High Spatial Resolution Remote Sensing: Data, Analysis, and Applications

✍ Scribed by Yuhong He(Editor); Qihao Weng(Editor)

• Publisher: CRC Press;Taylor & Francis
• Year: 2018
• Tongue: English
• Leaves: 407
• Category: Library

✦ Synopsis

High spatial remote sensing data have been often used as valuable sources of information throughout emergency management cycle. Information extracted in high spatial remote sensing data right after a devastating earthquake can help assess the earthquake's damage of roads and buildings and make emergency plans for contact and evacuation. The book will discuss emerging high spatial resolution data sources, and detail novel techniques and applications for handling, retrieving, and making best use of high spatial resolution remote sensing data.

✦ Table of Contents

Content: Section I: Data Acquisition and Preprocessing1. High-Resolution UAS Imagery in Agricultural Research: Concepts, Issues, and Research Directions[Michael P. Bishop, Muthukumar V. Bagavathiannan, Dale A. Cope, Da Huo, Seth C. Murray, Jeffrey A. Olsenholler, William L. Rooney, J. Alex Thomasson, John Valasek, Brennan W. Young, Anthony M. Filippi, Dirk B. Hays, Lonesome Malambo, Sorin C. Popescu, Nithya Rajan, Vijay P. Singh, Bill McCutchen, Bob Avant, and Misty Vidrine]2. Building a UAV-Hyperspectral System I: UAV and Sensor Considerations[Cameron Proctor]3. Building a UAV-Hyperspectral System II: Hyperspectral Sensor Considerations and Data Preprocessing[Cameron Proctor]4. LiDAR and Spectral Data Integration for Coastal Wetland Assessment[Kunwar K. Singh, Lindsey Smart, and Gang Chen]5. Multiview Image Matching for 3D Earth Surface Reconstruction[Chuiqing Zeng and Jinfei Wang]6. High-Resolution Radar Data Processing and Applications[Joseph R. Buckley]Section II: Algorithms and Techniques7. Structure from Motion Techniques for Estimating the Volume of Wood Chips[Travis L. Howell, Kunwar K. Singh, and Lindsey Smart]8. A Workflow to Quantify the Carbon Storage in Urban Trees Using Multispectral ALS Data[Xinqu Chen and Jonathan Li]9. Suitable Spectral Mixing Space Selection for Linear Spectral Unmixing of Fine-Scale Urban Imagery[Jian Yang]10. Segmentation Scale Selection in Geographic Object-Based Image Analysis[Xiuyuan Zhang, Shihong Du, and Dongping Ming]11. Computer Vision Methodologies for Automated Processing of Camera Trap Data: A Technological Review[Joshua Seltzer, Michael Guerzhoy, and Monika Havelka]Section III: Case Studies and Applications12. UAV-Based Multispectral Images for Investigating Grassland Biophysical and Biochemical Properties[Bing Lu and Yuhong He]13. Inversion of a Radiative Transfer Model Using Hyperspectral Data for Deriving Grassland Leaf Chlorophyll[Alexander Tong, Bing Lu, and Yuhong He]14. Wetland Detection Using High Spatial Resolution Optical Remote Sensing Imagery[Amy B. Mui]15. Geomorphic and Biophysical Characterization of Wetland Ecosystems with Airborne LiDAR: Concepts, Methods, and a Case Study[Murray Richardson and Koreen Millard]16. Fraction Vegetation Cover Extraction Using High Spatial Resolution Imagery in Karst Areas[Xiangkun Qi, Chunhua Zhang, Yuhong He, and Kelin Wang]17. Using High Spatial Resolution Imagery to Estimate Cherry Orchard Acreage in Michigan[Kin M. Ma]

✦ Subjects

Remote sensing;Optical radar;Environmental sciences -- Remote sensing;TECHNOLOGY & ENGINEERING / Mechanical