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Sustainable Development Using Geospatial Techniques

Edited by Disha Thakur, Sanjay Kumar, Har Amrit Singh Sandhu, and Chander Prakash
Copyright: 2024   |   Status: Published
ISBN: 9781394214341  |  Hardcover  |  
478 pages
Price: $225 USD
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One Line Description
This book is a must-have for anyone interested in leveraging geospatial technology, as it covers a wide range of applications and offers valuable insights into the mapping, visualization, and analysis of natural resource planning using GIS, remote sensing, and GPS.

Audience
Scientists, educators, industry professionals, researchers, and graduate and post-graduate students studying geospatial concepts

Description
Geospatial technology (GT) is a combination of geographic information systems (GIS), remote sensing (RS), and the global position system (GPS) for the mapping, visualization, and analysis of natural resource planning. Nowadays, GIS is widely used throughout the globe for a wide range of applications. GIS is a system that combines locations, geography, hardware, software, statistics, planning, and digital mapping. GIS is a system in which one can store, manipulate, analyze, and visualize or display spatial data. The basic components of GIS are hardware, software, data, input, and manpower. One can develop spatial, temporal, and dynamic models using GIS, which may help in effective decision-making tools.
Geospatial information is a computer programme that collects, stores, verifies, and presents information on locations on the surface of the Earth. Geographical information systems play a key role in sustainable development. Geospatial technology combines traditional database operations like query and statistical analysis with the specific graphical and geographic analytical capabilities offered by maps.
Data on people, such as population, income, or education level, may be included in the system. It may provide details on the topography, such as where streams are and what kinds of plants and soil are present. It may also contain details regarding the locations of storm drains, roads, and electricity lines as well as companies, farms, and educational institutions. People can use GIS technology to compare the locations of various objects to determine how they connect to one another. For instance, utilizing GIS, a single map might show both polluting and pollutant-sensitive locations, such as wetlands and rivers, as well as locations that cause pollution, such industrial plants. Geospatial techniques have also been used for different aspects of renewable energy studies like assessment, consumption, demand, site selection, agriculture, etc. and in various sectors like transport, telecommunications, public utilities, healthcare, and environmental design for sustainable development. Thus, geospatial techniques are essential tools for designing and implementing sustainable processes at scale. People around the world continue to compile scientific data about resources, ecosystems, and human impact. These techniques enable us to visualize and analyze these massive collections of data.

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Author / Editor Details
Disha Thakur, PhD is an assistant professor in civil engineering at the University Institute of Technology (UIT), Shimla, India. She has published 13 research and conference papers and book chapters in reputed journals and national and international Conferences. Her research interests include geotechnical engineering and solid waste management.

Sanjay Sharma, PhD is working an assistant professor at the University Institute of Technology, Himachal Pradesh University, Shimla, India. He has research experience in various areas of electrical engineering. He has published 24 research papers in reputed national and international journals and 18 research papers in national and international conferences. He has 8 years of teaching and has delivered expert lectures at many colleges and universities in India.

Har Amrit Singh Sandhu, PhD is part of the faculty in the Civil Engineering Department at Punjab Engineering College, Chandigarh, India. He is also president of the American Society of Civil Engineers’ Indian Chapter (North) and the coordinator at the Centre of Geospatial Technologies and a Digital India Land Records Modernization Programme cell. He has more than 20 years of experience in working, teaching, and researching in the geospatial field and has published various research papers in reputed national and international journals.

Chander Prakash, PhD is an assistant professor in the Civil Engineering Department at the National Institute of Technology (NIT), Hamirpur, India. He has published more than 25 research papers in reputed national and international journals and conferences and has completed a number of research and development projects.

