• 제목/요약/키워드: NDVI

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MODIS NDVI 시계열 패턴 변화를 이용한 산림식생변화 모니터링 방법론 (Method of Monitoring Forest Vegetation Change based on Change of MODIS NDVI Time Series Pattern)

  • 정명희;이상훈;장은미;홍성욱
    • Spatial Information Research
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    • 제20권4호
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    • pp.47-55
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    • 2012
  • 정규식생지수(NDVI)는 식생자원을 모니터링할 수 있도록 설계된 식생지수(VI-Vegetation Index) 중 하나로 여러 응용 분야에서 가장 많이 사용되고 있는 지수이다. 산림 분야에서도 NDVI가 많이 활용되고 있는데 본 논문에서는 산림 변화 모니터링을 위해 MODIS NDVI를 활용하는 방법론이 연구되었다. 특정 시점을 기준으로 NDVI 값을 비교 및 분류하여 변화를 탐지하는 방법은 기계나 기상상태의 영향으로 자료의 정확성이 떨어질 수 있고 장기적인 변화를 탐지하는데도 어려움이 있다. 이러한 점을 고려하여 본 논문에서는 하모닉 모형을 이용하여 NDVI 시계열 자료를 통해 NDVI 패턴을 고려하는 방법론을 제시하였다. 먼저 하모닉 모형을 적용하여 미관측 자료나 자료의 오류를 보정한 NDVI 시계열 자료를 재구축하고 추정된 하모닉 요소의 모수를 기준으로 장기적 패턴을 통해 식생의 변화를 모니터링할 수 있다. 제안된 방법은 한반도 지역의 2009년 8월 21일부터 2011년 9월 6일까지 총 49개의 MODIS NDVI 시계열 자료에 적용하여 모형의 유용성을 입증하였다.

The Study of Applicability to Fixed-field Sensor for Normalized Difference Vegetation Index (NDVI) Monitoring in Cultivation Area

  • Lee, Kyung-Do;Na, Sang-Il;Baek, Shin-Chul;Jung, Byung-Joon;Hong, Suk-Young
    • 한국토양비료학회지
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    • 제48권6호
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    • pp.593-601
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    • 2015
  • The NDVI (Normalized difference vegetation index) is used as indicators of crop growth situation in remote sensing. To measure or validate the NDVI, reliable NDVI sensors have been needed. We tested new fixed-field NDVI sensor, "SRS (Spectral Reflectance Sensor)" developed by Decagon Devices, during Kimchi cabbage growing season at the cultivation area located in Gochang, Gangneung and Taebaek in Korea from 2014 to 2015. The diurnal variation of NDVI measured by SRS (SRS NDVI) showed a slight ${\cap}$-profile shape and was affected by water on the sensor surface. This means that SRS NDVI around noontime is resonable, except rainy day. Comparisons were made between the SRS NDVI and NDVI of used widely mobile sensor (Cropcircle NDVI). The comparisons indicate that SRS NDVI are close to Cropcircle NDVI (R=0.99). SRS NDVI time series displayed change of the plant height and leaf width of Kimchi cabbage. An obvious exponential relationship is found between SRS NDVI and the plant height ($R^2{\geq}0.92$) and leaf width ($R^2{\geq}0.92$) of Kimchi cabbage. Thus, SRS NDVI will be used as indicator of crop growth situation and a very powerful tool for evaluation of remote sensing NDVI estimates and associated corrections.

지형요소에 따른 NDVI의 변화에 관한 연구 (A Study on Change of NDVI According to the Terrain Element)

  • 성춘자;정종철
    • 한국지리정보학회지
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    • 제6권2호
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    • pp.92-100
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    • 2003
  • 연구의 기본 목적은 지형단위를 분류할 수 있는 정량적 기준 마련에 두고, 본 연구에서는 사례 지역을 대상으로 고도, 사면경사, 사면방향 등 지형요소에 따른 NDVI의 차이와 변화를 분석하고 지형단위의 분류 지표로 NDVI의 활용 가능성을 진단하고자 하는 것이다. 사례지역을 대상으로 분석한 결과, 고도, 사면경사, 사면방향 등 분석된 지형요소와 NDVI가 선형의 관계를 나타내지는 않으며, 대체로 NDVI가 높게 나타났고, 고도와 사면경사가 증가함에 따라서 NDVI의 분산범위가 작아지는 경향을 보인다. 고도와 사면경사가 증가하면서 NDVI의 분산범위가 불연속적 변화양상을 보이는데 고도의 경우에는 대략 50m와 100m를 경계로, 사면경사의 경우에는 사면경사 $10{\sim}20^{\circ}$를 경계로 NDVI의 분산범위가 불연속적으로 감소된다. 그러나 사면방향에 따른 NDVI의 차이는 거의 나타나지 않았다.

