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Pavan Kumar · Haroon Sajjad
Bhagwan Singh Chaudhary
J. S. Rawat · Meenu Rani Editors
Remote
Sensing and
GIScience
Challenges and Future Directions

Pavan Kumar • Haroon Sajjad
Bhagwan Singh Chaudhary • J. S. Rawat
Meenu Rani
Editors
Remote Sensing and
GIScience
Challenges and Future Directions

Editors
Pavan Kumar
College of Horticulture and Forestry
Rani Lakshmi Bai Central Agricultural
University
Jhansi, Uttar Pradesh, India
Haroon Sajjad
Department of Geography, Faculty of
Natural Sciences
Jamia Millia Islamia
New Delhi, Delhi, India
Bhagwan Singh Chaudhary
Department of Geophysics
Kurukshetra University
Kurukshetra, Haryana, India
J. S. Rawat
Remote Sensing and GIS
Kumaun University
Almora, Uttarakhand, India
Meenu Rani
Department of Geography
Kumaun University
Nainital, Uttarakhand, India
ISBN 978-3-030-55091-2 ISBN 978-3-030-55092-9 (eBook)
https://doi.org/10.1007/978-3-030-55092-9
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland
AG 2021
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether
the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of
illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and
transmission or information storage and retrieval, electronic adaptation, computer software, or by
similar or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
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claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Switzerland AG
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Foreword
Remote sensing (RS) has emerged as an important technique and tool that blends
developments in computer science and Geographical Information System (GIS) for
analyzing the various dimensions of the environment and adheres to its applications in
almost every ﬁeld. Remote sensing being cost and time effective is helpful in analyzing
the temporal and spatial pattern of natural resources and distribution of population. The
multispectral remote sensing datasets have provided effective assessment of natural
resources and their management. These datasets are also promising in determining the
population pattern, urban sprawl, and changes in land use/land cover. RS and GIScience
have been proved effective tools for the scientiﬁc community to analyze spatial
phenomena on Earth and consequently for policy formulation globally. However,
certain challenges in handling large datasets and complex data formats still remain.
This book provides a comprehensive compilation of the use of remote sensing and
GIS for different applications. Agriculture productivity, air pollution, habitat suitability
mapping, assessment of vegetation vigor, as well as various data sets and their applica-
tions in assessment of natural resources, mapping the population pattern, and land
use/land cover will help the readers to obtain insightful information about the complex-
ity and challenges in their assessment. This book provides imperative assessment based
on remote sensing technique for measuring the spatio-temporal variability of population,
dynamics of land use, natural resources, and their sustainable management. I believe this
work will help different stakeholders to understand different aspects of remote sensing
along with the application of GIScience for various applications.
I congratulate the editors, the contributors’ from different parts of the country,
and the publisher for bringing out a timely publication depicting challenges and
future directions in remote sensing and GIScience and hope that this important book
shall serve as a reference for different institutions working in this area.
Vice-Chancellor, Rani Lakshmi Bai
Central Agricultural University, Jhansi,
Uttar Pradesh, India
Prof. Arvind Kumar
v

Contents
Part I General
Introduction to Challenges and Future Directions in Remote
Sensing and GIScience . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Raihan Ahmed, Pavan Kumar, and Meenu Rani
Part II Challenges in Sustainable Natural Resources Management
Environmental and Livelihood Impact Assessment of 2013 Flash
Flood in Alakananda and Mandakini River Valley,
Uttarakhand (India), Using Environmental Evaluation
System and Geospatial Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
Shruti Tripathi, G. Areendran, N. C. Gupta, Krishna Raj,
and Mehebub Sahana
Assessment of Vegetation Vigor Using Integrated Synthetic
Aperture Radars . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
Suman Sinha
Landslide Susceptibility Mapping Using Bivariate Frequency
Ratio Model and Geospatial Techniques: A Case from Karbi
Anglong West District in Assam, India . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Raihan Ahmed, Ravinder Singh, and Haroon Sajjad
Retreating Glacier Dynamics Over the Last Quarter of a Century
in Uttarakhand Region Using Optical Sensor Time Series Data . . . . . . . 75
Himanshu Kalita, Tapan Ghosh, Meenu Rani, J. S. Rawat,
Ram Kumar Singh, Susheel Kumar Singh, and Pavan Kumar
vii

Part III Remote Sensing and GIScience in Urban Growth
Management
Studying the Impact of Urbanization on HYV Rice Fields
at a Local Level Using Fine Resolution Temporal
RISAT-1 Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97
Koel Roychowdhury
Identiﬁcation of Impervious Built-Up Surface Features Using
ResourceSat-2 LISS-III-Based Novel Optical Built-Up Index . . . . . . . . . 113
Abhisek Santra, Shreyashi Santra Mitra, Suman Sinha, Shidharth Routh,
and Akhilesh Kumar
Subsidence Assessment of Building Blocks in Hanoi Urban
Area from 2011 to 2014 Using TerraSAR-X and COSMO-SkyMed
Images and PSInSAR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Van Anh Tran, Quoc Cuong Tran, Duc Anh Nguyen, Tong Minh Dinh Ho,
Anh The Hoang, Trung Khien Ha, and Dieu Tien Bui
Analysis of Land Use/Land Cover Mapping for Sustainable
Land Resources Development of Hisar District, Haryana, India . . . . . . . 151
B. S. Chaudhary, Reeta Rani, Sanjeev Kumar, Y. P. Sundriyal,
and Pavan Kumar
Part IV Challenges and Future Directions in GIScience
A Spatial Investigation of the Feasibility of Solar Resource
Energy Potential in Planning the Solar Cities of India . . . . . . . . . . . . . . 169
Koel Roychowdhury and Radhika Bhanja
Mapping Rice Growth Stages Employing MODIS NDVI
and ALOS AVNIR-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
Dyah R. Panuju, David J. Paull, Amy L. Grifﬁn,
and Bambang H. Trisasongko
Habitat Suitability Mapping of Sloth Bear (Melursus ursinus)
in the Sariska Tiger Reserve (India) Using a GIS-Based Fuzzy
Analytical Hierarchy Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
Purva Jain, Raihan Ahmed, Haroon Sajjad, Mehebub Sahana,
Abolfazl Jaafari, Jie Dou, and Haoyuan Hong
Estimation of Air Pollution Using Regression Modelling Approach
for Mumbai Region, Maharashtra, India . . . . . . . . . . . . . . . . . . . . . . . . 229
Maya Kumari, Shivangi S. Somvanshi, and Syed Zubair
Mapping of Agriculture Productivity Variability for the SAARC
Nations in Response to Climate Change Scenario for the Year 2050 . . . . 249
Ram Kumar Singh, Vinay Shankar Prasad Sinha, Pawan Kumar Joshi,
and Manoj Kumar
viii Contents

Part V GIScience for Revolution in Science and Society
Future Direction of GIScience for Revolution in Science
and Society Over the Past 20 Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
Bharat Lal, Susheel Kumar Singh, Meenu Rani, Abhishek Kumar Shukla,
and Pavan Kumar
Contents ix