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Table of Contents
Preface
1. Development of a Two-Layer Meta‑Classifier–Based Drought Stress Detection System for Wheat Crop Sustainability
Ankita Gupta, Lakhwinder Kaur and Gurmeet Kaur
1.1 Introduction
1.2 Literature Review
1.3 Background
1.4 Problem Formulation
1.5 Methodology for Drought/Water Stress Detection
1.5.1 Wheat Variety (V)
1.5.2 Chlorophyll Fluorescence Image Analysis (CFIA)
1.5.3 Feature Extraction and Selection
1.5.3.1 Gray-Level Co-Occurrence Matrix Texture Features
1.5.3.2 Color Features
1.5.3.3 Wheat Canopy Components
1.5.3.4 Wheat Canopy Landmark Features
1.5.4 Water Stress Detection in Wheat Crops
1.5.4.1 Results and Discussions
1.6 Application of Meta-Classifier–Based Detection for the Development of the Sustainable Model for Drought Detection
1.6.1 Meta-Machine Learning for Overcoming Agricultural Losses
1.6.1.1 Model Development (Meta-ML for Sustainable Agronomics: For Loss Reduction)
1.6.1.2 Effective Cost of Implementation
1.7 Conclusion
References
2. Comparison of Geo-Statistical Techniques: A Study Based on Mapping Soil Properties for a Lower Himalayan Watershed
Sahil Sharma, Shankar Yadav, Vinay Meena and Deepak Swami
2.1 Introduction
2.2 Materials and Methods
2.2.1 Study Area
2.2.2 Field and Remotely Sensed Datasets
2.2.3 Soil Physical Property Identification
2.2.4 Nature of LULC and Elevation of the Catchment
2.2.5 Spatial Interpolation Methods
2.2.5.1 Inverse Distance Weighting (IDW)
2.2.5.2 Kriging
2.2.6 Statistical Criteria
2.3 Results and Discussion
2.3.1 Soil Moisture and Organic Content Distribution Dynamics in the Catchment
2.3.2 Spatial Interpolation Methods
2.4 Conclusion and Future Scope
References
3. Monitoring Crop Conditions of Punjab State Using Big Data Analytics
Harpinder Singh, Ajay Roy, Shashikant Patel and Brijendra Pateriya
3.1 Introduction
3.2 Objectives
3.3 Study Area and Data
3.3.1 Study Area
3.3.2 Data
3.4 Methods
3.4.1 Preparing the MODIS EVI Dataset
3.4.2 Deviation
3.4.3 Masking the Non-Cropland Area
3.4.4 District-Wise Analysis
3.5 Results and Discussions
3.6 Conclusions
References
4. An Investigation into Use of Ethereum Blockchain Technology to Validate the Reliability and Quality of Stored Satellite Images
Lince Mathew, Hamid Jahankhan and Sumesh Dadwal
4.1 Introduction
4.2 Literature Review
4.2.1 Satellite Imaging Technology
4.2.2 Current Technology Used and Its Drawbacks and Impact of Using Blockchain Systems
4.2.2.1 Drawbacks of Current Technology
4.2.3 Impact of Using Blockchain Systems
4.2.4 Blockchain Technology
4.2.5 Ethereum Blockchain
4.2.6 Satellite Image Integrity and Accuracy
4.2.7 Blockchain-Based Approaches for Satellite Image Safekeeping
4.3 Methodologies and Tools Used for Simulating the Ethereum Blockchain
4.4 Evaluation Metrics and Criteria for Assessing the Effectiveness of Ethereum Blockchain in Satellite Image Safekeeping
4.5 Case Studies and Experiments Demonstrating the Integrity and Accuracy of Satellite Images Using Ethereum Blockchain Simulation
4.6 Research Method
4.7 Data Analysis and Critical Discussions
4.8 Testing Phase
4.8.1 Automated Validation
4.8.2 Transaction Information of this GPS Positioning
4.8.3 GPS Positioning Data
4.8.4 GPS Positioning Data During Transaction Information
4.8.5 Security Analysis of Ethereum Blockchain
4.8.6 Evaluation of Ethereum Blockchain
4.8.7 Discussions on Ethereum Blockchain’s Smart Contracts
4.9 Challenges and Future Directions
Conclusion
References
5. Urban Expansion and Traffic Congestion: A Geographical Study of Shimla
Akshat Sharma and Amardeep Boora
5.1 Introduction
5.2 Study Area
5.3 Methodology
5.4 Result and Discussion
5.5 Accuracy Assessment
5.6 Traffic Congestion Analysis
5.7 Conclusion
References
6. Landslide Susceptibility Analysis for Sustainable Development in the Indian Himalayas
Ankur Sharma and Har Amrit Singh Sandhu
6.1 Introduction
6.2 Study Area
6.3 Data
6.3.1 Landslide Inventory
6.3.2 Landslide Causal Factors
6.3.2.1 Elevation
6.3.2.2 Slope
6.3.2.3 Aspect
6.3.2.4 Curvature
6.3.2.5 Terrain Ruggedness Index (TRI)
6.3.2.6 Distance to Roads
