• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.583-590
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• 2008

This study presents a correlation between timber Age, image bands and vegetation indices for timber age estimation. Basically, this study used Landsat TM images of three difference years (1994, 1994, 1998) and difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED). Bands of 4, 5 and 7, Normalized Difference Vegetation Index (NDVI), Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SA VI) were obtained from Landsat TM images. Tasseled cap - greenness and wetness images were also made by Tasseled cap transformation. Finally, analysis of correlation between timber age, difference between Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED), individual TM bands (4, 5, 7), Normalized Difference Vegetation Index (NDVI), Tasseled cap-Greenness, Wetness, Infrared Index (II), Vegetation Condition Index (VCI) and Soil Adjusted Vegetation Index (SAVI) using regression model. In this study about 1,992 datasets were analyzed. The Tasseled cap - Wetness, Infrared Index (II) and Vegetation Condition Index (VCI) showed close correlation for timber age estimation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.4
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• pp.41-50
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• 1987

The present study was conducted to measure and predict the leachate generation and to establish the methods of leachate control and handling by both field and lab-lysimeter studies. The change of biodegradable matter, field capacity, dry density, quantity and quality of leachate as a function of time of landilling were measured. The model based on the theory of unsaturated flow and contaminant transport in porous media was developed and simulation model was used for the prediction of movement of landfill moisture and for the strength in leachate in terms of organic and inorganic contaminant. The model constructed from the present study in terms of unsaturated decomposition and transport combined with the evapotranspiration and surface runoff showed good agreement with the results obtained by lysimeter studies.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.191-202
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• 2024

Global warming is causing abnormal climates worldwide due to the increase in greenhouse gas concentrations in the atmosphere, negatively affecting ecosystems and humanity. In response, various countries are attempting to reduce greenhouse gas emissions in numerous ways, and interest in blue carbon, carbon absorbed by coastal ecosystems, is increasing. Known to absorb carbon up to 50 times faster than green carbon, blue carbon plays a vital role in responding to climate change. Particularly, the tidal flats of South Korea, one of the world's five largest tidal flats, are valued for their rich biodiversity and exceptional carbon absorption capabilities. While previous studies on blue carbon have focused on the carbon storage and annual carbon absorption rates of tidal flats, there is a lack of research linking tidal flat area changes detected using satellite data to carbon storage. This study applied the direct difference water index to high-resolution satellite data from PlanetScope and RapidEye to analyze the area and changes of the Nakdong River estuary tidal flats over six periods between 2013 and 2023, estimating the carbon storage for each period. The analysis showed that excluding the period in 2013 with a different tidal condition, the tidal flat area changed by up to approximately 5.4% annually, ranging from about 9.38 km² (in 2022) to about 9.89 km² (in 2021), with carbon storage estimated between approximately 30,230.0 Mg C and 31,893.7 Mg C.