudands 02-07-03-02
Alic Aquic Melanudands 02-07-03-03
Alic Pachic Melanudands 02-07-03-04
Alic Thaptic Melaundands 02-07-03-05
Alic Melanudands 02-07-03-06
Aquic Melanudands 02-07-03-07
Acrudoxic Vitric Melanudands 02-07-03-08
Acrudoxic Hydric elanudands 02-07-03-09
Acrudoxic Melanudands 02-07-03-10
Pachic Melanudands 02-07-03-11
Eutric Hydric Melanudands 02-07-03-12
Hydric Pachic Melanudands 02-07-03-13
Pachic Mealnudands 02-07-03-14
Eutric Pachic Melanudands 02-07-03-15
Vitric Melanudands 02-07-03-16
Hydric Melanudands 02-07-03-17
Thaptic Melanudands 02-07-03-18
Ultic Melanudands 02-07-03-19
Typic Melanudands 02-07-03-20
Fulvudands Hydric Lithic Fulvudands 02-07-04-01
Lithic Fulvudands 02-07-04-02
Alic Fulvudands 02-07-04-03
Aquic Fulvudands 02-07-04-04
Acrudoxic Hydric Fulvudands 02-07-04-05
Acrudoxic Ultic Fulvudands 02-07-04-06
Acrudoxic Fulvudands 02-07-04-07
Hydric Pachic Fulvudands 02-07-04-08

March 2001 Page 28
Eutric Pachic Fulvudands 02-07-04-09
Pachic Fulvudands 02-07-04-10
Hydric Thaptic Fulvudands 02-07-04-11
Hydric Fulvudands 02-07-04-12
Thaptic Fulvudands 02-07-04-13
Eutric Fulvudands 02-07-04-14
Typic Fulvudands, 02-07-04-15
Lithic Hydrudands 02-07-05-01
Aquic Hydraudands 02-07-05-02
Acrudoxic Thaptic Hydrudands 02-07-05-03
Acrudoxic Hydrudands 02-07-05-04
Thaptic Hydrudands 02-07-05-05
Eutric Hydrudands 02-07-05-06
Ultic Hydrudands 02-07-05-07
Typic Hydrudands 02-07-05-08
Hapludands Lithic Hapludands 02-07-06-01
Petroferric Hapludands 02-07-06-02
Anthraquic Hapludands 02-07-06-03
Aquic Duric Hapludands 02-07-06-04
Duric Hapludands 02-07-06-05
Alic Hapludands 02-07-06-06
Aquic Hapludands 02-07-06-07
Acrudoxic Hydric hapludands 02-07-06-08
Acrudoxic Thaptic Hapludands 02-07-06-09
Acrudoxic Ultic Hapludands 02-07-06-10
Acrudoxic Hapludands 02-07-06-11
Vitric Hapludands 02-07-06-12
Hydric Thaptic Hapludands 02-07-06-13
Hydric Hapludands 02-07-06-14
Eutric Thaptic Hapludands 02-07-06-15
Thaptic Hapludands 02-07-06-16
Eutric Hapludands 02-07-06-17
Oxic Hapludands 02-07-06-18
Ultic Hapludands 02-07-06-19
Alfic Hapludands 02-07-06-20
Typic Hapludands 02-07-06-21
The coding scheme will be extended to series level using the following table.
Soil Unit Order Sub-order Great Group Sub-group Family Series
Code AA BB CC DD EE FF
Table 4.1: Standard Soil Classification and Code (SOIL.LUT)

March 2001 Page 29
SOIL-Code I 8 Y
Order C 15 N
Sub-order C 15 N
Great Group C 30 N
Sub-group C 50 N
Family C 50 N
Series C 50 N
Table 4.2: Structure of Data

March 2001 Page 30
5 Geology - Lithology
The standard classification scheme for lithology unit and rock type (and code) is shown in Table 5.1
while the structure of data is described in Table 5.2. Only those units present in the map area shall be
classified, and any other unit present in the area and not covered by the scheme shall be mapped and
provided appropriate code.
5.2 Input Data
− Geocoded IRS LISS III FCC imagery in 1:50000 scale of summer season (with minimum
vegetation cover); where necessary Kharif or Rabi season data will be additionally used
− Existing geological and hydrogeological maps and literature
5.3 Methodology
Classification and mapping of lithologic units/rock types shall be performed through visual
interpretation of image characteristics and terrain information, supported by the a priori knowledge of
general geologic setting of the area. The description of rock types/lithologic units is provided in Table
5.3.
The tone (colour) and landform characteristics, and relative erodibility, drainage, soil type, land
use/cover and other contextual information are used in classification. Acidic and arenaceous rocks are
lighter in tone compared to basic/argillaceous rocks. Coarse-grained rocks with higher porosity and
permeability appear brighter as compared to fine-grained rocks with higher moisture retaining
capacity. Highly resistant rock formations occur as different hill types depending on their texture and
internal structure, while the easily erodible rocks occur as different types of plains and valleys.
Dentritic drainage indicates homogeneous rocks, while trellis, rectangular and parallel drainage
patterns indicate structural and lithologic controls. Coarse drainage texture indicates highly porous
and permeable rock formations, while fine drainage texture is present in less pervious formations.
Coarse textured and light coloured soils indicate acidic/arenaceous rocks rich in quartz and feldspars,
while fine textured and dark coloured soils indicate basic/argillaceous rocks. Convergence of evidence
from different interpretation elements shall be followed for reliable classification. The contacts of
identified rock types shall be extended over large areas based on tonal contrast or landform on
satellite imagery. Inferred boundaries (where the contrast is not adequate) is marked by different
symbol. The rock types are mapped and labeled as per classification scheme (Table 5.1).
After preliminary interpretation field visit shall be conducted for proper identification and classification
of rock types.
(Annexure I).
The transformation process shall involve geometric rectification through Ground Control Points
(GCPs) identified on the input coverage and corresponding SOI map. The HP data specification
standards in Table 2.2 need to be conformed. The resulting GIS coverage shall be backed up in CD

March 2001 Page 31
and labeled with corresponding SOI map sheet number, theme, generating agency, and generation
date.
5.4 Output Products
for clarifications.
Rock Group Rock Type/ Lithologic Unit LITH-Code
Unconsolidated Sediments
Gravel
Sand & silt
Clayey sand & silt
Sandy clay
Clay
Alternating sequence of sand/silt & clay
Colluvium
01-00
01-01
01-02
01-03
01-04
01-05
01-06
01-07
Residual cappings
Laterite
Bauxite
Kankar
Chert
Detrital Laterite
02-00
02-01
02-02
02-03
02-04
02-05
Deccan Traps and Intertrappeans
Inter & intra- trappean sand/clay bed
Tuffacious Basalt
Vesicular Basalt
Amygdaloidal Basalt
Massive Basalt
Red/Green Bole
03-00
03-01
03-02
03-03
03-04
03-05
03-06
Older Volcanics/Metavocanics
Basalt
Rhyolite
Dacite
Andesite
04-00
04-01
04-02
04-03
04-04
Semi-consolidated Sediments
Sandstone & conglomerate
Shaly sandstone
Sandstone with shale/coal partings
Shell Limestone/Limestone
Sandy Shale
Shale with sandstone partings
Shale/Coal/Lignite
05-00
05-01
05-02
05-03
05-04
05-05
05-06
05-07
Consolidated sediments
Thin bedded Sandstone/Quartzite
06-00
06-01

March 2001 Page 32
Rock Group Rock Type/ Lithologic Unit LITH-Code
Thin bedded Limestone/Dolomite
Thick bedded/Massive Limestone/Dolomite
Thick bedded Sandstone/Quartzite
Shaly Limestone
Conglomerate
Shale with Limestone/sandstone Bands/Lenses
Shale
06-02
06-03
06-04
06-05
06-06
06-07
06-08
Plutonic rocks
Granitic/Acidic rocks
Alkaline rocks
Basic rocks
Ultrabasic rocks
Quartz reef
Pegmatite/Aptite/Quartz vein
07-00
07-01
07-02
07-03
07-04
07-05
07-06
Note: Rock type and stratigraphy to be assigned on case by case basis as per GSI classification
Table 5.1: Rock Groups and Rock Type/ Lithologic Unit Classification (LITH-LUT)
(proposed by NRSA in RGDWTM mapping project)
LITH-Code I 4 Y
Rock Group C 30 N
Lithologic Unit C 50 N
Rock Type C 50 N
Stratigraphy C 50 N
Rock Type/ Lithologic Unit Description
Unconsolidated Sediments Quaternary sediments associated with alluvial, deltaic, coastal,
eolian, flood plains, valley fills, etc. Based on their composition, 7
litho-units are identified in this group as shown below
Gravel Comprising of granular sediments of 2-4 mm size
Sand & Silt Comprising of granular sediments of 2-1/256 mm size
Clayey Sand / Silt Comprising of dominantly granular sediments with significant clay
content
Sandy Clay Comprising of dominantly non-granular sediments with significant
sand content.
Clay Comprising of dominantly non-granular sediments having <256 mm
particle size
Alternating Sequence of Sand/
Silt and Clay
Interbedded granular (sand/silt) and non-granular sediments (clay
in different proportions
Colluvium Assorted mixture of cobbles, pebbles, sand, silt and clay
Residual Cappings Duricrusts associated with remnants of planar surfaces. Occur as
plateaus, mesas, buttes, etc. 4 litho-units are identified in this
group as shown below.
Laterite (Ferricrete) Hard and pisolitic oxidised crust at surface underlain by soft
lithomargic clays formed by deep chemical weathering and

