• Title/Summary/Keyword: MODIS image

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Detection of Vegetation Dieback Areas in the Subalpine Zone of Mt. Baekdu Using MODIS Time Series Data (MODIS 시계열 자료를 이용한 백두산 아고산대 식생 고사지역 탐지)

  • Kim, Nam-Sin
    • Journal of the Korean Geographical Society
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    • v.47 no.6
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    • pp.825-835
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    • 2012
  • The aim of this research is to develope technique and mapping for detecting distribution of vegetation dieback areas in the subalpine zone of Mt. Baekdu. A detection technique developed the rule-based model using MODIS images. Dieback areas could be classified as 4 categories of initial dieback, middle dieback, and end dieback by pruning stages of leaves. Dieback area was $28km^2$ from year 2001 to year 2006, intial dieback was $16km^2$, middle dieback was $10km^2$, and end dieback was $2km^2$ by the each stage. Dieback area was $35km^2$ from year 2006 to year 2011. Total area was $35km^2$ from year 2001 to year 2011, areas of middle dieback and end dieback were increased. The research method for this study may help to support in application with preliminary detection of dieback areas in the mountains by the global warming.

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Agricultural Drought Assessment Based on Evaporative Stress Index (ESI) Calculation using MODIS Satellite Image and ROC Analysis (MODIS 위성영상 기반 ESI 산정 및 ROC 분석을 활용한 농업가뭄평가)

  • Yoon, Dong-Hyun;Nam, Won-Ho;Lee, Hee-Jin;Park, Jong-Hwan;Kim, Dae-Eui
    • Proceedings of the Korea Water Resources Association Conference
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    • 2020.06a
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    • pp.156-156
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    • 2020
  • 가뭄은 다른 자연재해에 비해 진행 속도가 느리고 발생 시작 시기가 명확하지 않다. 또한 피해지역이 광범위하다는 점에서 사회, 경제적 피해와 농업 생산 시스템 및 수확량 등 농업 전반에 걸쳐 직접적인 영향을 미치고 있다. 전지구적 기후변화로 인해 국내의 가뭄 발생빈도는 2000년 이후 증가하고 있으며, 가뭄의 정량적 분석은 선제적 가뭄 대응을 위해 필요하다. 현재 국내에서는 여러 유관기관에서 지상 관측 데이터를 활용하여 가뭄을 모니터링하고, 가뭄 공간 분포 지도를 제공하고 있다. 하지만 지상 관측 데이터를 통한 가뭄 분포 지도는 미계측 지역에 대한 데이터 취득이 어렵고, 지형학적 특성을 고려하지 못하는 한계점이 있다. 이러한 한계점을 보완하기 위해 수자원 및 재해 분야에서 위성영상이 활용되고 있다. 위성영상을 활용한 가뭄 판단 및 예측에는 정규식생지수 (Normalized Difference Vegetation Index, NDVI)가 사용되고 있으며, 식생지수는 가뭄 발생, 진행 등에 있어 즉각적인 반응이 어렵다는 단점이 있다. 본 연구에서는 잠재 증발산과 실제 증발산의 비를 이용해 산정된 위성영상 기반 가뭄 지수인 Evaporative Stress Index (ESI)를 활용하였다. NASA (National Aeronautics and Space Administration)에서 제공하는 ESI는 전지구를 대상으로 5km 해상도로 제공하고 있다. 하지만 국내 가뭄 판단을 위해서는 높은 해상도의 영상이 필요하며, 본 연구에서는 MODIS (Moderate Resolution Imaging Spectroradiometer) 영상을 활용한 ESI의 산정을 통해 해상도의 문제를 개선하고자 한다. 산정한 500m 해상도의 ESI는 기존 5km 해상도의 ESI와 비교 검증하였으며, SPI 및 과거 가뭄 발생 현황 자료를 근거로 ROC (Receiver Operating Characteristics) 분석을 통해 시군 단위 농업가뭄평가의 적용성을 확인하고 한다.

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NASA EOS DB Receiving System Development by KARI

  • Ahn, Sang-il;Koo, In-Hoi;Yang, Hyung-Mo;Hyun, Dae-Hwan;Choi, Hae-Jin
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.89-94
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    • 2002
  • Recently, DARI implemented the receiving and processing system for MODIS sensor data from NASA EOS satellites (TERRA and AQUA). This paper shows the development strategy considered, system requirement derived, system design, characteristic and test results of processing system. System operation concept and sample image are also provided. Implemented system was proven to be fully operational through lots of pass operations activities from RF signal reception to level-1 processing.

