• 제목/요약/키워드: Landsat and Spot images

검색결과 25건 처리시간 0.026초

Monitoring urban growth in Metro Manila using multitemporal satellite images

  • Vinluan, Randy John N.;Quiblat, Carla;Batadlan, Beata;Asilo, Sonia;Sontillanosa, Rosalyn;Pereira, Rosalyn;Macapinlac, Oliver;Menguito, Mon Pierre
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.378-380
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    • 2003
  • One of the most common forms of land use change is urbanization. Fortunately, the temporal revisit capacity of remote sensing satellites and their multispectral imaging capability make it possible to monitor this process. Using two Landsat images taken in 1972 and 1989, and one SPOT image taken in 2000, urban growth in Metro Manila is monitored. The extent of urbanization in Metro Manila increased from about 39 percent in 1972 to about 74 percent in 2000, although a slowing of growth was observed in the last decade due to decreasing areas for development. Most cities and municipalities in Metro Manila exhibited urban growth rates higher than the metropolitan average. The drivers and environmental consequences of urban growth were determined as well as the relationship of the extent of urbanization with some socio-economic and environmental variables.

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다중센서와 GIS 자료를 이용한 접근불능지역의 토지피복 분류 (Land cover classification of a non-accessible area using multi-sensor images and GIS data)

  • 김용민;박완용;어양담;김용일
    • 한국측량학회지
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    • 제28권5호
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    • pp.493-504
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    • 2010
  • This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

Introduction of Integrated Management of Satellite Imagery Information

  • Chae, Gee-Ju;Yoon, Geun-Won;Hwang, Tae-Hyun;Park, Jong-Hyun
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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    • pp.197-201
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    • 2002
  • The high prices of satellite images prevent researchers from studying remote sensing and most non-professional people doesn't have the simple and easy solutions for the manipulation of satellite images. "Integrated Management of Satellite Imagery Information" project which will be promoted by ETRI (Electronics and Telecommunications Research Institute) will provide the solutions for the above mentioned problems. We will introduce the archiving center in this study. This includes the data construction, storage, management and distribution. We first review the background for this archiving center and introduce the interior and foreign institutes which archive and distribute satellite images. We review our H/W system and S/W system briefly. Finally, the further service of our project will be suggested. Since we will distribute the satellite images (Landsat, SPOT, JERS, Corona, Kompast-1) and will receive Landsat7 ETM+ in 2003 you, this will help the professional work dealing with the satellite image and attract the non-professional people for simple and easy manipulation solutions of satellite image.

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위성영상 종류에 따른 분리도 특성 (Class Separability according to the different Type of Satellite Images)

  • 손경숙;최현;김시년;강인준
    • 한국측량학회:학술대회논문집
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    • 한국측량학회 2004년도 춘계학술발표회논문집
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    • pp.245-250
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    • 2004
  • The classification of the satellite images is basic part in Remote sensing. In classification of the satellite images, class separability feature is very effective accuracy of the images classified. For improving classification accuracy, It is necessary to study classification methode than analysis of class separability feature deciding classification probability. In this study, IKONOS, SPOT 5, Landsat TM, were resampled to sizes 1m grid. Above images were calculated the class separability prior to the step for classification of pixels. The results of the study were valued necessary process in geometric information building. This study help to improve accuracy of classification as feature of class separability in the class through optimizing previous classification steps.

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Multi- Resolution MSS Image Fusion

  • Ghassemian, Hassan;Amidian, Asghar
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.648-650
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    • 2003
  • Efficient multi-resolution image fusion aims to take advantage of the high spectral resolution of Landsat TM images and high spatial resolution of SPOT panchromatic images simultaneously. This paper presents a multi-resolution data fusion scheme, based on multirate image representation. Motivated by analytical results obtained from high-resolution multispectral image data analysis: the energy packing the spectral features are distributed in the lower frequency bands, and the spatial features, edges, are distributed in the higher frequency bands. This allows to spatially enhancing the multispectral images, by adding the high-resolution spatial features to them, by a multirate filtering procedure. The proposed method is compared with some conventional methods. Results show it preserves more spectral features with less spatial distortion.

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시계열 MODIS 영상을 이용한 논 분류와 지형학적 인자에 따른 불확실성 분석 (An Uncertainty Analysis of Topographical Factors in Paddy Field Classification Using a Time-series MODIS)

  • 윤성한;최진용;유승환;장민원
    • 한국농공학회논문집
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    • 제49권5호
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    • pp.67-77
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    • 2007
  • The images of MODerate resolution Imaging Spectroradiometer (MODIS) that provide wider swath and shorter revisit frequency than Land Satellite (Landsat) and Satellite Pour I' Observation de la Terre (SPOT) has been used fer land cover classification with better spatial resolution than National Oceanic and Atmosphere Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR)'s images. Due to the advantages of MODIS, several researches have conducted, however the results for the land cover classification using MODIS images have less accuracy of classification in small areas because of low spatial resolution. In this study, uncertainty of paddy fields classification using MODIS images was conducted in the region of Gyeonggi-do and the relation between this uncertainty of estimating paddy fields and topographical factors was also explained. The accuracy of classified paddy fields was compared with the land cover map of Environmental Geographic Information System (EGIS) in 2001 classified using Landsat images. Uncertainty of paddy fields classification was analyzed about the elevation and slope from the 30m resolution Digital Elevation Model (DEM) provided in EGIS. As a result of paddy classification, user's accuracy was about 41.5% and producer's accuracy was 57.6%. About 59% extracted paddy fields represented over 50 uncertainty in one hundred scale and about 18% extracted paddy fields showed 100 uncertainty. It is considered that several land covers mixed in a MODIS pixel influenced on extracted results and most classified paddy fields were distributed through elevation I, II and slope A region.

