Abstract:

Remote sensing of vegetation is developing into a highly quantitative science. However, some concepts and terms related to quantitative remote sensing are confusing for novices of this field. The goal of this paper is to clarify fuzzy concepts and promiscuous terms and to introduce methods about data processing of remote sensing information. First, concepts about radiometric correction, radiometric calibration, atmospheric correction and the differences and relationships between them were discussed. In optical remote sensing, radiometric correction includes radiometric calibration and atmospheric correction. The aim of radiometric calibration is to eliminate the errors in the sensors of the satellite, and the aim of atmospheric correction is to eliminate the effects of atmospheric interference on satellite data. In general, the first step is radiometric calibration and then atmospheric correction. Apparent reflectance is one of the results of radiometric calibration and is a very important physical variable in processing remote sensing data. The definition of apparent reflectance can be indicated with a formula. The calculation of apparent reflectance was explained step-by-step using examples with Landsat-5 and Landsat-7 satellite images. A case study was presented in order to show the importance of apparent reflectance in the calculation of NDVI (Normalized difference vegetation index). Finally, its applications in vegetation remote sensing were listed and discussed.