Geographic Information Science for Land Resource Management E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Geographic Information Science for Land Resource Management is a comprehensive book focusing on managing land resources using innovative techniques of spatial information sciences and satellite remote sensing. The enormous stress on the land resources over the years due to anthropogenic activities for commercialization and livelihood needs has increased manifold. The only solution to this problem lies in stakeholder awareness, which can only be attained through scientific means. The awareness is the basis of the sustainable development concept, which involves optimal management of natural resources, subject to the availability of reliable, accurate, and timely information from the global to local scales. GIScience consists of satellite remote sensing (RS), Geographical Information System (GIS), and Global Positioning System (GPS) technology that is nowadays a backbone of environmental protection, natural resource management, and sustainable development and planning. Being a powerful and proficient tool for mapping, monitoring, modeling, and managing natural resources can help understand the earth surface and its dynamics at different observational scales. Through the spatial understanding of land resources, policymakers can make prudent decisions to restore and conserve critically endangered resources, such as water bodies, lakes, rivers, air, forests, wildlife, biodiversity, etc. This innovative new volume contains chapters from eminent researchers and experts. The primary focus of this book is to replenish the gap in the available literature on the subject by bringing the concepts, theories, and experiences of the specialists and professionals in this field jointly. The editors have worked hard to get the best literature in this field in a book form to help the students, researchers, and policymakers develop a complete understanding of the land system vulnerabilities and solutions.
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Table of Contents
Cover
Title Page
Copyright
Preface
Acknowledgements
1 Climate Change in South Asia: Impact, Adaptation and the Role of GI Science
1.1 Introduction
1.2 Climate Change
1.3 Climate Change Trends in South Asia
1.4 Climate Change Impact in South Asia
1.5 Climate Change Adaptation in South Asia and the Role of GI Science
1.6 Conclusion
References
2 Sustainable Land Resource Management Approach and Technological Interventions – Role of GI Science
2.1 Introduction
2.2 Land Resource Availability in India
2.3 Problems Associated with Land Resources
2.4 Important Interventions
2.5 Role of GI Science in Land Resource Management
References
3 GI Science for Assessing the Urban Growth and Sustainability in Agra City, India
3.1 Introduction
3.2 Database
3.3 Methodology
3.4 Study Area
3.5 Result and Discussion
3.6 Conclusion
References
4 The Use of GI Science in Detecting Anthropogenic Interaction in Protected Areas: A Case of the Takamanda National Park, South West Region, Cameroon
4.1 Introduction
4.2 Context and Justification
4.3 Material and Data Sources
4.4 Results and Discussion
4.5 Conclusion
References
5 Urban Heat Island Effect Concept and Its Assessment Using Satellite-Based Remote Sensing Data
5.1 Introduction
5.2 Classification of UHIs
5.3 Chief Causes
5.4 Consequences of UHI Formation
5.5 Detection and Measurement Techniques
5.6 Mitigation Strategies
5.7 Role of Remote Sensing and GIS in Assessing UHI Effect
5.8 Conclusion
References
6 Remote Sensing for Snowpack Monitoring and Its Implications
6.1 Introduction
6.2 Snowpack Characterization
6.3 Remote Sensing of Alpine Snow
6.4 Techniques for the Qualitative and Quantitative Analysis of Snow
6.5 Implications and Potential Applications
6.6 Conclusion
References
7 Spectral Ratioing: A Computational Model for Quick Information Retrieval of Earth’s Surface Dynamics
7.1 Introduction
7.2 Image Enhancement Techniques for Remotely Sensed Images and Their Categorization
7.3 Spectral Ratioing
7.4 Spectral Ratio for Urban Extraction and Mapping
7.5 Spatiotemporal Change in Urban Pattern Through Spectral Ratio
7.6 Conclusion
References
8 Delineation of Surface Water in Mining Dominated Region of Angul District of Odisha State, India Using Sentinel-2A Satellite Data
8.1 Introduction
8.2 Study Area
8.3 Materials and Method
8.4 Results and Discussion
8.5 Conclusions
Acknowledgements
References
9 Mapping Seasonal Variability and Spatio-Temporal Trends of Water Quality Parameters in Wular Lake (Kashmir Valley)
9.1 Introduction
9.2 Study Area
9.3 Datasets and Methodology
9.4 Methodology
