Sustainable development and geospatial technology. Volume 2, Applications and future directions /
This two-volume set showcases the various ways in which geospatial technology can be used to achieve sustainable development goals across different sectors such as urban planning, natural resource management, agriculture, disaster management, and energy management. The books provide insights into th...
| Other Authors: | , , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Cham :
Springer,
2024.
|
| Subjects: |
Table of Contents:
- 1 Integrated Water Resources Management (IWRM) in the Geospatial Epoch
- 2 Exploring Opportunities of Generative Artificial Intelligence for Sustainable Soil Analytics in Agriculture
- 3 Mapping of Groundwater Potential Zones Using Multi-Criteria Decision Making and Overlay Analysis
- 4 Global High-Resolution Hydro-Meteorological Variables Distribution Patterns
- 5 A Review on Application of GIS for the Assessment of Geo-Spatial Extent and Concentration of Environmental Occurrence and Impacts of Mercury Pollution
- 6 Spatial and Temporal Planform Study of River Godavari between Polavaram and Dowleswaram Bridge
- 7 Remote Sensing
- 8 Sustainability Considerations in Recent Advances of Numerical Techniques for Investigating Slope Stability
- 9 Reviewing Slope Stability Integration in Disaster Management and Land Use Planning
- 10 Quantitative Geospatial Analysis of Sedimentation Rates in Bhadar Reservoir through Advanced Remote Sensing & GIS Techniques
- 11 Application of Remote Sensing in Natural Resource Management
- 12 Harnessing Geospatial Approaches in Air Quality Mapping and Monitoring
- 13 Optimal Site Selection of Treatment Facilities and Landfill Zones for Municipal Solid Waste Disposal in Jodhpur, India using GIS and MCDA
- 14 Strategies and Implementation for Achieving Sustainable Flood Risk Management
- 15 Smart Cities and Geospatial Solutions
- 16 Applying Shadow Removal Technique for Urban Area Identification on High-resolution Aerial/Satellite Images Using Color Information and Deep Learning.