• 제목/요약/키워드: RS Imagery

검색결과 37건 처리시간 0.026초

Extraction of Some Transportation Reference Planning Indices using High-Resolution Remotely Sensed Imagery

  • Lee, Ki-Won
    • 대한원격탐사학회지
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    • 제18권5호
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    • pp.263-271
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    • 2002
  • Recently, spatial information technologies using remotely sensed imagery and functionality of GIS (Geographic Information Systems) have been widely utilized to various types of transportation-related applications. In this study, extraction programs of some practical indices, to be effectively used in transportation reference planning problem, were designed and implemented as prototyped extensions in GIS development environment: traffic flow estimation (TFL/TFB), urban rural index (URI), and accessibility index (AI). In TFL/TFB, user can obtain quantitative results on traffic flow estimation at link/block using high-resolution satellite imagery. Whereas, URI extension provides urban-rural characteristics related to road system, being considered one of important factors in transportation planning. Lastly, AI extension helps to obtain accessibility index between nodes of road segments and surrounding district areas touched or intersected with the road network system, and it also provides useful information for transportation planning problems. This approach is regarded as one of RS-T (Remote Sensing in Transportation), and it is expected to expand as new application of remotely sensed imagery.

STUDY ON THE DEVELOPMENT OF $a_{dom}$ ESTIMATION ALGORITHM BY EMPIRICAL METHOD FOR GOCI OCEAN COLOR SENSOR

  • Moon, Jeong-Eon;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Choi, Joong-Ki
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.49-52
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    • 2007
  • This study uses empirical method to estimate absorption coefficient of colored dissolved organic matter $(a_{dom})$ from GOCI satellite data with the relationship between band ratio of remote sensing reflectance $(R_{rs})$ and $a_{dom}$. For development of $a_{dom}$ estimation algorithm, the used data is in-situ data about ocean optical properties in the around seawater area of the Korean Peninsula during 1998 - 2005. The relationship of $R_{rs}$(412)/$R_{rs}$(555), $R_{rs}$(443)/$R_{rs}$(555), $R_{rs}$(490)/$R_{rs}$(555), $R_{rs}$(510)/$R_{rs}$(555) and $a_{dom}$(412) showed $R^2$ values of 0.707, 0.707, 0.597 and 0.552, respectively. The spectrum of $a_{dom}({\lambda})$ is shape of exponential function $a_{dom}({\lambda})$ value decreases with increasing wavelength. For estimation of $a_{dom}$ from satellite data, we developed an algorithm from the relationship of $a_{dom}$(412) and $R_{rs}$(412)/$R_{rs}$(555). This algorithm was employed on SeaWiFS imagery to estimate $R_{rs}$(412) in the South Sea, East Sea, Yellow Sea and northern East China Sea areas. Also, SeaDAS-derived $a_{dg}$(412) from same SeaWiFS imagery, These $a_{dg}$(412) was then compared with in-situ and empirical-algorithm-derived $a_{dom}$(412), but these values were different. We think two points that such different values are caused by discrepancy related to failure of standard atmospheric correction scheme, the other are caused by error related to definition of $a_{dom}$(412) and $a_{dg}$(412).

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위성영상정보의 중력모델기반 접근성지수 추출연계 및 적용 (Extraction of Gravity-typed Accessibility Index using Remotely Sensed Imagery and Its Application)

