• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.193-196
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• 2005

As global warming proceeds, South Eastern Asia is undergoing drought, and the harshness of drought in the middle area of Korea is increasing. Especially, there has been the worst spring drought in 2001 since the first meteorological observation, and the damages caused by that drought are being ana lysed in various ways. In this study, spectral indices derived from satellites are used to examine 2001 spring drought, and the application of MODIS Data products as the quantitative tool to analyse drought in the future is examined.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.85-85
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• 2016

가뭄은 다른 어떤 기상재해보다 광범위하고 긴 시간에 걸쳐 큰 피해를 초래할 뿐만 아니라 많은 변수들이 복합적으로 작용하여 발생하기 때문에 그 발생 원인을 이해하기 힘들다. 따라서 가뭄에 의한 피해를 최소화하기 위해서는 중, 장기적인 가뭄의 예측이 필요하며, 가뭄을 예측한다는 것은 가뭄의 발생의 시공간 분포와 발생 원인을 정확히 이해하는데서 시작할 수 있다. 현재 우리나라는 기후변화로 인한 이상기후의 영향으로 마른장마, 봄 가뭄 등 이상가뭄이 빈발하고 발생되고 있으며, 90년 이후로 남부지역을 중심으로 겨울에서 봄까지의 가뭄인 횟수가 점점 증가하고 있는 실정이다. 본 연구에서는 가뭄의 시공간적으로 분석하기 위하여 Terra의 MODIS 원격탐사 자료를 활용하였으며, 한반도를 대상으로 가뭄의 정량적 평가를 실시하고자 하였다. 본 연구의 성과는 제한된 관측정보를 통한 시공간 분석의 한계점을 가지고 있지만 가뭄 피해에 대한 현실적인 대책 및 적응전략 수립에 횔용 가능성이 높을 것으로 기대된다.

• 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.

• Journal of The Korean Society of Agricultural Engineers
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• v.60 no.6
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• pp.55-63
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• 2018

This paper aimed to characterize the spatial and temporal pattern of agricultural drought in Pre-Kharif season using Vegetation Health Index (VHI) and illustrated drought characteristics in Bangladesh during 2001-2015. VHI was calculated from TCI (Temperature Condition Index) and VCI (Vegetation Condition Index) derived from MODIS Terra satellite data, LST (Land Surface Temperature) and EVI (Enhanced Vegetation Index), respectively. The finding showed that all drought-affected areas were experienced by mild, moderate, severe and extreme droughts in several years of Pre-Kharif seasons. Significant drought events were found in the year of 2002 and 2013. On average, Chittagong district covered the largest drought area in all drought stages, and the fraction of drought area was the highest in Sylhet and Rangpur for Pre-Kharif season. Finally, overlaying annual VHI raster maps resulted in that the most vulnerable district to agricultural drought were Sylhet, Rangpur, and Mymensingh in the northern and eastern regions of Bangladesh.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.69-78
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• 2011

Rice is one of the world's staple foods. Paddy rice fields have unique biophysical characteristics that the rice is grown on flooded soils unlike other crops. Information on the spatial distribution of paddy fields and the timing of irrigation are of importance to determine hydrological balance and efficiency of water resource management. In this paper, we detected the timing of irrigation and spatial distribution of paddy fields using the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Aqua satellite. The timing of irrigation was detected by the combined use of MODIS-based vegetation index and Land Surface Water Index (LSWI). The detected timing of irrigation showed good agreement with field observations from two flux sites in Korea and Japan. Based on the irrigation detection, a land cover map of paddy fields was generated with subsidiary information on seasonal patterns of MODIS enhanced vegetation index (EVI). When the MODISbased paddy field map was compared with a land cover map from the Ministry of Environment, Korea, it overestimated the regions with large paddies but underestimated those with small and fragmented paddies. Potential reasons for such spatial discrepancies may be attributed to coarse pixel resolution (500 m) of MODIS images, uncertainty in parameterization of threshold values for discarding forest and water pixels, and the application of LSWI threshold value developed for paddy fields in China. Nevertheless, this study showed that an improved utilization of seasonal patterns of MODIS vegetation and water-related indices could be applied in water resource management and enhanced estimation of evapotranspiration from paddy fields.