9.5 Mapping Spatial Variations in Water Quality Parameters (WQP’S) Using IDW Method in Wular Lake
9.6 Results and Discussion
9.7 Temporal Variations in Water Quality Parameters of Wular Lake (1992-2015)
9.8 Conclusion
Acknowledgement
References
10 Water Quality Zoning Using GIS & Remote Sensing: A Case Study of Tehsil Matta District Swat Pakistan
10.1 Introduction
10.2 Martials and Methods
10.3 Results and Discussion
10.4 Conclusion
References
11 Assessing the Impacts of Global Sea Level Rise (SLR) on the Mangrove Forests of Indian Sundarbans Using Geospatial Technology
11.1 Introduction
11.2 Materials and Methods
11.3 Results and Discussions
11.4 Conclusion and Restoration of the Delta
11.5 Acknowledgements
References
12 Sustainable Water Resource Management Using Watershed Morphometry–A Case Study of Giri River Catchment, Himachal Pradesh, India
12.1 Introduction
12.2 Study Area
12.3 Datasets and Research Method
12.4 Results and Discussion
12.5 Conclusion
References
13 Improving the Procedure for River Flow Measurement and Mapping: Case Study River Plitvica, Croatia
13.1 Introduction
13.2 Study Area
13.3 Data Sets and Methodology
13.4 Methodology
13.5 Results and Discussion
13.6 Conclusion
Acknowledgement
References
14 Spatiotemporal Analysis of Forest Degradation in South Chotanagpur Division of India
14.1 Introduction
14.2 Forest Cover Dynamics In Study Area
14.3 District-Wise Forest And Population Dynamics
14.4 NDVI Analysis
14.5 Driving Forces of Forest Cover Change
14.6 Conclusion
References
15 Forest Fire Risk Assessment Using GIS Science – A Case Study of South India
15.1 Introduction
15.2 Study Area
15.3 Datasets Used
15.4 Factors Responsible for Forest Fire Over the Study Area
15.5 Methodology
15.6 Parameters Incorporated in the Study
15.7 Weighted Overlay Analysis in ArcGIS
15.8 NDVI
15.9 Results and Discussion
References
16 GI Science for Land Use Suitability Analysis in the Himalayas – A Case Study of Himachal Pradesh, India
16.1 Introduction
16.2 Study Area
16.3 Materials and Methods
16.4 Results and Discussion
16.5 Conclusion
Acknowledgment
References
17 Using Remote Sensing Data and Geospatial Techniques for Watershed Delineation and Morphometric Analysis of Beas Upper Catchment, India
17.1 Introduction
17.2 Study Area
17.3 Methodology
17.4 Result and Discussion
17.5 Conclusions
Acknowledgement
References
18 Sub-Watershed Prioritization for Soil and Water Conservation – A Case Study of Lower Wardha River, Maharashtra, India, Using GI Science
18.1 Introduction
18.2 Study Area
18.3 Data and Method
18.4 Morphometry of Lower Wardha
18.5 Results and Discussion
18.6 Conclusions
References
19 Understanding Hydrologic Response Using Basin Morphometry in Pohru Watershed, NW Himalaya
19.1 Introduction
19.2 Study Area
19.3 Materials and Method
19.4 Results and Discussion
19.5 Conclusion
References
20 Sintacs Method for Assessment of Groundwater Vulnerability: A Case of Ahmedabad, India
20.1 Introduction
20.2 Background
20.3 Study Area
20.4 Data Sets and Methodology
20.5 Results and Discussion
20.6 Conclusion
References
Index
End User License Agreement
List of Tables
Chapter 1
Figure 1.1 Land surface temperature (LST) anomalies for South Asia from (a) June...
Figure 1.2 Spatial distribution of highest daily maximum wet-bulb temperature, T...
Chapter 2
Figure 2.1 Land cover classification of 1950-51 (Source: Directorate of Economic...
Figure 2.2 Land cover classification of 2014-15 (Source: Directorate of Economic...
Chapter 3
Figure 3.1 Methodology.
Figure 3.2 Study area.
Figure 3.3 Land use and Land cover (a) LULC of Agra City, 2001; (b) LULC of Agra...
Figure 3.4 Registered motor vehicles.
Figure 3.5 PM
10
values (2011 – 2018).
Chapter 4
Figure 4.1 (a) Location of the TNP amongst other protected areas.
Photo 1 A cleared portion of the Takamanda National Park midway between Obonyi I...
Photo 2 Remains of an elephant reported to have been killed in the Takamanda Nat...
Photo 3 Livestock rearing in the Takamanda National Park. Picture credits: Takem...
Photo 4 Timber sawn in the TNP waiting to be transported. Picture credits: Takem...
Figure 4.2 (a) Spatial distribution of grazers in the TNP in 2014.
Chapter 5
Figure 5.1 Disparities between surface & air temperatures in diverse urban parts...
Figure 5.2 Factors contributing to UHI formation.
Figure 5.3 Urban heat island effect mitigation strategies and associated process...
Chapter 6
Figure 6.1 Schema for the different types of snowpack characterization.
Figure 6.2 The role of remote sensing technology in the studies of alpine snow.
Figure 6.3 Sensitivity of polarimetric parameters to different land cover as com...
Figure 6.4 Microwave propagation through the snowpack corresponding to the two-l...