  • 이기원;오세경;이봉규
    • 한국지리정보학회지
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    • 제6권3호
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    • pp.61-72
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    • 2003
  • 최근 다양한 센서정보의 민간 활용이 가능해지면서 고해상도 위성영상정보를 현실문제에 적용하려는 수요가 증가하고 있다. 1990년대 말부터 미국 등에서도 위성영상정보를 교통 문제에 실제적으로 적용하고자 하는 연구가 본격적으로 추진되고 있으며, 이러한 연구는 RS-T(remote sensing in transportation)라는 분야로 특성화되는 추세에 있다. 또한 이러한 연구는 이미 산업적 활용단계에 있는 GIS-T(GIS for transportation)와 연계되어 위성영상정보의 활용을 증대시키는데 기여하고 있다. 본 연구에서는 이러한 추세를 반영하여 RS-T를 개관한 뒤, 고해상도 위성영상정보를 이용한 도시교통 환경분석이 가능하도록 교통중력 모델에 기반하여 교통지리학에서 제안되어 온 몇 가지의 정량적 접근성지수 추출 알고리즘을 위성 영상정보를 보조자료로 하여 적용할 수 있도록 ArcView-GIS 환경의 확장 프로그램으로 시험적으로 구현하였으며, 시험 구현 모델 중에서 Ingram 모델과 G&G 모델을 이용하여 접근성지수 추출에 대한 적용하는 사례를 제시하고자 하였다. 적용 결과로서 도출된 정량적 지수정보는 분석 대상지역에 대한 교통접근성의 특성을 파악하는 데 활용이 가능하며, 시계열 위성자료를 적용하는 경우에는 주기적 도시교통 통계정보로 이용되어 광역적 교통계획을 위한 자료로 이용이 될 수 있을 것으로 생각된다.

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Design of a Reorganization and Non-Uniformity Correction Module for CCD Pixels in MSC(Multispectral Camera)

  • Kong, Jon-Pil;Yong, Sang-Soon;Heo, Haeng-Pal;Kim, Young-Sun;Paik, Hong-Yul
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.177.1-177
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    • 2001
  • This paper describes the design of a NUC(Non-uniformity Correction) module in MSC(Multispectral Camera) which will be a payload on KOMPSAT. This module is required inside a system with data compression module like MSC to minimize the loss of imagery due to non-uniform characteristics between CCD pixels when the imagery is received and processed on a ground station. It comprises Hotlink input/output for imagery data, RS-422 interface with main controller in MSC, a number of SRAMS for storing imagery data and parameters, FPGA controllers which control the entire NUC module under the control of main controller, etc. It inputs 8-channel imagery pixel data which consist of 2-channel MS(Multispectral) band and ...

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Application of RS and GIS in Extraction of Building Damage Caused by Earthquake

  • Wang, X.Q.;Ding, X.;Dou, A.X.
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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    • pp.1206-1208
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    • 2003
  • The extraction of earthquake damage from remote sensed imagery requires high spatial resolution and temporal effectiveness of acquisition of imagery. The analog photographs and visual interpretation were taken traditionally. Now it is possible to acquire damage information from many commercial high resolution RS satellites. The key techniques are processing velocity and precision. The authors developed the automatic / semiautomatic image process techniques including feature enhancement, and classification, designed the emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES). The paper introduced the functions of RSEDLES as well as its application to the earthquakes occurred recently.

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Predicting ground-based damage states from windstorms using remote-sensing imagery

  • Brown, Tanya M.;Liang, Daan;Womble, J. Arn
    • Wind and Structures
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    • 제15권5호
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    • pp.369-383
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    • 2012
  • Researchers have recently begun using high spatial resolution remote-sensing data, which are automatically captured and georeferenced, to assess damage following natural and man-made disasters, in addition to, or instead of employing the older methods of walking house-to-house for surveys, or photographing individual buildings from an airplane. This research establishes quantitative relationships between the damage states observed at ground-level, and those observed from space using high spatial resolution remote-sensing data, for windstorms, for individual site-built one- or two-family residences (FR12). "Degrees of Damage" (DOD) from the Enhanced Fujita (EF) Scale were determined for ground-based damage states; damage states were also assigned for remote-sensing imagery, using a modified version of Womble's Remote-Sensing (RS) Damage Scale. The preliminary developed model can be used to predict the ground-level damage state using remote-sensing imagery, which could significantly lessen the time and expense required to assess the damage following a windstorm.

