Spectral Mixture for Remote Sensing

Dr. Yosio Edemir Shimabukuro holds a degree in Forest Engineering from the Federal Rural University of Rio de Janeiro (1972), a Masters in remote sensing from the National Institute for Space Research (1977), Ph.D. in Forest Sciences/Remote Sensing from Colorado State University (1987), and was a Post-Doctoral researcher at NASA Goddard Space Flight Center (1993). He is currently a Senior Researcher in the Remote Sensing Division (DSR), Earth Observation Coordination (OBT) at the National Institute for Space Research (INPE), and professor / supervisor of the Post-Graduate Course in Remote Sensing at INPE. He has experience in Forest Resources and Forestry Engineering, with emphasis on Nature Conservation, working mainly on the following topics: Remote Sensing, Geoprocessing, Forestry Engineering and Environmental Sciences. He developed the linear spectral mixing model for remote sensing data.Flávio Jorge Ponzoni has worked as a researcher in the Remote Sensing Division at the National Institute for Space Research since 1985. His research interests have included the spectral characterization of vegetation, and recent studies that include the effect of multi-angularity in this characterization. Recently he has been dedicated to the absolute calibration of remotely located sensors, especially those of the CBERS program. In 2009, he joined the WGCV of the CEOS committee and has been involved in international calibration and data validation missions of the IVOS sub-group. He also works as a Professor of the Post-Graduate Course in Remote Sensing of INPE's Land Observation Coordination, teaching Radiometric Transformation of Orbital Data, Spectral Behavior of Targets, and Seminars in Remote Sensing.

• Chapter1: Basic concepts.- Chapter2: The origin of digital numbers (DN).- Chapter3: Orbital sensors.- Chapter4: Linear spectral mixing model.- Chapter5: Fraction images.- Chapter6: Applications of fraction images.- Chapter7: Final considerations.