6.3.2.7 Distance to Drainage
6.3.2.8 Distance to Faults
6.3.2.9 Land Use/Land Cover (LULC)
6.4 Methodology
6.4.1 Frequency Ratio Method
6.4.2 Weighted Linear Overlay
6.5 Results and Discussion
6.5.1 FR Analysis and Relative Importance of Causal Factors
6.5.2 LSZ Mapping and Its Validation
6.6 Conclusions
References
7. Application of Geospatial Tools in Glacial Lake Outburst Floods: Mapping and Monitoring
Anita Sharma, Vansheika and Chander Prakash
7.1 Introduction
7.1.1 Climate Change and Glacial Recession
7.1.2 Glacial Lakes
7.1.3 Formation of Glacial Lakes
7.1.4 Kinds of Glacial Lakes
7.1.5 History of Glacial Lake Outburst Floods and Events in the Himalayas
7.1.5.1 Dam-Break Floods
7.1.5.2 Subglacial Floods
7.1.5.3 Ice-Dammed Lake Floods
7.1.5.4 Lake Floods Caused by Moraines
7.1.5.5 Rain-Triggered Floods
7.2 Geospatial Techniques
7.2.1 Techniques for Mapping and Monitoring of Glacial Lakes
7.2.2 Spectral Feature-Based Glacial Lake Mapping
7.2.3 Google Earth Engine–Based Glacial Lake Mapping and Monitoring
7.2.4 Mapping and Monitoring of Glacial Lakes Using Deep Learning
7.3 Discussion and Conclusion
References
8. Dynamic Coastal Flood Risk Assessment of a Coastal Island in West Bengal, India
Praneta, N., Aishwarya, N. and Bharath, H. A.
8.1 Introduction
8.2 Study Area
8.3 Method
8.3.1 Multidimensional Parametric Flood Risk Model (MPFR - Model)
8.4 Results and Discussion
8.4.1 Land-Use Mapping
8.4.2 Future Built-Up Prediction
8.4.2.1 Mapping Growth Parameters
8.4.2.2 Land Suitability Analysis
8.4.2.3 Predicted Land-Use Map of 2050
8.4.3 Parameter Ranking Using AHP
8.4.3.1 Yaas Flooding as an Exposure Parameter
8.4.3.2 Ranking Using AHP
8.4.4 Flood Exposure Maps
8.4.5 Flood Vulnerability Maps
8.4.6 Flood Risk Zoning
8.5 Conclusion
Acknowledgments
References
9. A Review of Methods for Studying Glacier Dynamics Due to Climate Change in the Himalayas
Shanta Kumar and Anurag Linda
9.1 Introduction
9.2 Monitoring of Himalayan Glaciers by Different Methods
9.2.1 Mass Balance Through Remote Sensing Methods
9.2.2 Mass Balance Through AAR/ELA
9.2.2.1 Mass Balance Through Area Accumulation Ratio (AAR) Methods
9.2.2.2 Equilibrium Line Altitude (ELA) Method
9.2.3 Normalized Difference Snow Index (NDSI) Methods
9.2.4 Mass Balance Through Ice Surface Velocity
9.2.5 Mass Balance Through Glacier Delineation
9.2.6 Manual Digitization
9.2.7 Automatic Digitization
9.2.8 Field-Based Methods
9.2.8.1 Mass Balance Through Glaciological Approach
9.2.8.2 Mass Balance Through Geodetic Methods
9.3 Discussion and Conclusion
References
10. Geospatial Techniques for Flash Flood Hazard Assessment and Management
Nitesh Godara, Amit Challana, Tarun Bansal and Arun Bawa
10.1 Understanding Flash Flood Hazards
10.1.1 Introduction to Flash Floods
10.1.2 Flash Flood Causes and Triggers
10.2 Geospatial Tools Overview
10.2.1 Remote Sensing Fundamentals
10.2.2 Geographic Information Systems (GIS) Basics
10.3 Remote Sensing for Flash Flood Assessment
10.3.1 Satellite Imagery for Flood Monitoring
10.3.2 Radar and LiDAR in Flood Detection
10.3.2.1 Radar Technology
10.3.2.2 LiDAR Technology
10.3.3 Thermal Imaging for Flood Analysis
10.4 GIS Applications in Flash Flood Management
10.4.1 Hydrological and Hydraulic Modeling with GIS
10.4.2 Creating Flood Hazard Maps
10.5 Drone Mapping for Rapid Response
10.6 Collaborative Approaches and Socioeconomic Considerations
10.6.1 Collaboration Among Stakeholders
10.6.2 Socioeconomic Impacts of Flash Floods
10.6.3 Supply Chain Analysis and Resilience
10.7 Future Trends and Conclusion
10.7.1 Emerging Trends in Geospatial Techniques
10.7.2 Advancements in Flash Flood Management
10.7.3 Concluding Remarks and Future Directions
References
11. Prediction of Water Hardness Using Machine Learning and Model Interpretation
Aarti Kochhar, Harpinder Singh, Shashikant Patel, P.K. Litoria and Brijendra Pateriya
11.1 Introduction
11.2 Literature Survey
11.3 Materials and Methods
11.3.1 Parameters
11.3.2 Model Description
11.3.3 Modeling Procedure
11.4 Results and Discussions
11.4.1 Results: Machine Learning Models