Figure 6.5 Typical workflow for the estimation of snow parameters based on fully...
Chapter 7
Figure 7.1 Model representation in ERDAS IMAGINE for a spectral ratio; source: a...
Figure 7.2 Built-up indices after classification; source: author.
Figure 7.3 Images obtained from Landsat series on (a) 02/03/1973 (Landsat-1), (b...
Figure 7.4 Changes in the urban pattern of Mathura since 1973 obtained through N...
Chapter 8
Figure 8.1 Location map of study area (c) Angul district with block boundary in ...
Figure 8.2 Flowchart of the working methodology.
Figure 8.3 Thematic/classified maps (a) NDPI (b) Classified map showing water- a...
Figure 8.4 Annual variations in water and non-water bearing pixels in Angul dist...
Figure 8.5 Monthly variations in water- and non-water-bearing pixels in Angul di...
Figure 8.6 Annual trend of the coverage area of surface water.
Figure 8.7 Monthly trend of the coverage area of surface water.
Chapter 9
Figure 9.1 Location map of the study area showing Wular Lake & sampling sites.
Figure 9.2 Methodological flowchart adopted for the study.
Figure 9.3 Spatial variations in water temperature (a), pH (b), turbidity (c) an...
Figure 9.4 Spatial variations in electrical conductivity (e), dissolved oxygen (...
Figure 9.5 Spatial variations in total hardness (i), total alkalinity (j), nitra...
Chapter 10
Figure 10.1 Map showing the location of study area, Tehsil Matta District Swat.
Figure 10.2 pH map, Tehsil Matta District Swat.
Figure 10.3 DO map, Tehsil Matta District Swat.
Figure 10.4 EC map, Tehsil Matta District Swat.
Figure 10.5 Salinity map, Tehsil Matta District Swat.
Figure 10.6 Alkalinity map, Tehsil Matta District Swat.
Figure 10.7 TDS map, Tehsil Matta District Swat.
Figure 10.8 Chloride map, Tehsil Matta District Swat.
Figure 10.9 Sulphate map, Tehsil Matta District Swat.
Figure 10.10 BOD map, Tehsil Matta District Swat.
Figure 10.11 Water quality map, Tehsil Matta District Swat.
Chapter 11
Figure 11.1 Location of map of Sundarban coastal belt.
Figure 11.2 Sea level change 1950-2015 (Data Source: PSMSL).
Figure 11.3 Mean sea level erosion of 1990-2019 of Sagar island.
Figure 11.4 Shoreline change of 1990 to 2019.
Figure 11.5 Trend of SLR due to flood along the coast of Sagar Island.
Figure 11.6 Trend of salinity (1990-2019).
Figure 11.7 Salinity map of 1990.
Figure 11.8 Salinity map of 2019.
Figure 11.9 Mangrove forest change map (1990-2019).
Figure 11.10 Showing the bar graph of mangrove forest change.
Chapter 12
Figure 12.1 Study area.
Figure 12.2 Major streams of Giri watershed.
Figure 12.3 Stream order of Giri watershed.
Figure 12.4 Bifurcation ratio.
Figure 12.5 DEM.
Figure 12.6 Relief ratio.
Figure 12.7 Basin relief.
Figure 12.8 Ruggedness index.
Figure 12.9 Drainage density.
Chapter 13
Figure 13.1 Location map of Varaždin City [2].
Figure 13.2 Location of the measurement points on river Plitvica [3].
Figure 13.3 Location 1 - Jalkovec bridge [4].
Figure 13.4 Location 2 – Brezje bridge [4].
Figure 13.5 Measured values on location 1.
Figure 13.6 Measured values on location 2.
Figure 13.7 Reading of the values from the website of MHSC [5].
Figure 13.8 Cross section profile of the measuring station Vidovićev mlin [4].
Figure 13.9 RAPS for the river Plitvica.
Figure 13.10 RGB example of Plitvica river.
Chapter 14
Figure 14.1 Forest cover in 2011: Lohardagga and Ranchi District.
Figure 14.2 Forest cover in 2011: Simdega and Khunti District.
Figure 14.3 Forest cover in 2011: Gumla District.
Figure 14.4 NDVI classification 2014.
Figure 14.5 NDVI classification 2018.
Chapter 15
Figure 15.1 Location of the study area.
Figure 15.2 (a-f): (a) Vegetation type map, (b) Temperature map, (c) Rainfall ma...
Figure 15.3 Forest fire risk zone.
Figure 15.4 Forest fire spreading sensitivity.
Figure 15.5 NDVI maps (2006-2019).
Chapter 16
Figure 16.1 Study area map - Pandoh basin (Source: Toposheet).
Figure 16.2 Methodology chart.
Figure 16.3 (a) Rainfall Intensity (IMD), (b) LULC (LANDSAT 8 OLI/TIRS), (c) Slo...
