• Title/Summary/Keyword: normalized difference vegetation index

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A study on evapotranspiration using Terra MODIS images and soil water deficit index (Terra MODIS 위성영상과 토양수분 부족지수를 이용한 증발산량 산정 연구)

  • Jinuk Kim;Yonggwan Lee;Jeehun Chung;Jiwan Lee;Seongjoon Kim
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.119-119
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    • 2023
  • 본 연구에서는 Terra MODIS(MODerate resolution Imaging Spectroradiometer) 위성영상과 토양수분 부족지수(Soil Water Deficit Index, SWDI)를 이용하여 2012년부터 2022년까지 한반도 전국의 1km 공간 증발산량을 산정하였다. 공간 증발산량을 산정하기 위한 과정은 크게 두 가지로 구분된다. 첫 번째로 MODIS의 LST(Land Surface Temperature), NDVI(Normalized Difference Vegetation Index), 선행강우 및 무강우 누적일수를 이용해 1 km 공간 토양수분을 산정하였다. 농촌진흥청 토양수분관측망 자료 중 토지피복, 토양 속성을 고려하여 선정된 70개소 토양수분 실측데이터와 비교한 결과 지점별 평균 R2 0.63~0.90으로 유의미한 상관성을 나타내었다. 산정된 공간 토양수분은 생장저해수분점과 초기위조점의 관계를 이용한 SWDI로 변환하였다. 두 번째로 순 복사량, 기온 및 NDVI의 적은 수문인자를 통해 증발산량 산정이 가능한 MS-PT(Modified Satellite-based Priestley-Taylor) 모형을 기반으로 계절별 식생과 토양수분 상태를 고려하여 1 km 공간 증발산량을 산정하였다. MS-PT 모형에서 가정한 대기 증발 변수 Diurnal temperature (DT)와 지표 수분의 상관성 문제를 해결하기 위해 DT를 SWDI로 적용하였다. 모형 결과의 검증을 위해 국내 플럭스 타워 (설마천, 청미천, 덕유산) 증발산량 관측자료와의 결정계수(Coefficient of determination, R2), RMSE(Root Mean Square Error) 및 IOA(Index of Agreement)를 산정하였다. 본 연구의 결과로 생산되는 국내 증발산량의 시, 공간적 변동성은 증발산량을 통한 수문학적 가뭄지수 및 급성 가뭄을 파악하는데 활용될 수 있을 것으로 판단된다.

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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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Evaluation of the heat island in transition zone of three cities in Kyungpook, Korea (추이대(推移帶)를 중심으로 한 경상북도 3개 도시의 열섬 평가)

  • Park, In Hwan;Jang, Gab Sue;Kim, Jong Yong
    • Journal of Environmental Impact Assessment
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    • v.8 no.2
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    • pp.73-82
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    • 1999
  • This study analyzed the relationship between NDVI(Normalized Difference Vegetation Index) and urban heat island in three cities: Daegu, Kyungju, and Pohang for understanding the degree of nature conservation concentrating in the transition zone of them. Daegu city is the third city in Korea which has a dense population. Kyungju is a traditional city which has good nature. Pohang is an industrial city which has those of characters of Daegu and Kyungju. Landsat 1M data in May 17, 1997 were used for the analysis of heat island. There were about four theoretical models to estimate the surface temperature from TM data: Two-point linear model, Linear regression model, Quadratic regression model, and Cubic regression model. In this study, Linear regression model had been utilized to analyze the urban heat island. On the resultant images, the transition zone of Daegu was urbanized more extremely than those of other two cities. It is thought that the analysis of relationship between NDVI and surface temperature, used in this study, is regarded as one of effective methodologies for urban-environmental detection from satellite imageries.

