Remote Sensing of Land Cover and Land Use Changes in South and Southeast Asia, Volume 1

Mapping and Monitoring

Krishna Prasad Vadrevu, Christopher Justice, Garik Gutman

• Publisher: CRC Press
• Year: 2025
• eBook ISBN: 9781040387979
• Edition: 0
• Topic: Technology & Engineering
• Subtopic: Geography
• Index: Geography

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.

Table of contents

• Cover
• Half-Title Page
• Title Page
• Copyright Page
• Table of Contents
• Preface
• List of Contributors
• 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 through a Novel Spatial Attention Enhanced-Dual Path-Siamese Neural Network
• 4 Super-Resolution Enhancement of Landsat Satellite Data Using Generative Adversarial Networks (GANs) and UNET 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 Bạc 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
• Index