Figure 16.4 Land suitability map.
Figure 16.5 Agricultural area from soil map overlaid on LULC.
Chapter 17
Figure 17.1 Location map of Beas Upper Catchment. Source: IRS Resourcesat-2 LISS...
Figure 17.2 (a) Elevation of Beas upper catchment using 30 m ASTER DEM (b) Eleva...
Figure 17.3 Watershed delineated and boundary comparison map.
Figure 17.4 Slope map and (b) Aspect map of Beas upper catchments using ASTER an...
Chapter 18
Figure 18.1 Location map of the study area.
Figure 18.2 IRS P6 LISS-III FCC satellite data of Lower Wardha.
Figure 18.3 ASTER - Global Digital Elevation Model data of 30 meter resolution.
Figure 18.4 Slope map of the study area.
Figure 18.5 Drainage map of the study area.
Figure 18.6 Priority sub-watershed map based on Mophometric parameters of Lower ...
Figure 18.7 Final priority map shows ranking of Lower Wardha sub-watershed.
Chapter 19
Figure 19.1 Geological map of the study area [modified after Middlemiss (1910, 1...
Figure 19.2 Methodology for morphometric analysis.
Figure 19.3 Drainage map of the study area (Source: AIS & LUS, 2002).
Chapter 20
Figure 20.1 Location of the study area.
Figure 20.2 Maps of layers for SINTACS method (a) depth to water table (b) Net r...
Figure 20.3 Groundwater vulnerability index (a) DRASTIC (b) SINTACS.
Figure 20.4 (a) Area under various degrees of vulnerability for DRASTIC (Khakhar...
Figure 20.5 Coefficient of determination (r
2
) for DRASTIC and SINTACS.
Figure 20.6 Temporal SINTACS intrinsic vulnerability index for the year (a) 2000...
Figure 20.7 Spatial variation of quality parameters with respect to SINTACS vuln...
Figure 20.8 Spatial variation of quality parameters with respect to SINTACS vuln...
Figure 20.9 Spatial variation of quality parameters with respect to SINTACS vuln...
Figure 20.10 Land use for (a) 2000 and (b) 2012 for the study area.
Figure 20.11 Temporal Modified groundwater vulnerability indicating risk of cont...
Figure 20.12 Modified vulnerability index and populated areas.
List of Illustrations
Chapter 1
Table 1.1 Abstract of major climate change trends in South Asian countries.
Table 1.2 Abstract of observed changes in extreme events and severe climate anom...
Table 1.3 Climate impacts on macroeconomic aggregates (cumulative percent [%] 20...
Table 1.4 Impact of climate change on main food crops in South Asia.
Table 1.5 Water resources in South Asian countries.
Table 1.6 Health risk from climate change in South Asian countries.
Table 1.7 Sector-wise adaptation approaches in South Asia.
Chapter 2
Table 2.1 Statistics of land resources in India (in million hectares) (Source: D...
Chapter 3
Table 3.1 Data source.
Table 3.2 Total area of classes.
Table 3.3 (a) Accuracy assessment of referenced image 2001.
Table 3.3 (b) Accuracy assessment of referenced image 2011.
Table 3.3 (c) Accuracy assessment of referenced image 2020.
Table 3.4 Growth of number of registered motor vehicles (2011-2017).
Table 3.5 PM
10
for Agra City.
Table 3.6 Municipal solid waste management in Agra.
Chapter 4
Table 4.1 Number of unlawful farms identified and located in the TNP between 201...
Table 4.2 Cattle owners in the Takamanda National Park.
Table 4.3 Number of logging activities identified in the TNP (2012-2016).
Table 4.4 Some fish species caught in the study area.
Table 4.5 Number of fishing activities registered in the TNP (2012-2016).
Table 4.6 Some non-timber forest products harvested in the TNP.
Table 4.7 Summary of anthropogenic activities identified and located in the TNP ...
Chapter 5
Table 5.1 Characteristics of surface and atmospheric UHIs (Oke, 1997, Oke, 1987,...
Chapter 6
Table 6.1 Bulk weight density of different types of aged snow after Meløysund et...
Chapter 7
Table 7.1 Image enhancement techniques’ categorization in remote sensing; source...
Table 7.2 Various Spectral Indices; source: author.
Table 7.3 Built-up Indices used for this study; source: author.
Table 7.4 Built-up indices and their accuracy obtained through error matrix; sou...
Chapter 8
Table 8.1 Year-wise area coverage of surface water in Angul district.
Table 8.2 Monthly variation in area coverage of surface water in Angul district.
Chapter 9
Table 9.1 Sampling locations and their physical attributes.
Table 9.2 Water quality parameters recorded in different seasons (December 2014 ...
Table 9.3 Spatio-temporal trends of changing water quality parameters in Wular L...
