Remote Sensing Of Natural Resources

Description: Highlighting new technologies, Remote Sensing of Natural Resources explores 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 for evaluation of natural resources, including sampling design, land use and land cover classification, natural landscape and ecosystem assessment, forestry, agriculture, biomass and carbon-cycle modeling, wetland classification and dynamics monitoring, and soils and minerals mapping. The book combines review articles with case studies that demonstrate recent advances and developments of methods, techniques, and applications of remote sensing, with each chapter on a specific area of natural resources. Through a comprehensive examination of the wide range of applications of remote sensing technologies to natural resources, the book provides insight into advanced remote sensing systems, technologies, and algorithms for researchers, scientists, engineers, and decision makers.

Review: "... a comprehensive view on and real world examples of remote sensing technologies in natural resources assessment and monitoring. ... state-of-the-art knowledge in this multidisciplinary field. Readers can expect to finish the book armed with the required knowledge to understand the immense literature available and apply their knowledge to the understanding of sampling design, the analysis of multi-source imagery, and the application of the techniques to specific problems relevant to natural resources." -Yuhong He, University of Toronto Mississauga, Ontario, Canada "The list of topics covered is so complete that I would recommend the book to anyone teaching a graduate course on vegetation analysis through digital image analysis. ... I recommend this book then for anyone doing advanced digital image analysis and environmental GIS courses who want to cover topics related to applied remote sensing work involving vegetation analysis." -Charles Roberts, Florida Atlantic University, Boca Raton, USA, in Economic Botany

Contents: Remote Sensing Systems Introduction to Remote Sensing Systems, Data, and Applications, Qihao Weng Sampling Design and Product Quality Assessment Remote Sensing Applications for Sampling Design of Natural Resources, Guangxing Wang and George Z. Gertner Accuracy Assessment for Classification and Modeling, Suming Jin Accuracy Assessment for Soft Classification Maps, Daniel Gomez, Gregory S. Biging, and Javier Montero Spatial Uncertainty Analysis When Mapping Natural Resources Using Remotely Sensed Data, Guangxing Wang and George Z. Gertner Land Use and Land Cover Classification Land Use/Land Cover Classification in the Brazilian Amazon with Different Sensor Data and Classification Algorithms, Guiying Li, Dengsheng Lu, Emilio Moran, Mateus Batistella, Luciano V. Dutra, Corina C. Freitas, and Sidnei J. S. Sant'Anna Vegetation Change Detection in the Brazilian Amazon with Multitemporal Landsat Images, Dengsheng Lu, Guiying Li, Emilio Moran, and Scott Hetrick Extraction of Impervious Surfaces from Hyperspectral Imagery: Linear versus Nonlinear Methods, Xuefei Hu and Qihao Weng Road Extraction: A Review of LiDAR-Focused Studies, Lindi J. Quackenbush, Jungho Im, and Yue Zuo Natural Landscape, Ecosystems, and Forestry Application of Remote Sensing in Ecosystem and Landscape Modeling, Chonggang Xu and Min Chen Plant Invasion and Imaging Spectroscopy, Kate S. He and Duccio Rocchini Assessing Military Training-Induced Landscape Fragmentation and Dynamics of Fort Riley Installation Using Spatial Metrics and Remotely Sensed Data, Steve Singer, Guangxing Wang, Heidi R. Howard, and Alan B. Anderson Automated Individual Tree-Crown Delineation and Treetop Detection with Very-High-Resolution Aerial Imagery, Le Wang and Chunyuan Diao Tree Species Classification, Ruiliang Pu Estimation of Forest Stock and Yield Using LiDAR Data, Markus Holopainen, Mikko Vastaranta, Xinlian Liang, Juha Hyyppa, Anttoni Jaakkola, and Ville Kankare National Forest Resource Inventory and Monitoring System, Erkki Tomppo, Matti Katila, and Kai Makisara Agriculture Remote Sensing Applications on Crop Monitoring and Prediction, Bingfang Wu and Jihua Meng Remote Sensing Applications to Precision Farming, Haibo Yao and Yanbo Huang Mapping and Uncertainty Analysis of Crop Residue Cover Using Sequential Gaussian Cosimulation with QuickBird Images, Cha-Chi Fan, Guangxing Wang, George Z. Gertner, Haibo Yao, Dana G. Sullivan, and Mark Masters Biomass and Carbon Cycle Modeling Remote Sensing of Leaf Area Index of Vegetation Covers, Jing M. Chen LiDAR Remote Sensing of Vegetation Biomass, Qi Chen Carbon Cycle Modeling for Terrestrial Ecosystems, Tinglong Zhang and Changhui Peng Remote Sensing Applications to Modeling Biomass and Carbon of Oceanic Ecosystems, Samantha Lavender and Wahid Moufaddal Wetland, Soils, and Minerals Wetland Classification, Maycira Costa, Thiago S. F. Silva, and Teresa L. Evans Remote Sensing Applications to Monitoring Wetland Dynamics: A Case Study on Qinghai Lake Ramsar Site, China, Hairui Duo, Linlu Shi, and Guangchun Lei Hyperspectral Sensing on Acid Sulfate Soils via Mapping Iron-Bearing and Aluminum-Bearing Minerals on the Swan Coastal Plain, Western Australia, Xianzhong Shi and Mehrooz Aspandiar Index