March 2001 Page 33
enrichment of iron oxides by leaching.
Bauxite (Alecrete) Same as above, but formed due to enrichment of aluminium oxide.
Kankar (Calcrete) Produced by the formation of calcium carbonate nodules.
Chert (Silcrete) Cryptocrystalline silica; occur as bands or layers of nodules
Detrital Laterite Formed by deposition of laterite / ferrugenous detritus as valley fills.
Deccan Traps & Intertrappeans Upper Cretaceous to Palaeocene volcanic flows like Deccan
basalts and their equivalents. Based on their aquifer
characteristics, 6 litho-units are identified in this group as shown
below-
Inter-/Infra-trappean Sand/Clay
bed
Thin beds of semi-consolidated sediments occurring between
different lava flows and also at the base of Deccan traps.
Tuffacious Basalt Soft, friable and porous besalt formed mainly by volcanic tuff.
Vesicular Basalt Hard and vesicular basalt with limited porosity.
Amygdaloidal Basalt Vesicular basalt filled with amygdales.
Massive Basalt Hard and massive basalt. Fracturing and weathering lead to the
development of secondary porosity and permeability.
Red / Green Bole Red / Green clay beds of 0.5-5 m thickness occur between different
lava flows.
Older Volcanics/Metavolcanics Volcanic rocks of different composition of Precambrian age.
Besalt Hard and massive basalts
Rhyolite Hard and massive rhyolites
Dacite Hard and massive dacites
Andesite Hard and massive andesites
Semi-consolidated Sediments Upper Carboniferrous to Pliocene sediments comprising of mainly
Gondwanas, Rajamundry Sandsone, Nari, Gaj series, Cretaceous
beds to Trichy etc, which are partially consolidated, soft and friable
having significant intergranular pore spaces. Based on their
composition in this group as shown below -
Sandstone & Conglomerate Comprising of dominantly granular sediments with insignificant
shale / clay content.
Shaly Sandstone Comprising of dominantly granular sediments with significant shale
/ clay content.
Sandstone with Shale/Coal
partings
Dominantly granular sediments, interbedded with shale, clay or coal
partings.
Shell Limestone/Limestone Mainly formed by cementation of shell fragments and oolites.
Sandy Shale Comprising of dominantly non-granular sediments with significant
sand content.
Shale with Sandstone Partings Mainly shale/clay, coal, lignite formations with thin sandstone
partings.
Shale/Coal/Lignite Comprising of dominantly non-granular sediments with insignificant
sand content.
Consolidated Sediments Mainly Precambrian to Cambrian sedimentaries of Cuddapah,
Delhi, Vindhyan Groups and their equivalents, comprising of fully
consolidated sediments without any intergranular pore spaces
(except the bedding places). Based on their aquifer characteristics,
8 litho-units are identified in this group as shown below-
Thin Bedded
Sandstone/Quartzite
Hard and indurated sandstone/quartzite with a no. of well defined
bedding planes.
Thin Bedded Thin bedded, flaggy limestone / dolomite with a no. of defined

March 2001 Page 34
Limesone/Dolomite bedding planes.
Thick Bedded / massive
Limestone / Dolomite
Hard and massive limestone/dolomite with very few bedding
planes.
Thick Bedded
Sandstone/Quartzite
Hard and massive sandstone/quartzite, without any intergranular
pore spaces.
Shaly Limestone Dominantly limestone with significant shale content as impurity or
with shale intercalations.
Conglomerate Hard & massive conglomerate without significant intergranular pore
spaces
Shale with Limestone/
Sandstone Bands / Lenses
Mainly shale sequence with bands and lenses of
limestone/sandstone
Shale Hard and compact shale/claystone
Plutonic Rocks Include a variety of hard and massive plutonic igneous rocks with
no primary porosity.
Granitic / Acidic Rocks Hard and massive plutonic rocks of granitic/acidic composition.
Alkaline Rocks Hard and massive plutonic rocks of alkaline composition.
Basic Rocks Hard and massive plutonic rocks of basic composition.
Ultrabasic Rocks Hard and massive igneous rocks of ultrabasic composition.
Quartz Reef Hard and brittle quartz reefs.
Pegmatite/Aplite/Quartz Vein Hard and brittle veins of Pegmatite/Aplite/Quartz
Granite & Gneissic Complexes/
Migmatitic Complexes
Include Peninsular gneissic complex and equivalents with granitic
intrusions, and migmatitic complexes.
Granite & Gneissic Complex Comprising of gneisses and granites in roughly same proportion.
Grantic Gneiss Mainly comprising of gneisses with granitic lenses.
Migmatitic Complex Hard and massive migmatities.
Migmatite with Granite Lenses Hard and massive migmatites with lenses of granite.
Metamorphics Include, a variety of metamorphosed igneous, sedimentary and
volcanic rocks.
Gneiss Gneisses of different mineral composition with crude to well
developed foliations.
Schist Crudely foliated schists of different composition.
Quartzite Hard and brittle quartzites.
Slate Slates with well developed slaty cleavage.
Phyllite Crudely foliated phyllites.
Calc Gneiss Calcareous gneisses with crudely to well-developed foliations.
Calc Schist Crudely foliated calcareous schists.
Limestone / Marble Hard and brittle limesone / marble.
Table 5.3: Description of rock types/ lithologic units

March 2001 Page 35
6 Geology - Structures
The geological structures shall be mapped as per the classification scheme in Table 6.1. Only those
units present in the map area shall be classified, and any other unit present in the area and not
covered by the scheme shall be mapped and provided appropriate code.
6.2 Input Data
vegetation cover); where necessary Kharif or Rabi season data shall be additionally used
6.3 Methodology
Different types of primary and secondary geological structures (attitude of beds, schisticity/foliation,
folds, lineaments, circular features, etc.) can be visually interpreted by studying the landforms, slope
asymmetry, outcrop pattern, drainage pattern, and stream/river courses. Lineaments (faults, fractures,
shear zones, and thrusts.) appear as linear and curvilinear lines on the satellite imagery, and are often
indicated by the presence of moisture, alignment of vegetation, straight drainage courses, alignment
of tanks/ponds, etc. Lineaments are further sub-divided based on image characteristics and
geological evidence.
The attitude of beds (strike and dip) shall be estimated by studying the slope asymmetry, landform,
drainage characteristics, etc. For instance horizontal to sub-horizontal beds show mesa/butte type of
landform, dentritic drainage pattern and tonal/colour banding parallel to the contour lines; inclined
beds show triangular dip facets, cuestas, homoclines and hogbacks. The Schistosity/foliation of the
rocks shall be shown as numerous thin, wavy and discontinuous trend lines. Non-plunging and
plunging folds shall be mapped from the marker horizons. Non-plunging folds produce outcropping in
parallel belts, and plunging folds produce V or U shaped outcrop pattern. Doubly plunging folds shall
be indicated by oval shaped outcrops. Further classification into anticline or syncline can be made on
the basis of dip direction of beds. Circular features, representing structural domes/basins, sub-surface
igneous intrusions, salt domes, etc. show circular to quasi-circular outcrops and trend lines with
radial/annular drainage pattern. Reference to existing literature can support confirmation of interpreted
details. The geological structures shall be mapped with standard symbols.
The pre-field structural map shall be checked in the field and validated.
(Annexure I).
date.

