• 제목/요약/키워드: land surface cover

검색결과 315건 처리시간 0.025초

A Statistic Correlation Analysis Algorithm Between Land Surface Temperature and Vegetation Index

  • Kim, Hyung-Moo;Kim, Beob-Kyun;You, Kang-Soo
    • Journal of Information Processing Systems
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    • 제1권1호
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    • pp.102-106
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    • 2005
  • As long as the effective contributions of satellite images in the continuous monitoring of the wide area and long range of time period, Landsat TM and Landsat ETM+ satellite images are surveyed. After quantization and classification of the deviations between TM and ETM+ images based on approved thresholds such as gains and biases or offsets, a correlation analysis method for the compared calibration is suggested in this paper. Four time points of raster data for 15 years of the highest group of land surface temperature and the lowest group of vegetation of the Kunsan city Chollabuk_do Korea located beneath the Yellow sea coast, are observed and analyzed their correlations for the change detection of urban land cover. This experiment based on proposed algorithm detected strong and proportional correlation relationship between the highest group of land surface temperature and the lowest group of vegetation index which exceeded R=(+)0.9478, so the proposed Correlation Analysis Model between the highest group of land surface temperature and the lowest group of vegetation index will be able to give proof an effective suitability to the land cover change detection and monitoring.

용담댐 유역에서 식생 이질성이 FLO-2D 유량 산정에 미치는 영향 (Impact of Vegetation Heterogeneity on Rainfall Excess in FLO-2D Model : Yongdam Catchment)

  • 송호준;이길하
    • 한국환경과학회지
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    • 제28권2호
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    • pp.259-266
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    • 2019
  • Two main sources of data, meteorological data and land surface characteristics, are essential to effectively run a distributed rainfall-runoff model. The specification and averaging of the land surface characteristics in a suitable way is crucial to obtaining accurate runoff output. Recent advances in remote sensing techniques are often being used to derive better representations of these land surface characteristics. Due to the mismatch in scale between digital land cover maps and numerical grid sizes, issues related to upscaling or downscaling occur regularly. A specific method is typically selected to average and represent the land surface characteristics. This paper examines the amount of flooding by applying the FLO-2D routing model, where vegetation heterogeneity is manipulated using the Manning's roughness coefficient. Three different upscaling methods, arithmetic, dominant, and aggregation, were tested. To investigate further, the rainfall-runoff model with FLO-2D was facilitated in Yongdam catchment and heavy rainfall events during wet season were selected. The results show aggregation method provides better results, in terms of the amount of peak flow and the relative time taken to achieve it. These rwsults suggest that the aggregation method, which is a reasonably realistic description of area-averaged vegetation nature and characteristics, is more likely to occur in reality.

PHENOLOGICAL ANALYSIS OF NDVI TIME-SERIES DATA ACCORDING TO VEGETATION TYPES USING THE HANTS ALGORITHM

  • Huh, Yong;Yu, Ki-Yun;Kim, Yong-Il
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.329-332
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    • 2007
  • Annual vegetation growth patterns are determined by the intrinsic phenological characteristics of each land cover types. So, if typical growth patterns of each land cover types are well-estimated, and a NDVI time-series data of a certain area is compared to those estimated patterns, we can implement more advanced analyses such as a land surface-type classification or a land surface type change detection. In this study, we utilized Terra MODIS NDVI 250m data and compressed full annual NDVI time series data into several indices using the Harmonic Analysis of Time Series(HANTS) algorithm which extracts the most significant frequencies expected to be presented in the original NDVI time-series data. Then, we found these frequencies patterns, described by amplitude and phase data, were significantly different from each other according to vegetation types and these could be used for land cover classification. However, in spite of the capabilities of the HANTS algorithm for detecting and interpolating cloud-contaminated NDVI values, some distorted NDVI pixels of June, July and August, as well as the long rainy season in Korea, are not properly corrected. In particular, in the case of two or three successive NDVI time-series data, which are severely affected by clouds, the HANTS algorithm outputted wrong results.