11.4.2 Machine Learning Model Explanation
11.5 Conclusion
Conflict of Interest
References
12. Air Quality Mapping Using GIS for Kanpur City, India
Varun Yadav and Rajiv Ganguly
12.1 Introduction
12.2 Methodology
12.2.1 Site Selection and Data Collection
12.2.2 Geospatial Techniques
12.2.3 Software and Tools
12.3 Data Analysis and Results
12.3.1 Descriptive Analysis
12.3.2 Interpolation Results
12.3.3 Comparison of Interpolation Techniques
12.3.4 Hotspots of Air Pollution
12.3.5 Policy Implications and Recommendations
12.4 Discussions and Conclusion
12.4.1 Discussion
12.4.2 Conclusion
References
13. Geospatial Modeling Approach and Characteristics Study of Graphene‑Anchored Cu-Nanoferrites and Their Potential in Arsenic Containing Wastewater Treatment
G. Murtaza and Ahmad Ayyaz
13.1 Introduction
13.2 Experimentation
13.2.1 Preparation of CuFe2O4
13.2.2 Preparation of G/CuFe2O4-NP Composites
13.2.3 Characterization
13.2.4 Arsenic Removal
13.3 Results and Discussion
13.3.1 X-Ray Diffraction (XRD)
13.3.2 Fourier Transform Infrared Spectroscopy (FTIR)
13.3.3 Surface Morphological Analysis
13.3.4 Energy Dispersive X-Ray Spectroscopy (EDX)
13.3.5 Magnetic Properties
13.3.6 Brunauer-Emmett-Teller Method for Textural Features
13.3.7 Arsenic Removal
13.4 Conclusion
References
14. Managing Construction and Demolition Waste Illegal Dumping through GIS: A Case Study of Urban Metropolitan
Shubhi Nuna, Bharath H. Aithal and Brajesh Dubey
14.1 Introduction
14.1.1 CDW Statistics for India
14.1.2 Negative Impacts of Improper CDW Management
14.1.3 CDW Management Barriers in India
14.1.4 Proposed CDW Management Model
14.2 CDWM Using GIS Tools and Multivariate Analysis Techniques
14.2.1 Predicting Probable Locations of Illegal Dumpsites (ILs)
14.2.2 Approaches to Spatial Analysis for Optimal Facility Locations
14.2.3 Location-Allocation Problems
14.2.3.1 Minimize Impedance (MI)
14.2.3.2 Maximize Coverage (MC)
14.2.3.3 Minimize Facilities (MF)
14.2.3.4 Maximize Attendance (MA)
14.3 The Case Study of Gurugram Municipality
14.3.1 Current CDW Collection System
14.3.2 Data Collection—Thematic and Spatial Database
14.4 Methodology
14.4.1 Probable Illegal Dumps Occurrence Mapping
14.4.2 Emplacement by MCE Analysis
14.4.3 Emplacement by Network Analysis
14.5 Results and Discussion
14.6 Conclusion
Acknowledgment
References
15. Assessment of Human Health Risk in Baitarani Basin, Odisha Using Water Quality Index (WQI), Cluster Analysis (CA), and Geographic Information Systems (GIS)
Abhijeet Das
15.1 Introduction
15.2 Study Area
15.3 Materials, Sampling, and Analysis
15.4 Methodology
15.4.1 Surface Water Quality (SWQ) Modeling
15.4.1.1 WAWQI Model
15.4.1.2 SPI Model
15.4.1.3 NPI Model
15.4.1.4 CPI Model
15.4.1.5 OIP Model
15.4.2 Cluster Analysis (CA)
15.5 Results and Discussions
15.5.1 Blending Approach of Different WQIs with GIS
15.6 Conclusions
Acknowledgments
References
16. Drone Mapping for Agricultural Sustainability: Applications and Benefits
Arun Bawa, Gurjinder Baath, Pulkit Juneja and Jaiveer Brar
16.1 Introduction
16.2 Agricultural Remote Sensing: Satellite and Drones
16.2.1 Satellite
16.2.2 Drones
16.2.3 Satellite Versus Drones
16.2.4 Drone Mapping: A Complementing System
16.3 Drone Mapping for Precision Agriculture
16.3.1 Crop Health Monitoring and Assessment
16.3.2 Field Management Zones and Variable Rate Application
16.3.3 Weed, Insect, and Disease Detection and Management
16.3.4 Yield Forecasting
16.4 Economic Perspectives
16.5 Challenges
16.6 Future Perspectives
16.7 Conclusions
References
17. Advanced Use of Drones in Irrigation and Water Management
Swati Sharma and Pragya Singh
17.1 Introduction
17.2 Study Area
17.3 Methodology
17.3.1 Flight Planning
17.3.2 Drone Survey with DGPS
17.3.3 Image Processing and Georeferencing
17.3.4 Area Assessment and Crop Identification
17.3.5 Digitization of Plan Map
17.3.6 Preparation of L-Section in AutoCAD
17.3.6.1 Slope
17.4 Result and Discussion
17.4.1 Contour Map
17.4.2 Grid Map
17.4.3 Final Plan Map
17.4.4 L-Sections
17.5 Conclusion
Acknowledgments
References
Index

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