• Korean Journal of Remote Sensing
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• v.38 no.6_4
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• pp.1935-1943
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• 2022

The development and application of a high-resolution soil moisture mapping method using satellite imagery has been considered one of the major research themes in remote sensing. In this study, soil moisture mapping in the test area of Jeju Island was performed. The soil moisture was calculated with optical images using linearly adjusted Synthetic Aperture Radar (SAR) polarization images and incident angle. SAR Backscatter data, Analysis Ready Data (ARD) provided by Google Earth Engine (GEE), was used. In the soil moisture processing process, the optical image was applied to normalized difference vegetation index (NDVI) by surface reflectance of KOMPSAT-3 satellite images and the land cover map of Environmental Systems Research Institute (ESRI). When the SAR image and the optical images are fused, the reliability of the soil moisture product can be improved. To validate the soil moisture mapping product, a comparative analysis was conducted with normalized difference water index (NDWI) products by the KOMPSAT-3 image and those of the Landsat-8 satellite. As a result, it was shown that the soil moisture map and NDWI of the study area were slightly negative correlated, whereas NDWI using the KOMPSAT-3 images and the Landsat-8 satellite showed a highly correlated trend. Finally, it will be possible to produce precise soil moisture using KOMPSAT optical images and KOMPSAT SAR images without other external remotely sensed images, if the soil moisture calculation algorithm used in this study is further developed for the KOMPSAT-5 image.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.599-608
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• 2023

The increasing interest in soil moisture data using satellite data for applications of hydrology, meteorology, and agriculture has led to the development of methods for generating soil moisture maps of variable resolution. This study demonstrated the capability of generating soil moisture maps using Sentinel-1 and Sentinel-2 data provided by Google Earth Engine (GEE). The soil moisture map was derived using synthetic aperture radar (SAR) image and optical image. SAR data provided by the Sentinel-1 analysis ready data in GEE was applied with normalized difference vegetation index (NDVI) based on Sentinel-2 and Environmental Systems Research Institute (ESRI)-based Land Cover map. This study produced a soil moisture map in the research area of Victoria, Australia and compared it with field measurements obtained from a previous study. As for the validation of the applied method's result accuracy, the comparative experimental results showed a meaningful range of consistency as 4-10%p between the values obtained using the algorithm applied in this study and the field-based ones, and they also showed very high consistency with satellite-based soil moisture data as 0.5-2%p. Therefore, public open data provided by GEE and the algorithm applied in this study can be used for high-resolution soil moisture mapping to represent regional land surface characteristics.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.139-147
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• 2009

The gravity data collected and reserved in Korea is seriously biased in its distribution. That is, only the west-southern part of the peninsula including Chungcheong and Jeonla area has dense distribution while only a part is covered in Gyoungsang area. Especially, the low density of the gravity data in mountainous area basically limits the accuracy of the gravimetric geoid in Korea. As one of the solution to overcome the problem, an airborne gravity survey were conducted from Dec. 2008 $\sim$ Jan. 2009. In this study, free-air gravity anomaly derived from the airborne gravity data which has consistent quality are presented. The data processing for the airborne gravity is composed of several corrections of errors such as errors from gravity measurement, errors from flight dynamics, errors from GPS, and errors from time synchronization. We presented detailed explanations on the data processing with the final cross-over results. The free-air anomaly from airborne gravity finally shows the cross-over accuracy of 2.21mGal which reflects the precision of each track is 1.56mGal. It is expected that the result from this study will play a role as input data in precision geoid determination with ground and ship-borne gravity data after appropriate fusion process.