March 2001 Page 36
6.4 Output Products
for clarifications.
Structure Sub- categories STRU-Code
Bedding
Horizontal (dip angle between 0 and 5 degrees)
Gentle (dip angle between 5 and 15 degrees)
Moderate (dip angle between 15 and 45 degrees)
Steep(dip angle between 45 and 80 degrees)
Vertical to sub-vertical(dip angle greater than 80 degrees)
Overturned (beds are overturned)
01-00
01-01
01-02
01-03
01-04
01-05
01-06
Schistosity/
Foliation
Moderate (dip angle less than 45 degrees)
Steep( dip angle between 45 and 80 degrees)
Vertical to sub-vertical ( dip angle greater than 80 degrees)
Overturned (Schistosity / foliation overturned)
02-00
02-01
02-02
02-03
02-04
Faults/ Fractures/
Lineaments/ Shear
zones/ Thrusts Confirmed
Inferred
03-00
03-01
03-02
Folds
Anticline/ Antiform
Syncline/Synform
Folds to be classified as non-plunging, plunging, doubly
plunging and overturned
04-00
04-01
04-02
04-03
Circular features
Structural dome
Structural basin
05-00
05-01
05-02
Trend lines 06-00
Escarpment 07-00
Table 6.1: Geologic Structure Classification and Code (STRU-LUT)
(proposed by NRSA in RGDWTM mapping project)
Stru-Code I 4 Y
Structure C 30 N
Sub-Structure C 100 N
Table 6.2 Structure of Data

March 2001 Page 37
7 Geomorphology
Geomorphic units/different landforms shall be mapped as per the classification scheme (and code) in
Table 7.1, and the structure of data is described in Table 7.2. While the scheme is comprehensive
only those units present in the area to be mapped shall be classified, and any other units present in
the area and not listed in Table 7.1 shall be classified and appropriate code/symbol used.
7.2 Input Data
vegetation cover); where necessary Kharif or Rabi season data shall be additionally used
7.3 Methodology
The geomorphic units/landforms in the classification scheme are described in Table 7.3. The satellite
imagery shall be visually interpreted into geomorphic units/landforms based on image elements such
as tone, texture, shape, size, location and association, physiography, genesis of landforms, nature of
rocks/ sediments, and associated geological structures. The topographic information in SOI topomaps
aids in interpreting satellite imagery. Three major geomorphic units – hills and plateaus, piedmont
zones, and plains- based on physiography and relief. Within each zone different geomorphic units
shall be mapped based on landform characteristics, their areal extent, depth of weathering, thickness
of deposition, etc.
The interpreted geomorphic units/landforms shall be verified through field visits, in which the depth of
weathering, nature of weathered material, thickness of deposition, nature of deposited material, etc.
shall be examined at nala and stream cuttings, existing wells, lithologs of wells drilled, etc.
(Annexure I).
date.
7.4 Output Products
for clarifications.

Zone Geomorphic Unit Sub- categories Landforms GU-Code
Structural hills 01-01-00-00-00
Denudational hills 01-02-00-00-00
Plateaus
Upper
Undissected
Moderately dissected
Highly dissected
Middle
Undissected
Highly dissected
Lower
Undissected
Highly dissected
01-03-00-00-00
01-03-01-00-00
01-03-01-01-00
01-03-01-02-00
01-03-01-03-00
01-03-02-00-00
01-03-02-01-00
01-03-02-02-00
01-03-02-03-00
01-03-03-00-00
01-03-03-01-00
01-03-03-02-00
01-03-03-03-00
Hills and
Plateaus
Valleys
Structural valley
Intermontane valley
Linear/Curvilinear ridge
Cuesta
Mesa
Butte
Dome (Structural)
Dome (massive)
Inselberg
01-04-00-00-00
01-04-01-00-00
01-04-02-00-00
01-00-00-00-01
01-00-00-00-02
01-00-00-00-03
01-00-00-00-04
01-00-00-00-05
01-00-00-00-06
01-00-00-00-07
Pediment.
Buried pediment
Dissected pediment
Pediment-Inselberg complex
02-01-00-00-00
02-01-01-00-00
02-01-02-00-00
02-01-03-00-00
Piedmont slope 02-02-00-00-00
Piedmont alluvium
Shallow
Moderate
Deep
02-03-00-00-00
02-03-01-00-00
02-03-02-00-00
02-03-03-00-00
Piedmont Zone

Bajada
Shallow
Moderate
Deep
Cuesta
Mesa
Butte
Dome (Structural)
Dome (massive)
Inselberg
02-04-00-00-00
02-04-01-00-00
02-04-02-00-00
02-04-03-00-00
02-00-00-00-01
02-00-00-00-02
02-00-00-00-03
02-00-00-00-04
02-00-00-00-05
02-00-00-00-06
02-00-00-00-07
Pediplain
Weathered
Shallow
Moderate
Deep
Buried
Shallow
Moderate
Deep
Cuesta
Mesa
Butte
Dome (Structural)
Dome (massive)
Inselberg
Valleyfill-Shallow
Valleyfill-Moderate
Valleyfill-Deep
03-01-00-00-00
03-01-01-00-00
03-01-01-01-00
03-01-01-02-00
03-01-01-03-00
03-01-02-00-00
03-01-02-01-00
03-01-02-02-00
03-01-02-03-00
03-01-00-00-01
03-01-00-00-02
03-01-00-00-03
03-01-00-00-04
03-01-00-00-05
03-01-00-00-06
03-01-00-00-07
03-01-00-00-08
03-01-00-00-09
03-01-00-00-10
Plains
Etch plain
Shallow weathered
Moderately weathered
Deeply weathered
Cuesta
Mesa
Butte
03-02-00-00-00
03-02-01-00-00
03-02-02-00-00
03-02-03-00-00
03-02-00-00-01
03-02-00-00-02
03-02-00-00-03
03-02-00-00-04

Dome (Structural)
Dome (massive)
Inselberg
Valleyfill-Shallow
Valleyfill-Moderate
Valleyfill-Deep
03-02-00-00-05
03-02-00-00-06
03-02-00-00-07
03-02-00-00-08
03-02-00-00-09
03-02-00-00-10
Stripped plain
Shallow basement
Moderate basement
Deep basement
Cuesta
Mesa
Butte
Dome (Structural)
Dome (massive)
Inselberg
Valleyfill-Shallow
Valleyfill-Moderate
Valleyfill-Deep
03-03-00-00-00
03-03-01-00-00
03-03-02-00-00
03-03-03-00-00
03-03-00-00-01
03-03-00-00-02
03-03-00-00-03
03-03-00-00-04
03-03-00-00-05
03-03-00-00-06
03-03-00-00-07
03-03-00-00-08
03-03-00-00-09
03-03-00-00-10
Flood plain
Older/Upper
Shallow
Moderate
Deep
Younger/ Lower
Shallow
Moderate
Deep
Channel bar
Point bar
River terrace
Natural levee
Backswamp
Cut-off meander
Abandoned channel
Ox-bow lake
Paleochannel
Buried channel
03-04-00-00-00
03-04-01-00-00
03-04-01-01-00
03-04-01-02-00
03-04-01-03-00
03-04-02-00-00
03-04-02-01-00
03-04-02-02-00
03-04-02-03-00
03-04-00-00-01
03-04-00-00-02
03-04-00-00-03
03-04-00-00-04
03-04-00-00-05
03-04-00-00-06
03-03-00-00-07
03-04-00-00-08
03-04-00-00-09
03-04-00-00-10

Alluvial plain
Older/Upper
Shallow
Moderate
Deep
Younger/ Lower
Shallow
Moderate
Deep
Channel bar
Point bar
River terrace
Natural levee
Backswamp
Cut-off meander
Abandoned channel
Ox-bow lake
Paleochannel
Buried channel
03-05-00-00-00
03-05-01-00-00
03-05-01-01-00
03-05-01-02-00
03-05-01-03-00
03-05-02-00-00
03-05-02-01-00
03-05-02-02-00
03-05-02-03-00
03-05-00-00-01
03-05-00-00-02
03-05-00-00-03
03-05-00-00-04
03-05-00-00-05
03-05-00-00-06
03-05-00-00-07
03-05-00-00-08
03-05-00-00-09
03-05-00-00-10
Deltaic plain
Older/Upper
Shallow
Moderate
Deep
Younger/ Lower
Shallow
Moderate
Deep
Channel bar
Point bar
River terrace
Natural levee
Backswamp
Cut-off meander
Abandoned channel
Ox-bow lake
Paleochannel
Buried channel
03-06-00-00-00
03-06-01-00-00
03-06-01-01-00
03-06-01-02-00
03-06-01-03-00
03-06-02-00-00
03-06-02-01-00
03-06-14-02-02
03-06-00-02-03
03-06-00-00-01
03-06-00-00-02
03-06-00-00-03
03-06-00-00-04
03-06-00-00-05
03-06-00-00-06
03-06-00-00-07
03-06-00-00-08
03-06-00-00-09
03-06-00-00-10

Coastal plain
Older/Upper
Shallow
Moderate
Deep
Younger/ Lower
Shallow
Moderate
Deep
Beach
Beach ridge
Beach ridge & Swale complex
Swale
Off-shore bar
Spit
Mud flat
Salt flat
Tidal flat
Lagoon
Sand dune
Channel island
Paleochannel
Buried Channel
03-07-00-00-00
03-07-01-00-00
03-07-01-01-00
03-07-01-02-00
03-07-01-03-00
03-07-02-00-00
03-07-02-01-00
03-07-02-02-00
03-07-02-03-00
03-07-00-00-01
-3-07-00-00-02
03-07-00-00-03
03-07-00-00-04
03-07-00-00-05
03-07-00-00-06
03-07-00-00-07
03-07-00-00-08
03-07-00-00-09
03-07-00-00-10
03-07-00-00-11
03-07-00-00-12
03-07-00-00-13
03-07-00-00-14
Eolian plain
Shallow
Moderate
Deep
Sand dune
Stabilised dune
Dune complex
Interdunal depression
Interdunal flat
Playa
Desert Pavement
Loess
Paleochannel
Buried Channel
03-08-00-00-00
03-08-01-00-00
03-08-02-00-00
03-08-03-00-00
03-08-00-00-01
03-08-00-00-02
03-08-00-00-03
03-08-00-00-04
03-08-00-00-05
03-08-00-00-06
03-08-00-00-07
03-08-00-00-08
03-08-00-00-09
03-08-00-00-10
Table 7.1: Geomorphic Classification Scheme and Code (GU-LUT); (proposed by NRSA in RGDWTM mapping project)

