Digital Soil Mapping Tools and Methods 1
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The document focuses on developing a database for Digital Soil Mapping (DSM), emphasizing user-friendly features and necessary software tools. It outlines steps for obtaining and documenting soil data from various sources, creating a workspace for DSM processes, and providing examples of data acquisition methods. Additionally, it includes guidance for building a geo-database, detailing the characteristics of the data that should be documented and reported.
Digital Soil Mapping Tools and Methods 1
- 1. DSM TOOLS AND METHODS Day1: Lecture 3
- 2. Database development • The core of DSM • Features – It should be user friendly – It should contain adequate information – Amenable to DSM software • Software – MS Office – QGIS – ILWIS
- 3. Obtaining DSM data • Clarify what is to be done (Map properties/classes) • Specify type of data needed • Identify sources and summarize data availability • Document available data and check for gaps • Obtain the data Data Type Source Soil Soil profiles ISRIC (http://www.isric.org/data/isric-wise-global-soil-profile-data-ver-31) Soil maps UN-FAO (http://www.fao.org/soils-portal/soil-survey/soil-maps-and- databases/soil-profile-databases/en/) IIASA (http://www.iiasa.ac.at/web/home/research/modelsData/HWSD/HWSD.en.html) Soil legacy reports FAO (http://www.fao.org/soils-portal/soil-survey/soil-maps-and-databases/soil- legacy-reports/en/) Laboratory analytical data National soil laboratories, research institutes (e.g. NGOs, Universities, etc) Remote sensing image MODIS NDVI (250 m) USDA (http://pekko.geog.umd.edu/usda/apps/) Land cover (300 m) ESA (http://due.esrin.esa.int/globcover/) Landsat (30 m) GLCF (http://glcf.umd.edu/data/) Cover (< 30 m) National aerial photo missions DEM SRTM (90 m) http://srtm.usgs.gov/ ASTER (30 m) http://asterweb.jpl.nasa.gov/gdem.asp DEM (<30 m) National contour maps Geology 1:1 M National geologic maps > 1:1 M Sub-regional (sub-national) geologic maps Climate Rainfall National meteorological departments Create DSM workspace C:DSM - where we will work C:DSMInput - where to keep input data C:DSMOutput - where to keep output data
- 4. Example data acquisition • Interest: to map clay content • Identified study area – in Makueni (Kenya) • Data sources – ISRIC – soil profiles – EUSOILS – Soil map – Government soil department – soil profiles – Academic institution – soil profile • Document the data availability and gaps Soil data
- 5. Download online data • Soil map at http://eusoils.jrc.ec.europa.eu/esdb_archive/ eudasm/africa/index.html • Soil profile at http://www.isric.org/data/isric-wise-global-soil- profile-data-ver-31 • Other soil data – Gvt – Academic institution
- 6. Obtaining data from EUSOIL Example
- 7. Example of downloaded map
- 8. Obtaining data from ISRIC Example
- 9. Other examples: online data acquisition • Land cover http://due.esrin.esa.int/globcover/ • DEM http://srtm.usgs.gov/ • Other (Gvt departments) – Rainfall – Geology – Landform Environmental covariate data
- 10. Example: 300 m Land cover (2009)
- 11. Example: 30 m DEM
- 13. Which soil data is available Which environmental covariate is available Detailed soil map with Legends and soil data Soil point data with site description Detailed soil map with legend No data All covariates C, O, R, P At least 3 covariates Including R & O At least 2 covariates Including R Only one covariate No data Increasing level of data inadequacy Climate (C) Organism (O) Relief (R) Parent (P) Relief (R) Organism (O) Relief (R) Climate – mean rainfall (map or weather station data) Organism – Land use/land cover Relief – Elevation map (DEM) Parent – Geology map Soil – georeferenced soil properties, profile, map
- 14. Data Type Number Source
- 15. Assignment: Building geo-database for DSM application-STEP 1 • Use your own data • Explore the data • Document the characteristics of the data: – Source and author of data – Data type (profile, analytical, georeferenced, maps, etc.) – Number of samples/cases – Use the table format (use Data, Type, Number, Source, as column heading) • Save the database & documentation (C:DSMInput) • Remember to hand in your work by Next Morning before start of the session