• Title/Summary/Keyword: Time series NDVI

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Suggestion of Method to Classify Moisture or Dryness Condition from Moisture Index Obtained by NDVI (NDVI를 이용한 습윤지표를 기준으로 습윤 및 건조상황의 분류 방법 제안)

  • Kim, Joo-Cheol;Shin, Sha-Chul;Lee, Sang-Jin;Hwang, Man-Ha
    • Journal of the Korean Association of Geographic Information Studies
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    • v.12 no.4
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    • pp.84-94
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    • 2009
  • Moisture Index time series derived from NOAA/AVHRR data have showed to be useful for humid and arid states. The humid/arid states of the Geum river basin are classified by means of the moisture index estimated from the climatic water budget model. Validations showed that the moisture index has excellent ability to detect humid/arid conditions and to measure time of its onset, intensity and duration. In this study, a simple method to classify the moisture index is proposed by statistical distribution condition. Also, the moisture index is compared with the regional actual state to detect drought area.

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A Study on Estimating Rice Yield in DPRK Using MODIS NDVI and Rainfall Data (MODIS NDVI와 강수량 자료를 이용한 북한의 벼 수량 추정 연구)

  • Hong, Suk Young;Na, Sang-Il;Lee, Kyung-Do;Kim, Yong-Seok;Baek, Shin-Chul
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.441-448
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    • 2015
  • Lack of agricultural information for food supply and demand in Democratic People's republic Korea(DPRK) make people sometimes confused for right and timely decision for policy support. We carried out a study to estimate paddy rice yield in DPRK using MODIS NDVI reflecting rice growth and climate data. Mean of MODIS $NDVI_{max}$ in paddy rice over the country acquired and processed from 2002 to 2014 and accumulated rainfall collected from 27 weather stations in September from 2002 to 2014 were used to estimated paddy rice yield in DPRK. Coefficient of determination of the multiple regression model was 0.44 and Root Mean Square Error(RMSE) was 0.27 ton/ha. Two-way analysis of variance resulted in 3.0983 of F ratio and 0.1008 of p value. Estimated milled rice yield showed the lowest value as 2.71 ton/ha in 2007, which was consistent with RDA rice yield statistics and the highest value as 3.54 ton/ha in 2006, which was not consistent with the statistics. Scatter plot of estimated rice yield and the rice yield statistics implied that estimated rice yield was higher when the rice yield statistics was less than 3.3 ton/ha and lower when the rice yield statistics was greater than 3.3 ton/ha. Limitation of rice yield model was due to lower quality of climate and statistics data, possible cloud contamination of time-series NDVI data, and crop mask for rice paddy, and coarse spatial resolution of MODIS satellite data. Selection of representative areas for paddy rice consisting of homogeneous pixels and utilization of satellite-based weather information can improve the input parameters for rice yield model in DPRK in the future.

Ecoclimatic Map over North-East Asia Using SPOT/VEGETATION 10-day Synthesis Data (SPOT/VEGETATION NDVI 자료를 이용한 동북아시아의 생태기후지도)

  • Park Youn-Young;Han Kyung-Soo
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.8 no.2
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    • pp.86-96
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    • 2006
  • Ecoclimap-1, a new complete surface parameter global database at a 1-km resolution, was previously presented. It is intended to be used to initialize the soil-vegetation- atmosphere transfer schemes in meteorological and climate models. Surface parameters in the Ecoclimap-1 database are provided in the form of a per-class value by an ecoclimatic base map from a simple merging of land cover and climate maps. The principal objective of this ecoclimatic map is to consider intra-class variability of life cycle that the usual land cover map cannot describe. Although the ecoclimatic map considering land cover and climate is used, the intra-class variability was still too high inside some classes. In this study, a new strategy is defined; the idea is to use the information contained in S10 NDVI SPOT/VEGETATION profiles to split a land cover into more homogeneous sub-classes. This utilizes an intra-class unsupervised sub-clustering methodology instead of simple merging. This study was performed to provide a new ecolimatic map over Northeast Asia in the framework of Ecoclimap-2 global database construction for surface parameters. We used the University of Maryland's 1km Global Land Cover Database (UMD) and a climate map to determine the initial number of clusters for intra-class sub-clustering. An unsupervised classification process using six years of NDVI profiles allows the discrimination of different behavior for each land cover class. We checked the spatial coherence of the classes and, if necessary, carried out an aggregation step of the clusters having a similar NDVI time series profile. From the mapping system, 29 ecosystems resulted for the study area. In terms of climate-related studies, this new ecosystem map may be useful as a base map to construct an Ecoclimap-2 database and to improve the surface climatology quality in the climate model.