March 2001 Page 43
GU-Code I 10 Y
Descr-Level 1 C 50 N
Descr-Landform C 50 N
Geomorphic Unit/ Landform Description
Structural Hills Linear to arcuate hills showing definite structural trends.
Denudational Hills Hills formed due to differential erosion and weathering, so that
a more resistant formation or intrusion stand as mountains/
hills.
Plateaus Elevated flat uplands occupying fairly large area (greater than
5 km x 5 km) and bound by escarpments/steep slopes on all
sides. Based on their geomorphic position, they are classified
into 3 categories – 1) Upper, 2) Middle and 3) Lower. Further
based on dissection, these Upper, Middle and Lower Plateaus
have been further classified into undissected, moderately
dissected and highly dissected categories.
- Undissected A plateau (upper/middle/lower) which is fully preserved in its
original form and has not been dissected.
- Moderately Dissected A plateau (upper/middle/lower) dissected by deep
valleys/gullies changing the original form considerably.
- Highly Dissected A plateau (upper/middle/lower) more frequently dissected by
deep valleys separating into individual mesas/buttes.
Valleys Low lying depressions and negative landforms of varying size
and shape occurring within the hills associated with
stream/nala courses.
Structural Valleys Narrow linear valleys formed alone the structurally weak
planes like faults, fractures, lithological-contacts etc.
Intermonate Valley Small valleys occurring within the structural/denudational hills.
Linear / Curvilinear Ridge A narrow linear/curvilinear resistant ridge formed by dolerite
dyke, quartz reef, quartzite bed, etc.
Cuesta An isolated hill formed by gently dipping (5-10o) sedimentary
beds having escarpent/steep steep slopes on one side and
gentle dip slopes on the other side.
Mesa Flat-topped hills having width 2 km to 250 m.
Butte Flat-topped hills having width <250 m.
Dome (Structural) Dome shaped hills of structural origin.
Dome (Massive) Dome shaped hills formed by exfoliation and sheeting of
plutonic rocks.
Inselberg An Isolated hill of massive type abruptly rising above
surrounding plains.
Pediment Gently undulating plain dotted with rock outcrops with or
without thin veneer of soil cover.
Buried Pediment Same as above, but buried under unconsolidated sediments.
Dissected pediment Same as pediment, but dissected.
Pediment-Inselberg Complex Pediment dotted with a number of inselbergs which cannot be
separated and mapped as individual units.
Piedmont Slope Slope formed by bajada and pediment together.
Piedmont Alluvium
- Shallow
- Moderate
Alluvium deposited along foot hill zone due to sudden loss of
gradient by rivers/streams in humid and sub-humid climate.
Based on the thickness, it is divided into 3 categories – 1)

March 2001 Page 44
- Deep Shallow (0-10 m), 2) Moderate (10-20m), and 3) Deep (more
than 20 m).
Bajada
- Shallow
- Moderate
- Deep
Detrital alluvial out-wash of varying grain size deposited along
the foot hill zone in arid and semi-arid climate. Based on the
thickness, it is divided into 3 categories – 1) Shallow (0-10 m),
2) Moderate (10-20 m) and 3) Deep (>20 m).
Alluvial Fan A fan shaped mass of sediment deposited at a point along a
river where there is a decrease in gradient.
Talus Cone A cone shaped deposit of coarse debris at the foot of hills/
cliffs adopting the angle of repose.
Pediplain-Weathered
- Shallow Weathered
- Mod. Weathered
- Deeply Weathered
Gently undulating plain of large areal extent often dotted with
inselbergs formed by the coalescence of several pediments.
Based on the depth of weathering, weathered pediplains are
classifed into 3 categories – 1) Shallow (0-10 m), 2) Moderate
(10-20 m), and 3) Deep (more than 20 m)
Pediplain-Buried
- Shallow
- Moderate
- Deep
Same as above, but buried under transported material. Based
on the total thickness of transported material and depth of
weathering, buried pediplains are classified into 3 categories –
1) Shallow (0-10m), 2) Moderate (10-20 m), and 3) Deep
(more than 20 m).
Etch Plain
- Shallow Weathered
- Mod. Weathered
- Deeply Weathered
A plain formed by deep chemical weathering and stripping.
Based on the depth of weathering, etch plains are classified
into 3 categories – 1) Shallow (0-10 m), 2) Moderate (10-20 m)
and 3) Deep (more than 20 m).
Stripped Plain
- Shallow Basement
- Mod. Basement
- Deep Basement
Gently undulating plain formed by partial stripping (erosion) of
older pediplains. The presence of rock outcrops along valleys
and deeply weathered zones along inter-stream divides
indicate the stripped plains. Based on depth to basement, it is
classified into 3 categories – 1) Shallow (0-10 m), 2) Moderate
(10-20 m) and 3) Deep (more than 20 m).
Valley Fill
- Shallow
- Moderate
- Deep
Valleys of different shapes and sizes occupied by valley fill
material (partly detrital and partly weathered material). They
are classified into 3 categories - 1) Shallow (0-10 m), 2)
Moderate (10-20 m) and 3) Deep (more than 20 m).
Flood Plain Alluvium deposited along the river/stream courses due to
repeated flooding. It is classified into 2 categories -–1) Older/
Upper and 2) Younger/Lower.
Flood Plain-Older/Upper
- Shallow
- Moderate
- Deep
Same as above. Older refers to earlier cycle of deposition and
upper refers to higher elevation8. Based on the thickness of
alluvium, it is classified into 3 categories - 1) Shallow (0-10 m),
2) Moderate (10-20 m) and 3) Deep (more than 20 m).
Flood Plain-Younger/ Lower
- Shallow
- Moderate
- Deep
Same as above. Younger refers to late cycle of deposition
and lower refers to lower elevation. Based on the thickness of
Alluvial Plain Nearly level plain formed by the deposition of alluvium by
major rivers. It is further classified into 2 categories – 1) Older
/Upper and 2) Younger / Lower.
Alluvial Plain-Older / Upper
- Shallow
upper refers to higher elevation8. Based on the thickness of

March 2001 Page 45
- Moderate
- Deep
Alluvial Plan-Younger / Lower
- Shallow
- Moderate
- Deep
Deltaic Plain Alluvial plain formed by the distributary network of the rivers/
streams at their confluence with sea, it is further classified into
2 categories – 1) Older / Upper and 2) Younger/Lower.
Deltaic Plain-Older / Upper
- Shallow
- Moderate
- Deep
upper refers to higher elevation. Based on the thickness of
Deltain Plain – Younger / Lower
- Shallow
- Moderate
- Deep
Channel Bar Sand bar formed in the braided river course due to vertical
accrition of the sediments.
Point Bar Sand bar formed at the convex side of meandering river by
lateral accrition of sediment.
River Terrace Flat upland adjoining the river course, occurring at different
levels and occupied by river-borne alluvium. It indicates the
former valley floor.
Natural Levee Natural embankment formed by deposition of alluvium on river
bank due to flooding.
Back Swamp Depressions formed adjacent to natural levees in the flood
plains of major streams/rivers. Occupied by clay & silt with or
without water.
Cut-off Meander Meander loop of a matured river, cut-off from the main stream
/ river, filled with river-borne sediments.
Abandoned Channel An old river bed cut-off from the main stream, occupied by
channel-lag / channel-fill material.
Ox-bow Lake A lunate shaped lake located in an abandoned meandering
channel.
Coastal Plain Nearly level plain formed by marine action along the coast,
mainly containing brackish water sediments. It is further
classified into 2 categories – 1) Older / Upper and 2) Younger /
Lower.
Coastal Plain- Younger / Upper
- Shallow
- Moderate
- Deep
upper refers to higher elevation. Based on the thickness of
Coastal Plain – Younger /
Lower
- Shallow
- Moderate
- Deep
Beach Narrow stretch of unconsolidated sand / silt deposited by tidal
waves along the shore line.
Beach Ridge A linear ridge of unconsolidated sand/ silt parallel to the shore
line.
Beach Ridge & Swale Complex A group of beach ridges and swales occurring together.
Swale Linear depression occurring between two beach ridges.
Offshore Bar Embankments of sand and gravel formed on the sea floor by
waves and currents, occurring parallel to the coast line.
Spit Off-shore bar attached to the land at one end and terminating
in open water at the other.