Chapter 10
Table 10.1 Range and mean (standard deviation) concentrations of physical parame...
Table 10.2 Range and mean (standard deviation) concentrations of chemical parame...
Table 10.3 Showing the area covered by different classes.
Chapter 11
Table 11.1 Sea level rise (SLR) in Sundarban region and its possible impacts.
Chapter 12
Table 12.1 Data used.
Table 12.2 Methodology adopted.
Table 12.3 Stream order and no. of streams.
Table 12.4 Stream length (Lu).
Table 12.5 Mean stream length (Lsm).
Table 12.6 Stream length ratio (RI).
Table 12.7 Bifurcation ratio (Rb).
Table 12.8 Stream frequency (Fs).
Table 12.9 Texture and circulatory ratio (Rc).
Chapter 14
Table 14.1 Forest cover in South Chotanagpur Division from 1911 to 2011.
Table 14.2 Forest cover and population dynamics in Gumla District.
Table 14.3 Forest cover and population dynamics in Khunti District.
Table 14.4 Forest cover and population dynamics in Ranchi District.
Table 14.5 Forest cover and population dynamics in Simdega District.
Table 14.6 Forest cover and population dynamics in Lohardagga District.
Table 14.7 NDVI classification.
Chapter 15
Table 15.1 For identifying Forest Fire Risk Zones through this analysis, the fol...
Table 15.2 For mapping the Probable Forest Fire Spreading Zones, the criterion t...
Chapter 16
Table 16.1 Soil depth and weightage.
Table 16.2 Slope angle and weightage.
Table 16.3 Rainfall intensity and weightage.
Table 16.4 Land use land cover and weightage.
Table 16.5 Land use code and class.
Table 16.6 Agricultural land suitability map.
Chapter 17
Table 17.1 Linear, areal, and relief morphometric perimeters, their symbol, form...
Table 17.2 Difference between the areas of Beas upper catchment delineated using...
Table 17.3 Linear aspect of Beas upper catchment using ASTER DEM.
Table 17.4 Liner aspect of Beas upper catchment using Cartosat DEM.
Table 17.5 Aerial aspect of Beas upper catchment using ASTER and Cartosat DEM.
Table 17.6 Relief aspect of Beas upper catchment using ASTER and Cartosat DEM.
Chapter 18
Table 18.1 Data set of the study area.
Table 18.2 Calculation of basin parameters.
Table 18.3 Morphometric parameters of the Lower Wardha sub-watershed.
Table 18.4 Calculation of morphometric parameters of study area.
Table 18.5 Calculation of morphometric parameters of study area.
Table 18.6 Calculation of compound values and assignment of final priority for t...
Chapter 19
Table 19.1 Lithostratigraphic succession of the Pohru watershed of Northwestern ...
Table 19.2 Statistics of streams in Pohru watershed.
Table 19.3 Morphological parameters for Pohru watershed.
Chapter 20
Table 20.1 The weights of parameters for DRASTIC and SINTACS method (Aller
et al
...
Table 20.2 Ranges and rating for DRASTIC parameters Civita & Marina De Maio (200...
Table 20.3 Spearman correlation coefficient for intrinsic vulnerability index an...
Table 20.4 Permissible limit for quality parameters for drinking as per IS 10500...
Table 20.5 Ranges and rating for the land use parameter.
Table 20.6 Modified vulnerability index and percentage areas.
Guide
Cover
Table of Contents
Title Page
Copyright
Preface
Acknowledgements
Begin Reading
Index
End User License Agreement
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Scrivener Publishing
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Beverly, MA 01915-6106
Publishers at Scrivener
Martin Scrivener ([email protected])
Phillip Carmical ([email protected])
Geographic Information Science for Land Resource Management
Edited by
Suraj Kumar Singh,
Shruti Kanga,
Gowhar Meraj,
Majid Farooq,
and
Sudhanshu
This edition first published 2021 by John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, USA and Scrivener Publishing LLC, 100 Cummings Center, Suite 541J, Beverly, MA 01915, USA© 2021 Scrivener Publishing LLCFor more information about Scrivener publications please visit www.scrivenerpublishing.com.
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Preface
Sustainable development refers to utilizing natural capital using qualitative and quantitative integrity by balancing anthropogenic practices, such as social activities, acquired awareness, modern technology, and food production with conservation. Sustainability attempts to identify resource scarcity, deforestation, destruction of ecosystems, and global and local environmental degradation. Sustainable utilization and control of critical natural resources cannot be accomplished without considering its impact on humans. An interdisciplinary approach is needed to ensure the long-term management of natural resources and their sustainable use from an ecological and socioeconomic viewpoint.