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Radiometric Characteristics of Geostationary Ocean Color Imager (GOCI) for Land Applications

  • Lee, Kyu-Sung;Park, Sung-Min;Kim, Sun-Hwa;Lee, Hwa-Seon;Shin, Jung-Il
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.277-285
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    • 2012
  • The GOCI imagery can be an effective alternative to monitor short-term changes over terrestrial environments. This study aimed to assess the radiometric characteristics of the GOCI multispectral imagery for land applications. As an initial approach, we compared GOCI at-sensor radiance with MODIS data obtained simultaneously. Dynamic range of GOCI radiance was larger than MODIS over land area. Further, the at-sensor radiance over various land surface targets were tested by vicarious calibration. Surface reflectance were directly measured in field using a portable spectrometer and indirectly derived from the atmospherically corrected MODIS product over relatively homogeneous sites of desert, tidal flat, bare soil, and fallow crop fields. The GOCI radiance values were then simulated by radiative transfer model (6S). In overall, simulated radiance were very similar to the actual radiance extracted from GOCI data. Normalized difference vegetation index (NDVI) calculated from the GOCI bands 5 and 8 shows very close relationship with MODIS NDVI. In this study, the GOCI imagery has shown appropriate radiometric quality to be used for various land applications. Further works are needed to derive surface reflectance over land area after atmospheric correction.

Characteristics of UAV Aerial Images for Monitoring of Highland Kimchi Cabbage

  • Lee, Kyung-Do;Park, Chan-Won;So, Kyu-Ho;Kim, Ki-Deog;Na, Sang-Il
    • Korean Journal of Soil Science and Fertilizer
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    • v.50 no.3
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    • pp.162-178
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    • 2017
  • Remote sensing can be used to provide information about the monitoring of crop growth condition. Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to assess weather UAV aerial images are suitable for the monitoring of highland Kimchi cabbage. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110, IXUS/ELPH camera during farming season from 2015 to 2016 in the main production area of highland Kimchi cabbage, Anbandegi, Maebongsan, and Gwinemi. The Normalized Difference Vegetation Index (NDVI) by using UAV images was stable and suitable for monitoring of Kimchi cabbage situation. There were strong relationships between UAV NDVI and the growth parameters (the plant height and leaf width) ($R^2{\geq}0.94$). The tendency of UAV NDVI according to Kimchi cabbage growth was similar in the same area for two years (2015~2016). It means that if UAV image may be collected several years, UAV images could be used for estimation of the stage of growth and situation of Kimchi cabbage cultivation.

A New Method to Retrieve Sensible Heat and Latent Heat Fluxes from the Remote Sensing Data

  • Liou Yuei-An;Chen Yi-Ying;Chien Tzu-Chieh;Chang Tzu-Yin
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.415-417
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    • 2005
  • In order to retrieve the latent and sensible heat fluxes, high-resolution airborne imageries with visible, near infrared, and thermal infrared bands and ground-base meteorology measurements are utilized in this paper. The retrieval scheme is based on the balance of surface energy budget and momentum equations. There are three basic surface parameters including surface albedo $(\alpha)$, normalized difference vegetation index (NOVI) and surface kinetic temperature (TO). Lowtran 7 code is used to correct the atmosphere effect. The imageries were taken on 28 April and 5 May 2003. From the scattering plot of data set, we observed the extreme dry and wet pixels to derive the fitting of dry and wet controlled lines, respectively. Then the sensible heat and latent heat fluxes are derived from through a partitioning factor A. The retrieved latent and sensible heat fluxes are compared with in situ measurements, including eddy correlation and porometer measurements. It is shown that the retrieved fluxes from our scheme match with the measurements better than those derived from the S-SEBI model.

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Land-use Mapping and Change Detection in Northern Cheongju Region (청주 북부지역의 토지이용 매핑과 변화탐지)

  • Na, Sang-Il;Park, Jong-Hwa;Shin, Hyoung-Sup
    • Journal of The Korean Society of Agricultural Engineers
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    • v.50 no.3
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    • pp.61-69
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    • 2008
  • Land-use in northern Cheongju region is changing rapidly because of the increased interactions of human activities with the environment as population increases. Land-use change detection is considered essential for monitoring the growth of an urban complex. The analysis was undertaken mainly on the basis of the multi-temporal Landsat images (1991, 1992 and 2000) and DEM data in a post-classification analysis with GIS to map land-use distribution and to analyse factors influencing the land-use changes for Cheongju city. The area of each land-use category was also calculated for monitoring land-use changes. Land-use statistics revealed that substantial land-use changes have taken place and that the built-up areas have expanded by about $17.57km^2$ (11.47%) over the study period (1991 - 2000). This study illustrated an increasing trend of urban and barren lands areas with a decreasing trend of agricultural and forest areas. Land-use changes from one category to others have been clearly represented by the NDVI composite images, which were found suitable for delineating the development of urban areas and land use changes in northern Cheongju region. Rapid economic developments together with the increasing population were noted to be the major factors influencing rapid land use changes. Urban expansion has replaced urban and barren lands.