March 2001 Page 46
Mud Flat Mud deposited in the back swamps and along tidal creeks.
Salt Flat Flat lands along the coast comprising of salt encrustations.
Tidal Flat Flat surface formed by tides comprising of mostly mud and fine
sand.
Lagoon An elongated body of water lying parallel to the coast line and
separated from the open sea by barrier islands.
Channel island An island formed in the braided river course.
Eolian Plain
- Shallow
- Moderate
- Deep
A plain formed by the deposition of wind blown sand dotted
with a number of sand dunes. Based on the thickness of sand
sheet and dissection, it is classified into 3 categories - 1)
Shallow (0-10 m), 2) Moderate (10-20 m) and 3) Deep (more
than 20 m).
Sand Dune Heaps of sand of different shapes and sizes formed by wind
action in the desertic terrain.
Stabilized Dune Same as above, but stabilised.
Dune Complex Group of sand dunes occurring together which cannot be
mapped separately.
Interdunal Depression Depression occurring between sand dunes.
Interdunal Flat Flat land occurring between sand dunes.
Playa Dry lake in an interior desert basin.
Desert Pavement Flat or gently sloping surfaces, developed on fans, bajadas
and desert flats formed by concentration of pebbles after
removal of finer material by wind action.
Loess Deposit of wind-blow silt.
Palaeochannel An earlier river course filled with channel lag or channel fill
sediments.
Buried Channel Old river course filled with channel lag or channel fill deposits,
buried by recent alluvium / soil cover.
Table 7.3: Description of Geomorphic units and Landforms

March 2001 Page 47
8 Administrative Units
The primary layers of administrative units upto Block shall be created. The code shall be created to
account also for future expansion of database to States outside HP.
Administrative Unit State District Tahsil Block
Code AA BB CC DD
Table 8.1: Classification Scheme and Code for Administrative Units (ADMIN.LUT)
8.2 Input Data
− Most recent SOI map in 1:50000 scale
− Latest map from State Survey Department in comparable scale, and list of administrative unit
names
8.3 Methodogy
The list of administrative units with names shall be obtained from State Revenue Department, and the
information on boundaries from most recent SOI map shall be updated with the help of State Survey
department map. It shall be desirable to prepare a fresh cartographic product of such boundaries on
clean polyester film for scanning and digitization.
The administrative unit map shall be scanned and digitized using an appropriate scanner (Annexure
II). The Arc/Info coverage shall be created and edited to remove digitization errors, and the topology
shall be built. The features shall be labeled as per codes/symbols defined in Table 8.1. The coverage
Since the State survey department maps may not have accuracy similar to SOI map, the
transformation process will involve geometric rectification through Ground Control Points (GCPs)
identified on the input coverage and corresponding SOI map. The HP data specification standards in
Table 2.2 need to be conformed. The resulting GIS coverage shall be backed up in CD and labeled
with corresponding SOI map sheet number, theme, generating agency, and generation date.
8.4 Output Products
for clarifications.

March 2001 Page 48
9 Hydrologic Units
The primary layers of hydrologic units upto watershed shall be created. The classification scheme
follows the hierarchical system of watershed delineation developed by AISLUS.
Hydrologic Unit Region Basin Catchment Sub-Catchment Watershed
WS-Code A B CC DD EE
Table 8.2: Classification Scheme and Code for Hydrologic Units (WS-LUT)
9.2 Input Data
− SOI map in 1:50000 scale SOI map in 1:50000 scale
− Watershed Atlas of India from All India Soil and Land Use Survey (AISLUS) in 1:1 million scale
9.3 Methodology
The hydrologic boundary upto watershed in AISLUS Atlas shall be drawn from 1:250000 scale SOI
maps (and further into sub-watershed using 1:50000 scale SOI maps) but shown in 1:1 million scale
map. The boundary delineation of hydrologic units at different hierarchical level in AISLUS
classification shall also based on keeping the unit size relevant to river valley project and flood prone
river management. Thus the hydrologic boundaries need to be updated using 1:50000 scale SOI map,
generally following the stream order (rather than point of interception such as dam, barrage, etc.). The
six water resources regions are as suggested by Dr. Khosla in 1949. Each water resources region
shall be delineated into basins drained by a single major river or a group of small rivers or a major
distributary of a major river. Each basin shall be subdivided into catchments, drained by a single major
river or a group of small rivers or a major tributary of a major river such as Cauvery. Each catchment
shall be divided into sub-catchments, drained by a single river or a group of small rivers or a major
distributary of a major river like Vaigai. Each sub-catchment shall be divided into watersheds, drained
by a single river or group of small rivers or a tributary of a major river.
The hydrologic unit map shall be scanned and digitized using an appropriate scanner (Annexure II).
The Arc/Info coverage shall be created and edited to remove digitization errors, and the topology shall
be built. The features shall be labeled as per codes/symbols defined in Table 9.1. The coverage shall
then be projected and transformed into polyconic projection and coordinate system in meters. The HP
9.4 Output Products
for clarifications.

March 2001 Page 49
10 Settlements
All urban settlements (towns) and rural settlements (villages) shall be mapped as per the coding
scheme below:
Type Code
Settlement
Town/ City
Village
01-00
01-01
01-02
Table 10.1: Settlement Classification Scheme and Code (SettlP.LUT & SettlA. LUT)
SettlA(&SettlP)-Code I 4 Y
Type C 30 N
Sub-category C 30 N
It is not proposed to categorize the settlements by size, which can be performed in the GIS by
attaching population data.
10.2 Input Data
− most recent SOI map in 1:50000 scale
− Census data and maps
− most recent IRS LISS III FCC geocoded imagery in 1:50000 scale
10.3 Methodology
The location of towns and villages shall be mapped from SOI map, and updated with reference to
Census map and satellite data.
The settlement boundary shall be taken from SOI map (and village boundary from revenue or census
map), and updated with reference to satellite imagery. In case of sparse distribution of settlement,
only the main part of settlement shall be shown.
The settlement location and spread map shall be scanned and digitized using an appropriate scanner
(Annexure II). The Arc/Info coverage shall be created and edited to remove digitization errors, and the
topology shall be built. The features shall be labeled as per codes/symbols defined in Section 10.1.
The coverage shall then be projected and transformed into polyconic projection and coordinate
system in meters. The HP data specification standards in Table 2.2 need to be conformed. The
resulting GIS coverage shall be backed up in CD and labeled with corresponding SOI map sheet
number, theme, generating agency, and generation date.

March 2001 Page 50
10.4 Output Products
for clarifications.

March 2001 Page 51
11 Transport Network
The classification scheme for roads and rail is shown in Table 11.1
Type Sub-category TRNPT-Code
Metalled Road
National highway
State highway
District road
Village road
01-00
01-01
01-02
01-03
01-04
Un- Mettaled Road
National highway
State highway
District road
Village road
02-00
02-01
02-02
02-03
02-04
Tracks 03-00
Rail 04-00
Table 11.1: Road Classification Scheme and Code (TRNPT.LUT)
TRNPT-Code I 4 Y
Type C 30 N
Sub-category C 30 N
11.2 Input Data
− most recent SOI map in 1:50000 scale
− maps from State Transport department
11.3 Methodology
The road and rail alignments from SOI map shall be mapped and symbolized. All roads shall be
classified into specified categories, while all rail tracks shall be shown as single category. .
The road and rail map shall be scanned and digitized using an appropriate scanner (Annexure II). The
built. The features shall be labeled as per codes/symbols defined in Section 11.1. The coverage shall

March 2001 Page 52
for clarifications.

March 2001 Page 53
12 Drainage
The classification shall cover perennial, seasonal and peripheral categories. Minor streams and rivers
shall be represented by line, while the major rivers with edges in the SOI map shall be represented by
polygon.
Drainage Type Code
Perennial Stream/River 01
Seasonal Stream/River 02
Ephemeral Stream/River 03
Table 12.1: Drainage Classification Scheme and Code (DRNL.LUT and DRNP.LUT)
Field Name Field Type Field
Width
Key
DRNL-Code/ DRNP-Code I 2 Y
Description C 30 N
12.2 Input Data
− Most recent SOI map in 1:50000 scale
− Flow data from State Water Resources Department
12.3 Methodology
The drainage details shall be digitized from SOI map in 1:50000 scale. Where necessary flow data
from the State Water Resources Department and kharif and rabi season satellite imagery may be
used to support further classification into perennial, seasonal and ephemeral streams/rivers. Major
rivers with defined water edge shall be represented by polygons while minor streams will be shown as
lines.
The road and rail map shall be scanned and digitized using an appropriate scanner (Annexure II). The
built. The features shall be labeled as per codes/symbols defined in Section 12.1. The coverage shall

March 2001 Page 54
for clarifications.

March 2001 Page 55
13 Contours and Spot Heights
All contours of 20 m interval in SOI map in 1:50000 scale shall be represented as lines and spot
heights shall be shown as points. The contour shall be coded as integer by its value (ContL.LUT), and
spot heights shall be coded as 58J14S1, where the first five alphanumeric characters represent the
SOI map number, and the next two characters represent the sequential number of spot heights within
the sheet (ContP.LUT).
13.2 Input Data
13.3 Methodology
The contours and spot heights from SOI map shall be scanned and digitized. The Arc/Info coverage
shall be created and edited to remove digitization errors, and the topology shall be built. The features
shall be labeled as per codes/symbols defined in Section 13.1. The coverage shall then be projected
and transformed into polyconic projection and coordinate system in meters. The HP data specification
date.
for clarifications.

