Kooperativer Bibliotheksverbund

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Format: 1 online resource (347 pages)

Edition: First edition.

ISBN: 3-031-52561-2

Series Statement: Geotechnologies and the Environment Series ; Volume 26

Note: Intro -- Preface -- Acknowledgments -- Contents -- Chapter 1: Insights into the Multifaceted Application of Technology to Empower Disaster Resilience: A Geospatial Perspective -- 1.1 Introduction -- 1.2 Emerging Trend of Disaster Risk Reduction and Resilience Building -- 1.3 Disaster Resilience: Role of Geospatial Technology -- 1.3.1 Allocation of Resources -- 1.3.2 Civilian Engagement and Crowd-Sourced Data -- 1.3.3 Risk Assessment, Vulnerability Analysis and Prediction Modeling -- 1.3.4 Post-disaster Recovery and Reconstruction -- 1.4 Limitations -- 1.4.1 Data Quality and Accuracy -- 1.4.2 Technological Accessibility -- 1.4.3 Capacity Building and Education -- 1.4.4 Privacy and Ethical Concerns -- 1.5 Future Scope -- 1.5.1 Enhanced Data Resolution and Accuracy -- 1.5.2 Integration with Emerging Technologies -- 1.5.3 Ethical and Inclusive Practices -- 1.5.4 Continuous Education and Capacity Building -- References -- Chapter 2: River Conservation and Water Resource Management -- 2.1 Introduction -- 2.2 Environmental Impacts -- 2.3 River Rejuvenation -- 2.4 Sustainable Development -- 2.5 Climate: Resilient Nation -- 2.6 Conclusion -- References -- Chapter 3: Morphometric Analysis for Prioritizing Sub-watersheds of the Chulband River Basin, India, Using Geospatial Techniques -- 3.1 Introduction -- 3.2 Study Area -- 3.3 Methods -- 3.4 Results and Discussion -- 3.4.1 Linear Parameters -- Stream Order (U) -- Stream Number (Nu) -- Stream Length (Lu) -- Bifurcation Ratio (Rb) -- Stream Length Ratio (Rl) -- Mean Bifurcation Ratio -- Stream Frequency (Fs) -- Mean Stream Length Ratio -- Drainage Density -- Drainage Texture -- Length of Overland Flow -- Rho Coefficient -- Drainage Intensity -- Infiltration Number -- Constant of Channel Maintenance -- 3.4.2 Areal/Shape Parameters -- Relief -- Relief Ratio -- Relative Relief -- Ruggedness Number. , 3.4.3 Relief Parameters -- Watershed Area -- Watershed Perimeter -- Circulatory Ratio -- Elongation Ratio (re) -- Form Factor -- Lemniscate Ratio -- Shape Index -- Compactness Coefficient -- Morphometric Sub-watershed Prioritization and Ranking -- Conclusions -- References -- Chapter 4: A GIS Based Study of the Effects of Groundwater, Soil Quality and Rainfall on Agriculture in Bagh River Basin, India -- 4.1 Introduction -- 4.2 Study Area -- 4.3 Data Used and Methodology -- 4.3.1 Ground Water Quality -- 4.3.2 Groundwater Sampling and Physico-chemical Analysis -- 4.3.3 Descriptive Statistics Analysis -- 4.3.4 Mann-Kendall Test (Non-parametric Test) -- 4.3.5 Spearman's Rank Correlation Coefficient -- 4.3.6 Inverse Distance Weighing -- 4.3.7 Soil Health -- 4.4 Results and Discussion -- 4.4.1 Ground Water Qualities -- Groundwater Effects on Agriculture -- Groundwater Quality Index -- 4.4.2 Soil Health -- Agricultural Productivity and Intensity -- Land Capability -- Soil Fertility -- Reasons for Low Fertility Index BRB -- Soil Quality Effect on Agriculture -- 4.5 Rainfall