Extraction of Non-Point Pollution Using Satellite Imagery Data

  • Lee, Sang-Ik;Lee, Chong-Soo;Choi, Yun-Soo;Koh, June-Hwan
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.96-99
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    • 2003
  • Land cover map is a typical GIS database which shows the Earth's physical surface differentiated by standardized homogeneous land cover types. Satellite images acquired by Landsat TM were primarily used to produce a land cover map of 7 land cover classes; however, it now becomes to produce a more accurate land cover classification dataset of 23 classes thanks to higher resolution satellite images, such as SPOT-5 and IKONOS. The use of the newly produced high resolution land cover map of 23 classes for such activities to estimate non-point sources of pollution like water pollution modeling and atmospheric dispersion modeling is expected to result a higher level of accuracy and validity in various environmental monitoring results. The estimation of pollution from non-point sources using GIS-based modeling with land cover dataset shows fairly accurate and consistent results.

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두만강 하류 사구의 분포와 변화에 관한 연구 (A Study on the Distribution and Changes of Sand Dune at the Lower Reach of Duman River, North Korea)

  • 이민부;김남신;이광률;한욱
    • 대한지리학회지
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    • 제41권3호
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    • pp.331-345
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    • 2006
  • 본 연구는 두만강 하류 지역에 대규모로 발달한 사구 지형의 분포 및 지표 환경, 퇴적물의 특성, 기원 및 형성과정을 밝히고, 두만강 하류 일대의 하천 및 해안 환경변화를 고찰하고자 한다. 이를 위해, Landsat, Spot 영상을 이용하여 지표피복을 분석하고, 2회의 현지 야외조사를 실시하였으며, 입도분석 및 현미경 관찰을 통해 사구 퇴적물 시료를 분석하였다. 위성영상에서 파악된 사질퇴적지형 요소들은 삼각주, 사취, 이동사구, 정착사구, 사주, 사주피복 수변식생으로 구분되었다. 사구 퇴적물에 대한 입도 분석 결과, 조사 지역 중 가장 상류 쪽에 해당하는 DM3과 DM4에서 하성보다는 해성 모래와의 상관성이 높게 나타났다. 이는 현재 사구를 이루는 모래의 입도 특성이 두만강 하류 지역의 현재 자연환경을 반영하고 있지 않음을 의미하는 것이다. 현미경 분석 결과, 모든 시료에서 풍화에 가장 강한 석영의 비율이 $65{\sim}83%$로 가장 높았다. 그러나 $30{\sim}40%$를 차지하는 광물 입자의 표면은 화학적 풍화를 받아 황색의 물질로 표면이 코팅되어 있으며, 물리 화학적 풍화에 의한 바늘 및 그물 모양의 거친 표면 형태와 에칭 피트가 나타난다.

유전자 알고리즘을 이용한 트레이닝 최적화 기법 연구 - 정규분포를 고려한 통계적 영상분류의 경우 - (A Study on the Training Optimization Using Genetic Algorithm -In case of Statistical Classification considering Normal Distribution-)

  • 어양담;조봉환;이용웅;김용일
    • 대한원격탐사학회지
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    • 제15권3호
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    • pp.195-208
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    • 1999
  • 위성영상 분류작업에서 분류클래스에 대한 샘플화소의 대표성은 분류 정확도에 많은 영향을 미친다. 따라서, 통계적 영상분류방법에서는 분류 기법 자체보다 분류 확률을 결정하는 트레이닝 단계, 즉 샘플화소의 최적화가 필요하다. 본 연구에서는 SPOT XS, LANDSAT TM을 이용한 위성영상 화소분류작업에서 분류 이전단계, 즉 샘플화소의 정규성을 계산하여, 정규성에 악영향을 미치는 화소를 객관적 기준으로 조정하였다. 정규화과정을 위한 유전자 알고리즘 적용의 생존확률 평가함수로 다변량 Q-Q plot의 상관계수와 트레이닝의 분산값을 고려하였으며, 5% 유의수준을 적용하였다. 연구결과, 실험대상지역의 경우, 유전자 알고리즘을 이용한 트레이닝 정규화 결과가 대부분의 클래스에 대하여 그 평균과 분산을 모집단에 근사시키고 있다는 것을 입증하였고, 해당 클래스의 모집단 분포를 예측할 수 있는 가능성을 제시하였다.

PROBABILISTIC LANDSLIDE SUSCEPTIBILITY AND FACTOR EFFECT ANALYSIS

  • LEE SARO;AB TALIB JASMI
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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    • pp.306-309
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    • 2004
  • The susceptibility of landslides and the effect of landslide-related factors at Penang in Malaysia using the Geographic Information System (GIS) and remote sensing data have been evaluated. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from Landsat TM (Thermatic Mapper) satellite images; and the vegetation index value from SPOT HRV (High Resolution Visible) satellite images. Landslide hazardous areas were analysed and mapped using the landslide-occurrence factors employing the probability-frequency ratio method. To assess the effect of these factors, each factor was excluded from the analysis, and its effect verified using the landslide location data. As a result, land 'cover had relatively positive effects, and lithology had relatively negative effects on the landslide susceptibility maps in the study area. In addition, the landslide susceptibility maps using the all factors showed the relatively good results.

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