About the Editors
Pavan Kumar is a Faculty Member at the College of Horticulture and Forestry,
Rani Lakshmi Bai Central Agricultural University, Jhansi, U.P., India. He obtained
his Ph.D. degree from the Faculty of Natural Sciences, Jamia Millia Islamia, New
Delhi. Dr. Kumar completed his B.Sc. (Botany) and M.Sc. (Environmental Science)
at Banaras Hindu University, Varanasi, India, and subsequently obtained Master’s
degree in Remote Sensing (M.Tech.) from Birla Institute of Technology, Mesra
Ranchi, India. His current research interests include climate change and coastal
studies. He is recipient of Innovation China National Academy Award for Remote
Sensing. Dr. Kumar has published 50 research papers in national journals and
authored a number of books. He has visited countries like the USA, France, the
Netherlands, Italy, China, Indonesia, Brazil, and Malaysia for various academic/
scientific assignments, workshops, and conferences. Dr. Kumar is member of the
International Association for Vegetation Science, USA and Institution of Geospatial
and Remote Sensing, Malaysia.
Haroon Sajjad is Professor in the Department of Geography, Faculty of Natural
Sciences, Jamia Millia Islamia, New Delhi, India. His present research interests
include environmental management, sustainable development, watershed manage-
ment, and applications of remote sensing and GIS. He authored four books and has
published more than hundred research papers in journals of international repute.
Prof. Sajjad has presented 50 research papers at national and international confer-
ences. Ten scholars have been awarded doctoral degrees under his supervision. He is
reviewer of many scientific research journals and member of various scientific
bodies.
Bhagwan Singh Chaudhary is currently working as Professor and Chairman in the
Department of Geophysics at Kurukshetra University, India, since December 2017.
He is also Registrar (offg.) of Kurukshetra University since June 5, 2020. Prof.
Chaudhary has also worked as Founder Registrar at Chaudhary Bansi Lal University,
xi

Bhiwani, from Aug. 2014 to Dec. 2017. He started his career as Scientist at Haryana
Space Application Centre, Hisar, in 1990 and worked there till 2004. Prof. Chaudhary
was awarded DAAD Fellowship at the University of Freiburg, Germany, from 1997
to 1999. He has been working in the domain of geospatial technology for natural
resources for about 30 years and has published more than 70 research papers in
various national and international journals/conferences. Prof. Chaudhary has visited
many countries like the USA, the UK, Austria, Germany, France, the Netherlands,
Switzerland, Poland, China, South Africa, Indonesia, Bangladesh, Sri Lanka, Nepal,
and Thailand for various academic/scientific assignments and conferences.
J. S. Rawat is presently Director of the Centre of Excellence for Natural Resources
Data Management System in Uttarakhand (COE NRDMS), Coordinator of M.Sc.
Remote Sensing and GIS Course at Kumaun University, and Director of
Uttarakhand Centre on Climate Change. He is a Gold Medalist of Kumaun Univer-
sity and was awarded Senior Fulbright Fellowship by the Council for International
Exchange of Scholars, Washington, D. C., USA, in 1988. Prof. Rawat has published
about 122 research papers in international/national journals/books; written 3 books;
participated in 15 international conferences including in Canada, Germany, and
China; and participated in 89 conferences/expert committee meetings in India.
Meenu Rani received her M. Tech. degree in Remote Sensing from Birla Institute
of Technology, Ranchi, India. She is currently affiliated to the Department of
Geography, Kumaun University, Nainital, Uttarakhand, India. Dr. Rani has worked
on remote sensing applications as a Junior Research Fellow at HARSAC and as
Research Associate at the Indian Council of Agricultural Research and GB Pant
National Institute of Himalayan Environment and Sustainable Development.
Dr. Rani has authored and co-authored several peer-reviewed scientific research
papers and presented works at many national and international conferences includ-
ing the USA, Italy, and China. She has been awarded with various fellowships from
the International Association for Ecology, Future Earth Coast, and SCAR Scientific
Research Programme. Dr. Rani received early career scientists achievement award in
2017 at Columbia University, New York, USA.
xii About the Editors

Introduction to Challenges and Future
Directions in Remote Sensing and GIScience
Raihan Ahmed, Pavan Kumar , and Meenu Rani
Abstract This book provides an overview of remote sensing and GIScience (GIS)
and their challenges and future directions. Modern technology like remote sensing
and GIS with timely and accurate information helps to monitor and analyze a wide
range of phenomena like water, vegetation, land, and human activities. Inter-
disciplinary studies are also noticed in human–environment interaction between
stakeholders and decision makers for real world applications. Remote sensing data
products and their limitations are also discussed in the book. To overcome this
situation, artiﬁcial intelligence (AI), along with cloud computing and big data
analytics, is the need of the hour. Decision support system based on the AI in remote
sensing and GIS is key to the implementation of decision-making and planning in a
sustainable manner. The book is segregated into 5 parts spreading over 15 chapters.
Part I discusses the challenges and future direction of remote sensing and GIS in
various ﬁelds. Chapters 2–5 in the second part are devoted to challenges in sustain-
able natural resources management. Various applications of remote sensing and GIS
in urban growth management are presented in Chapters 6–9 of Part III. In Part IV,
challenges and future directions in GIS have been discuss in Chapters 10–14 through
GIS modeling. Part V devoted to one chapter deals with the GIS revolution in
science and society.
Keywords Remote sensing · GIScience · Challenges and Future direction
R. Ahmed
Department of Geography, Faculty of Natural Science, Jamia Millia Islamia, New Delhi,
Delhi, India
P. Kumar (*)
College of Horticulture and Forestry, Rani Lakshmi Bai Central Agricultural University, Jhansi,
Uttar Pradesh, India
M. Rani
Department of Geography, Kumaun University, Nainital, Uttarakhand, India
© The Editor(s) (if applicable) and The Author(s), under exclusive license to
Springer Nature Switzerland AG 2021
P. Kumar et al. (eds.), Remote Sensing and GIScience,
https://doi.org/10.1007/978-3-030-55092-9_1
3

