• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.171-178
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• 2004

The advantage of the remote sensing is extraction the information of wide area rapidly. Such advantage is the resource and environment are quick and efficient method to grasps accurately method through the land cover classification of wide area. Accordingly this study was presented more better land cover classification method through an algorithm development. We accomplished FCM(Fuzzy C-Mean) classification technique with MLC (Maximum Likelihood classification) technique to be general land cover classification method in the content of research. And evaluated the accuracy assessment of two classification method. This study is used to the high-resolution(6.6m) Electro-Optical Camera(EOC) panchromatic image of the first Korea Multi-Purpose Satellite 1(KOMPSAT-1) and the multi-spectral Moderate Resolution Imaging Spectroradiometer(MODIS) image data(36 bands).

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1466-1470
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• 2010

토양수분은 지표의 다양한 과정을 통제하는 중요한 수문학적 변수며 이에 신뢰할 수 있는 토양수분의 정보를 습득하는 것은 매우 중요하다. 그러나 정확한 토양수분의 실측자료는 그 설치비용과 인력부족으로 매우 빈약하여 이를 대체할 만한 정보를 획득하기 위한 연구 또한 부족하다. 요즘, 많은 수문모형의 개발로 토양 수분 또한 결과물로써 많이 이용된다. 그러나 모형에서 모의된 토양수분의 신뢰성을 판단할 때는 실측자료를 이용하는 것이 가장 이상적이나, 토양수분의 실측값이 부족하므로, 유역의 토양수분 실측자료 대신 모의된 토양수분을 적용할 필요가 있다. 이에 따라 본 연구에서는 우리나라 소양강댐 유역에 대하여 SWAT(Soil and Water Assessment Tool) 모형을 이용하여 실측 토양수분자료를 최대한 활용함으로써 토양수분을 모의하였다. 또한 모의된 토양수분을 Terra MODIS NDVI(Normalized Difference Vegetation Index)와 LST(Land Surface Temperature)과의 상관성을 계절별, 월별로 분석하여 그 관계식을 도출하고자 하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.172-183
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• 2012

In 2011, floods were at the worst stage of devastation in Chao Phraya river basin of Thailand. The purpose of this study is to trace the flood inundation area around Chao Phraya river basin by using Terra MODIS image because it has the ability of spatiotemporal dynamics. The MODIS indices, which included the enhanced vegetation index(EVI), land surface water index(LSWI), and the difference in the values of EVI and LSWI(DVEL), were extracted from MODIS product MOD09 8-day composite datasets with a spatial resolution of 500m from Jul. 29, 2011 to Jan. 09, 2012. We found that combined application of EVI, LSWI, and DVEL was suitable for monitoring flood inundation. For the extracted flood inundation area and water-related area. The result can be used to acquire the flood inundation data scattered and demonstrate the potential for the use of MODIS data for temporal and spatial detection of flood effects.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1125-1137
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• 2020

This study aimed to propose the method of linking satellite image-based forest fire data to supplement the limitation of forest fire survey data that records only the ignition location and area of forest fire. For this purpose, a method was derived to link the fire survey data provided by the Korea Forest Service between January 2012 and December 2019 with MODIS and VIIRS image-based forest fire data. As a result, MODIS and VIIRS-based forest fire data out of 191 wildfires in the forest fire survey data were able to identify 11% and 44% of fire damage area, respectively. An average of 56% of forest damage area was extracted from VIIRS-based forest fire data compared to forest fire areas identified by high-resolution Sentinel-2A satellites. Therefore, for large-scale forest fires, VIIRS wildfire data can be used to compensate for the limitations of forest fire survey data that records only the ignition location and area.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.84-88
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• 2009

토양수분은 물순환계통을 이해하기 위한 필수적인 수문학적 변수이나 설치비용과 인력부족으로 실측자료가 매우 부족한 실정이다. 많은 수문모형의 개발로 토양수분 또한 결과물로써 많이 이용되지만, 그 결과의 신뢰성을 판단하기가 쉽지 않다. 본 연구에서는 활용성이 높다고 판단되는 수문모형인 SWAT 모형을 통해 산림지역의 토양수분을 모의하고 MODIS NDVI와의 상관성을 분석하여, 모의된 토양수분의 신뢰성 판단을 위한 MODIS NDVI의 활용성을 파악하고자 하였다. 대상유역은 산림이 전체유역의 약 82%를 차지하고 있는 충주댐 유역으로 하였으며 NDVI 자료는 시간해상도 16일, 공간해상도 250m 인 MODIS 영상의 Product를 이용하였다. 보다 신뢰성 있는 자료를 얻기 위해 유역의 특성이 다른 두 지점을 선정하여 다지점 검보정을 수행하였으며, 2003년부터 2006년까지의 유출 자료를 이용하여 모형을 보정하고, 2000, 2001 그리고 2002년에 대하여 검증하였다. 검보정 결과 모형 효율성 계수는 상류와 하류에 대하여 각각 0.91, 0.87, 결정계수는 각각 0.90, 0.80으로 분석되었다. 본 연구에서는 NDVI 특성에 따라 봄 기간과 가을기간으로 나누어 분석을 수행하였으며, NDVI와 토양수분의 상관관계는 NDVI가 증가하는 봄 기간에 토양수분은 감소하며 역 관계로 나타났고 NDVI가 감소하는 가을 기간에 토양수분은 증가하는 순 관계를 보였다.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.16 no.5
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• pp.59-69
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• 2013