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NASA EOS DB Receiving System Development by KARI

  • Ahn, Sang-Il;Koo, In-Hoi;Yang, Hyung-Mo;Hyun, Dae-Hwan;Choi, Hae-Jin
    • Korean Journal of Remote Sensing
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    • v.19 no.1
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    • pp.37-42
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    • 2003
  • Recently, KARI implemented the receiving and processing system for MODIS sensor data from NASA EOS satellites (TERRA and AQUA). This paper shows the development strategy considered, system requirement derived, system design, characteristic and test results of processing system. System operation concept and sample image are also provided. Implemented system was proven to be fully operational through lots of pass operations activities from RF signal reception to level-1 processing.

Relationship between Vegetation Index and Meteorological Element in Yongdam Catchment (용담댐시험유역 기상자료와 식생지수의 상관성 분석)

  • Lee, Hyeong-keun;Hwang, Ji-hyeong;Lee, Khil-Ha
    • Journal of Environmental Science International
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    • v.27 no.11
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    • pp.983-989
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    • 2018
  • The real-time monitoring of surface vegetation is essential for the management of droughts, vegetation growth, and water resources. The availability of land cover maps based on remotely collected data makes the monitoring of surface vegetation easier. The vegetation index in an area is likely to be proportional to meteorological elements there such as air temperature and precipitation. This study investigated relationship between vegetation index based on Moderate Resolution Image Spectroradiometer (MODIS) and ground-measured meteorological elements at the Yongdam catchment station. To do this, 16-day averaged data were used. It was found that the vegetation index is well correlated to air temperature but poorly correlated to precipitation. The study provides some intuition and guidelines for the study of the droughts and ecologies in the future.

Proposal of Prediction Technique for Future Vegetation Information by Climate Change using Satellite Image (위성영상을 이용한 기후변화에 따른 미래 식생정보 예측 기법 제안)

  • Ha, Rim;Shin, Hyung-Jin;Kim, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.10 no.3
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    • pp.58-69
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    • 2007
  • The vegetation area that occupies 76% in land surface of the earth can give a considerable impact on water resources, environment and ecological system by future climate change. The purpose of this study is to predict future vegetation cover information from NDVI (Normalized Difference Vegetation Index) extracted from satellite images. Current vegetation information was prepared from monthly NDVI (March to November) extracted from NOAA AVHRR (1994 - 2004) and Terra MODIS (2000 - 2004) satellite images. The NDVI values of MODIS for 5 years were 20% higher than those of NOAA. The interrelation between NDVIs and monthly averaged climate factors (daily mean, maximum and minimum temperature, rainfall, sunshine hour, wind velocity, and relative humidity) for 5 river basins of South Korea showed that the monthly NDVIs had high relationship with monthly averaged temperature. By linear regression, the future NDVIs were estimated using the future mean temperature of CCCma CGCM2 A2 and B2 climate change scenario. The future vegetation information by NOAA NDVI showed little difference in peak value of NDVI, but the peak time was shifted from July to August and maintained high NDVIs to October while the present NDVI decrease from September. The future MODIS NDVIs showed about 5% increase comparing with the present NDVIs from July to August.

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Aerosol Optical Thickness Retrieval Using a Small Satellite

  • Wong, Man Sing;Lee, Kwon-Ho;Nichol, Janet;Kim, Young J.
    • Korean Journal of Remote Sensing
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    • v.26 no.6
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    • pp.605-615
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    • 2010
  • This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface reflectances, the modified Minimum Reflectance Technique (MRT) is used on three winter ortho-rectified CHRIS images: Dec-18-2005, Feb-07-2006, Nov-09-2006. For validation purpose, MRT image was compared with ground based multispectral radiometer measurements and atmospherically corrected Landsat image. Results show good agreements between CHRIS-derived surface reflectance and both by ground measurement data as well as by Landsat image (r>0.84). The Root-Mean-Square Errors (RMSE) at 485, 551 and 660nm are 0.99%, 1.19%, and 1.53%, respectively. For aerosol retrieval, Look Up Tables (LUT) which are aerosol reflectances as a function of various AOT values were calculated by SBDART code with AERONET inversion products. The CHRIS derived Aerosol Optical Thickness (AOT) images were then validated with AERONET sunphotometer measurements and the differences are 0.05~0.11 (error=10~18%) at 440nm wavelength. The errors are relatively small compared to those from the operational moderate resolution imaging spectroradiometer (MODIS) Deep Blue algorithm (within 30%) and MODIS ocean algorithm (within 20%).

