- De-Striping and De-Smiling of Aerial Hyperspectral Image for Water Color Analysis
-
Wonkook Kim, Seungil Baek, Soon Heun Hong
-
GEO DATA. 2023;5(4):355-363. Published online December 27, 2023
-
DOI: https://doi.org/10.22761/GD.2023.0035
-
-
 Abstract
 PDF
- Hyperspectral imagery is typically acquired in push-broom mechanism, which is prone to image artifacts such as striping and smile for the sensor array whose sensor elements are not perfectly calibrated. The best practice would be to calibrate the sensor elements before the flight, but post-correction is required when images are already acquired without calibration. While there are some studies that addressed those striping and smile effects for hyperspectral images acquired from satellite or aircraft platforms, few studies were done for hyperspectral images that are focusing water color analysis, where the radiance level is approximately only a tenth of terrestrial scenes. This study proposes a correction method specialized for water scenes that also may contain terrestrial objects together, and analyzes the results using real drone-borne hyperspectral imagery taken for an island area in Korea. The result revealed that the variation in columnar mean before the de-striping, which ranges 5-15%, reduced to under 2% after the correction, also exhibiting successful removal of striping in visual inspection. The smile effect that ranges approximately 1-2 mW/m2/nm/sr, which accounts for 30% of radiance from water area, also reduced to under 0.1 mW/m2/nm/sr after the smile correction.
- BRDF Data for Coniferous Forests Acquired from Multispectral Camera Onboard a Unmanned Aerial Vehicle
-
Seungil Baek, Sooyoon Koh, Jong Hyuk Lee, Wonkook Kim
-
GEO DATA. 2023;5(4):371-379. Published online December 28, 2023
-
DOI: https://doi.org/10.22761/GD.2023.0057
-
-
Abstract
PDF
- Bidirectional reflectance distribution function (BRDF) is a distribution of directional reflectance for varying viewing and solar geometry. BRDF of a target is important in processing optical image data from satellites, because the observed radiance has great dependency on the direction (or angle) of reflection. It is desirable that the BRDF of any targets is characterized for rigorous BRDF correction of satellite data, since the sun-sensor-target geometry of satellites often varies in a very limited range, limiting the full characterization of target BRDF. This study provides BRDF data set for typical coniferous forests in Korea, by using a multispectral camera onboard a unmanned aerial vehicle (UAV). By operating the UAV in a goniometer-like way, reflectance data for all possible viewing zenith and azimuth angles were obtained. The BRDF data collected from the 3 campaigns in different days were visualized in a polar-coordinate, together with the standard deviation calculated for each zenith/azimuth bin made in 1˚ interval. The data sets demonstrated reflectance distribution over the wide range of angles with sound data quality, suggesting commonly known BRDF characteristics for forests such as strong back-scattering and hot spot area in the viewing zenith angle near the solar zenith angle. This data set is expected to be utilized for the BRDF correction of various satellites including Agro-forest satellite of Korea which is to be launched in 2025 that has similar spectral bands with the ones used in this study.
|
GAIDAS