March 2001 Page 56
Annexure I
Classification and Mapping Accuracy
1. Classification Accuracy
The thematic classification accuracy is evaluated through Kappa coefficient2
, which is a measure of
agreement between classification and truth as obtained from ground verification. This is determined
from the error matrix, which provides the number of correctly classified units but also the errors of
commission (classifying some other category as the target category) and omission (wrongly
classifying target category as some other class).
Kappa statistic is defined as follows
K= (θ1-θ2 ) ÷ (1-θ2 )
Where,
θ1 = Σxii / N
θ2 = Σxi+ *x+i /N2
Where i = 1 to r
r = no. of rows in the error matrix
xii i th diagonal element
xi+ marginal total of row i
x+i marginal total of column i
N no. of observations
Large sample variance of the kappa estimate is given as;
Var (k) = (θ1* (1-θ)) ÷ (1- θ2)2
+[2 *(1-θ2)2
*(2* (1-θ1)*(2θ1*θ2 - θ3) ÷ (1-θ2)3
] + [(1-θ1)2
*
(θ4-4*θ2
2
) ÷ (1-θ2)4
]
Where θ3 = Σx ii *(xi+ + x+i) ÷ N2
i=1 to r
θ4 = Σ x ij * (xj+ + x+i)2
÷ N3
The kappa coefficient of .9 means that the classification is 90 % accurate.
Using the variance value, confidence interval is estimated. For example, kappa coefficient can be
90% +/- (plus or minus) 5 % at 90 % confidence level and so on..
Individual class accuracy or conditional kappa coefficient is calculated as
2
Congalton G.R. 1991. A review of assessing the accuracy of classifications of remotely sensed data, Remote
Sensing of Environment, 37, (35-46)

March 2001 Page 57
K[i] = (N*x ii - (xi+ * x+i) ) ÷(N *
x i+ - (xi+ * x+i))
σ2
(k(i)) = 1 ÷ N * [A * (B+C)] where
A= Pi+ - Pii ÷ Pi+
3
*(1-P+i)3
B = (Pi+- Pii ) * (Pi+ * P+i – Pii)
C= Pii * (1 – Pi+ - P+i – Pii)
Pii = xii ÷N
Pi+ = xi+ ÷ N
P+i = x+i ÷ N
Minimum sample size is determined as under
n = ( W h
ph
qh
) Z 2
/e2
W h
= N h /N is the stratum weight
N = total no. of units
ph
is the expected accuracy level of the category
e allowable/permissible error
Z = 1.96 for 95 % conf. Level
An ideal sampling scheme requires lesser number of sample points for field checking, producing yet
reliable statistics. Cost, time and other logistic considerations in operational remote sensing projects
do not allow for field checking of large number of points for accuracy evaluation. It is suggested that
for 90 per cent accuracy at least 30 points are needed per stratum.
2. Mapping (planimetric) Accuracy
The thematic maps derived from geocoded satellite imagery after digitization is transformed to
polyconic projection (and rubber sheeting as required). The input coverage Tics are compared to
those in output coverage and the Root Mean Square (RMS) error is reported. The RMS error
describes the deviation between the locations in the input coverage and those in the output coverage.
In case of high RMS error repeat the transformation process till acceptable accuracy is achieved.
It may be easier to transform the scanned raster image of thematic map to real world coordinates
through an image processing software such as ERDAS or EASI/PACE than in the GIS environment.

March 2001 Page 58
Annexure II
Standard Procedure for Digitization
1. Prepare each input thematic map on separate tracing paper, with cartography done using
Rotring or any other similar pen of preferably 0.2 number on clean polyester film.
2. Scan the map in 300 dpi and store data in ‘tiff’ uncompressed format for use by any raster to
vector conversion software.
3. Raster to Vector conversion using either Arc/Info GIS or CAD software.
4. Add Tic points (map sheet corner lat-long coordinates or any other known coordinate points –
preferably about 12 points) for easy transformation and map jointing at a later stage.
5. Edit to remove digitization errors, and clean and build topology.
6. Label features as per standard code / symbols in Look Up Tables.
7. Transform each coverage using same projection parameters (central meridien, standard
parallels, and false easting and northing etc.) for the State.
8. Check edgematching and map joining errors and error in co-registration of different layers.

March 2001 Page 59
Annexure III
Quality Control (QC)/Quality Assurance (QA) Strategy and Plan
1. Scope
The Hydrology Project envisages preparation of selected spatial data sets from multiple sources and
multiple formats through the services of State Remote Sensing agencies (RSA), which shall
subsequently be integrated with point measurements within the GIS system by HP agencies for
multiple analysis objectives. A formal QC/QA programme is the key to creating high quality data sets
in such an environment. The QC programme needs to be both preventive and pro-active, from project
conception to final digital data delivery, and also subsequently in the integration of multi-layer data
sets in the GIS environment.
Quality control in the GIS context is ‘ delivering data which precisely meets the product specifications
defined by the data producer or data user’. This is achieved through a two stage process:
1) implementing techniques and procedures that attempt to reduce errors and eliminate mistakes, and
2) reviewing all completed work to identify and correct errors before any product is released. High
quality data is that which has had minimal degradation in data integrity or very low error propagation
during the preparation of final digital GIS products.
Primary and secondary data in GIS include both geographical (spatial) information as well as attribute
data (descriptive information associated with the spatial data). Primary data collection covers fresh
conventional ground surveys and using GPS, and interpreting thematic information from aerial
photographs and satellite imagery. Secondary data collection compiles data from existing digital and
hardcopy documents. Since the quality of source data ultimately limits the quality of the final product,
selection of hardcopy and digital data sources and methods used to integrate these data are critical. A
review of literature indicates that the standards and specifications for secondary data collection and
information on QC measures for digital data are not readily found or easily developed. Generic step-
by-step QC/ QA procedures are also not well documented.
The HP requires spatial digital data sets in GIS format covering nine peninsular states, in tiles
corresponding to SOI maps in 1:50000 scale. The directory of HP GIS data base is shown in Table
2.1.) Primary data collection covers fresh preparation of land use, soil, geology and geomorphology
maps (where these are not available or suitable for HP) and further digitization. Secondary data
collection covers digitization of existing and suitable thematic (including SOI) maps, or procurement of
digital data sets compying with HP data acceptance criteria.
Delivery of high quality digital data will be supported by:
1. the methodology manual for generating spatial data sets and the QC/QA Test Strategy and Plan
document (prepared by the HP consultants),
2. procedure sheet and log sheet for each data set, operator log books and final QA report on
specific data quality elements and descriptors and certification of conformance with product
specifications (to be developed by State RSA),
3. the modality and reporting formats of external independent quality audit to be jointly developed by
HP Consultants and the State RSA, and
4. modality and reporting formats for acceptance testing of delivered products (to be developed
jointly between the Consultants and the State RSA)
At the production of GIS data site, the procedure sheet for each data set shall describe the detailed
and exact mapping and/or digitization procedure to be followed (including the actual software
commands) and the hardware/software environment to be used in generating the data set, such as a

March 2001 Page 60
land use coverage. The procedural log sheet for each data set records the actual progress and
development of the process, including the messages and transactions associated with the processing
generated by the hardware or software, and other details such as the date a specific task was
performed and who performed it. While log sheets are specific to each data set, log books are specific
to each operator. When a mapping task is involved the ground truth collection formats for a specific
data set shall be compiled in the form of a report. All thematic mapping and/or data conversion
personnel shall record in the logbook on a day-to day basis the data set they are working on, tasks
performed, and notes and problems associated. Logs of external independent audit shall also be
maintained by the vendor. The deliverable data product, after successful internal QC/QA, shall be
accompanied by a QA Conformance statement.
Creation of metadata (data content, quality and bibliography) and documentation on procedures for
integrating different data sets into the GIS are also vital in subsequent GIS database development
and maintenance through the years.
The QC / QA test strategy and plan includes what to test, how much to test, how to test quantitatively
and qualitatively, and acceptance criteria. The measures for various specified QC/QA elements shall
be evaluated through software tools, and visual checks in online or in hardcopy format. Successful
QC/QA strategy calls for iterative internal QC loops in the production process, independent internal
QA certification, and external independent quality audit at specific stages of production and
acceptance testing of delivered products. Maintenance of log books, procedural log sheets, and QC
reports at critical stages is an integral part of QC/QA process.
The proposed QC/QA test plan addresses both fresh thematic mapping and digitization of existing
and fresh thematic maps, generated through out-sourcing through State Remote Sensing agencies,
and ground hydrologic and hydrometeorological measurements (point locations and values) by HP
agencies. Section 2 covers QC/QA procedures in fresh thematic mapping while Section 3 addresses
similar procedures in digitization of fresh and existing thematic and topographic maps. Section 4
covers independent quality audit procedures, and Section 5 is on acceptance testing of delivered
products. Section 6 covers QC/QA aspects relating to subsequent integration of these spatial data
sets and the point measurements by HP agencies within the GIS environment.
It should be noted that standard QC/QA procedures and definition and acceptability criteria of
qualitative and quantitative measures of GIS data are still under development in India. This document
is an attempt to provide an initial QC/QA framework, which may evolve into a full fledged strategy
based on actual experience during spatial data preparation for GIS database development.
2. QC/QA in Fresh Thematic Mapping
Where HP specified thematic maps are not available as source maps, fresh maps are interpreted from
most recent satellite data. The QC procedure covers all the three stages: 1) Input stage - selection of
satellite data product, 2) Process stage - interpretation and mapping, 3) Product stage - certification of
final analogue map product.
2.1. Input stage - Selection of Satellite Data
Year: select normal rainfall year (in the context of land use mapping) within the preceding 5
years
Seasons: satellite overpass dates to cover the different agricultural seasons, and corresponding
to optimum ground coverage in each season
Sensor : select sensor with spatial resolution compatible to mapping scale

