• 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.

• Korean Journal of Soil Science and Fertilizer
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• v.44 no.5
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• pp.878-886
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• 2011

The soybean is one of the oldest cultivated crops in the world. Microwave remote sensing is an important tool because it can penetrate into cloud independent of weather and it can acquire day or night time data. Especially a ground-based polarimetric scatterometer has advantages of monitoring crop conditions continuously with full polarization and different frequencies. In this study, soybean growth parameters and soil moisture were estimated using polarimetric discrimination ratio (PDR) by radar scatterometer. A ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the soybean growth condition and soil moisture change. It was set up to obtain data automatically every 10 minutes. The temporal trend of the PDR for all bands agreed with the soybean growth data such as fresh weight, Leaf Area Index, Vegetation Water Content, plant height; i.e., increased until about DOY 271 and decreased afterward. Soil moisture lowly related with PDR in all bands during whole growth stage. In contrast, PDR is relative correlated with soil moisture during below LAI 2. We also analyzed the relationship between the PDR of each band and growth data. It was found that L-band PDR is the most correlated with fresh weight (r=0.96), LAI (r=0.91), vegetation water content (r=0.94) and soil moisture (r=0.86). In addition, the relationship between C-, X-band PDR and growth data were moderately correlated ($r{\geq}0.83$) with the exception of the soil moisture. Based on the analysis of the relation between the PDR at L, C, X-band and soybean growth parameters, we predicted the growth parameters and soil moisture using L-band PDR. Overall good agreement has been observed between retrieved growth data and observed growth data. Results from this study show that PDR appear effective to estimate soybean growth parameters and soil moisture.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.191-201
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• 2011

Soybean has widely grown for its edible bean which has numerous uses. Microwave remote sensing has a great potential over the conventional remote sensing with the visible and infrared spectra due to its all-weather day-and-night imaging capabilities. In this investigation, a ground-based polarimetric scatterometer operating at multiple frequencies was used to continuously monitor the crop conditions of a soybean field. Polarimetric backscatter data at L, C, and X-bands were acquired every 10 minutes on the microwave observations at various soybean stages. The polarimetric scatterometer consists of a vector network analyzer, a microwave switch, radio frequency cables, power unit and a personal computer. The polarimetric scatterometer components were installed inside an air-conditioned shelter to maintain constant temperature and humidity during the data acquisition period. The backscattering coefficients were calculated from the measured data at incidence angle $40^{\circ}$ and full polarization (HH, VV, HV, VH) by applying the radar equation. The soybean growth data such as leaf area index (LAI), plant height, fresh and dry weight, vegetation water content and pod weight were measured periodically throughout the growth season. We measured the temporal variations of backscattering coefficients of the soybean crop at L, C, and X-bands during a soybean growth period. In the three bands, VV-polarized backscattering coefficients were higher than HH-polarized backscattering coefficients until mid-June, and thereafter HH-polarized backscattering coefficients were higher than VV-, HV-polarized back scattering coefficients. However, the cross-over stage (HH > VV) was different for each frequency: DOY 200 for L-band and DOY 210 for both C and X-bands. The temporal trend of the backscattering coefficients for all bands agreed with the soybean growth data such as LAI, dry weight and plant height; i.e., increased until about DOY 271 and decreased afterward. We plotted the relationship between the backscattering coefficients with three bands and soybean growth parameters. The growth parameters were highly correlated with HH-polarization at L-band (over r=0.92).

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.531-542
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• 2021

Open-pit mines require constant monitoring as they can cause surface changes and environmental disturbances. In open-pit mines, there is little vegetation at the mining site and can be monitored using InSAR (Interferometric Synthetic Aperture Radar) coherence imageries. In this study, activities occurring in mine were analyzed by applying the recently developed InSAR coherence-based NDAI (Normalized Difference Activity Index). The March 5 Youth Mine is a North Korean mine whose development has been expanded since 2008. NDAI analysis was performed with InSAR coherence imageries obtained using Sentinel-1 SAR images taken at 12-day intervals in the March 5 Youth Mine. First, the area where the elevation decreased by about 75.24 m and increased by about 9.85 m over the 14 years from 2000 was defined as the mining site and the tailings piles. Then, the NDAI images were used for time series analysis at various time intervals. Over the entire period (2017-2019), average mining activity was relatively active at the center of the mining area. In order to find out more detailed changes in the surface activity of the mine, the time interval was reduced and the activity was observed over a 1-year period. In 2017, we analyzed changes in mining operations before and after artificial earthquakes based on seismic data and NDAI images. After the large-scale blasting that occurred on 30 April 2017, activity was detected west of the mining area. It is estimated that the size of the mining area was enlarged by two blasts on 30 September 2017. The time-averaged NDAI images used to perform detailed time-series analysis were generated over a period of 1 year and 4 months, and then composited into RGB images. Annual analysis of activity confirmed an active region in the northeast of the mining area in 2018 and found the characteristic activity of the expansion of tailings piles in 2019. Time series analysis using NDAI was able to detect random surface changes in open-pit mines that are difficult to identify with optical images. Especially in areas where in situ data is not available, remote sensing can effectively perform mining activity analysis.