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위성 및 AWS 자료를 이용한 지표면 피복 조건의 차이가 대구의 도시 열환경에 미치는 영향 (Effect of Difference of Land Cover Conditions on Urban Thermal Environment in Daegu Using Satellite and AWS Data)

  • 안지숙;김해동;김상우
    • 한국환경과학회지
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    • 제19권3호
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    • pp.281-293
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    • 2010
  • The present study explores time and spatial thermal environment for Daegu, which is a city built on a basin area, according to varying land cover conditions of the earth's surface by analyzing data derived from meteorological observation and satellite images. The study has classified land use by utilizing MODIS satellite images and analyzed land surface temperature. Also, by using data acquired from automatic weather system, the study has evaluated the effects of atmospheric heating caused by city pavements by analyzing the sensible heat flux between the city's land surface and the atmosphere. The results are as follows. 1) Classification of land use in the Daegu area shows 46.64% of urban and built-up area, 1.39% of watersides, 35.19% of forest, 11.43% of crops, and 5.37% grasslands. 2) During the weekdays throughout the year, the land surface temperature was high for Dalseogu, Bukgu, and Seogu regions where industrial complexes could be found. Comparatively, lower temperature could be observed in the woodlands. 3) While the land surface temperature displayed the effects of pushing air upwards during the weekdays in urban areas, the reverse was true for forest regions. During the night, the temperature did not exert any significant influence on air movement.

토지이용도와 초기 기상 입력 자료의 선택에 따른 지상 기온 예측 정확도 비교 연구 (Comparative Study on the Accuracy of Surface Air Temperature Prediction based on selection of land use and initial meteorological data)

  • 김해동;김하영
    • 한국환경과학회지
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    • 제33권6호
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    • pp.435-442
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    • 2024
  • We investigated the accuracy of surface air temperature prediction according to the selection of land-use data and initial meteorological data using the Weather Research and Forecasting model-v4.2.1. A numerical experiment was conducted at the Daegu Dyeing Industrial Complex. We initially used meteorological input data from GFS (Global forecast system)and GDAPS (Global data assimilation and prediction system). High-resolution input data were generated and used as input data for the weather model using the land cover data of the Ministry of Environment and the digital elevation model of the Ministry of Land, Infrastructure, and Transport. The experiment was conducted by classifying the terrestrial and topographic data (land cover data) and meteorological data applied to the model. For simulations using high-resolution terrestrial data(10 m), global data assimilation, and prediction system data(CASE 3), the calculated surface temperature was much closer to the automatic weather station observations than for simulations using low-resolution terrestrial data(900 m) and GFS(CASE 1).

서울 도심지의 인본열에 의한 지표온도 분석: 위성영상 적용 사례 (Analysis of the Land Surface Temperature by the Anthropogenic Heat in the Urban Area of Seoul: An Example in Application of Satellite Images)

  • 방건준;박석순
    • 환경영향평가
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    • 제19권4호
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    • pp.397-407
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    • 2010
  • The increase of the solar reradiation from urban areas relative to suburban due to urbanization heats up the air temperature in urban areas and this is called the urban heat island (UHI) effect. This UHI effect has a positive relationship with the degree of urbanization. Through the studies on UHI using the satellite imagery, the effect of the surface heat radiation was observed by verifying the relationship between the air temperature and the land cover types (surface materials such as urban, vegetation, etc.). In this study, however, the surface temperature distribution was studied in terms of land use types for Seoul. Using land use types, the surface temperature in urban areas such as residential, industrial, and commercial areas in Yeongdeungpo, highly packed with industrial and residential buildings, was maximum $6^{\circ}C$ higher than in the bare ground, which indicated that the surface temperature reflected the pattern of the human-consumed energy on the areas and showed that one of the important causes influencing the air temperature except the surface heat reradiation by the sun is the anthropogenic heat. Also, the effect due to the restoration of the Chunggae stream on UHI was investigated. The average surface temperature for the Chunggae stream was reduced about $0.4^{\circ}C$ after restoration. Considering that each satellite image pixel includes mixture of several materials such as concrete and asphalt, the average surface temperature might be much lower locally reducing UHI near the stream.

Landsat TM 데이터에 의한 식생피복율과 지표면온도와의 관계 해석 (Analysis of Relationship between Vegetation Cover Rates and Surface Temperature Using Landsat TM Data)

  • 박종화;나상일;김진수
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2005년도 학술발표논문집
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    • pp.569-573
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    • 2005
  • Land surface temperature(LST) is one of the key parameters in physics and meteorology of land-surface processes on regional and global scales. Urban Heat Island(UHI), a meteorological phenomenon by which the air temperature in an urban area increases beyond that in the suburbs, grows with the progress of urbanization. Satellite remote sensing has been expected to be effective for obtaining thermal information of the earth's surface with a high resolution. The main purpose of this study is to produce LST map of Cheongju and to analyze the spatial distributions of surface heat fluxes in urban areas. This study, taking Cheongju as the study area, aims to examine relationship between vegetation cover rates and surface temperature, and to clarify a method for calculation surface temperature with Landsat TM thermal images.

