期刊
REMOTE SENSING
卷 13, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/rs13183550
关键词
atmospheric corrections; normalised difference vegetation index (NDVI); sensor intercomparability; Landsat 8; Sentinel-2; unmanned aerial vehicle (UAV)
类别
资金
- Technology Agency of the Czech Republic (Environment for Life program) [SS01010046]
This study tested the impact of six different atmospheric correction methods on NDVI results, finding significant differences in results based on the method chosen. It also demonstrated that proper use of atmospheric correction methods can increase the intercomparability between data from Landsat 8 and Sentinel-2 satellite imagery.
Sentinel-2 and Landsat 8 satellites constitute an unprecedented source of freely accessible satellite imagery. To produce precise outputs from the satellite data, however, proper use of atmospheric correction methods is crucial. In this work, we tested the performance of six different atmospheric correction methods (QUAC, FLAASH, DOS, ACOLITE, 6S, and Sen2Cor), together with atmospheric correction given by providers, non-corrected image, and images acquired using an unmanned aerial vehicle while working with the normalised difference vegetation index (NDVI) as the most widely used index. We tested their performance across urban, rural, and vegetated land cover types. Our results show a substantial impact from the choice of the atmospheric correction method on the resulting NDVI. Moreover, we demonstrate that proper use of atmospheric correction methods can increase the intercomparability between data from Landsat 8 and Sentinel-2 satellite imagery.
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