GI Science consists of satellite remote sensing (RS), Geographical Information System (GIS), and Global Positioning System (GPS) technology that is nowadays a backbone of environmental protection, natural resource management, and sustainable development and planning. Being a powerful and proficient tool for mapping, monitoring, modeling, and managing natural resources, it can understand the Earth’s surface and its dynamics at different observational scales. Through the spatial understanding of the problem concerning land resources, policymakers can make prudent decisions to restore and conserve critically endangered resources, such as water bodies, lakes, rivers, air, forests, wildlife, and biodiversity.
Geographic Information Science for Land Resource Management is a comprehensive book focusing on managing land resources using innovative spatial information sciences and satellite remote sensing techniques and has been written by prominent researchers actively working in this field of science. The enormous stress on the land resources over the years due to anthropogenic activities for commercialization and livelihood needs has increased manifold. The only solution to this problem lies in the stakeholders’ awareness, which can only be attained through scientific means. This awareness is the basis of sustainable development, which involves optimal natural resources management, subject to reliable, accurate, and timely information from the global to the local scale. The primary focus of this book is to replenish the gap in the available literature on the subject by bringing the concepts, theories, and experiences of the specialists and professionals in this field jointly. The editors have worked hard to bring the best literature in this field in book form to help students, researchers, and policymakers develop a complete understanding of the land system’s vulnerabilities and solutions. We hope the book shall do service to humanity, as it is intended to do.
Chapter 1 starts with the review of various literature concerning climate change in South Asia and GIScience’s role in its adaptation of mitigation. According to the authors, South Asia is one of the world’s oldest civilizations. However, it is currently facing grave issues regarding climate change, particularly the changes in the precipitation and temperature patterns. South Asia is home to more than 20% of the world population. The region is already facing the pressure of high population, and degradation of natural resources makes this region more vulnerable to climate change. Other environmental indicators include increasing temperature, melting of Himalaya ice with a high rate, rising sea level in coastal areas, floods, increasing frequency of cyclones. Remote Sensing and GIS allow to gather information quickly and use it to adapt and help with damage assessment. South Asia needs a collective policy framework to mitigate climate change’s disastrous impacts to achieve sustainable development objectives. Chapter 2 reviews the importance of land resources and the role of GI technology in its management. Land resources are renewable, extensive, and provide ground for all development activities. Twelve million hectares of land degrades every year globally, while a hundred million hectares of India is non-arable land. India promised to turn 26 million hectares of land into agricultural land that requires holistic information about landforms (like plains, hills, plateaus). The land resource planners need a synoptic view of land resources. Potential intervention areas include smart funding machinery, geospatial technology, private sector involvement, and funding diverted to increasing the ability to replenish natural resources.
In Chapter 3, Agra city’s urbanization has been assessed using analysis of satellite imagery to show spatial and temporal aspects of urban growth in Agra city. The LULC classification has been performed on Landsat TM, ETM+, and OLI satellite datasets. The city has been attracting more migrants resulting in environmental, economic, social, and ecological impacts. The author argues that proper urban planning must be coordinated between the local government and decision-makers for the sustainable development of Agra. Chapter 4 aims to define anthropogenic practices in contravention of the legislation in place and then, using geospatial methods, map out these interaction activities in Takamanda National Park, Cameroon. This study was done between 2014-2017. The majority of the information was retrieved using PAs management authority’s database; however, GPS and Garmin eTrex systems have also been used to capture the locations of anthropogenic practices in the study area. ArcGIS 10.2.2 was used to map these practices. The anthropogenic practices observed were fishing, hunting/poaching, harvesting non-timber forest products-NTFPs, and livestock rearing in the protected area (PA). The study has highlighted PA management’s problems and the urgency for a successful PA structure to be placed in motion if the SDGs are to be achieved at the country level.
Chapter 5 reviews the Urban Heat Island (UHI) effect and addresses how a micro-climate event is identified as the most distinguished urban climate representative. It has been considered a perilous predicament for years for its harmful contribution to global warming, heat-related deaths, erratic climate patterns, patterns of energy expenditure, urban air quality, and critical threat well-being of urban residents. With the change in land use patterns in urban areas, the landscape’s ability to manage the UHI effect has also changed. The author demonstrates how the impact of UHI can be significantly mitigated by using energy-efficient technologies and improving urban landscape planning and strategies. Despite increased studies on the UHI effect, no comprehensive assessment of the UHI effect elements has been reported in the existing literature. This chapter addresses the urgent need to recognize and categorize the elements that participate and mitigate the UHI effect to understand its underlying mechanisms systematically. Chapter 6 provides an introduction to the mountain cryosphere and its main concepts. Authors discuss the significance of snow studies in the alpine regions and discuss snowpack properties in the alpine regions that are essential for snowpack characterization. The authors further discuss the role of remote sensing and the importance of using it to get a more precise grasp of the snow’s physical properties and conclude that these techniques allow monitoring the alpine snowpack and their application to hydrological modeling, and avalanche forecasting.