AGE ESTIMATION TECHNIQUE OF INDUSTRIALIZED TIMBER PLANTATION USING VARIOUS REMOTE SENSING DATA

  • Kim, Jong-Hong;Heo, Joon;Park, Ji-Sang
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.94-97
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    • 2006
  • Timber stand age information of timber in industrialized plantation forest is generally collected by field surveying which is labor-intensive, time-consuming, and very costly. It is also inconsistent in analyses perspective. As an alternative, The objective of this research is to present a practical solution for estimating timber age of loblolly pine plantation using Landsat thematic mapper (TM) images, shuttle radar topography mission (SRTM), and national elevation dataset (NED). A multivariate regression model was developed based upon satellite image-based information (i.e.normalized difference vegetation index (NDVI), tasseled cap (TC) transformation, and derived tree heights). A residual studentized technique was applied to remove potential outliers. After that, a refined age estimation model with a correlation coefficient R-square of 84.6% was obtained. Finally, the feasibility test of estimated model was performed by comparing estimated and measured stand ages of timber plantations using test datasets of plantation stands (2,032 stands). The result shows that the proposed method of this study can estimate loblolly pine stand age within an error of $2{\sim}3$ years in an effective and consistent way in terms of time and cost.

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PERFORMANCE OF COMS SNOW AND SEA ICE DETECTION ALGORITHM

  • Lee, Jung-Rim;Chung, Chu-Yong;Ahn, Myoung-Hwan;Ou, Mi-Lim
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.278-281
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    • 2007
  • The purpose of this study is to develop snow and sea ice detection algorithm in Communication, Ocean and Meteorological Satellite (COMS) meteorological data processing system. Since COMS has only five channels, it is not affordable to use microwave or shortwave infrared data which are effective and generally used for snow detection. In order to estimate snow and sea ice coverage, combinations between available channel data(mostly visible and 3.7 ${\mu}m$) are applied to the algorithm based on threshold method. As a result, the COMS snow and sea ice detection algorithm shows reliable performance compared to MODIS products with channel limitation. Specifically, there is partial underestimation over the complicated vegetation area and overestimation over the area of high level clouds such as cirrus. Some corrections are performed by using water vapor and infrared channels to remove cloud contamination and by applying NDVI to detect more snow pixels for the underestimated area.

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NDVI RESPONSES TO THE FOREST CANOPY AND FLOOR IN EASTERN SIBERIA

  • Suzuki, Rikie;Kobayashi, Hideki;Delbart, Nicolas;Hiyama, Tetsuya;Asanuma, Jun
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.325-328
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    • 2007
  • We discuss the Normalized Difference Vegetation Index (NDVI) of the forest canopy and floor separately based on airborne spectral reflectance measurements and simultaneous airborne land surface images acquired around Yakutsk, Siberia in 2000. The aerial land surface images were visually classified into four forest types: no-green canopy and snow floor (Type-1), green canopy and snow floor (Type-2), no-green canopy and no-snow floor (Type-3), and green canopy and no-snow floor (Type-4). The mean NDVI was calculated for these four types. Although Type-2 had green canopy, the NDVI was rather small (0.17) because of high reflection from the snow cover on the floor. Type-3, which had no green canopy, indicated considerably large NDVI (0.45) due to the greenness of the floor. Type-4 had the largest NDVI (0.75) because of the greenness of both the canopy and floor. These results reveal that the NDVI depends considerably on forest floor greenness and snow cover in addition to canopy greenness.

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