EFFECTS OF RANDOMIZING PATTERNS AND TRAINING UNEQUALLY REPRESENTED CLASSES FOR ARTIFICIAL NEURAL NETWORKS

  • Kim, Young-Sup;Coleman Tommy L.
    • 한국공간정보시스템학회:학술대회논문집
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    • 한국공간정보시스템학회 2002년도 춘계학술대회 논문집
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    • pp.45-52
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    • 2002
  • Artificial neural networks (ANN) have been successfully used for classifying remotely sensed imagery. However, ANN still is not the preferable choice for classification over the conventional classification methodology such as the maximum likelihood classifier commonly used in the industry production environment. This can be attributed to the ANN characteristic built-in stochastic process that creates difficulties in dealing with unequally represented training classes, and its training performance speed. In this paper we examined some practical aspects of training classes when using a back propagation neural network model for remotely sensed imagery. During the classification process of remotely sensed imagery, representative training patterns for each class are collected by polygons or by using a region-growing methodology over the imagery. The number of collected training patterns for each class may vary from several pixels to thousands. This unequally populated training data may cause the significant problems some neural network empirical models such as back-propagation have experienced. We investigate the effects of training over- or under- represented training patterns in classes and propose the pattern repopulation algorithm, and an adaptive alpha adjustment (AAA) algorithm to handle unequally represented classes. We also show the performance improvement when input patterns are presented in random fashion during the back-propagation training.

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RS/GIS를 이용한 토지이용변화에 의한 녹지의 이산화탄소 (CO2) 흡착량 분포 추정 (Estimation of Carbon Absorption Distribution by Land Use Changes using RS/GIS Method in Green Land)

  • 나상일;박종화;박진기
    • 한국농공학회논문집
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    • 제52권3호
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    • pp.39-45
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    • 2010
  • Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.

GIS와 RS에 기반한 지방자치단체 지리정보콘텐츠의 개발에 관한 연구 (A Study on Development of Geographic Information Contents in Local Government on the basis of GIS and RS)

  • 김항집;서동조
    • 한국콘텐츠학회:학술대회논문집
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    • 한국콘텐츠학회 2003년도 춘계종합학술대회논문집
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    • pp.251-254
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    • 2003
  • 이 연구는 지방정부의 홈페이지를 중심으로 지역주민과 관광객에게 제공할 수 있는 다양한 지역정보 콘텐츠를 개발하기 위한 것이다. 특히, 공간정보기술인 GIS(Geographic Information Systems)와 RS(Remote Sensing)기법을 활용하여 지역정보의 콘텐츠를 개발함으로써, 지방정부 홈페이지의 콘텐츠를 다양타함과 동시에 공간정보의 응용분야를 확대하고자 하였다. 이를 위하여 연구대상지역인 전라남도 무안군을 대상으로 인터넷 관련 콘텐츠, 지리정보 관련 콘텐츠 및 인공위성영상 관리프로그램의 3가지 지역정보콘텐츠를 개발하여 제시하였으며, 이를 통하여 지역정보 및 관광정보 둥 공간정보의 현실성과 가독성을 높이는데 기여하였다.

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IKONOS 영상을 이용한 고해상도 토지피복도 작성 (High-resolution Land Cover Mapping of Rural Area Using IKONOS Imagery)

  • 홍성민;정인균;김성준
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2004년도 학술발표회
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    • pp.1271-1275
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    • 2004
  • The purpose of this study is to present a standardized scheme for providing agriculture-related information at various spatial resolutions of satellite images including Landsat +ETM, KOMPSAT-1 EOC, ASTER VNIR, and IKONOS panchromatic and multi-spectral images. The satellite images were interpreted especially for identifying agricultural areas, crop types, agricultural facilities and structures. The results were compared with the land cover/land use classification system suggested by Ministry of Construction & Transportation based on NGIS (National Geographic Information System) and Ministry of Environment based on satellite remote sensing data. As a result, high-resolution agricultural land cover map from IKONOS imageries was made out. The results by IKONOS image will be provided to KOMPSAT-2 project for agricultural application.

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