Effects on Agriculture -- 4.6 Agricultural Model -- 4.6.1 Integrated Farming System Model -- 4.7 Conclusion -- References -- Chapter 5: Statistical Approach to Visualize the Seven-Decadal Rainfall Variation as Response to Climate Change in a Semiarid Region of Karnataka, India -- 5.1 Introduction -- 5.2 Study Area and Dataset -- 5.3 Methodology -- 5.4 ITA -- 5.5 MK -- 5.6 SS Estimator -- 5.7 Result -- 5.8 Pre-monsoon -- 5.9 Southwest Monsoon -- 5.10 Northeast Monsoon -- 5.11 Annual -- 5.12 Discussion and Conclusion -- References -- Chapter 6: AI-Based Rainfall-Runoff Modelling for Sustainable Water Management in Potteruvagu Watershed, India -- 6.1 Introduction -- 6.2 Study area -- 6.3 Material and Methods -- 6.3.1 Data -- 6.3.2 AI Models -- 6.3.3 Performance Evaluation of the Model. , 6.4 Results and Discussions -- 6.4.1 ANN Model -- 6.4.2 KNN Model -- 6.4.3 RF Model -- 6.4.4 Comparison of Three AI Models -- 6.5 Conclusions -- References -- Chapter 7: Building Flood Resilience Through Flood Risk Assessment with Optical and Microwave Remote Sensing -- 7.1 Introduction -- 7.1.1 Conceptual Framework of Flood Risk -- 7.1.2 Prioritization Order of Influencing Factors -- 7.1.3 Flood: Indian Perspective -- Role of Indian Space Research Organization -- 7.1.4 Flood Protection Measures -- 7.2 Methods of Flood Risk Assessment -- 7.2.1 Historical Methods Used for Flood Risk Assessment -- 7.2.2 Contemporary Methods to Flood Risk Assessment -- 7.3 Quantitative Models Used in Flood Risk Assessment Worldwide -- 7.4 Tool and Techniques -- 7.4.1 Type of Flood Hazards -- 7.4.2 Remote Sensing Techniques Used for Flash Flood -- 7.4.3 Use of UAV-LiDAR System -- 7.4.4 Use of SAR Data -- 7.4.5 Flood and Hydrologic Engineering -- 7.5 Conclusion -- References -- Chapter 8: Satellite Image-Based Drought Monitoring: Vision to Enhance Drought Resilience -- 8.1 Introduction -- 8.2 Study Area -- 8.2.1 Soil and Crops -- 8.2.2 Weather Conditions -- 8.3 Data Used and Methodology -- 8.3.1 Satellite Data -- 8.3.2 Processing and Analysis of MODIS Data -- 8.3.3 The Jodhpur District's Rainfall Pattern -- 8.3.4 Standardized Precipitation Index (SPI) -- 8.3.5 Normalized Difference Vegetation Index (NDVI) -- 8.3.6 Correlation of SPI and NDVI Using Regression Analysis -- 8.4 Results & -- Discussion -- 8.4.1 Drought Monitoring Through SPI -- 8.4.2 Variation in the NDVI with Time and Space -- 8.4.3 Assessment of Vegetation Pattern -- 8.4.4 Temporal Variation of NDVI and SPI -- 8.4.5 Correlation Analysis of Seasonal NDVI and SPI -- 8.5 Conclusions -- References. , Chapter 9: The Power of Machine Learning in Forest Fire Risk Analysis and Resilience: Navigating Best Practices, Challenges, and Opportunities -- 9.1 Introduction -- 9.1.1 Case Studies on the Impact of Forest Fire in an Environment -- 9.1.2 Important Areas of Research Related to Forest or Wildfire as Follows -- 9.2 Rationale of the Study -- 9.3 Methods -- 9.3.1 Types of Forest Fire -- 9.3.2 Types of Fire Detection Techniques -- 9.3.3 Data Acquisition System -- 9.3.4 Prediction of Fire Risks Using Machine and Deep Learning Techniques -- 9.3.5 Time and Location Alarming System -- 9.4 Discussion -- 9.4.1 Case Studies -- 9.4.2 Challenges -- 9.4.3 Advantages -- 9.4.4 Opportunities -- 9.4.5 Best Practices -- 9.4.6 Limitations -- 9.5 Conclusion -- References -- Chapter 10: Machine Learning for Forest Fire Risk and Resilience -- 10.1 Introduction -- 10.2 Types of Forest Fires -- 10.3 Causes of Forest Fires -- 10.3.1 Natural Causes -- 10.3.2 Human Causes -- 10.4 Effects of Forest Fire -- 10.5 Forest Fires That Have Occurred in India -- 10.6 Global Forest Fires -- 10.7 Role of Machine Learning -- 10.7.1 Predictive Modelling -- 10.7.2 Image Recognition -- 10.7.3 Natural Language Processing -- 10.7.4 Remote Sensing -- 10.7.5 Decision Making -- 10.8 Challenges & -- Limitations of Machine Learning Use -- 10.9 Conclusion -- References -- Chapter 11: Advanced Application of Unmanned Aerial Vehicle (UAV) for Rapid Surveying and Mapping: A Case Study from Maharashtra, India -- 11.1 Introduction -- 11.2 Study Area -- 11.3 Material and Methods -- 11.3.1 Reconnaissance -- 11.3.2 GCP Establishment -- 11.3.3 Flight Planning and Image Acquisition -- 11.3.4 Image Processing -- 11.3.5 Image Orientation -- 11.3.6 Dense Point Cloud Generation -- 11.3.7 Digital Elevation Model -- 11.3.8 Orthophoto Generation -- 11.3.9 Map Preparation -- 11.4 Results and Discussion. , 11.4.1 Coordinates Collected -- 11.4.2 Survey Data -- 11.4.3 Camera Locations (Fig. 11.7) -- 11.4.4 Image Orientation -- 11.4.5 Digital Elevation Model -- 11.5 Conclusion -- 11.5.1 Role of Drones in Building a Climate-Resilient Nation -- References -- Chapter 12: Application of Digital Technologies & -- Remote Sensing in Precision Agriculture for Sustainable Crop Production -- 12.1 Introduction -- 12.2 Precision Agriculture & -- Its Goal -- 12.3 Review of Literature -- 12.4 Method Used in Precision Agriculture -- 12.5 Tools & -- Technologies Used in Experimental Set up in Precision Agriculture -- 12.6 Methodology -- 12.7 Benefits of Precision Agriculture -- 12.8 Economic Benefits & -- Environmental Impacts of Precision Agriculture -- 12.9 Result Analysis & -- Discussion -- 12.10 Conclusion -- References -- Websites -- Journal Articles -- Conference Paper -- Chapter 13: Advances in Soil Resource Management in Geoinformatics Domain: A Comprehensive Review -- 13.1 Introduction -- 13.2 Visual Interpretation of Satellite (VIS) Images -- 13.3 Several Indices Involved in Remote Sensing and GIS Techniques -- 13.4 Soil Analysis -- 13.5 Soil Organic Carbon and Non photosynthetic Vegetation -- 13.6 Iron Content (Fe) -- 13.7 Carbonates -- 13.8 Estimation of Moisture Stress in Soils -- 13.9 Water and Nutrient Stress -- 13.10 Soil Salinity Assessment -- 13.11 Soil Pollution and Remediation -- 13.12 Land Capability and Soil Site Suitability Analysis -- 13.13 Soil Health -- 13.14 Conclusions -- References -- Chapter 14: Smart Village Planning Towards Sustainability Using Geospatial Techniques - A Case Study of Muzaffarnagar District, India -- 14.1 Introduction -- 14.2 Study Area -- 14.3 Data Used and Methodology -- 14.4 Results and Discussion -- 14.5 Conclusion -- References. , Chapter 15: A Review of Spatial Analysis Techniques Used for LULC Change Detection Over Delhi NCR in the Past Two Decades.

Additional Edition: ISBN 3-031-52560-4

Language: English