图书简介
This book addresses the environmental challenges that Libya and similar countries in the regions are currently facing. Each chapter of this book provides a methodology using remote sensing (RS) and geographical information systems (GIS) dealing with one of these environmental challenges such as monitoring and mapping soil salinity and prediction of soil properties, monitoring and mapping of land degradation, spatiotemporal land use/cover, agricultural drought monitoring, hydrological applications such as spatial rainfall distribution, surface runoff, geo-morphometric analysis, flood hazard assessment and mapping, hydrologic and hydraulic modeling, pollution hazard assessment, and climate-related geophysical processes. This book also assesses the impacts of climate change on natural resources using both RS and GIS, as well as other applications, covering different parts of Libya. This book is beneficial for graduate students, researchers, policy planners, and stakeholders in Libya as well as other countries that share similar environmental issues. Also, the methodologies followed in the book’s chapters can be applied to any other regions around the world with similar landscapes and climatic conditions.
1. Introduction to “Environmental Applications of Remote Sensing and GIS in Libya”.- 2. Application of remote sensing and GIS in land cover/land use mapping and change detection using Google Earth Engine platform: a case study in northwestern Libya.- 3. Evaluation of selected vegetation indices to assess rangeland vegetation in eastern Libya.- 4. Spatiotemporal analysis of Vegetation Health Index (VHI) and drought patterns in Libya based on remote sensing time series.- 5. Integration of remotely sensed data and machine learning technique for spatial prediction of selected soil properties in northwestern Libya.- 6. Field and laboratory estimation of soil erodibility, erosion and degradation of the semi-arid Aljabal Alkhdar region, Libya.- 7. DRAINMOD applications to design drainage systems in Libya using soil salinity data predicted by GIS, remote sensing and Artificial Neural Networks.- 8. Surface water potential and suitable sites identification for RWH in the semi-arid and arid watershed of Wadi Sammalus, northeast Libya using GIS and Remote Sensing approach.- 9. Stepwise approach for morphometric modeling of Wadi Zamzam watershed in north-western Libya using GIS and remote sensing techniques.- 10. Geospatial mapping and analysis of the 2019 Flood Disaster extent and impact in the city of Ghat in southwestern Libya using Google Earth Engine and deep learning technique.- 11. Oil pollution monitoring and detection using GIS and remote sensing techniques: case study from Libya.- 12. Conclusions, and Recommendations for Environmental Applications of Remote Sensing and GIS in Libya.
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