Development of remote sensing and GIScience (GIS) is crucial for scientific explo-
ration of the earth’s system, such as hydrosphere, lithosphere and biosphere. The
phenomenon of the earth’s system such as natural and human-induced has much
significance in today’s world. Remote sensing and GIS are modern technologies
with timely and accurate information. Information access through these technologies
helps to monitor and analyze a wide range of phenomena like water, vegetation,
land, and human activities. It also helps to explore the potential natural resources for
human use. Therefore, it is being used widely in various disciplines and multi-
disciplinary subject areas for decision-making and problem-solving processes.
The human–environment interaction (HEI) plays a key role in the dynamics of
global environmental system. HEI analysis uses disparate datasets for every partic-
ular study. However, there are some similarities between methods and techniques in
remote sensing and GIS practitioners. It creates an inter-disciplinary study in HEI
and collaboration between authors of various disciplines. Increased collaboration
beyond academics is also seen nowadays by stakeholders and decision makers for
real world applications. Remote sensing and GIS provide information through data
mining and processing. Therefore, ground reference data inclusion in remote sensing
and GIS are crucial for the relevance of every study.
In the era of industrialization and climate change, HEI deteriorates the earth’s
biosphere and its carbon and hydrological cycles. To overcome this problem, a large
amount of data and processing power is required along with the decision-making
system. This is the main challenge for remote sensing and GIS, which have large
spectrum of data with various limitations. Remote sensing data products are avail-
able with various spatial, spectral, and temporal resolutions. Therefore, studies use
site-specific data products to fulfill the need of the specific study. For example,
temporal changes in urban land use need high spatial, which requires large storage of
data with specific time interval. Therefore, storage as well as processing need time
for this kind of research. Some studies need spectral resolution for identifying the
objects. Hyperspectral remote sensing data products with high spectral resolution
have provided satisfactory results for this kind of research.
Promising solutions for these challenges can be obtained with the help of cloud
computing and big data analytics. It is obvious that artificial intelligence (AI), along
with cloud computing and big data analytics, is the future of remote sensing and GIS.
Decision support system based on AI in remote sensing and GIS is the key to the
implementation of decision-making and planning in a sustainable manner. Visuali-
zation of spatial data in GIS is a way forward to achieve planning and decision-
making for stakeholders. It helps decision makers to take action based on the data
visualization through GIS, e.g., natural hazards, urban planning, environmental
management, and crime. Prediction and modeling of natural hazards are extremely
difficult in the real world due to its complex nature. Till date, there is no such method
to predict the results with zero uncertainty. AI has achieved the deal with precision
modeling for complex problems of the earth’s system. It can analyze the different
aspects with sufficient detail and iteration for a complex problem.
Google Earth Engine is a platform based on cloud computing to analyze the
geospatial data. It has massive computational capabilities to analyze a large amount
4 R. Ahmed et al.

of spatial data in a short time period. The advantage of this platform is to analyze
spatial data without storing them in personal computers. Therefore, it helps to
process large scale studies such as those at regional and country levels with efficient
results. An attempt has been made in this book by the contributors to evaluate the
efficiency of remote sensing and GIS techniques through various studies. Chapters in
this volume have been grouped into five parts: General, Challenges in Sustainable
Natural Resources Management, Remote Sensing and GIScience in Urban Growth
Management, Challenges and Future Directions in GIScience, and GIScience for
Revolution in Science and Society. Part I deals with the usefulness of remote sensing
and GIS in various field of study. It covers the applicability of remote sensing and
GIS in HEI, natural hazards, and environmental management. The future of remote
sensing and GIS in the light of AI, cloud computing, and big data analytics is also
focused on in this part.
Part II deals with the Challenges in Sustainable Natural Resources Management.
It comprises four chapters concentrating on flood, vegetation, landslide, and glacier
retreat and their direct and indirect impact on natural resources. In chapter “Environ
mental and Livelihood Impact Assessment of 2013 Flash Flood in Alakananda and
Mandakini River Valley, Uttarakhand (India) Using Environmental Evaluation
System and Geospatial Techniques,” Tripathi et al. made an attempt for environ-
mental and livelihood impact assessment of 2013 disastrous flood in Mandakini
valley. They used Landsat data product for preparing land use land cover (LULC)
maps and the statistical changes were estimated in the respective LULC classes. The
results showed significant changes in terms of LULC dynamics in the whole region.
In chapter “Assessment of Vegetation Vigor Using Integrated Synthetic Aperture
Radars,” Sinha assessed the vegetation using Integrated Synthetic Aperture Radars
(SAR). In the study, the author uses SAR data to estimate forest biomass. Study
shows a suitable approach in assessing vegetation vigor from above ground biomass
through SAR. In the chapter “Landslide Susceptibility Mapping using Bivariate
Frequency Ratio Model and Geospatial Techniques: A Case from Karbi Anglong
West District in ASSAM, India,” Ahmed et al. made an attempt to prepare an
inventory map of landslide susceptibility using geospatial technology and bivariate
frequency ratio model for Karbi Anglong West district. The study revealed that
frequency ratio model along with geospatial technique helped not only in identifying
landslide prone areas but also proved to be instrumental in examining level of
susceptibility. In the chapter “Retreating Glacier Dynamics Over the Last Quarter
of a Century at Uttarakhand Region Using optical Sensors Time Series Data,” Kalita
et al. examined the retreating glacier dynamics over the last quarter of a century in
Uttarakhand. In their study, they used optical remote sensing data products for
examining the changes from 1994 to 2015 and changes detected for snow and
vegetation were 1377 km2
and 896 km2
, respectively. The study results showed
the actual determination of glacier dynamics and its kinetic of change rate and how
climate is impacting over snow and ice resources.
Part III deals with the Remote Sensing and GIScience in Urban Growth Manage-
ment. It contains four chapters focusing on the impact of urbanization on agriculture,
impervious built-up, building subsidence, and LULC for land resource development.
Introduction to Challenges and Future Directions in Remote Sensing and GIScience 5

In the chapter “Studying the Impact of Urbanization on HYV Rice Fields at a Local
Level Using Fine Resolution Temporal RISAT-1 Datasets,” Roychowdhury and
Bhanja assessed the Impact of urbanization on High Yielding Variety (HYV) rice
fields at a local level. Their study estimates the HYV rice fields vulnerable to
conversion due to non-farm uses around sprawling urban settlements. In the chapter
“Identification of Impervious Built-Up Surface Features Using Resources at 2 LISS-
III Based Novel Optical Built-Up Index,” Santra et al. tried to identify the impervi-
ous built-up surface through built-up index. In their study, they used several built-up
indices for comparison. Their newly developed Impervious Built-up Index shows
the maximum accuracy, i.e., 92.33%. In the chapter “Subsidence Assessment of
Building Blocks in Hanoi Urban Area from 2011 to 2014 Using TerraSAR-X and
COSMO-SkyMed Images and PSInSAR,” Anh et al. assessed building subsidence
in Hanoi urban area from 2011 to 2014 by high resolution radar satellite images.
Their results revealed that high precision leveling is the key to assess the accuracy of
subsidence determination of buildings. In the chapter “Analysis of Land Use/Land
Cover Mapping for Sustainable Land Resources Development of Hisar District,
Haryana, India,” Rani et al. mapped the LULC for sustainable land resource
development in Hisar district. They used IRS/LANDSAT data products to analyze
various land resource constraints by taking collateral information on soil types,
groundwater quality, and depth along with geomorphological constraints.
Part IV deals with the challenges and future directions in GIScience. The part
consists of five chapters concentrating on solar energy potential, rice growth stage
mapping, habitat suitability mapping, air pollution modeling, and agricultural pro-
ductivity mapping. In the chapter “A Spatial Investigation of the Feasibility of Solar
Resource Energy Potential in Planning the Solar Cities of INDIA,” Roychowdhury
and Bhanja investigated the feasibility of solar resource energy potential in planning
the solar cities of India. Their study focused on identifying solar hotspots of India
and how the spatial distribution of solar energy resources accentuate or hinder the
performance of the solar cities. The study also conducted a techno-economic feasi-
bility using solar resource datasets derived from high resolution satellites. In the
chapter “Mapping Rice Growth Stages Employing MODIS NDVI and ALOS
AVNIR-2,” Panuju et al. mapped rice growth stages using MODIS NDVI and
ALOS AVNIR-2. They used time-series NDVI for growth-stage indication and
five classifiers for mapping the growth stages. The study revealed the efficiency of
neural network and support vector machine in mapping growth stages. In the chapter
“Habitat Suitability Mapping of Sloth Bear (Melursusursinus) in the Sariska Tiger
Reserve (India) Using a GIS-Based Fuzzy Analytical Hierarchy Process,” Jain et al.
mapped the habitat suitability of the sloth bear (Melursusursinus) in the Sariska
Tiger Reserve (India) using a GIS-based fuzzy analytical hierarchy process. Nine
parameters have been used for assessing sloth bear habitat suitability in the study.
Their suitability classes were validated through zonal statistics of beat wise habitat
intensity data of sloth bear in the Reserve. In the chapter “Estimation of Air Pollution
Using Regression Modelling Approach for Mumbai Region Maharashtra, India,”
Kumari et al. estimated air pollution using regression model for Mumbai. The study
was an integrated approach to attain the spatio-temporal attributes of air pollution
6 R. Ahmed et al.

