Abstract

Object spectral reflectance plays an important role in recognizing and discriminating object of interests from remote sensing images. It provides key recognition of objects for image classification purposes. This study aims to compare the effectiveness of radiometric calibration algorithms applied to Small Format Aerial Photography (SFAP) and WorldView-2 (WV-2) images with the closed-range field spectrometer measurement. Some dominant objects were selected as basis for spectral reflectance observation, this includes grass, nonmangrove vegetation, mangrove vegetation, soil, and asphalt. The SFAP and the WV-2 image were radiometrically corrected up to at-surface reflectance level. As reference, the spectral reflectance of selected objects was collected in the field using JAZ EL-350 spectrometer. To compare the spectral reflectance results, spectral resampling procedure was applied to the spectrometer measurement based on the center wavelength of each images to match up the spectral resolution of the images. The results showed that the pixel values of the SFAP and WV-2 corrections have similar pattern. This pattern shows that the radiometric/atmospheric correction applied to WV-2 and SFAP has been successful and they have equal capability in differentiating sampled objects.

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