• Korean Journal of Remote Sensing
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• v.35 no.4
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• pp.503-516
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• 2019

We have estimated the vertical column density (VCD) of formaldehyde (HCHO) on a global scale using a multiple linear regression method (MRM) with Ozone Monitoring Instrument (OMI) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. HCHO VCDs were estimated in regions of biogenic, pyrogenic, and anthropogenic emissions using independent variables, including $NO_2$ VCD, land surface temperature (LST), an enhanced vegetation index (EVI), and the mean fire radiative power (MFRP), which are strongly correlated with HCHO. To evaluate the HCHO estimates obtained using the MRM, we compared estimates of HCHO VCD data measured by OMI ($HCHO_{OMI}$) with those estimated by multiple linear regression equations (MRE) ($HCHO_{MRE}$). Good MRM performances were found, having the average statistical values (R = 0.91, slope = 1.03, mean bias = $-0.12{\times}10^{15}molecules\;cm^{-2}$, percent difference = 11.27%) between $HCHO_{MRE}$ and $HCHO_{OMI}$ in our study regions where high HCHO levels are present. Our results demonstrate that the MRM can be a useful tool for estimating atmospheric HCHO levels.

• KCID journal
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• v.21 no.1
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• pp.78-88
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• 2014

This study is to analyze the 2012 spring drought of Korea using drought index and satellite image. The severe spring drought recorded in May of 2012 showed 36.4% of normal rainfall(99.5mm). The areas of west part of Gyeonggi-do and Chungcheong-do were particularly serious. The drought indices both the SPI(Standardized Precipitation Index) and WADI(WAter supply Drought Index) represented the drought areas from the end of May and to the severe drought at the end of June. The drought by SPI completely ended at the middle of July, but the drought by WADI continued severe drought in the agricultural reservoir watersheds of whole country even to the end of the July. On the other hand, the results by spatial NDVI(Normalized Difference Vegetation Index) and EVI(Enhanced Vegetation Index) data from Terra MODIS, both indices showed relatively low values around the areas of Sinuiju, Pyongyang, and west coast of North Korea and Gyeonggi-do and Chungcheong-do of South Korea indicating drought condition. Especially, the values of NDVI and EVI at Chungcheong-do were critically low in June compared to the normal year value.

• Korean Journal of Ecology and Environment
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• v.47 no.3
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• pp.186-193
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• 2014

This study aimed to analyze spatio-temporal trends of phenological characteristics in South Korea by using MODIS EVI. For the phenology analysis, we had applied double logistic function to MODIS time-series data. Our results showed that starting date of phenology seems to have a tendency along with latitudinal trends. Starting date of phenology of Jeju Island and Mt. Sobeak went back for 0.38, 0.174 days per year, respectively whereas, Mt. Jiri and Mt. Seolak went forward for 0.32 days, 0.239 days and 0.119 days, respectively. Our results exhibited the fluctuation of plant phonological season rather than the change of phonological timing and season. Starting date of plant phenology by spatial distribution revealed tendency that starting date of mountain area was late, and basin and south foot of mountain was fast. In urban ares such as Seoul metropolitan, Masan, Changwon, Milyang, Daegu and Jeju, the phonological starting date went forward quickly. Pheonoligcal attributes such as starting date and leaf fall in urban areas likely being affected from heat island effect and related warming. Our study expressed that local and regional monitoring on phonological events and changes in Korea would be possible through MODIS data.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.883-893
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• 2019

In this study, crop coefficients were calculated in two different methods and the results were evaluated. In the first method, appropriateness of GLDAS-based evapotranspiration was evaluated by comparing it with observed data of Cheongmi-cheon (CMC) Flux tower. Then, crop coefficient was calculated by dividing actual evapotranspiration with potential evapotranspiration that derived from GLDAS. In the second method, crop coefficient was determined by using MLR (Multiple Linear Regression) analysis with vegetation index (NDVI, EVI, LAI and SAVI) derived from MODIS and in-situ soil moisture data observed in CMC, In comparison of two crop coefficients over the entire period, for each crop coefficient GLDAS K_c and SM&VI K_c, shows the mean value of 0.412 and 0.378, the bias of 0.031 and -0.004, the RMSE of 0.092 and 0.069, and the Index of Agree (IOA) of 0.944 and 0.958. Overall, both methods showed similar patterns with observed evapotranspiration, but the SM&VI-based method showed better results. One step further, the statistical evaluation of GLDAS K_c and SM&VI K_c in specific period was performed according to the growth phase of the crop. The result shows that GLDAS K_c was better in the early and mid-phase of the crop growth, and SM&VI K_c was better in the latter phase. This result seems to be because of reduced accuracy of MODIS sensors due to yellow dust in spring and rain clouds in summer. If the observational accuracy of the MODIS sensor is improved in subsequent study, the accuracy of the SM&VI-based method will also be improved and this method will be applicable in determining the crop coefficient of unmeasured basin or predicting the crop coefficient of a certain area.