Global warming also has effects on the phenology. The limitation of phenology study is an acquisition of phenology data. Satellite images analysis can make up limitation of monitering data. This study is to analyze spatial distribution and characteristics of phenology changes using MODIS images. Research data collected images of 16 day intervals of 11 years from year 2001 to 2010. The data analyzed 228 images of 11 years. It can figure out changes of phenology by analyzing enhanced vegetation index of MODIS image. We made a comparison between changes of phenology and flowering of cherry blossoms. As a results, Startup of season spatially was getting late from southern area to north area. Startup of Phenology was foreshortened 13 days during 11 years, and change ratios of cherry blooming was getting more faster from 0.18 dat to 0.22 day per year during that same period.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.111-115
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• 2009

본 연구에서는 SWAT 모형에서 모의된 토양수분의 신뢰성을 판단하기 위해 MODIS NDVI의 활용성을 파악하고자 하였다 MODIS 위성영상을 이용하여 시간해상도 16일, 공간해상도 250m의 NDVI를 추출하였으며, 대상유역은 면적이 약 $6661.3km_2$ 이고 그 중 산림이 약 82.2%를 차지하고 있는 충주댐 유역으로 하였다. 보다 신뢰성 있는 자료를 얻기 위해 토양, 토지이용 등 유역의 특성이 다른 상류와 하류로 나누어 다지점 검보정을 수행하였으며, 2003년부터 2006년까지의 유출 자료를 이용하여 모형을 보정하고, 2000, 2001 그리고 2002년에 대하여 검증하였다. 검보정 결과 모형 효율성 계수는 상류와 하류에 대하여 각각 0.91, 0.87, 결정계수는 각각 0.90, 0.80으로 분석되었다. 분석 기간은 2000년부터 2006년까지이고, NDVI의 특성에 따라 봄기간과 가을기간으로 나누어 분석하였으며, 선형회귀 방적식과 결정계수를 이용하여 상관성을 판단하였다. 분석결과 SWAT에서 모의된 토양수분과 MODTS NDVI는 약 55%의 상관성을 나타내었고, 가뭄해인 2001년에 약 85%로 상관성이 매우 높고, 비가 많이 온 해인 2002년에 약 2%로 상관성이 매우 낮아 NDVI는 가뭄 기간 SWAT에서 모의된 토양수분의 신뢰성을 검증할 수 있는 자료로 사용될 수 있다고 판단되었다.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.90-104
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• 2015

The purpose of this paper is to build a spatio-temporal evapotranspiration(ET) estimation model using Terra MODIS satellite image and by calibrating with the flux tower ET data from watershed. The fundamentals of spatial ET model, Surface Energy Balance Algorithm for Land(SEBAL) was adopted and modified to estimate the daily ET of Yongdam Dam watershed in South Korea. The daily Normalized Distribution Vegetation Index(NDVI), Albedo, and Land Surface Temperature(LST) from MODIS and the ground measured wind speed and solar radiation data were prepared for 2 years(2012-2013). The SEBAL was calibrated with the forest ET measured by Deokyusan flux tower in the study watershed. Among the model parameters, the important parameters were surface albedo, NDVI and surface roughness in order for momentum transport during calculation of sensible heat flux. As a result of the final calibration, the monthly averaged albedo and NDVI were used because the daily values showed big deviation with unrealistic change. The determination coefficient($R^2$) between SEBAL and flux data was 0.45. The spatial ET reflected the geographical characteristics showing the ET of lowland areas was higher than the highland ET.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.1-18
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• 2022

Currently, the Korea Meteorological Administration evaluates the meteorological drought by region using SPI6(standardized precipitation index 6), which is a 6-month cumulative precipitation standard. However, SPI is an index calculated only in consideration of precipitation at 69 weather stations, and the drought phenomenon that appears for complex reasons cannot be accurately determined. Therefore, the purpose of this study is to calculate and compare SPI considering only precipitation and SDCI (Scaled Drought Condition Index) considering precipitation, vegetation index, and temperature in Gyeonggi. In addition, the advantages and disadvantages of the station data-based drought index and the satellite image-based drought index were identified by using results calculated through the comparison of SPI and SDCI. MODIS(MODerate resolution Imaging Spectroradiometer) satellite image data, ASOS(Automated Synoptic Observing System) data, and kriging were used to calculate SDCI. For the duration of precipitation, SDCI1, SDCI3, and SDCI6 were calculated by applying 1-month, 3-month, and 6-month respectively to the 8 points in 2014. As a result of calculating the SDCI, unlike the SPI, drought patterns began to appear about 2-month ago, and drought by city and county in Gyeonggi was well revealed. Through this, it was found that the combination of satellite image data and station data increased efficiency in the pattern of drought index change, and increased the possibility of drought prediction in wet areas along with existing dry areas.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1385-1394
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• 2022

This study was to analyze the change in albedo by level-2 land cover map for 20 years(2002-2021) using MODerate resolution Imaging Spectroradiometer (MODIS) data. Also, the difference from the MODIS data was analyzed using the 10-year (2012-2021) data of Visible Infrared Imaging Radiometer Suite (VIIRS). For the albedo data of MODIS and VIIRS, daily albedo data, MCD43A3 and VNP43IA, of 500 m spatial resolution of sinusoidal tile grid produced by Bidirectional Reflectance Distribution Function (BRDF) model were prepared for the South Korea range. Reprojection was performed using the code written based on Python 3.9, and the nearest neighbor was applied as the resampling method. White sky albedo and black sky albedo of shortwave were used for analysis. As a result of 20-year albedo analysis using MODIS data, the albedo tends to rise in all land use. Compared to the 2000s (2002-2011), the average albedo of the 2010s (2012-2021) showed the most significant increase of 0.0027 in the forest area, followed by the grass increase of 0.0024. As a result of comparing the albedo of VIIRS and MODIS, it was found that the albedo of VIIRS was larger from 0.001 to 0.1, which was considered to be due to differences in the surface reflectivity according to the time of image capture and sensor characteristics.