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Intercomparison of interannual changes in NDVI from PAL and GIMMS in relation to evapotranspiration over northern Asia

  • Suzuki Rikie;Masuda Kooiti;Dye Dennis
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.162-165
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    • 2004
  • The authors' previous study found an interannual covariability between actual evapotranspiration (ET) and the Normalized Difference Vegetation Index (NDVI) over northern Asia. This result suggested that vegetation controls interannual variation in ET. In this prior study, NDVI data from the Pathfinder AVHRR Land (PAL) dataset were analyzed. However, studies of NDVI interannual change are subject to uncertainty, because NDVI data often contain errors associated with sensor- and atmosphere-related effects. This study is aimed toward reducing this uncertainty by employing NDVI dataset, from the Global Inventory Monitoring and Modeling Studies (GIMMS) group, in addition to PAL. The analysis was carried out for the northern Asia region from 1982 to 2000. 19-year interannual change in PAL-NDVI and GIMMS-NDVI were both compared with interannual change in model-assimilated ET. Although the correlation coefficient between GIMMS-NDVI and ET is slightly less than for PAL-NDVI and ET, for both NDVI datasets the annual maximum correlation with ET occurs in June, which is near the central period of the growing season. A significant positive correlation between GIMMS-NDVI and ET was observed over most of the vegetated land area in June as well as PAL-NDVI and ET. These results reinforce the authors' prior research that indicates the control of interannual change in ET is dominated by interannual change in vegetation activity.

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드론 영상을 이용한 Sentinel-2, Landsat-8 위성 NDVI 평가: 벼 병해 발생 지역을 대상으로 (Evaluation of NDVI Retrieved from Sentinel-2 and Landsat-8 Satellites Using Drone Imagery Under Rice Disease)

  • 류재현;안호용;나상일;이병모;이경도
    • 대한원격탐사학회지
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    • 제38권6_1호
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    • pp.1231-1244
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    • 2022
  • 이상기상으로 인해 노지 작물이 스트레스 상황에 노출되는 빈도가 증가하고 있다. 우리나라에서도 대표적인 벼 재배지역에서 대규모의 병해가 발생하는 사례가 나타났으며, 특정 시기에 대규모 필지에서 발생하는 피해를 현장방문으로 조사하는 것은 한계가 있다. 위성 기반의 원격탐사 기법은 시군 영역을 대상으로 작물을 모니터링하기에 유용하나 작물의 생육이상에 따른 민감도 평가가 선행되어야 한다. 본 연구에서는 벼 병해 발생 지역에서 서로 다른 공간해상도를 가지는 위성 기반의 정규화식생지수(normalized difference vegetation index, NDVI)를 드론 영상을 이용하여 평가하였다. 10 m와 30 m의 공간해상도를 가지는 Sentinel-2, Landsat-8 위성 영상을 평가하였으며, 드론 영상은 약 8-10 cm의 공간해상도를 가졌다. 위성 영상에 맞춰 리샘플링(resampling)된 드론 NDVI는 Sentinel-2 NDVI 와 0.867-0.940의 상관관계를 가졌으며, Landsat-8 NDVI와는 0.813-0.934의 상관관계를 가졌다. 센서의 차이, 관측 시점의 차이 등으로 인한 편향(bias) 영향을 최소화하였을 때, Sentinel-2 NDVI는 Landsat-8 NDVI에 비해 드론 NDVI와 0.2-2.8% 더 적은 정규화된 평균 제곱근 오차를 가졌다. 또한, Sentinel-2 NDVI는 드론 NDVI와 병해 피해 정도와 관계없이 일정한 오차를 가졌으나 Landsat-8 NDVI는 병해 피해 정도에 따라 드론 NDVI와 오차 특성이 다르게 나타났다. 농경지 경계에서 오차가 크다는 것을 고려했을 때 공간해상도가 높은 영상을 활용하는 것이 작물 모니터링에 효과적이라고 판단된다.

Multi-temporal image derived Ratio Vegetation Index and NDVI in a landslide prone region

  • Paramarthalingam, Rajakumar;Shanmugam, Sanjeevi
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.257-259
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    • 2003
  • Landuse maps are prepared from satellite imagery and field observations were conducted at various locations in the study area. Compared to the field data and NDVI and RVI thematic maps, NDVI is better than RVI, because it compensates for changing illumination conditions, surface slope, aspect and other factors. Clouds, water and snow have negative values for RVI and NDVI. Rock and bare soils have similar reflectance in both NIR and visible band, so RVI and NDVI are near zero. In forest areas with good vegetation cover, NDVI is high and landslide occurrence is less. But if annual and biennial vegetations are present and if cultivation practices are changed frequently, NDVI is medium and landslide occurrence is moderate. In areas where deforestation and settlement is in progress, NDVI is less and landslide occurrence is more. The NDVI FCC thematic map may be used as an important layer in GIS application for landslide studies. Analyzing other layers such as slope, rainfall, soil, geology, drainage, lineament, etc with NDVI FCC layer will give a better idea about the identity of landslide prone areas.