In Chapter 7, a computational model known as spectral ratioing is discussed and explained in spatiotemporal feature extraction through satellite imagery. Since multispectral satellite images are in multiple spectral bands, a different mathematical combination is used for each spectral band. The chapter discusses how spectral ratioing can be used to derive different features. Categorization of spectra is reviewed, and spectral indices are listed along with examples. The chapter explores the types of spectral ratios and indexes and their applicability for different purposes. The spectral ratio method has been used to explore the features that can be characterized in the image by their spectral properties. Chapter 8 aims to quantify surface water coverage in the mining region of Odisha. The study estimated the changes from 2016-2019 and the changes from January 2019 to December 2019. A decision tree method was used to detect all water-bearing pixels in the study area. The chapter emphasizes satellite data’s role in tracking the variations in area coverage of surface water over time and space that helps in sustainable water management decisions.
In Chapter 9, spatial variations of physicochemical parameters of Wular lake, one of Asia’s largest freshwater lakes, were investigated using mapping of higher plumes/identifying critical areas. The authors have observed that the lake water is alkaline, characterized by medium total dissolved solids and electrical conductivity. The average concentration of parameters like calcium, magnesium, and nitrates was highest in the Lake’s northern side due to anthropogenic inputs. Other parameters like water temperature, turbidity, total dissolved solids, dissolved oxygen, hardness, alkalinity, and phosphates also showed a variable character throughout the Lake both temporally and spatially. The results highlight the varied lake water character in different seasons with the increase and decrease in Lake’s flow. In Chapter 10, a water quality assessment has been carried out in Tehsil Matta District SWAT Pakistan. The water samples have been tested for pH, electric conductivity, DO, salinity, alkalinity, total dissolved solids, chloride, sulphate, and BOD in the Environmental Sciences University of Peshawar. The results showed that pH, electrical conductivity, DO, salinity, alkalinity, total dissolved solids, chloride, sulphate, and BOD were all average values. Satellite data and GIS has been used for mapping water quality zones using spatial interpolation techniques. Matta was found safe regarding water quality. The authors used the National Standards Drinking water quality Pakistan and WHO criteria to classify water quality parameters.
Chapter 11, using satellite data, demonstrated that the sea level rise is higher in the Sundarbans area than the global mean sea level rise. A LANDSAT data analysis revealed that mangroves in this area cover 1599.9 square kilometers that have been tremendously reduced due to sea-level rise. The Sundarbans area is very susceptible to flooding. Natural hazards such as storms and coastal erosion are common in the reserve forest, significantly affecting the Sundarban mangrove forest. Chapter 12 focuses on the proper management of river catchments for efficient water and soil conservation. The study used a detailed study of morphometric patterns in the Giri watershed, Himachal Pradesh, India, a part of the Yamuna river drainage system. The results suggested that the river has often experienced high rainfall in the monsoon season, thus altering the drainage basin characteristics. The drainages are dendritic and parallel pattern in the watershed, resulting in an enormous influence on the changing watershed. The high rainfall runoff and soil erosion might be a more significant concern during the monsoon season and winter rainfall periods in the watershed.
Chapter 13 seeks to improve techniques for calculating flow and water levels in rivers in Varaždin, Croatia. They have used the RAPS approach (Rescaled Adjusted Partial Sums) to assess the subseries within the initial time series of the averaged regular flow. It has significance in calculating the periods that the river is going to flood. The approach is based on the relationship between the measured water levels and the watercourse flow in its cross-section, the rating curve. The work has proposed a geographic database and a map of all calculated locations for experts in this research field. Chapter 14 aims to assess the forest dynamics in the South Chota Nagpur districts of Jharkhand – a region that has experienced rapid population growth within a short span. There has been a decline in forest cover, which is exceptionally dense. There are multiple pockets of deforestation where development has led to changing vegetation patterns. When forests change, the people who depend on the forests may change economically. The rapid growth of population, industrialization, and urbanization has caused significant impacts on the forests in the region.
Chapter 15 attempts to show whether forest fires resulted from specific vegetation in three districts of Tamil Nadu or not. Wildfires are becoming very common in Tamil Nadu, India. In a single year, there were fires of hectares of forest land. The study generated NDVI maps from the MODIS imagery during the last three years of fire season to visualize the fires’ impact. Factors considered include vegetation type, temperatures, precipitation, roads, and the study area routes. Risk and spread maps were created with a weighted overlay tool in ArcGIS 10.3. The study proposed a mobile app that hikers can use to plan their hikes, avoiding dangerous areas. Chapter 16 attempts to delimit the land suitable for agriculture using the weighted overlay method. By understanding the land-use change, the work has focussed on performing the region’s land-use suitability analysis. About 22.34% of the land area was observed to be highly suitable for agricultural practices. The land-use suitability revolves around the concepts of land use and land cover. The term land cover refers to the biological, physical spread over the outside of the land, counting vegetation, water, soil, and built-up lands. The term land use is a progressively perplexing phenomenon that environmental researchers characterize land use as the anthropogenic activities, such as ranger service, farming, and development of the urban area that affects activities on the surface of the land hydrology, biogeochemistry, and biodiversity.
