Lapan A3 images encode their pixel values as digital numbers (DN). To conduct index analysis using these images, it is necessary to convert the DN values into surface reflectance values, which requires atmospheric correction. This study focuses on performing atmospheric correction on Lapan A3 imagery, specifically over the Batu Jamus rubber plantation and its surroundings in Karanganyar Regency, Central Java. Three atmospheric correction methods were employed: histogram adjustment, FLAASH, and 6S. The corrected reflectance values were subsequently utilized to calculate the Normalized Difference Vegetation Index (NDVI). The analysis demonstrated that atmospheric correction generally led to a reduction in reflectance values in the red and near-infrared (NIR) bands. Moreover, NDVI calculations revealed notable changes in values before and after correction. Histogram adjustment yielded a median NDVI value of 0.772, higher than the pre-correction value, while the FLAASH and 6S methods resulted in reduced median NDVI values of 0.256 and 0.462, respectively. Pearson correlation analysis indicated a strong positive correlation between pre- and post-correction NDVI values, with correlation coefficients exceeding 0.87. In the FLAASH and 6S methods, there are two land cover types that exhibit similar reference NDVI values. Therefore, the recommended atmospheric correction methods for calculating NDVI values using LAPAN A3 data are the FLAASH and 6S methods.
Implications Atmospheric Correction for Normalized Difference Vegetation Index (NDVI) Analysis in Multispectral Camera LAPAN A3
08.11.2024
515065 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Effect of Atmosphere Correction for Unsupervised Classification in Multispectral Camera LAPAN A3
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