Downscaling GPM Precipitation Using Finer-scale MODIS Based Optical Image in Korean Peninsula (MODIS 광학 영상 자료를 통한 한반도 GPM 강우 자료의 상세화 기법)

  • Oh, Seungcheol;Jeong, Jaehwan;Lee, Seulchan;Choi, Minha
    • Korean Journal of Remote Sensing
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    • v.36 no.5_1
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    • pp.749-762
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    • 2020
  • Precipitation is closely related to various hydrometeorological phenomena, such as runoff and evapotranspiration. In Korean Peninsula, observing rainfall intensity using weather radar and rain gauge network is dominating due to their accurate, intuitive and precise detecting power. However,since these methods are not suitable at ungauged regions, rainfall detection using satellite is required. Satellite-based rainfall data has coarse spatial resolution (10 km, 25 km), and has a limited range of usage due to its reliability of data. The aim of this study is to obtain finer scale precipitation. Especially, to make the applicability of satellite higher at ungauged regions, 10 km satellite-based rainfall data was downscaled to 1 km data using MODerate Resolution Imaging Spectroradiometer (MODIS) based cloud property. Downscaled precipitation was verified in urban region, which has complex topographical and environmental characteristics. Correlation coefficient was similar in summer (+0), decreased in spring (-0.08) and autumn (-0.01), and increased in winter (+0.04) season compared to Global Precipitation Measurement (GPM) based precipitation. Downscaling without calibration using in situ data could be useful in areas where rain gauge system is not sufficient or ground observations are rarely available.

Estimation of spatial evapotranspiration using Terra MODIS satellite image and SEBAL model in mixed forest and rice paddy area (SEBAL 모형과 Terra MODIS 영상을 이용한 혼효림, 논 지역에서의 공간증발산량 산정 연구)

  • Lee, Yong Gwan;Jung, Chung Gil;Ahn, So Ra;Kim, Seong Joon
    • Journal of Korea Water Resources Association
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    • v.49 no.3
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    • pp.227-239
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    • 2016
  • This study is to estimate Surface Energy Balance Algorithm for Land (SEBAL) daily spatial evapotranspiration (ET) comparing with eddy covariance flux tower ET in Seolmacheon mixed forest (SMK) and Cheongmicheon rice paddy (CFK). The SEBAL input data of Albedo, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) from Terra MODIS products and the meteorological data of wind speed, and solar radiation were prepared for 2 years (2012-2013). For the annual average flux tower ET of 302.8 mm in SMK and 482.0 mm in CFK, the SEBAL ETs were 183.3 mm and 371.5 mm respectively. The determination coefficients ($R^2$) of SEBAL ET versus flux tower ET for total periods were 0.54 in SMK and 0.79 in CFK respectively. The main reason of SEBAL ET underestimation for both sites was from the determination of hot pixel and cold pixel of the day and affected to the overestimation of sensible heat flux.

Analysis of the Cloud Removal Effect of Sentinel-2A/B NDVI Monthly Composite Images for Rice Paddy and High-altitude Cabbage Fields (논과 고랭지 배추밭 대상 Sentinel-2A/B 정규식생지수 월 합성영상의 구름 제거 효과 분석)

  • Eun, Jeong;Kim, Sun-Hwa;Kim, Taeho
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1545-1557
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    • 2021
  • Crops show sensitive spectral characteristics according to their species and growth conditions and although frequent observation is required especially in summer, it is difficult to utilize optical satellite images due to the rainy season. To solve this problem, Constrained Cloud-Maximum Normalized difference vegetation index Composite (CC-MNC) algorithm was developed to generate periodic composite images with minimal cloud effect. In thisstudy, using this method, monthly Sentinel-2A/B Normalized Difference Vegetation Index (NDVI) composite images were produced for paddies and high-latitude cabbage fields from 2019 to 2021. In August 2020, which received 200mm more precipitation than other periods, the effect of clouds, was also significant in MODIS NDVI 16-day composite product. Except for this period, the CC-MNC method was able to reduce the cloud ratio of 45.4% of the original daily image to 14.9%. In the case of rice paddy, there was no significant difference between Sentinel-2A/B and MODIS NDVI values. In addition, it was possible to monitor the rice growth cycle well even with a revisit cycle 5 days. In the case of high-latitude cabbage fields, Sentinel-2A/B showed the short growth cycle of cabbage well, but MODIS showed limitations in spatial resolution. In addition, the CC-MNC method showed that cloud pixels were used for compositing at the harvest time, suggesting that the View Zenith Angle (VZA) threshold needsto be adjusted according to the domestic region.