Detection of Forest Fire and NBR Mis-classified Pixel Using Multi-temporal Sentinel-2A Images (다시기 Sentinel-2A 영상을 활용한 산불피해 변화탐지 및 NBR 오분류 픽셀 탐지)

  • Youn, Hyoungjin;Jeong, Jongchul
    • Korean Journal of Remote Sensing
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    • v.35 no.6_2
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    • pp.1107-1115
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    • 2019
  • Satellite data play a major role in supporting knowledge about forest fire by delivering rapid information to map areas damaged. This study, we used 7 Sentinel-2A images to detect change area in forests of Sokcho on April 4, 2019. The process of classify forest fire severity used 7 levels from Sentinel-2A dNBR(differenced Normalized Burn Ratio). In the process of classifying forest fire damage areas, the study selected three areas with high regrowth of vegetation level and conducted a detailed spatial analysis of the areas concerned. The results of dNBR analysis, regrowth of coniferous forest was greater than broad-leaf forest, but NDVI showed the lowest level of vegetation. This is the error of dNBR classification of dNBR. The results of dNBR time series, an area of forest fire damage decreased to a large extent between April 20th and May 3rd. This is an example of the regrowth by developing rare-plants and recovering broad-leaf plants vegetation. The results showed that change area was detected through the change detection of danage area by forest category and the classification errors of the coniferous forest were reached through the comparison of NDVI and dNBR. Therefore, the need to improve the precision Korean forest fire damage rating table accompanied by field investigations was suggested during the image classification process through dNBR.

Assessment of the Contribution of Weather, Vegetation, Land Use Change for Agricultural Reservoir and Stream Watershed using the SLURP model (I) - Preparation of Input Data for the Model - (SLURP 모형을 이용한 기후, 식생, 토지이용변화가 농업용 저수지유역과 하천유역에 미치는 기여도 평가(I) - 모형의 입력자료 구축 -)

  • Park, Geun-Ae;Lee, Yong-Jun;Shin, Hyung-Jin;Kim, Seong-Joon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.2B
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    • pp.107-120
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    • 2010
  • The effect of potential future climate change on the inflow of agricultural reservoir and its impact to downstream streamflow by reservoir operation for paddy irrigation water was assessed using the SLURP (semi-distributed land use-based runoff process), a physically based hydrological model. The fundamental input data (elevation, meteorological data, land use, soil, vegetation) was collected to calibrate and validate of the SLURP model for a 366.5 $km^2$ watershed including two agricultural reservoirs (Geumgwang and Gosam) located in Anseongcheon watershed. Then, the CCCma CGCM2 data by SRES (special report on emissions scenarios) A2 and B2 scenarios of the IPCC (intergovernmental panel on climate change) was used to assess the future potential climate change. The future weather data for the year, m ms, m5ms and 2amms was downscaled by Change Factor method through bias-correction using 3m years (1977-2006) weather data of 3 meteorological stations of the watershed. In addition, the future land uses were predicted by modified CA (cellular automata)-Markov technique using the time series land use data fromFactosat images. Also the future vegetation cover information was predicted and considered by the linear regression between monthly NDVI (normalized difference vegetation index) from NOAA AVHRR images and monthly mean temperature using eight years (1998-2006) data.