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Consideration of NDVI and Surface Temperature Calculation from Satellite Imagery in Urban Areas: A Case Study for Gumi, Korea

  • Bhang, Kon Joon;Lee, Jin-Duk
    • 한국측량학회지
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    • 제35권1호
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    • pp.23-30
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    • 2017
  • NDVI (Normalized Difference Vegetation Index) plays an important role in surface land cover classification and LST (Land Surface Temperature Extraction). Its characteristics do not full carry the information of the surface cover typically in urban areas even though it is widely used in analyses in urban areas as well as in vegetation. However, abnormal NDVI values are frequently found in urban areas. We, therefore, examined NDVI values on whether NDVI is appropriate for LST and whether there are considerations in NDVI analysis typically in urban areas because NDVI is strongly related to the surface emissivity calculation. For the study, we observed the influence of the surface settings (i.e., geometric shape and color) on NDVI values in urban area and transition features between three land cover types, vegetation, urban materials, and water. Interestingly, there were many abnormal NDVI values systematically derived by the surface settings and they might influence on NDVI and eventually LST. Also, there were distinguishable transitions based on the mixture of three surface materials. A transition scenario was described that there are three transition types of mixture (urban material-vegetation, urban material-water, and vegetation-water) based on the relationship of NDVI and LST even though they are widely distributed.

Inter-Annual and Intra-Annual Variabilities of NDVI, LAI and Ts Estimated by AVHRR in Korea

  • Ha, Kyung-Ja;Oh, Hyun-mi;Kim, Ki-Young
    • 대한원격탐사학회지
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    • 제17권2호
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    • pp.111-119
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    • 2001
  • This study analyzes time variability of the normalized difference vegetation index (NDVI), the leaf area index (LAI) and surface temperature (Ts) estimated from AVHRR data collected from across the Korean peninsula from 1981 to 1994. In the present study, LAI defined as vegetation density, as a function of NDVI applied for the vegetation types and Ts defined by the split-window formulation of Becker and Li (1990) with emissivity of a function of NDVI, are used. Results of the inter-annual, intra-annual and intra-seasonal variabilities in Korea show: (1) Inter-annual variability of NDVI is generally larger in the southem and eastern parts of the peninsula than in the western part. This large variability results from the significant mean variation. (2) Inter-annual variability of Ts is larger in the areas of smaller NDVI. This result shows that the NDVI play a small role in emissivity. (3) Inter-annual variability of LAI is larger in the regions of higher elevation and urban areas. Changes in LAI are unlikely to be associated with NDVI changes. (4) Changes in NDVI and Ts are likely dominant in July and are relatively small in spring and fall. (5) Urban effect would be obvious on the time-varying properties of NDVI and Ts in Seoul and the northern part of Taejon, where NDVI decreases and Ts increases with a significant magnitude.

소나무, 주목, 느티나무 그리고 단풍나무의 입면 NDVI 비교 분석 - 강원대학교 내 조경수목식재종을 대상으로 - (Analysis of Elevation NDVI (Normalized Difference Vegetation Index) for Taxus cuspidata, Pinus densiflora, Zelkova serrata and Acer palmatum - Focused on landscaping trees in Kangwon National University -)

  • 길승호
    • 한국환경복원기술학회지
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    • 제20권6호
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    • pp.151-160
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    • 2017
  • This study was conducted by using a Nikon Coolpix S800c camera equipped with a NIR filter to measure the NDVI(Normalized Difference Vegetation Index). It was used for the measurement of the three trees of Pinus densiflora, Taxus cuspidata, Zelkova serrata and Acer palmatum in Kangwon National University. The NDVI value of the surface of the building was compared and analyzed. The average value of NDVI in August and September was high in all species. The NDVI distribution of Taxus cuspidata was higher than the other trees. The NDVI distribution of Pinus densiflora and Taxus cuspidata did not show any significant seasonal differences, but The NDVI distribution of Zelkova serrata and Acer palmatum were relatively low in May and June, which are leafless periods. Previous studies related to NDVI value were generally analyzed using satellite imagery. However, it was scarce related to study the NDVI value of each tree or study the changing process of NDVI by time series. Previous studies have used NDVI values on the ground but this study used NDVI values in the ground section. Future studies will be necessary to measure the NDVI value at different times for various species and also to make efforts to generalize the measurement method. In addition, research related to various fields such as the relationship between NDVI and carbon stocks and the relationship with LAI needs to be conducted.

NOAA AVHRR데이터를 이용한 한반도의 순별 NDVI와 LAI 특성 (Characteristics of 10-day composite NDVI and LAI in Korea Peninsula Using NOAA AVHRR Data)

  • 박종화;전택기;나상일;박민서
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2005년도 학술발표논문집
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    • pp.649-654
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    • 2005
  • This study proposes a particular approach to assess information about NDVI(Normalized Difference Vegetation Index) and LAI(Leaf Area Index) from the spectroradiometer and NOAA/AVHRR satellite data. AVHRR data were collected in twelves months over a one year period in 2004. We calculated 10-day composite NDVI using daily composite AVHRR surface reflectance products(1km spatial resolution). The 10-day composite NDVI have a great effect on the plant growth conditions. Considerably, NDVI was increased by developing muscle fiber tissue from April to May. Then the NDVI increased until the August and then decreased until February. The highest month was at August and the lower month was at December. The difference NDVI analysis using December and another months data was conducted, the results were provided information on the variation of vegetation coverage. The result suggest that a relationship established between the LAI and NDVI in 2004.

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