Remote Sensing of Natural Resources

• Main Authors: Wang, Guangxing, Weng, Qihao
• Format: eBook Book
• Language: English
• Published: Boca Raton CRC Press 2014; Taylor & Francis Group
• Edition: 1
• Series: Remote sensing applications series
• Subjects: Natural resources; Natural resources > Remote sensing; NATURE / Environmental Conservation & Protection. bisacsh; Remote sensing; TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems. bisacsh; Error Matrix; Sample Plots; RS Image; LiDAR Data; LiDAR Point Cloud; LiDAR Metric; End Members Selection; RS Data; Tree Species Classification; LULC Type; LULC Category; LiDAR Remote Sensing; Hyperspectral Data; ALOS PALSAR; LiDAR System; Reference Data; Remote Sensing; Accuracy Assessment; Airborne LiDAR; Tree Crown Boundaries; LSMA; LULC Classification; IRS Image; Vegetation Cover Factor; Profile LiDAR
• ISBN: 1466556927; 9781466556928
• DOI: 10.1201/b15159

This book emphasizes the most advanced remote sensing systems and algorithms for image processing, enhancement, feature extraction, data fusion, image classification, image-based modeling, image-based sampling design, map accuracy assessment and quality control. It also discusses their applications...

Table of Contents:

• Front Cover -- Contents -- Acknowledgments -- Editors -- Contributors -- Introduction to Remote Sensing of Natural Resources -- Chapter 1 - Introduction to Remote Sensing Systems, Data, and Applications -- Chapter 2 - Remote Sensing Applications for Sampling Design of Natural Resources -- Chapter 3 - Accuracy Assessment for Classification and Modeling -- Chapter 4 - Accuracy Assessment for Soft Classification Maps -- Chapter 5 - Spatial Uncertainty Analysis When Mapping Natural Resources Using Remotely Sensed Data -- Chapter 6 - Land Use/Land Cover Classification in the Brazilian Amazon with Different Sensor Data and Classification Algorithms -- Chapter 7 - Vegetation Change Detection in the Brazilian Amazon with Multitemporal Landsat Images -- Chapter 8 - Extraction of Impervious Surfaces from Hyperspectral Imagery: Linear versus Nonlinear Methods -- Chapter 9 - Road Extraction: A Review of LiDAR-Focused Studies -- Chapter 10 - Application of Remote Sensing in Ecosystem and Landscape Modeling -- Chapter 11 - Plant Invasion and Imaging Spectroscopy -- Chapter 12 - Assessing Military Training-Induced Landscape Fragmentation and Dynamics of Fort Riley Installation Using Spatial Metrics and Remotely Sensed Data -- Chapter 13 - Automated Individual Tree-Crown Delineation and Treetop Detection with Very-High-Resolution Aerial Imagery -- Chapter 14 - Tree Species Classification -- Chapter 15 - Estimation of Forest Stock and Yield Using LiDAR Data -- Chapter 16 - National Forest Resource Inventory and Monitoring System -- Chapter 17 - Remote Sensing Applications on Crop Monitoring and Prediction -- Chapter 18 - Remote Sensing Applications to Precision Farming -- Chapter 19 - Mapping and Uncertainty Analysis of Crop Residue Cover Using Sequential Gaussian Cosimulation with QuickBird Images
• Chapter 20 - Remote Sensing of Leaf Area Index of Vegetation Covers -- Chapter 21 - LiDAR Remote Sensing of Vegetation Biomass -- Chapter 22 - Carbon Cycle Modeling for Terrestrial Ecosystems -- Chapter 23 - Remote Sensing Applications to Modeling Biomass and Carbon of Oceanic Ecosystems -- Chapter 24 - Wetland Classification -- Chapter 25 - Remote Sensing Applications to Monitoring Wetland Dynamics: A Case Study on Qinghai Lake Ramsar Site, China -- Chapter 26 - Hyperspectral Sensing on Acid Sulfate Soils via Mapping Iron-Bearing and Aluminum-Bearing Minerals on the Swan Coastal Plain, Western Australia -- Back Cover