index of particulate matter (PM10 and PM2.5) and trace gas (O3, NO2, and CO)
pollutants in Mumbai. They used spatial variation of API for different air pollutants
to simulate the Inverse Distance Weighted method of interpolation. In the chapter
“Mapping of Agriculture Productivity Variability for the SAARC Nations in
Response to Climate Change Scenario for the Year 2050,” Singh et al. mapped the
agriculture productivity variability for the SAARC nations in response to climate
change scenario for the year 2050. They assessed the impacts of climate change on
agriculture productivity net primary productivity using Joint UK Land Environment
Simulator. Results of the study revealed a slight decrease in productivity with spatial
variability across the SAARC nations.
Part V deals with the GIScience for Revolution in Science and Society. It
comprises one chapter focused on the revolution of GIS in science and society for
solving the future challenges in spatial information. In the chapter “Future Direction
of GIScience for Revolution in Science and Society Over the Past Twenty Years,”
Lal et al. emphasized the need of GIS in society for problem-solving with the help of
spatial data and modeling as GIS plays a vital role in monitoring the physical
characteristics of the earth’s surface over decades. The advancement of GIS tech-
nologies, speciﬁcally in GIS geomorphologic mapping, has provided us with core
data of landform development, including those due to geophysical or climatic events
such as earthquake, volcanic eruption, landslides, and cyclone.
Introduction to Challenges and Future Directions in Remote Sensing and GIScience 7

Part II
Challenges in Sustainable Natural
Resources Management

Environmental and Livelihood Impact
Assessment of 2013 Flash Flood
in Alakananda and Mandakini River
Valley, Uttarakhand (India), Using
Environmental Evaluation System
and Geospatial Techniques
Shruti Tripathi, G. Areendran, N. C. Gupta, Krishna Raj, and
Mehebub Sahana
Abstract India has been historically susceptible to natural disasters due to its
unique geo-climatic conditions in which the Himalayan ecosystem is very fragile
and a little disturbance can cause harmful effects. The present work is an attempt to
assess the environmental and livelihood impact of the 2013 flood in Mandakini
valley, Uttarakhand (India), using geospatial techniques and an environmental
evaluation system. The land use land cover (LULC) maps for the years 2011,
2014, and 2017 (Alaknanda basin) and 1997, 2011, and 2017 (Mandakini basin)
were prepared using Landsat satellite imageries, and the statistical changes were
estimated in the respective LULC classes derived. The results showed significant
changes in terms of LULC dynamics in the whole region. Further, to analyze
changes in vegetation cover in the region, Normalized Difference Vegetation
Index was calculated, depicting the overall decrease in vegetation cover. By using
Battelle Columbus method of environmental evaluation system, the impact of the
flood on ecological and cultural aesthetics and human interests, with and without the
disaster is also derived. A questionnaire-based survey was conducted in Gaurikund
and Kedarnath to assess the repercussions of the flood on the livelihoods of inhab-
itants. It showed that the stoppage of tourism-based livelihood activities, which were
critical to the local people, deems it necessary to map the footprint of the flood on
livelihood generation activities. The overall result of this study is that there are
significant impacts of flood on both the environment and people residing in the
region, and anthropogenic activities were major contributors to the catastrophe. The
major outcomes of this analysis will help in creating the baseline data for major
S. Tripathi · N. C. Gupta
Guru Gobind Singh Indraprastha University, New Delhi, India
G. Areendran · K. Raj · M. Sahana (*)
IGCMC, WWF–India, New Delhi, India
e-mail: gareendran@wwfindia.net; kraj@wwfindia.net; msahana@wwfindia.net
© The Editor(s) (if applicable) and The Author(s), under exclusive license to
Springer Nature Switzerland AG 2021
P. Kumar et al. (eds.), Remote Sensing and GIScience,
https://doi.org/10.1007/978-3-030-55092-9_2
11

disastrous studies in India and also support sustainable management strategies in
response to these extreme events.
Keywords Mandakini valley · Geospatial techniques · LULC · Livelihood
framework · NDVI · Battelle Columbus method
1 Introduction
India is highly prone to floods, droughts, cyclones, and earthquakes. The frequency
of avalanches, forest fire, and landslides is high in the Himalayan region of northern
India (Sahana and Sajjad 2017; Sahana et al. 2018; Khatun et al. 2018; Areendran
et al. 2020). In India, 25 out of 36 states/union territories are more vulnerable to
natural calamities. Around 50 million people in the country are affected by one or the
other disaster every year on an average, besides the loss of property worth several
million (Sharma 2005). The Himalayan region is seismically and tectonically active,
geologically unstable, remotely located and ecologically most fragile (Sati 2008). In
successive years, the same area encounters one or more disasters. Many people live
in these disaster-prone areas and generate a livelihood from available natural
resources (Sahana and Sajjad 2019). The World Bank has stated that a large number
of people who come under the extremely poor section live on “insubstantial” lands,
including forest ecosystems, slopes, and poor soils (World Bank 2003, p. xvi).
Around 240 million people live in forested areas, constituting 18.5% of the 1.3
billion people living in environmentally fragile lands (World Bank 2003, p. 60). If all
these natural disasters could be predicted and prevented with a state of preparedness
and ability to respond quickly to the calamity, it can considerably cut or mitigate the
loss of life and property.
In June 2013, heavy rainfall triggered flash flooding and landslides throughout
the Indian Himalayan state of Uttarakhand, which killed more than 6000 people. The
destruction and fatalities resulted directly from a lake outburst and debris flow
originating from above the village of Kedarnath (Allen et al. 2016). The heavy
downpour (>400 mm) created a huge flash flood causing damage to agricultural
fields, settlements, and infrastructure and loss of human and animal lives, and
widespread devastation of natural resources in different parts of the state
(Uttarakhand). Around 100,000 pilgrims and tourists were stuck because of the
destruction of trekking routes and roads until civic and military authorities arrived
and evacuated them (Martha et al. 2015; Sharma and Tyagi 2013). There were two
landslides that occurred in Kedarnath on the 16th of (month?), one in the North East
and the other in the North West, both originating around the glacier. Debris flow was
initiated by the landslide in the North East that ran down en-route. In the North West,
conditions are very different. Landslides and moraines left by retreating glaciers
blocked drainage and allowed the formation of a pool that overtopped the moraine
barrier and led to a catastrophic breach (Sahana and Sajjad 2017). This released high
volumes of water downstream in the low-lying area, causing a flash flood (Patley
12 S. Tripathi et al.