Analysis of the Spatial and Temporal Variability of NDVI Time Series in South Korea (남한지역 정규식생지수의 시공간 변화도 분석)

  • Kim, Gwang-Seob;Yim, Tae-Kyung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2005.05b
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    • pp.119-122
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    • 2005
  • 정규식생지수는 일반적으로 식생의 활력도를 나타나는 지표로서 널리 사용되고 있다. 최근에는 정규식생지수가 특정지역의 강우량과 온도의 계절 및 경년변화와 어떤 상관관계를 가지며 기후변화는 식생지수에 어떠한 영향을 미치는지 등에 관한 연구가 활발히 수행되고 있다. 본 연구에서는 1981년부터 2001년까지의 NOAA/AVHRR 영상으로부터 계산된 남한지역 정규식생지수의 주성분 분석을 통해 자료의 공간변화패턴을 분석하고 경험적 직교함수를 이용하여 시간적 변화 양상을 파악하였다. 분석결과 정규식생지수의 공간변화도는 첫 주성분에 의하여 약 $60\%$ 정도 설명되어지며 첫 주성분은 남한지역의 지형 자료 패턴을 따르고 두 번째 주성분은 전체 변화도의 약 $17\%$를 나타내며 강한 남북기울기를 보여주는 것은 계절변화와 상관한 위도변화에 따른 정규식생지수의 변화를 나타낸다. 그리고 소양강댐 및 안동댐 유역의 정규식생지수, 강우량 및 유입량 상관관계 분석 결과 정규식생지수의 계절변화와 경년변화는 강우량의 변화에 그리 민감하지 않은 것으로 나타났다.

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Impact of Land Use Land Cover Change on the Forest Area of Okomu National Park, Edo State, Nigeria

  • Nosayaba Osadolor;Iveren Blessing Chenge
    • Journal of Forest and Environmental Science
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    • v.39 no.3
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    • pp.167-179
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    • 2023
  • The extent of change in the Land use/Land cover (LULC) of Okomu National Park (ONP) and fringe communities was evaluated. High resolution Landsat imagery was used to identify the major vegetation cover/land use systems and changes around the national park and fringe communities while field visits/ground truthing, involving the collection of coordinates of the locations was carried out to ascertain the various land cover/land use types identified on the images, and the extent of change over three-time series (2000, 2010 and 2020). The change detection was analyzed using area calculation, change detection by nature and normalized difference vegetation index (NDVI). The result of the classification and analysis of the LULC Change of ONP and fringe communities revealed an alarming rate of encroachment into the protected area. All the classification features analyzed had notable changes from 2000-2020. The forest, which was the dominant LULC feature in 2000, covering about 66.19% of the area reduced drastically to 36.12% in 2020. Agricultural land increased from 6.14% in 2000 to 34.06% in 2020 while vegetation (degraded land) increased from 27.18% in 2000 to 38.89% in 2020. The magnitude of the change in ONP and surroundings showed the forest lost -247.136 km2 (50.01%) to other land cover classes with annual rate change of 10%, implying that 10% of forest land was lost annually in the area for 20 years. The NDVI classification values of 2020 indicate that the increase in medium (399.62 km2 ) and secondary high (210.17 km2 ) vegetation classes which drastically reduced the size of the high (38.07 km2 ) vegetation class. Consequent disappearance of the high forests of Okomu is inevitable if this trend of exploitation is not checked. It is pertinent to explore other forest management strategies involving community participation.

Comparison of vegetation recovery according to the forest restoration technique using the satellite imagery: focus on the Goseong (1996) and East Coast (2000) forest fire

  • Yeongin Hwang;Hyeongkeun Kweon;Wonseok Kang;Joon-Woo Lee;Semyung Kwon;Yugyeong Jung;Jeonghyeon Bae;Kyeongcheol Lee;Yoonjin Sim
    • Korean Journal of Agricultural Science
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    • v.50 no.3
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    • pp.555-567
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    • 2023
  • This study was conducted to compare the level of vegetation recovery based on the forest restoration techniques (natural restoration and artificial restoration) determined using the satellite imagery that targeted forest fire damaged areas in Goseong-gun, Gangwon-do. The study site included the area affected by the Goseong forest fire (1996) and the East Coast forest fire (2000). We conducted a time-series analysis of satellite imagery on the natural restoration sites (19 sites) and artificial restoration sites (12 sites) that were created after the forest fire in 1996. In the analysis of satellite imagery, the difference normalized burn ratio (dNBR) and normalized difference vegetation index (NDVI) were calculated to compare the level of vegetation recovery between the two groups. We discovered that vegetation was restored at all of the study sites (31 locations). The satellite image-based analysis showed that the artificial restoration sites were relatively better than the natural restoration sites, but there was no statistically significant difference between the two groups (p > 0.05). Therefore, it is necessary to select a restoration technique that can achieve the goal of forest restoration, taking the topography and environment of the target site into account. We also believe that in the future, accurate diagnosis and analysis of the vegetation will be necessary through a field survey of the forest fire-damaged sites.