Chapter 17 is a quantitative study that emphasizes morphometric characteristics’ role by addressing the linear, aerial, and relief aspects of Beas Upper Catchment, India. Data input for the study included ASTER & CARTOSAT DEM (30m) and IRS LISS-IV Imagery. The authors demonstrated how proper planning and management of available natural resources is necessary for the region’s progress and development. They elucidated the role of satellite remote sensing and the Geographic Information System (GIS) as a competent tool for delineating and analyzing the watershed for proper planning and forecasting the topography, hydrological behavior, and drainage pattern, engineering, site suitability, and water potential of the catchment area. Chapter 18 focuses on the watershed prioritization for soil and water conservation in the lower Wardha river of Wardha River basin, Maharashtra, India. The results indicated that the drainage network is dendritic to sub-dendritic pattern and is non-perennial. Inadequate soil cover, sparse vegetation, erratic rainfall, and lack of soil moisture characterize the area for most of the year. Recurring drought coupled with an increase in groundwater exploitation results has resulted in a decline in the groundwater level. The morphometric parameters are computed using ArcMap 10.2 version GIS software. The research has divided the entire subwatershed is divided into five smaller units viz., SW-I, SW-II, SW-III, SW-IV, and SW-V that are intended to be taken up for development and management plans to conserve natural resources on a sustainable basis with immediate effects. The chapter demonstrated the implementation of timely soil and water conservation using the high, medium, and low priority watersheds to effectively make decisions.
Chapter 19 deals with the morphometric analysis of Pohru water, Kashmir Himalayas, wherein different linear, aerial, and relief parameters were calculated using Strahler’s (1964) modified scheme of stream order. The study reveals that the study area’s drainage reflects hard-rock terrain control despite unconsolidated erosional deposits at low lying areas. The overall geomorphic landscape is mature to youthful. The maximum stream segment length is noted for first-order streams, which generally decrease as the stream order increases. It is pertinent to mention that the research the calculated sinuosity index value of 1.36 for the watershed indicates that the river Pohru is of the meandering type. The study concluded that the watershed has moderate to high susceptibility to flooding in low lying areas. Chapter 20 aims to derive groundwater’s intrinsic vulnerability using the GIS platform and compares the two models– DRASTIC and SINTACS to derive the intrinsic groundwater vulnerability. The first part of the chapter aims to derive the SINTACS model’s appropriateness to find the study area’s intrinsic groundwater vulnerability. Both the models use parameters as depth, recharge, aquifer, soil, topography, vadose zone, and hydraulic conductivity. Maps representing each of these parameters depicting the hydrogeology of the area are created in the GIS environment. The vulnerability zones for both the models were derived using the weighted overlay tool in ArcGIS 10.4. Further, the results from both models were validated to the contaminants in the wells. The statistical result showed that both DRASTIC and SINTACS methods showed comparable results and can be successfully used for the alluvium aquifer system. The second part of the research assesses the temporal variation of intrinsic groundwater vulnerability for the years 2000 and 2012 and contaminants exceeding the prescribed limits concerning land use in the year 2012 for the study area using the SINTACS method. The research showed that the degree of vulnerability under the ‘extremely high’ class has increased from 3% in the year 2000 to 15% in 2012, clearly indicating groundwater’s increasing vulnerability.
EditorsSuraj Kumar SinghShruti KangaGowhar MerajMajid FarooqSudhanshu
Acknowledgements
Completing this book, Geographic Information Science for Land Resource Management, could not have been possible without the grace of almighty God.
We are grateful to Hon’ble Sunil Sharma, Chairperson, Suresh Gyan Vihar University, Jaipur, for his encouragement and support. Words cannot express our indebtedness to Hon’ble Dr. Sudhanshu, Chief Mentor, Suresh Gyan Vihar University, Jaipur, for his continuous guidance, expert suggestions, and motivation for the completion of this book.
The editors would like to express heartfelt gratitude to all the editorial advisory board members for their endless support and valuable instructions at all stages of the preparation of this book. Special thanks are due to all the reviewers for taking the time to review the chapters. We thank all the colleagues, friends, and relatives who shared their constant and moral support in one way or another. The editors are eternally thankful to Scrivener Publishing for providing us the opportunity to work and publish with them.
EditorsSuraj Kumar SinghShruti KangaGowhar MerajMajid FarooqSudhanshuMay 2021