2013). The reason for maximum devastation in Kedarnath valley was the breach of
the moraine-dammed Chorabari Lake that was situated 1.5 km above Kedarnath
town from where the unconsolidated moraine debris was deposited and breached
down to the town. Landslides due to floods damaged several houses and killed many
people who were trapped in these structures. Entire villages and settlements such as
Gaurikund and the market town of Rambada got damaged, while the market town of
Sonprayag suffered heavy damage and loss of lives (Indian Disaster Report 2013).
The total roof area in Kedarnath before the disaster was 37,299 m2
(259 structures),
44.2% of which were completely destroyed and 26.7% were partly damaged,
representing 138 and 56 structures, respectively. Around 26.9% of the roof area of
partly destroyed structures was gone. Only the Kedarnath temple emerged as an
unharmed structure in this disaster (Das et al. 2015).
The study of the socio-economic impact of the disaster consists of both qualitative
and quantitative approaches. Quantitative household questionnaires and qualitative
key informant’s interviews were used to collect data. Among all-natural disasters,
floods are the most frequent and 33 million people were affected by floods from
1953 to 2000 (Syyed et al. 2013; Mohapatra and Singh 2003). A study was
conducted by Belaid (2003) to show urban-rural land use change using remote
sensing and GIS and concluded that these technologies together with secondary
data can be used to assist decision-makers to prepare future plans in order to find out
the appropriate solution to urbanization (Syyed et al. 2013). Four hundred and eighty
people inhabit Kedarnath during the summer months and also from neighboring
towns. People come every year in search of livelihood and leave during the winters
like the rest of the residents. Roughly, around 5000 people arrive and leave daily
during pilgrimage time. People who live in the town earn through tourist-related
activities during yatra time. This is also because of the harsh winter season (https://
www.yatra.com/india-tourism/Kedarnath/people). In 2012, the number of pilgrims
reached a high of 259,900 (by a tour of India) and they provide a variety of income-
generating sources. People have been engaged in tourism-based activities for gen-
erations. So, this flood had snatched their main income-generating source for almost
2–3 years. Many researchers tried to map the impact of the flood on livelihood in
other disasters like Pakistan which faced a tragic flood in 2010 that affected more
than 20.1 million people in the whole country (Ashraf et al. 2013). Ashraf et al. in
2013 conducted a study in southern Punjab to explore the effect of floods on food
security and the livelihood of rural communities. Results revealed that flood affected
the natural capitals (land, irrigation, orchards, and livestock) pushing the income-
generating sources into darkness. Flood becomes a hazard only where human
encroachment occurs in flood-prone areas (Smith and Ward 1998; Sahana et al.
2015; Sahana and Patel 2019). A study that was undertaken in Scotland suggests that
social impacts are linked to the level of wellbeing of individuals, communities, and
societies. It also includes aspects that are related to education and literacy, the
existence of security and peace, basic human rights, good governance, positive
traditional value, social equity, custom and ideological belief, knowledge structure,
and overall organization systems. Some groups are more vulnerable to floods than
others like the poor and under-privileged (Nott 2006). Poor people are more
Environmental and Livelihood Impact Assessment of 2013 Flash Flood in. . . 13

vulnerable to disasters because they lack physical, social, and knowledge-based
resources to respond to and prepare for threats. Because they are poor, they are
more vulnerable, and hence are at greater risk in the face of hazard, leading to
disasters (Das et al. 2005; Rehman et al. 2019; Bjarstig and Stens 2018). The loss in
case of flooding has many dimensions; in addition to economic loss and loss of life
or injury, there may be irreversible loss of land and of history of cultural ecological
valuables (Muis et al. 2015). Among natural hazards, flooding claimed more lives
than any other single hazard from 1986 to 1995. Flooding accounted for 31% of
global economic losses from natural catastrophes and 55% causalities (De Bruin
et al. 2014).
These conditions lead to food insecurities and food deficits as people use con-
taminated commodities, especially water (Sahana et al. 2020). So, taking all this into
consideration, this paper’s major focus is on the impact of the flood on the environ-
ment and livelihood of the people involved in Kedarnath yatra every year. Other
papers tried to discover the reason for the floods and damage caused. It is very
important to map the footprint of the flood on livelihoods. It will help policymakers
and institutions help these vulnerable people and make their livelihood sustainable.
2 Study Area
Uttarakhand is predominantly a hill state, having international boundaries with
China in the north and Nepal in the east. The Himalayan region in Uttarakhand
(~53,483 km2
) lies between Kali Ganga (bordering with Nepal) and Tons-Yamuna
(bordering with Himachal Pradesh). Around 10% of the total area of Uttarakhand is
covered by snow, ice, and glaciers. These are the perennial source of water for four
major river systems, viz. Yamuna, Bhagirathi, Alaknanda, and Kali (Singh and
Rawat 2011; Dobhal et al. 2013). In Uttarakhand, 4 districts were majorly affected
by the flood in which Rudraprayag district saw greater loss in terms of lives and
property (NIDM Report 2013). Many lost their family members, houses, jobs,
shelter, and so on. In this study, Mandakini valley was selected to understand the
effects of the disaster. Figure 1 shows the study site.
Alaknanda basin is located at 30.1333
latitude and 78.6029
longitude. Its main
tributaries are Mandakini, Nandakini, and Pinder and considered to rise at the foot of
the Satopath glacier in Uttarakhand (Sati 2009). The Alaknanda river basin is
sandwiched between the crystalline? of lesser and higher Himalayas. It is character-
ized by high-grade metamorphic rocks of higher Himalayan crystalline in the north
and lesser Himalayan sequence in the south (Metcalfe 1993; Valdiya et al. 2000;
Valdiya 1995). High mountainous ranges in the northern part, particularly in the
north eastern and north western part of the watersheds, are covered with snow-fields
or glaciers. The rivers of Alaknanda basin are perennial, since runoff in these rivers
is controlled by both precipitation and glacial melt (Sati 2009).
River Mandakini, the main river of the Alaknanda basin and valley, is a major
tributary of River Alaknanda and originates from the Chorabari Glacier, situated just

