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||Remote Sensing for Sustainability 1st Edition
Author: Qihao Weng
Description: Driven by the societal needs and improvement in sensor technology and image processing techniques, remote sensing has become an essential geospatial tool for understanding the Earth and managing Human-Earth interactions. Remote Sensing for Sustainabilityintroduces the current state of the art remote sensing knowledge integral for monitoring the worlds natural resources and environments, managing exposure to natural disasters and man-made risks, and helping understand the sustainability and productivity of natural ecosystems. Bridging the gap between remote sensing and sustainability science this book examines theories and methods as well as practical applications of sustainable development for cities using remote sensing; focuses on remote sensing methods and techniques for sustainable natural resources with emphasize on forests; answers questions on how and what the remote sensing methods and techniques can do for the sustainability of environmental systems; and examines the issues of energy use and sustainable energy sources using remote sensing technology in countries such as Germany, China, the U.S, drawing on case studies to demonstrate the applicability of remote sensing techniques. This comprehensive guide, which can serve to professors, researchers, and students alike, takes in consideration the United Nations set of sustainable development goals and intends to contribute to the GEOs Strategic Plan by addressing and exemplifying a number of societal benefit areas of remote sensing data sets, methods, and techniques for sustainable development.
Table of Content: Foreword. Preface. Remote Sensing for Sustainable Cities. Extraction of Parameters from Remote Sensing Data for Environmental Indices for Urban Sustainability. John C. Trinder Earth Observation for Urban and Spatial Planning. Mattia Marconcini, Annekatrin Metz, Thomas Esch, and Julian Zeidler Assessment of Urban Growth in the Pearl River Delta, China, Using Time Series Landsat Imagery. Lei Zhang and Qihao Weng InSAR Monitoring of Land Subsidence for Sustainable Urban Planning. Abduwasit Ghulam, Mark Grzovic, Maitiniyazi Maimaitijiang,and Mamat Sawut A Tale of Two Cities: Urbanization in Greensboro, North Carolina, USA, and Guiyang, Guizhou, China. Honglin Xiao and Qihao Weng Remote Sensing for Sustainable Natural Resources. Role of Remote Sensing in Sustainable Grassland Management: A Review and Case Studies for a Mixed-Grass Prairie Ecosystem. Alexander Tong, Bing Lu, Yuhong He, and Xulin Guo Classifying Tree Species Using Fine Spatial Resolution Imagery to Support the Conservation of an Endangered Bird Species in Hawaii. Qi Chen Remote Sensing of Forest Damage by Diseases and Insects. Gang Chen and Ross K. Meentemeyer Monitoring Water Quality with Remote Sensing Image Data. Bunkei Matsushita, Wei Yang, Lalu Muhamad Jaelani,Fajar Setiawan, and Takehiko Fukushima Remote Sensing for Sustainable Environmental Systems. Urban Air Quality Studies Using EO Data. Xuefei Hu Heat Hazard Monitoring with Satellite-Derived Land Surface Temperature. Yitong Jiang and Qihao Weng Remote Sensing Identification of Threshold Zones along a Mediterranean to Arid Climatic Gradient. Maxim Shoshany Moisture Using Optical Remote Sensing and Ground Measurements: A Case Study from Pakistan. Mudassar Umar, Siraj Munir, Iftikhar Ali, Salman Qureshi, Claudia Notarnicola, Said Rahman, and Qihao Weng Remote Sensing for Sustainable Energy. Earth Observation and Its Potential to Implement a Sustainable Energy Supply—A German Perspective. Thomas Esch, Markus Tum, and Annekatrin Metz Use of Nighttime Imaging Data to Assess Decadal Trends in Energy Use in China. Yanhua Xie and Qihao Weng Support of Wind Resource Modeling Using Earth Observation—A European Perspective on the Status and Future Options. Thomas Esch, Charlotte Bay Hasager, Paul Elsner, Janik Deutscher, Manuela Hirschmugl, Annekatrin Metz Assessing Solar Energy Potential and Building Energy Use in Indianapolis Using Geospatial Techniques. Yuanfan Zheng and Qihao Weng Index.