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실내인공강우기를 이용한 경사지 밭의 토양유실량과 오염부하 모의 (Simulation of generable muddy water quantity and pollutant loads in sloping field using artificial rainfall simulator)

  • 신민환;최용훈;서지연;이재운;최중대
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2009년도 학술발표회 초록집
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    • pp.986-990
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    • 2009
  • Using artificial rainfall simulator, the soil loss, which is deemed as most cause of muddy water problem among Non-point source(NPS) pollutant, was studied by the analysis of direct runoff flow, groundwater runoff, and groundwater storage properties concerned with rainfall intensity, slope of area, and land cover. The direct runoff showed increasing tendency in both straw covered and bared boxes which are 5%, 10%, and 20% sloped respectively. Also the direct runoff volume from straw covered surface boxes were much lower than bared surface boxes. It's deemed as that the infiltration capacity of straw covered surface boxes were increased, because the surface sealing by fine material of soil surface didn't occurred due to the straw covering. Under the same rainfall intensity and slope condition, 2.4 ${\sim}$ 8.2 times of sediment yield were occurred from bared surface boxes more than straw covered surface boxes. The volume of infiltrated were increased due to straw cover, the direct runoff flow were decreased with decreasing of tractive force in surface. To understand of relationship the rate of direct runoff flow, groundwater runoff, and groundwater storage by the rainfall intensity, slope, and land cover, the statistical test was performed. It shows good relationship between most of factors, expect between the rate of groundwater storage and rainfall intensity.

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지역기후모델에서 고해상도 지면피복이 1989년 동아시아 여름몬순 순환에 미치는 영향 (Impacts of the High Resolution Land Cover Data on the 1989 East-Asian Summer Monsoon Circulation in a Regional Climate Model)

  • 서명석;이동규
    • 대기
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    • 제15권2호
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    • pp.75-90
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    • 2005
  • 이 연구에서는 지면-대기 모수화 방안 (BATS1e)이 접합된 미국 국립기상연구센터 (NCAR)에서 개발한 지역기후모델(RegCM2)을 이용하여 지면피복의 변화가 동아시아 여름몬순에 미치는 영향에 대해서 조사하였다. 지면피복 변화의 영향을 분석하기 위하여 두 종류의 지면피복 자료를 이용하였다. 하나는 NCAR에서 제공하는 지면피복 자료 (CTL 실험)이고 다른 하나는 최근의 기상위성자료로부터 직접 분류한 고해상도 지면피복분류 자료(LCV 실험)이다. CTL 실험에서는 중국 중부지역과 몽고지역의 지면온도가 각각 약 $1-3^{\circ}C$ 높고 낮게 모의되었다. 또한 모의 영역 북부지역에서는 강수가 과다하게 모의된 반면 모의영역 남부 바다지역의 강수는 과소하게 모의되었다. 지면피복 변화에 의한 알베도, 거칠기 길이 및 최소기공저항계수와 같은 지면의 생물리적 요소들의 변화는 지면-대기 상호작용을 변경시켰다. 즉, 지면피복이 낙엽활엽수림에서 농지와 관계농지로 변경된 LCV 실험의 중국 중부지역에서는 잠열 속과 풍속이 현저하게 증가되었다. 그 결과 CTL 실험에서 나타났던 중국 중부지역에서의 온난편차가 LCV 실험에서는 대부분 완화되었다. 중국 중부지역에서의 강한 기온 하강은 태평양과 대륙사이의 기압 차를 약화시키고 있다. 남동에서 북서방향으로의 기압경도력이 약화됨에 따라 중국 남부와 남중국해로부터 북동쪽으로의 수증기 수송도 약화되었다. 이러한 수증기 수송의 변화는 모의 영역 북부지역에서의 과다한 강수 모의와 남중국해에서의 과소한 강수모의를 동시에 크게 완화시켰다. 그러나 지면피복의 변화는 특히 7월과 8월에 한반도와 일본 열도 지역에서의 강수를 크게 증기시키고 있다.

Land cover classification using LiDAR intensity data and neural network

  • Minh, Nguyen Quang;Hien, La Phu
    • 한국측량학회지
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    • 제29권4호
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    • pp.429-438
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    • 2011
  • LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.