2 km above Shri Kedarnath shrine. The Shri Kedarnath town is situated in the
Central Himalayas (30
440
6.700
N; 79
040
100
E) in the Mandakini River valley.
The catchment area is situated in the glacier-modified U-shaped valley; the altitude
ranges from 1700 m asl to 6578 m asl. Such a variation in the altitude provides
various landscapes. BhartKhunta (6578 m), Kedarnath (6940 m), Mahalaya peak
(5970 m), and Hanuman top (5320 m) are major peaks in the area. The climate of the
region largely depends on altitude as elevation ranges between 1600 m and 6500 m
asl. Winter is from mid-October to April. The slope of the study area lies between
30 and 60
and toward the South East aspect. The alpine habitat usually starts at
timberline and is characterized by the complete absence of trees. The soil in
Kedarnath valley is dark brown on the surface and yellowish-brown below (Singh
et al. 1986). Floristic composition shows mixed forests of rhododendron,
Quercusleuco trichophora (Banj), Quercus floribunda (Moru), and Quercusseme
carpifolia (Kharsu), Buxus wallichiana (papri), Acer spp. (Kaijal), Betula alnoides
(Katbhuj), and Alnus nepalensis (Utis) up to an elevation and the rest are alpine
pastures. This area has traditionally occupied an important position in the socio-
cultural, spiritual, and medicinal arena of rural and tribal lives of Uttarakhand
(Rawat 2016). According to the report of Climate Himalaya on plausible reasons
for this flood, the root of the disaster is in the Chorabari Glacier located in Mandakini
valley. This is why Mandakini valley was chosen as the study area to access
environmental damage and its impact on the livelihoods of inhabitants.
Fig. 1 Location map of Alaknanda and Mandakini basin and the GPS points collected during the
field survey

3 Material and Methodology
3.1 Data Collection
Materials that were used during the study are various websites from the internet like
Earth Explorer, Bhuvan, and Diva GIS; GIS software like ERDAS Imagine and
Arcmap10; national and international journals, a questionnaire for the assessment of
damage and pre-disaster livelihood options. Satellite images used in this study are
mentioned in Table 1.
3.2 Data Collection for the Survey
Field survey was conducted to assess the impact of the ﬂood on socio-economic
parameters of the valley’s residents. For that purpose, livelihood’s 5 capitals were
studied, i.e., physical, natural, ﬁnancial, health, and social capitals. Sample data were
collected through the questionnaire-based survey in Gaurikund village, en-route to
Kedarnath temple and in Kedarnathghati. Figure 1 shows the GPS points that
were selected by random selection method to select the interviewees. It was learned
that, in Mandakini valley, en-route Kedarnath temple, many people earn their
livelihood from various food stalls or carrying people to the temple using horses
and on their back. Figure 2 shows various types of livelihoods in which inhabitants
are engaged in.
Table. 1 Satellite images
used in this study
S. no. Name of satellite Year Resolution
For Alaknanda basin
1. Landsat 5 January 2011 30 m
For Mandakini basin
1. Landsat 5 January, 1997 30 m
3. Landsat 8 June 2013 30 m
For rainfall
1. TRMM (Netcdf) 2001–2016 (June) 0.25

3.3 Analysis of the Satellite Images for Impacts of Flood
3.3.1 Image Acquisition
Satellite images that were used in this study are mentioned in Table 1. These images
were downloaded from USGS Earth Explorer official site and Bhuvan. These
imageries are freely available on the mentioned portals.
3.3.2 Georectification
The topographical maps were georectified by selecting ground control points
throughout the area projected in the projection system geographic (Lat/long) with
spheroid and datum being WGS 84. From georeferenced imageries, the study area
was obtained through a subset using the AOI boundary vector file (Hughes et al.
2006).
3.3.3 Image Extraction (Subset/Mosaicking)
Satellite images that were downloaded from the Earth Explorer website were opened
in ARC GIS, and the area of interest was extracted from that image to use for further
study. However, in our case, our area of interest was spread across two satellite
Fig. 2 Field photographs of livelihood types in the Kedarnath and Gaurikund regions

images. So, we used the Mosaic tool in ERDAS Imagine to mosaic the images and
then extracted our study of area from it.
3.3.4 Image Classification
The purpose of image classification was to categorize all pixels in an image into
different land cover classes. Digital image classification uses the spectral informa-
tion represented by the digital numbers in one or more spectral bands to classify each
pixel. This process assigns each pixel in an image to a particular class or theme based
on the statistical characteristics of the pixel brightness values (Guo and Zhang 2009).
3.3.5 Unsupervised Classification
In unsupervised classification, outcomes are based on the software analysis of an
image without the user providing sample classes (Source Extension.org). In this type
of classification, spectral classes were grouped first into 85 classes, based solely on
the numerical information in the data. The classes that result from unsupervised
classification are spectral classes distinguishing urban from the open area, agricul-
ture from forest class, etc., and is often difficult because of similar reflectance
patterns. Therefore, for more accurate classification, the number of classes classified
initially was more. References like Google Earth maps prepared by other sources
were used to recode and clean the initially classified image. AOI tools like polygon/
polyline were used for cleaning.
3.3.6 Digitization (for Vector Layer)
Different features like roads, rivers, towns, and soil types were extracted from
scanned and georeferenced images using ArcGIS 10 digitization tools. Features
like water bodies and settlements were extracted using Google Earth. The files
obtained were in .kmz format, which were converted to shapefile using ArcGIS
10 conversion tools. Digitization was carried out manually. All the features were
digitized as point, line, or polygon. Figure 3 shows the methodological framework
used in this study.
3.4 Environmental Impact Assessment of Flood
Many research papers used Land Use Land Cover (LULC) analysis to assess the
impact of flood on environmental settings and on human settlements (Sinha 1998;
Ferrari et al. 2009). The method described in Fig. 4 was used to generate the LULC.
We first downloaded the satellite images that are mentioned in Table 1 study area
and then digitized and classified the post-flood-affected area in Uttarakhand. After

Fig. 3 Methodological framework used in this study
Fig. 4 Land use land cover pattern of Alaknanda basin (a) 2011, (b) 2014, and (c) 2017

that, we compared it with pre-disaster images to analyze the most to least affected
areas. Landsat 8 images were used to digitize the flood-affected area with the help of
data that was taken from the Bhuvan portal. Using Google Earth, roads, agricultural
land, and settlements were digitized and then compared with flood-affected areas to
analyze the damage caused by this flood in Mandakini valley.
We used the Battelle Columbus method for environmental impact assessment to
evaluate environmental settings before and after the disaster. Battelle method is a
quantitative method where 78 measurable environmental parameters are divided into
4 categories: environmental contamination, ecology, aesthetics, and human interest.
In this method, 2 steps are involved; first is to convert parametric estimates into an
environmental quality (EQ) scale that ranges between 0 and 1, where 0 denotes very
bad quality and 1 denotes good quality. The second step is the multiplication of EQ
values with the respective parameter importance unit values to obtain environmental
impact units (EIU) for each parameter. Composite score is obtained by the addition
of all EIU values. The total environmental impact is calculated by evaluating the
expected future condition of the EQ with and without the project (Syyed et al. 2013).
E1 =
Xm
i¼1
Vi
ð Þ1Wi
Xm
i¼1
Vi
ð Þ2Wi ð1Þ
Where
E1 ¼ Environmental impact
(Vi)1 ¼ Value in the EQ of parameter i with a project.
(Vi)2 ¼ Value in EQ of parameter i without a project.
Wi ¼ Relative weight (importance) of parameter i
m ¼ Total number of parameters
To do this, a checklist with all environmental parameters was made and assessed
during the field visit and compared by weightage underlined in the Battelle method.
3.5 Normalized Difference Vegetation Index (NDVI)
This is a numerical indicator that uses the red and near-infrared spectral bands.
NDVI is highly associated with vegetation content. High NDVI values correspond
to areas that reflect more in the near-infrared spectrum. Higher reflectance in the
near-infrared correspond to dense and healthy vegetation.
NDVI ¼ Band5 Band 4=Band 5 þ Band4 using Landsat 8 data
ð Þ ð2Þ

