• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.4
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• pp.298-306
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• 2010

In this study, we evaluated the performance of Korea Land Data Assimilation System (KLDAS) for the estimation of evapotranspiration (ET) by comparing the modeled against the observed ET at Gwangneung deciduous forest of KoFlux site (GDK) from 2006 to 2008. Although the magnitudes of ET by KLDAS overestimated the observed ET, the seasonal patterns of KLDAS ET were comparable with the correlation coefficient of 0.78. The difference between the KLDAS ET and the observed ET was larger in spring and summer due to rapid plant growth and frequent rainfalls with high cloud cover, respectively. Compared to the ET estimated by NASA Global Land Data Assimilation System (GLDAS) with $0.25^{\circ}$ and $1^{\circ}$ resolution, the ET by KLDAS with 10 km resolution showed better agreement with the observation at the GDK site. Albeit further improvement is necessary, our results suggest that KLADS can be used as a practical tool to map ET and to examine its spatiotemporal variability over the Korean Peninsula.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.97-110
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• 2018

This study examined the value of the old roads and roadscapes as modern assets. Topographic maps of the two years (1916 and 1919, which were produced by the Japanese Government-General of Korea) and the digital topographic map produced in 2017, were analyzed. The total amount of roads that have survived for the past 100 years are located in 108 places and total 26.32km. After examining the remnants of the roads in YeongDo, the type of scenery experienced along the roads were classified into nine kinds. The place where a sequential scenery experience takes place due to the survival of the past, the experience is based on the transition of historical scenery, not the scenery of the present time. A new model that can preserve, manage and plan this scenery is required. Therefore, we propose a new landscape model that elevates the concept of gaze from a spatial concept to a spatiotemporal concept. Based on this model, we propose a conservation criterion of the landscape viewed on the road as a viewpoint. As a modern asset for the next 100 years of YeongDo, it is necessary to understand and preserve the meaning of the landscape and roadside scenery as a transit landscape network. The remnant of roads from 100 years ago suggests that the scenery on the road was has been maintained, and it is the historical landscape of the YeongDo area. Through the landscape conservation plan proposed in this study, it is expected that the historical roads and their landscape will be positioned as a modern asset and an aspect of local heritage, and the future conservation and management of the roads and roadscapes will continue.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1105-1114
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• 2022

A study on a method to overcome the limitations of the topographical and hydrological observation environment for estimating the QPE with high consistency with the ground rainfall by utilizing the spatiotemporal observation advantages of the rainfall radar for use in flood forecasting, and quantitative observations of localized rainfall due to these limiting conditions Uncertainty should be identified in terms of flood analysis. Against this background, in this study, 22 major heavy rain events in 2016 were analyzed for each of Mt. Biseul (BSL), Mt. Sobaek (SBS), Mt. Gari (GRS), Mt. Mohu (MHS), and Mt. Seodae (SDS) to determine the observation distance and altitude. The uncertainty of observation was quantified and an error map was derived. As a result of the analysis, it was found that, on average, the rainfall radar exceeded 10% up to 100 km and 30% over 150 km. Based on the average radar operating altitude angle, it was found that the error for the altitude was approximately 10% or less up to the second altitude angle, 20% at the third or higher altitude angle, and more than 50% at the fourth altitude angle or higher.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1285-1300
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• 2022

Turbidity, the measure of the cloudiness of water, is used as an important index for water quality management. The turbidity can vary greatly in small river systems, which affects water quality in national rivers. Therefore, the generation of high-resolution spatial information on turbidity is very important. In this study, a turbidity retrieval model using the Korea Multi-Purpose Satellite-3 and -3A (KOMPSAT-3/3A) images was developed for high-resolution turbidity mapping of Han River system based on eXtreme Gradient Boosting (XGBoost) algorithm. To this end, the top of atmosphere (TOA) spectral reflectance was calculated from a total of 24 KOMPSAT-3/3A images and 150 Landsat-8 images. The Landsat-8 TOA spectral reflectance was cross-calibrated to the KOMPSAT-3/3A bands. The turbidity measured by the National Water Quality Monitoring Network was used as a reference dataset, and as input variables, the TOA spectral reflectance at the locations of in situ turbidity measurement, the spectral indices (the normalized difference vegetation index, normalized difference water index, and normalized difference turbidity index), and the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived atmospheric products(the atmospheric optical thickness, water vapor, and ozone) were used. Furthermore, by analyzing the KOMPSAT-3/3A TOA spectral reflectance of different turbidities, a new spectral index, new normalized difference turbidity index (nNDTI), was proposed, and it was added as an input variable to the turbidity retrieval model. The XGBoost model showed excellent performance for the retrieval of turbidity with a root mean square error (RMSE) of 2.70 NTU and a normalized RMSE (NRMSE) of 14.70% compared to in situ turbidity, in which the nNDTI proposed in this study was used as the most important variable. The developed turbidity retrieval model was applied to the KOMPSAT-3/3A images to map high-resolution river turbidity, and it was possible to analyze the spatiotemporal variations of turbidity. Through this study, we could confirm that the KOMPSAT-3/3A images are very useful for retrieving high-resolution and accurate spatial information on the river turbidity.