March 2001 Page 61
Product type :
Coverage
− geocoded/part of satellite data scene
− Corresponding SOI 1:50000 scale map numbers
Digital Format
− - 6250 BPI / 525 MB cartridge/ 5 GB 8 mm Exabyte DAT/ 650 MB CD-ROM;
− - LOGSOWG format and Band Interleaved/ Band Sequential type
Hard copy format:
− FCC film negative/ positive/ FCC paper print
Specifications:
Processing level
− no correction/ only radiometric correction/ radiometric and standard geometric correction/
precision geometric correction;
Locational accuracy
− value and reference to NRSA Data Centre document
Scale (if hard copy)
− 1:50000
Resampling technique
− no sampling/ cubic convolution/ nearest neighbour, projection
Enhancement used-
− no enhancement/ scene based enhancement
Area coverage
– lat-long corner coordinates and corresponding SOI map numbers.
The log sheet shall record the details of satellite data selected for thematic mapping of each data tile
(which corresponds to one SOI map in 1:50000 scale), and shall be signed by the interpreter and the
interpretation team leader.
2.2. Process Stage - Interpretation and mapping
Visual interpretation techniques are recommended to ensure uniformity and consistency between
multiple vendors. The interpretation of each map tile shall cover development of interpretation key,
preliminary interpretation, ‘ground truth’ collection, finalization of interpretation key, final thematic
mapping, and validation of classification and map parameters. Non- acceptable QA results shall result
in a second iteration till criteria are met. The QC checks cover 1) preparation of preliminary and final
interpretation key, 2)-ground truth collection and mapping, and 3) validation of classification and
mapping accuracy. The output of this stage shall be an analogue map with features delineated and
coded as per HP Methodology Manual. Symbolization and colouring are not recommended for this
working map, which forms the input to the digitization process.

March 2001 Page 62
When satellite derived thematic maps are mapped it is recommended to create a map of
administrative and hydrologic boundaries, settlements, and drainage (with reference to SOI map), and
use as base to transfer thematic details to ensure consistency between different layers.
The interpretation key shall cover category name, and description of interpretation elements such as
tone/colour, size, shape, texture, association, etc. The preliminary key shall be finalized based on field
visits, and include all thematic categories extant in the map tile and the revised interpretation
descriptors. The QC log sheet at this stage shall check for preparation of keys, completeness of
categories covered in the map tile, and flagging and explaining any large variation between
preliminary and final keys. Any inconsistency between keys of adjacent sheets shall also be flagged
and briefly explained. The sheet shall be signed by the interpreter and the interpretation team leader.
It is difficult to define a quantified measure of acceptable ground truth to support interpretation, in view
of tile-to-tile differences in the ground context, or possibility to optimize field data collection in
contiguous areas of ground homogeneity. It is recommended that in each map tile typically 3 sites be
visited for each specified land use category, and distributed across the scene to cover possible
variability. In soil mapping about 20 profiles and about 60 to 100 samples shall be studied. The
requirement in geological and geomorphologic mapping shall be restricted to doubtful
boundaries/contacts, random sample checks for confirmed boundaries and field evidence of inferred
faults/fractures and shear zones. The QC check at this stage shall cover review of field log book,
containing the overview of ground truth collection programme, a small scale map showing locations of
field visit, and compilation of completed standard proforma for each visit location. While the site-
specific proforma shall be signed by the personnel conducting field visit and the interpreter, the log
book shall be certified by the interpreter. Since the geocoded satellite imagery is not precision
corrected and has residual geographic inaccuracy, the interpreted features have to be transferred and
adjusted into the base map.
The third QC check shall cover completeness and accuracy of thematic classification and mapping.
The overall and category –wise thematic accuracy shall be measured by the Kappa Coefficient based
on the matrix of commission and omission errors. The statistical sample size for field validation shall
be defined based on number of primary sampling units and the target accuracy and confidence level.
Randomly selected and accessible points in ground shall be visited and compared with classification
to develop the error matrix.
The map shall be checked for logical consistency, positional accuracy and completeness. Logical
consistency check shall compare settlement location, drainage, and forest boundary between satellite
derived thematic maps and SOI map. Consistency between different thematic layers also needs to be
checked, such as between soil categories and physiography. Extension of line and polygon features
and identical labeling of such features with adjoining sheets is another test of logical consistency.
Positional accuracy in regard to scale and location shall be evaluated with reference to corresponding
SOI map. Map completeness shall be checked for feature coding, feature continuity, and existence of
appropriate number of tick marks (about 12 points recommended) and map title and number map
number (eg. Landuse54J14 – theme as prefix and SOI map number). Cartographic checks include
use of standard tracing film (Garware 75 microns) and Rotring or equivalent pen of appropriate line
thickness (as per guidelines followed in national programmes such as IMSD or RGDWTM). The QC
results shall be included in the log sheet and signed by the interpreter and a second independent
internal auditor. Non-conformance with acceptance criteria shall result in a further iteration of
classification process till acceptance. The final iteration shall be signed by the interpreter, independent
auditor and the team leader.
2.3 QA of Final Map Product
The QA certification shall be performed by the QA Division or an independent team within the RSAs
office. The inputs to the QA process shall be log books and log sheets at different stages and
randomly selected sample maps (25 percent of total number in each theme in each vendor site). The
QA shall evaluate:

March 2001 Page 63
i) Appropriate selection of satellite data
ii) Ground truth collection
iii) Final interpretation key
iv) Classification accuracy
v) Logical consistency
vi) Map accuracy
vii) Map completeness
The parameters and acceptance criteria are listed in Table 1. The QA report shall be signed by the
independent auditor and the project leader. Any rejection report shall result in a second iteration of
map till the criteria are met. Large scale rejection of sampled maps (greater than 25 percent) shall call
for 100 percent inspection of maps.
Parameters Acceptance Criteria
Appropriate selection
of satellite data
Use of satellite data of required specifications (age, two season data,
overpass dates near full ground cover, additional summer data for soil
mapping, geocoded product)
Ground truth collection as specified in QC document, including use of standard proforma for each
site visited, and proper recording of field data including analysis of soil
samples
Final interpretation key Use of standard terminology, consistency with general domain
understanding and with adjoining sheets
Classification
accuracy
Minimum mapping unit 1 ha; Overall Kappa accuracy greater than 95 % at
95 percent confidence level (and selected category-wise accuracy better
than 90 %)
Logical consistency Consistency with other themes and topography; consistency of features
and labels with adjoining sheets
Map accuracy RMS error less than 25 m in comparison with SOI map
Map completeness no incomplete or erroneous features and attributes; lat-long tick marks
(preferably about 12); linear scale
Table 1: Acceptance Criteria for Freshly Generated Thematic Maps Using Satellite Data
The map (planimetric) accuracy is based on the root mean square error computed from a comparison
of coordinates of more than 30 well defined points. The acceptable limit is prescribed taking into
account the inherent positional error in the satellite image product, and the visual interpretation
procedure, the method of part-by-part transfer of details on the base map and the error in measuring
the coordinates. The method of measuring classification accuracy is described in the methodology
manual.
3. QC in Digitization
The QC checks are performed at i) pre-digitization stage, ii) digitization stage, and iii) post-digitization
stage.
3.1 QC in Pre-digitization Stage
Unlike primary data, secondary source maps used in building the GIS database need to be checked
for consistency, accuracy and completeness. While the fresh thematic maps generated under HP
have gone through a QC/ QA screening, secondary data sources (existing source maps) may suffer
from a wide range of errors. A preliminary screening of existing source data is performed based on
available QC/QA records, and evaluation of sample maps (10 percent of total number). If
unacceptable deviations from HP criteria are noticed it is recommended to resort to fresh thematic
mapping since correction and revision of existing maps will be impractical.