3.6 Livelihood Impact Assessment
To fulfill the second major objective of this study to link the impact of the flood on
the livelihood of inhabitants, we did a questionnaire survey during Kedarnath yatra
in June 2017. The random selection method was applied to select the interviewee.
The questionnaire was based on five pillars of sustainable livelihood framework
(DFID 2009). In Kedarnath yatra, we can find different types of livelihood options,
i.e., food stalls, hotels, horse sawari, pitthusawari, and so on. In this survey, we tried
to incorporate all kinds of livelihood options. Here we questioned the interviewees
who are currently engaged in some kind of work to generate income from yatra. The
questions were framed according to the five livelihood capitals (Scoones 1998).
Answer options were in the form of 1 (low intensity), 2 (medium intensity), and
3 (High intensity). Here intensity means the effect of the flood on a particular
parameter.
4 Result/Discussions
4.1 Land Use Changes in Alaknanda and Mandakini Basin
Land cover maps from Landsat images from 2011–2017 (Alaknanda basin) have
shown considerable changes in the study area (Fig. 4). The study area was divided
into 7 different classes. LULC maps were prepared for 3 time periods, i.e., January
2011, January 2014, and January 2017 and changes in these LULC classes were
analyzed in the present study. Classified images of the study area of 2011, 2014, and
2017 as well as changes in the abovementioned classes are demonstrated percentage
wise to have a clear view on this, as mentioned in Table 2.
The study area was divided into 7 different classes. LULC map was prepared for
3 time periods: January 1997, January 2011, and January 2017; changes in these
LULC classes were analyzed in the present study (Fig. 5). Classified images of the
study area of 1997, 2011, and 2017 are shown. The LULC classification is summa-
rized for the years 1997, 2011, and 2017 in Table 3. From 1997 to 2017, dense forest,
scrub forest, water bodies, and snow cover decreased. On the other hand, open forest,
Table 2 Statistical representation of area under different classes in Alaknanda basin
Classes
2011 area 2014 area 2017 area
(hectare) (%) (hectare) (%) (hectare) (%)
Dense forest 290,761 26.3097 265,584 24.079 256,577 23.2604
Open forest 178,675 16.1675 158,991 14.4148 143,966 13.0515
Scrub forest 67032.8 06.0655 92448.9 08.3818 89329.9 08.0983
Water bodies 7661.06 0.6932 7593.01 00.6884 7522.78 0.682
Snow cover 489,680 44.309 489,672 44.3958 478,228 43.3546
Rocky land 71337.8 06.455 88679.2 08.0401 127,439 11.5532

built-up land, and rocky land cover increased. We can have a clear view of this in
Table 3. Therefore, the changes in dense forests are due to the climate change effect
over the years and some parts changed into open forest. Over 20 years’ time, there
was an increase in built-up land and agricultural land that shows high anthropogenic
activities in this fragile ecosystem.
Fig. 5 Land use land cover pattern of Mandakini basin, (a) 2011, (b) 2014, and (c) 2017

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FIG. 5.—GENERAL PLAN OF GATUN DAM.

Remote Sensing and GIScience : Challenges and Future Directions Pavan Kumar

X. SANITATION
At Panama the seasons are divided into two well defined
periods: the dry, or winter, and the wet, or summer seasons. By this
occurrence of maximum moisture and maximum heat, the health
conditions are made the worst possible.
The dry season includes the months of January, February, March
and April, the rainy season the remainder of the year. During the dry
season the average temperature at Colon for 6 years was 70.5° F,
with a monthly maximum of 90.9° F, which came in January, and a
monthly minimum of 68.4° in the same month. During the rainy
season the maximum average temperature for any month occurred
in October and was 91.9° F. The minimum was 66.9° F., for August.
A record of 15 years at Colon shows a maximum rainfall of 154.9
inches and a mean of 130.2 inches. Four years’ records at Panama
show a maximum of 84.73 inches and an average of 66.8 inches. At
Culebra the records for 3 years showed a maximum of 98.97 inches
and a minimum of 64.25 inches.
The most common forms of disease on the Isthmus are due to
fevers. According to good authority the most sickly period is
September, October and November, during which time dysentery and
a severe bilious fever are very common. Foreigners seldom acquire
the immunity of the natives from local diseases. The Isthmus by
various writers has been called, “The Grave of the European”, “The
Pest-House of the Tropics”, and one author says that here truly “Life
dies and death lives”.
On account of the health conditions the labor question is greatly
complicated. For this reason extreme care has been taken by the

United States Government to do all in the power of science to make
the zone a healthy locality. Sanitation expenses will average at least
$2,000,000 per year. The work has been under the direct supervision
of Colonel W. C. Gorgas. The war on the mosquito has been
continual and unrelenting. For the first two months of the fiscal year
1908–’09, the work in the Canal Zone, consisted of the collection
and disposal of garbage and night soil, the cutting of grass and
brush, and sanitary drainage and oiling. In the terminal cities the
work consists of inspection, fumigation, grass cutting, surface
drainage, and oiling undrained areas.
This department also has charge of the hospitals and of the
quarantine. As far as possible all the sick are concentrated at Ancon.
Last year’s records show an improvement over the preceding
year. The total number of employees admitted to the hospitals and
sick camps amounted to 46,194, representing 23.49 as the number
of men sick daily as against 23.85 for the preceding year. The
number of deaths was 530. According to these figures the Canal
Zone is one of the healthiest communities in the world; but it must
be remembered that the population there consists of men and
women in the prime of life and that a number of the sick are
returned to the United States before death overtakes them.
There were no cases of plague or yellow fever originating on the
Isthmus during the year 1908–’09. The last case of yellow fever
occurred in May, 1906.
A supply of perfectly healthful water has been secured by the
construction of reservoir at different points of the Zone, and the
Commission hotels and cottages have all the advantages of an
excellent modern water system.

