Remote Sensing of Land Cover and Land Use Changes in South and Southeast Asia, Volume 1 (eBook, ePUB)

Mapping and Monitoring
Redaktion: Vadrevu, Krishna Prasad; Gutman, Garik; Justice, Christopher

• Format: ePub

Produktbeschreibung

South and Southeast Asian countries are experiencing rapid land cover and land use changes (LCLUC) due to urbanization, agricultural expansion, deforestation, and infrastructure development. These changes have far-reaching consequences for biodiversity, water resources, food security, and climate regulation, underscoring the urgent need for effective monitoring and management strategies. Remote sensing data is essential for mapping and monitoring these changes. A variety of remote sensing data, ranging from coarse to very high resolution, can be used to assess land use patterns, and quantify changes.

Volume 1 showcases the practical utility of remote sensing data in various LCLUC studies. The book features contributions from the NASA-funded South/Southeast Asia Research Initiative and collaborators from multiple countries in South and Southeast Asia.

Key Features:

• Explores the latest methodologies, from deep learning to novel data integrations, for mapping LCLUC.
• Demonstrates case studies to monitor and map land cover changes using very-high, medium, and coarse-resolution satellite data.
• Highlights the role of remote sensing in integrating biophysical and socioeconomic data.
• Provides case studies on urban expansion, deforestation, and agricultural intensification.
• Demonstrates advanced remote sensing methods for tracking land use changes.
• Offers insights into sustainable land management using remote sensing and geospatial technologies.

This book serves as a cornerstone for advancing research and collaboration in the field of remote sensing and land use studies, particularly in South and Southeast Asia. It will be an invaluable resource for mapping and monitoring professionals, including remote sensing experts, geographers, environmental scientists, ecologists, and all others involved in land use/cover change research.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 386
• Erscheinungstermin: 22. Juli 2025
• Englisch
• ISBN-13: 9781040387979
• Artikelnr.: 74303983

Autorenporträt

Dr. Krishna Prasad Vadrevu is a remote sensing scientist at NASA's Marshall Space Flight Center in Huntsville, Alabama, USA. His research focuses on land cover and land use change (LCLUC), fire dynamics, and biomass burning emissions. With 25 years of experience in satellite remote sensing, he has an extensive publication record. He is the Deputy Program Manager for NASA's LCLUC Program and leads the South/Southeast Asia Research Initiative. Dr. Christopher Justice is a Distinguished University Professor in the Department of Geographical Sciences at the University of Maryland, College Park, USA, with 45 years of experience in remote sensing research. He is a Project Scientist for the NASA LCLUC Program, the Land Discipline Lead for NASA MODIS, and a Suomi-NPP VIIRS Science Team member. Additionally, he is the Co-Chair of the GEO Global Agricultural Monitoring Initiative (GEOGLAM), Chief Scientist for NASA HARVEST, and Chair of the international Global Observations of Forest and Land Use Dynamics (GOFC-GOLD) program. Dr. Garik Gutman is Program Manager for the NASA Land-Cover/Land-Use Change (LCLUC) Program. After 14 years of research on deriving land surface variables from satellite data at the National Oceanic and Atmospheric Administration (NOAA), he joined NASA Headquarters in 1999 and has been leading the LCLUC program, as well as Landsat-related activities, at NASA for over 25 years. He is the author of over 90 publications in peer-reviewed scientific journals and of several chapters in various climate- and land-cover related scientific volumes.

Inhaltsangabe

1. Land Cover/Land Use Changes in South and Southeast Asia: An Overview. 2.
Monitoring the Extent of Trees Outside of Forests in South Asia:
Nature-based Solutions for Climate Change Mitigation. 3. Land Use and Land
Cover Change (LULCC) Detection in Bangalore, India Using Multi-Temporal
Synthetic Aperture Radar and Spatial Attention Enhanced Siamese Network. 4.
Super-Resolution Enhancement of Landsat Satellite Data Using Generative
Adversarial Networks (GANs) and U-Net Deep Learning Algorithms. 5.
Agriculture Crop Monitoring for Yield Estimation with Zero Shot Fruit
Detection: A Deep Learning Approach. 6. Mapping Forest Types in Myanmar
Helps Set Conservation Priorities in a Key Indo-Burma Biodiversity Hotspot.
7. Vegetation Disturbance and Fragmentation in Uttarakhand, India: A Case
Study Using MODIS and Very High-Resolution Satellite Datasets. 8. Machine
Learning of NDVI Time Series Identifies Ghost Villages in Uttarakhand,
India. 9. Evaluation of Deep Learning Algorithms for Mapping Burnt Areas in
an Agricultural Landscape. 10. Deep Learning Models for Fire Prediction: A
Comparative Study. 11. Land Cover Change in Cambodia, Laos, Myanmar,
Thailand, And Vietnam and the Effects of Varied Spatial Scales and Land
Cover Classes. 12. Characterizing Aquaculture-Associated Land Cover Land
Use Changes in Central Thailand, 1990-2020. 13. Crop Type Mapping in
Smallholder Agricultural Settings Using Sentinel-1 SAR Imagery and Deep
Learning. 14. Land Use/Land Cover Changes in the Mekong Delta, Vietnam
Using Landsat Remote Sensing Data. 15. Satellite Observations of Land Cover
and Land Use in the B¿c Liêu Province, Vietnam. 16. Spatio-Temporal Pattern
Mapping of Ganoderma Disease in Oil Palm Plantations with PALSAR-2
Time-Series. 17. Monitoring Urban Sprawl Using Synthetic Aperture Radar
(SAR) Data: A Case Study of the Denpasar Greater Area, Bali, Indonesia.