March 2001 Page 64
3.1.1. Satellite derived thematic maps
All source maps are visually scanned for cartographic clarity, physical condition, and completeness
(features and codes/symbols/colours) and obvious errors such as missing line segments. Registration
with topographic map and with other thematic maps shall then be checked for consistency and
corrected where appropriate. Logical consistency between themes, and of common features such as
drainage line, settlement and water bodies, shall also ensured. Positional/projection accuracy shall be
evaluated with reference to SOI map of 1:50000 scale. While the HP agency shall take all care to
supply acceptable source maps (based on QA certification of these maps or based on sample
evaluation) the RSA shall verify compliance with HP standards for source data before proceeding on
digitization.
The acceptance criteria for existing source maps and digital data sets are listed in Table 2 and 3. The
map and digital data sets shall be available in spatial tiles corresponding to SOI map in 1:50000 scale.
Parameter Acceptance Criteria
Age of map As per HP Methodology Manual
Lineage derived from IRS IC LISS III satellite data
Physical condition map shall not be torn/patched/folded; shall be on tracing film/paper with
dimensional stability like Mylar; preferably original map, and not optically
reproduced
Cartographic clarity features shall be clear & unambiguous; scannable symbols and colour
scheme; existence of lat-long tick marks
Classification content Scheme as per HP Methodology Manual
Accuracy better than 90 % at 90 % confidence level
Data completeness no missing line segment, polygon errors & attribute code
Positional accuracy less than 25 m in comparison with SOI map
Map projection Polyconic
Logical consistency 100 %
Table 2: Acceptance Criteria for Existing Source Maps derived from Satellite Data
Parameter Acceptance Criteria
Positional Accuracy less than 12.5 m with corresponding SOI map
Projection Polyconic
Data completeness 99 % (no missing / erroneous features, matching attribute codes)
Attribute accuracy 99 %
Edgematching 99 %
Table 3: Acceptance Criteria for Existing Digital Data sets
3.1.2. SOI Maps
SOI maps generally undergo a rigorous QC/QA process and hence are acceptable as source maps
without any need for preliminary screening. It would be desirable to use the colour separates of
topographic maps (available from SOI) corresponding to selected themes of drainage, settlements,
transport network and contours and spot heights. When paper maps are used as source, these shall
be in good physical condition and not folded. Maps of most recent publication year shall be used. The
dimensional stability of the printed map can be evaluated when necessary from the dimensional
values and coordinates of cutting points provided by SOI for each sheet.

March 2001 Page 65
3.2. Digitization Process
The digitizing process is similar whether the source map is derived from satellite data or published by
SOI. QC checks at this stage mainly covers distortion checks on the scanned images, digitization
consistency, line segment accuracy and attribute accuracy. Digitization consistency shall be ensured
by use of procedural log sheets and specific technical guidelines for digitization.
The scanner specifications are set at 300 dpi or better, colour and output in TIFF uncompressed
format. The digitizing environment shall preferably be ArcEDIT.
Following each machine process in digitization, preliminary checks shall be made by the digitizing
personnel using the digitization software for acceptable tolerance limits. One such check covers errors
of omission (features overlooked during digitizing) and commission (feature digitized more than once).
A report shall be generated on the number of map features in a coverage and tallied with the number
in the source map. In a similar sense the attribute files shall be reviewed (by comparing the number of
records in the file with the number of features that should have been coded. Scanning for empty or
zero value fields also indicate attribute coding omissions. and errors identified for correction.
Topographical integrity shall also be checked for correct definition of features. The software flags non-
connected lines or open polygons on-screen, while unlabelled polygon errors shall be checked by
comparing the number of attribute labels with the number of digitized polygons.
The next step in the QC procedure is the checking an edit plot, either online or in hard copy format.
The edit plot is at the same scale as the source map, and contains all features and their attribute
codes. Edit plots shall be checked against the source map on the screen (when digitally superposed)
or a light table for logical consistency or topological integrity, such as slivers, pseudo-nodes and
polygon errors including unclosed polygons, overlapping polygons, wrong labeling, unlabelled
polygons, or polygons with more than one label point. Typically the digitized feature may deviate from
its location on the source map by the width of one pen line on the edit plot. Use of proper names and
spelling shall also be checked. After error correction, the new edit plot of all features and labels are
made in the same scale as source map, and shall be compared. Another technique to check feature
omission and attribute coding errors involves comparison of spatially adjacent coverages, either on-
screen or on hard copy. The features along the common edge shall be identical as also the attribute
code.
Attribute accuracy includes checking for standard terminology, and missing or illogical entry in item
fields. Reduction in attribute errors shall be ensured through defining data dictionary, or by
predefining a menu’ pick list’ of attribute values and terminology. In addition to attributing the coverage
features with an ID number and feature code, the bulk of information shall be contained an a dBASE
file, related to the coverages by the ID number or feature code. Typically the table shall include the
category description and other associated information. QC of this database shall also performed with
macros for inaccurate data entry, missing data, and table relationships.
The positional accuracy shall be checked by comparing the digital coordinates of atleast 30 ground
control points and computing the root mean square error. The points shall be well distributed over the
map sheet area, and shall be well defined, such as road junction, road-canal intersection, sharp bend
in drainage and similar non-changing features. The RMS error in the transformation process is kept
less than 12.5 m. The evaluation of scale accuracy shall be based on a minimum of 20 straight lines,
and the error shall be contained within 0.3 mm.
All data shall be in correct projection, and each coverage shall have defined projection parameters.
Snapping and edge matching shall be performed to reduce errors of commission and omission. QC
shall be performed by snapping nodes between coverages and mapjoining across data layers. The
final digital data shall be in Arc/Info export (e00) file format.

March 2001 Page 66
The first review edit shall first be performed by the digitizing personnel and corrected, and the second
edit by another independent internal team. The QC at this stage shall be 100 percent.
3.3. QA at Post-digitization Stage
Final digital data are delivered as master coverage for each data layer (as hard copy and GIS files)
and related ‘look up table’ in dBASE. Post- digitization QA procedures evaluate the deliverable
product against the product specifications (Table 4). It is recommended that at least 50 percent of
each data layer be checked. The QC reports in the preceding stages shall also be reviewed.
Final plots of features and attributes shall be compared with the original source maps, and checked
for accuracy. The QA feedback report shall provide certification on conformance to standards and
specific comments on the type of error, description and location for correction. Rejection report shall
invite a second iteration till acceptance criteria are met. The acceptance certificate shall be signed by
the independent QA unit, and lead to product delivery.
Parameter Acceptance criteria
File naming, directory structure, readability, data
structure , formats
100 %
Positional accuracy less than 12.5 m
Topological integrity
- accuracy
- completeness
99 %
99 %
Attribute accuracy 99 %
Edgematching 99 % (on account of anomalies
inherent in the source maps)
Table 4: Acceptance Criteria for Final Spatial Data Product
4. Independent Quality Audit
In addition to in-house QC/QA at vendor site, it shall be desirable to conduct independent audit of the
digitizing services and products at different key stages. The methodology principally consists of review
of QC records and procedures followed by the RSAs, and testing of intermediate products (on sample
basis) under progress at RSA site and verifying the authenticity of QC/QA records. The modality and
reporting formats of external independent quality audit to be jointly developed by HP Consultants and
the RSA.
5. Acceptance Test of Delivered Products
The delivered digital data products shall be tested on sample basis, and accepted for HP. The
modalities and reporting formats shall be jointly developed by the Consultants and the RSAs for data
conversion services.
6. QC/QA in Integrating Spatial Data and Point Data in HP GIS Database
The spatial data sets produced through RSAs shall be supported by the accompanying QA statement,
and hence QC procedures at integration stage in the State and National Data Centres shall mainly
cover checks to ensure that no unexpected errors are introduced during the database creation
process, and that the thematic layer is consistent with other layers which describe identical features or
associated features, or other layers such as on measurement sites. Any unacceptable logical
inconsistency may require clarifications and if necessary regeneration as per HP QA standards. The
GIS directory shall be updated to include the data layers that have been integrated.

March 2001 Page 67
When digital satellite derived theme coverages are imported into GIS it is recommended to create a
template layer of administrative and hydrologic boundaries, settlements, surface water bodies, and
drainage, and use as common base (eg. ‘Union’ spatial operation in Arc/Info GIS software and edit
features) to ensure logical consistency between different layers.
GIS layers showing point location of measurement sites have been generated. This data shall be
subjected to QC for positional accuracy, attribute accuracy, completeness, logical consistency, and
temporal accuracy, and QA statement generated for the data set prior to integration in GIS. If
necessary fresh data set shall be generated with acceptable quality measures.

March 2001 Page 68
Annexure IV
Format for Textual Report accompanying Digital Spatial Dataset
Report for Theme _________________ SOI Map Sheet No. ____________
Prepared by Agency____________________________________________________
Generation Date ______________
Source Data :
1) For fresh thematic mapping: Specify satellite data specifications including satellite and sensor Id,
product type and quality parameters and date of acquisition
2) For existing source maps: Specify map title and scale, map content (including classification
scheme), geographic coverage, quality/ accuracy specifications, dates of publication and survey, data
collection modality, current source of map, generating agency, and publication reference.
Collateral Data: Specify data type and scale (if map), date of data, source of data and publication
reference.
Interpretation Methodology: Interpretation key, field visit period, places and data collected, offices
contacted and objective of data collection (to aid interpretation, estimation of classification accuracy)
Output Data : digital data set Id and specifications (as per parameters in Table 2.2 )
Quality Assessment : enclose internal QC/ QA report and external QA inputs
Contact Address in Vendor Office :

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