XI. SOCIAL LIFE
Those who have endeavored to better the standard of social life
at Panama have met with difficulties always connected with an
enterprise of the character and magnitude of the great Canal. It is
surprising what has been accomplished. Questionable amusements
there are, but that is to be expected among such an assemblage of
men. Nevertheless, the conditions of living there are gradually
approaching what we find in the average community in the United
States.
There is a well organized school system in the Canal Zone.
Twelve schools are maintained for white children and seventeen for
colored children. The highest monthly enrollment was 675 whites
and 1,417 colored pupils. There is a superintendent of schools and
assistant supervisor of primary grades.
Two high schools are in operation, one at Culebra and one at
Cristobal. Children at other points in the Zone requiring high school
instruction are given free transportation over the railroad by the
Commission. Instruction is given in algebra, geometry, physical
geography, general history, botany, English, German, French,
Spanish, and Latin. There were but 25 children who took high school
work in 1908–’09.
In addition to the transportation given high school pupils,
transportation is given to children in towns where no white schools
are maintained. Last year children were also carried by wagon from
Balboa to Ancon, as were high school pupils from Empire and
Culebra. A boat and ferryman were employed in two cases.

Quarters are furnished free to all the men, married and
unmarried. Roosevelt, upon his return from Panama said the wives
of the employees seemed satisfied with their home life and
surroundings. The houses are excellent considering the conditions.
Employees purchase all necessary supplies from government
commissaries at about the same prices as are current in the United
States. On every workday a refrigerator car runs from Colon to
Panama and delivers to the various villages all orders previously
placed for supplies such as ice, meat, vegetables and fruit. Payment
is made by the use of coupons, their values being deducted from the
employee’s salary.
Employees are allowed free medical, surgical, and hospital
attendance, including medicines and food while in the hospital.
Employees with salaries fixed on an annual or monthly basis
receive no pay for overtime work but if their health requires it, will
be granted a leave of 6 weeks absence or less during the year with
full pay. Those who are paid by the hour do, of course, receive pay
for overtime work.
A number of suitable church buildings has been erected by the
Commission. They are two-story buildings, the upper floors being
fitted up as lodge rooms and the first floor for religious purposes.
Practically every religious denomination is now represented on the
Isthmus by the chaplains employed by the Commission.
Roosevelt stated after his visit to the Zone that “It is imperatively
necessary to provide ample recreation and amusement if the men
are to be kept well and healthy.” To this end four clubhouses have
been completed at Culebra, Empire, Gorgona, and Cristobal and
several more are contemplated. The four are alike in design, and
consist of a front building of two stories connected with a rear
building of one story. The front part is 135 feet by 45 feet, and
contains a social parlor, a card room, a billiard and writing room on
the first floor and an assembly hall on the second floor. The rear
building, 100 feet by 28 feet, contains a double bowling alley, a

gymnasium, shower baths, and over a hundred single lockers. The
Commission, assisted by the Young Men’s Christian Association,
manages these buildings. Besides furnishing a library of 787 volumes
to each of these buildings provision is made for the delivery of 100
weekly and monthly periodicals.
Last year 1908–’09, 2,140 employees availed themselves of
regular membership privileges. The membership rate is 10 dollars
per year. The fact that 56,835 games in bowling took place during
the year shows the extensive use made of these buildings.
There are various athletic organizations on the Isthmus.
Gymnasium activities have consisted mostly of basket ball and
indoor baseball. Field sports are sometimes held on moonlight nights
and holidays. An athletic park has been built near Cristobal.
During the year there were 81 performances given by lyceum
and vaudeville talent from the United States, with an attendance of
18,225. Chess, checker, glee, minstrel, dramatic, and orchestra clubs
have been successfully maintained.
“These associations have held a vital relation to the canal
construction in promoting contentment among employees, furnishing
healthful amusement, effecting greater permanency of the force,
and in elevating the standards of living”.

XII. ECONOMIC IMPORTANCE
The economic importance of the Panama Canal is a fruitful topic
for discussion. Some authorities think that a large share of the
world’s commerce will naturally and immediately use this new path
between the oceans; but the general opinion of those best fitted to
decide is that the canal will not be a paying investment, at least for
the first years of its operation. As a German paper puts it, “Nobody
thinks of remunerativeness any more. The fruits of the enterprise
consist in indirect profits; they must be looked for in the military-
political field and in the promotion of American commerce. In this
lies the center of gravity of the situation”.
From a commercial standpoint the canal will be of little or no
advantage to Europe for the way to the whole of eastern Asia and
Australia, inclusive of New Zealand via the Suez Canal will remain
much nearer. For Europe, then, the only saving is in traffic with the
west coast of America. In commerce with western South America
England occupies first place, and is followed by Germany, the United
States and France, in the order named. It is to be noted that vessels
trading with the southern portion of the west coast of South America
will prefer to go around Cape Horn rather than pay the tolls through
the Panama Canal.
The greatest commercial advantage comes to the eastern ports
of the United States, namely 9,531 nautical miles between New York
and San Francisco, so that New York on this route gains 2,889 miles
more, for example, than Hamburg, Germany. The main fact,
however, is that this saving is so large on the route from New York
to Eastern Asia and Australia that it changes the present
disadvantage of New York into an advantage when compared with

many European ports. From Hamburg to Hongkong, via Suez, the
distance is 10,542 miles; from New York to Hongkong, via Suez, it is
11,655 miles. The Panama Canal will give nothing to Hamburg but a
saving of 1,820 miles to New York so that the distance will be 707
miles less than from Hamburg. In routes to the more northern ports
of eastern Asia, as well as to those of eastern Australia, the gain of
New York is still greater. From Hamburg via Suez to Melbourne is
12,367 miles; from New York 12,500 miles. Via Panama, however,
the distance from New York is only 10,427 miles, so that New York
will be about 2,000 miles nearer than Hamburg. In many cases
therefore the Panama Canal will give New York a decided advantage
over European ports.
There are other than commercial reasons for building the canal.
The effect which it will have upon the tropical districts of the west is
worth considering. An author on “Social Evolution” in describing this
region said that there are only two words which adequately
represent the conditions of this country, “anarchy and bankruptcy”,
and he suggests removing the anarchy by the substitution of strong
and righteous government. Can any one doubt that the construction
of an international waterway through the Isthmus will tend to
improve administration in the American tropics?

G E N E R A L M A P
OF THE
CANAL ZONE
AND THE
PANAMA CANAL

Transcriber’s Notes
Transcriber modified the original cover and added a
map to it, taken from the original book. The
modifications as well as the original are in the Public
Domain.
Punctuation and spelling were made consistent when
a predominant preference was found in this book;
otherwise they were not changed.
The original text was typed, not printed.
Consequently, there were more typographical errors than
would normally be found in a book, and Transcribers
corrected most of them without noting the individual
corrections here.
Ambiguous hyphens at the ends of lines were
retained; occurrences of inconsistent hyphenation have
not been changed.
Transcriber segmented the map at the end of the
book into three larger parts for readability, in addition to
retaining an image of the original.
“Maratime” was printed that way, twice; “Maritime”
did not occur in this book.
Page 3: “concensus” was printed that way.
Page 15: “built on the lock canal” was printed as
“built on the sea-level canal”, but “sea-level” was crossed

out by hand and replaced by what appears to be “Loc”.
Given the context and name of the chapter, Transcribers
decided it was intended to be “lock”.

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