The objective of this investigation was to study and optimize a hyperspectral unmanned aerial vehicle (UAV)-based remote-sensing system for the Brazilian environment. Comprised mainly of forest and sugarcane, the study area was located in the western region of the State of São
Paulo. A novel hyperspectral camera based on a tunable Fabry–Pérot interferometer was mounted aboard a UAV due to its flexibility and capability to acquire data with a high temporal and spatial resolution. Five approaches designed to produce mosaics of hyperspectral images, which
represent the hemispherical directional reflectance factor of targets in the Brazilian environment, are presented and evaluated. The method considers the irradiance variation during image acquisition and the effects of the bidirectional reflectance distribution function. The main goal was
achieved by comparing the spectral responses of radiometric reference targets acquired with a spectroradiometer in the field with those produced by the five different approaches. The best results were achieved by correcting the bidirectional reflectance distribution function effects and by
applying a least squares method to a radiometric block adjustment using only the image data, thereby achieving a root mean square error of 11.35%.
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Document Type: Research Article
Postgraduate Program in Cartographic Science, School of Technology and Science, São Paulo State University (UNESP), Presidente Prudente, Brazil
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, Masala, Finland
Department of Cartography, São Paulo State University (UNESP), Presidente Prudente, Brazil
Publication date: August 18, 2018
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