Distribution Characteristics Analysis of Pine Wilt Disease Using Time Series Hyperspectral Aerial Imagery (소나무재선충병 발생시기별 피해목 탐지를 위한 시계열 초분광 항공영상의 활용)

  • Kim, So-Ra;Kim, Eun-Sook;Nam, Youngwoo;Choi, Won Il;Kim, Cheol-Min
    • Korean Journal of Remote Sensing
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    • v.31 no.5
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    • pp.385-394
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    • 2015
  • Pine wilt disease has greatly damaged pine forests not only in East Asia including South Korea and China, but also in European region. The damage caused by pine wood nematode (Bursaphelenchus xylophilus) is expressed in bundles within stands and rapidly spreading, however, present field survey methods have limitations to detecting damaged trees at regional level. This study extracted the damaged trees by pine wilt disease using time series hyperspectral aerial photographs, and analyzed their distribution characteristics. Hyperspectral aerial photographs of 1 meter spatial resolution were obtained in June, September, and October. Damaged trees by pine wilt disease were extracted using Normalized Difference Vegetation Index (NDVI) and Vegetation Index green (VIgreen) of the September photograph. Among extracted damaged trees, dead trees with leaves and without leaves were classified, and the spectral reflectance values from the photographs obtained in June, September, and October were compared to extract new outbreaks in September and October. Based on the time series dispersion of extracted damaged trees, nearest neighbor analysis was conducted to analyze distribution characteristics of the damaged trees within the region where hyperspectral aerial photographs were acquired. As a result, 2,262 damaged trees were extracted in the study area, and 604 dead trees (dead trees in last year) with leaves in relation to the damaged time and 300 and 101 newly damaged trees in September and October were classified. The result of nearest neighbor analysis using the data shows that aggregated distribution was the dominant pattern both previous and current year in the study area. Also, 80% of the damaged trees in current year were found within 60 m of dead trees in previous year.

Assessment of MODIS Leaf Area Index (LAI) Influence on the Penman-Monteith Evapotranspiration Estimation of SLURP Model (MODIS 위성영상으로부터 추출된 엽면적지수(LAI)가 SLURP 모형의 Penman-Monteith 증발산량 추정에 미치는 영향 평가)

  • Ha, Rim;Shin, Hyung-Jin;Hong, Woo-Yong;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2008.05a
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    • pp.1087-1091
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    • 2008
  • Evapotranspiration (ET) is an important factor while simulating daily streamflow in hydrological models. The LAI (Leaf Area Index) value reflecting the conditions of vegetation generally affects considerably in the estimation of ET, for example, when using FAO Penman Monteith equation. Recently in evaluating the vegetation condition as a fixed quantity, the remotely sensed LAIs from MODIS satellite data are avaliable, and the time series values of spatial LAI coupled with land use classes are utilized for ET evaluation. The 4 years (2001-2004) MODIS LAI data were prepared for the evaluation of continuous hydrological model, SLURP (Semi-distributed Land Use-based Runoff Processes). The model was applied for simulating the dam inflow of Chungjudam watershed ($6661.58\;km^2$) located in the upstream of Han river basin of South Korea. From the model results, the FAO Penman Monteith ET was affected by the MODIS LAIs. Especially for the ET of deciduous forest, the Total ET was 33.9 % lager than coniferous forest for the 3.8 % lager of LAI. The watershed average LAI caused a 7.0 % decrease in average soil moisture of the watershed and 14.3 % decrease of ground water recharge.

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