• Spatial Information Research
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• 제2권2호
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• pp.135-145
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• 1994

토지이용실태에 관한 자료는 국토계획이나 지역계획을 수립하는데 있어서 필수적인 기초자료의 하나이다. 그러나 현재로서는 토지이용실태를 그대로 반영하고 있는 정확한 자룔르 구득하는 일이 그렇게 쉬운 일만은 아니다. 이러한 물리적 토지이용실태에 관한 자료들은 지리정보시스템기법과 원격탐사자료의 영상처리기법등을 적절히 잘 활용함으로써, 적은 비용으로도 신속하게 관련 정보를 추출할 수 있다. 이러한 동기에서 이 연구는 인공위서에서 감지한 수도권의 원격탐사자료(1979년 MSS자료와 1991년 TM자료)를 이용하여 첫째 착도권의 토지이용실태를 분석하고 둘째 지난 12년간 착도권내 도시지형의 확산모습과 토지용이변화과정을 그림과 통계로 정리함으로써 수도권 정책을 평가하는데 필요한 기초자료를 생산하며, 셋째 향후 국토계획이나 지역계획 수립시 인공위성 원격탐사자료를 적극 활용할 수 있는 연구토양과 분위기를 조성하는데 연구의 목적을두고 있다.

• 대한원격탐사학회지
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• 제21권3호
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• pp.189-211
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• 2005

This paper makes an effort to compare the recently evolved soft classification method based on Linear Spectral Mixture Modeling (LSMM) with the traditional hard classification methods based on Iterative Self-Organizing Data Analysis (ISODATA) and Maximum Likelihood Classification (MLC) algorithms in order to achieve appropriate results for mapping, monitoring and preserving valuable coastal wetland ecosystems of southern India using Indian Remote Sensing Satellite (IRS) 1C/1D LISS-III and Landsat-5 Thematic Mapper image data. ISODATA and MLC methods were attempted on these satellite image data to produce maps of 5, 10, 15 and 20 wetland classes for each of three contrast coastal wetland sites, Pitchavaram, Vedaranniyam and Rameswaram. The accuracy of the derived classes was assessed with the simplest descriptive statistic technique called overall accuracy and a discrete multivariate technique called KAPPA accuracy. ISODATA classification resulted in maps with poor accuracy compared to MLC classification that produced maps with improved accuracy. However, there was a systematic decrease in overall accuracy and KAPPA accuracy, when more number of classes was derived from IRS-1C/1D and Landsat-5 TM imagery by ISODATA and MLC. There were two principal factors for the decreased classification accuracy, namely spectral overlapping/confusion and inadequate spatial resolution of the sensors. Compared to the former, the limited instantaneous field of view (IFOV) of these sensors caused occurrence of number of mixture pixels (mixels) in the image and its effect on the classification process was a major problem to deriving accurate wetland cover types, in spite of the increasing spatial resolution of new generation Earth Observation Sensors (EOS). In order to improve the classification accuracy, a soft classification method based on Linear Spectral Mixture Modeling (LSMM) was described to calculate the spectral mixture and classify IRS-1C/1D LISS-III and Landsat-5 TM Imagery. This method considered number of reflectance end-members that form the scene spectra, followed by the determination of their nature and finally the decomposition of the spectra into their endmembers. To evaluate the LSMM areal estimates, resulted fractional end-members were compared with normalized difference vegetation index (NDVI), ground truth data, as well as those estimates derived from the traditional hard classifier (MLC). The findings revealed that NDVI values and vegetation fractions were positively correlated ($r^2$= 0.96, 0.95 and 0.92 for Rameswaram, Vedaranniyam and Pitchavaram respectively) and NDVI and soil fraction values were negatively correlated ($r^2$ =0.53, 0.39 and 0.13), indicating the reliability of the sub-pixel classification. Comparing with ground truth data, the precision of LSMM for deriving moisture fraction was 92% and 96% for soil fraction. The LSMM in general would seem well suited to locating small wetland habitats which occurred as sub-pixel inclusions, and to representing continuous gradations between different habitat types.

• 한국지리정보학회지
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• 제2권3호
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• pp.1-15
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• 1999

본 연구는 낙동강 하구의 습지를 대상으로 습지생태계의 종합적인 정보 추출을 위해 지리정보시스템 및 원격탐사 기법을 이용하여 습지 데이터베이스를 구축하였다. 습지 데이터베이스 구축을 위해 낙동강 하구를 대상으로 1998년 3월부터 9월까지 현지조사를 실시하였다. 또한, Landsat TM 영상자료(1997. 5. 17)를 1:50,000 지형도로 기하보정한 후, 감독분류 및 무감독분류를 실시하여 현지 식생조사 자료와 비교, 분석해 습지분류도를 제작하였으며, 습지식생의 활력을 측정하기 위해 중합차식생지수(NDVI:Normalized Difference Vegetation Index)에 의한 식생활력도 지도와 습지의 생산력을 분석하기 위해 낙동강 하구 습지의 우점식물종인 갈대군락의 생산성에 근거한 습지생산력 지도 및 습지식생의 변화를 사전에 예측한 식생천이 예상도를 작성하였다. 본 연구에서 구축한 낙동강 하구 습지생태계 데이터베이스는 습지생태계 보존 및 관리를 위한 기초자료로써 활용될 수 있으며, 식물 뿐 만 아니라 습지생태계 전반에 대하여 상세한 정보구축이 이루어지면 습지보존과 관리가 효과적으로 실현될 것이다. 또한, 이러한 기법들은 우리나라 전역의 습지목록 작성에 활용될 수 있을 것이다.

• 한국관개배수논문집
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• 제7권2호
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• pp.34-48
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• 2000

The tidal land reclamation schemes and projects located along the western coast of North Korea were investigated by the remote sensing using sattelite image data such as Landsat TM and Jers-1 data. North Korea reported their ambitious territory expansion

• 한국농공학회:학술대회논문집
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• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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• pp.544-549
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• 1999

The objective of this study is to identify the applicability of land cover image classified by remotely sensed data ; Landsat TM merged by SPOT for hydrological applications such as SCS runoff estimation . By comparing the calssified land cover image with the statistical data, it was proved that hey are agreed well with little errors. As a simple application , SCS runoff estimation was tested by varying rainfall intensity and AMC with Soilmap classfied by hydrologica soil map.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.2184-2189
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• 2009

China is one of the countries in which flood occurs most frequently in the world and with the current economic growth; flood disaster causes more and more economic losses. Chinese government pays more attention to flood monitoring and assessment by space technology. Since1983, NOAA(AVHRR), Landsat-TM, LANDSAT-ETM+, JERS-1, SPOT, ERS-2, Radarsat-1, CBERS-1, Envisat have been used for flood monitoring and assessment. Due to the bad weather conditions during flood, microwave remote sensing is the major tools for flood monitoring. Envisat is one of the best satellite with powerful SAR. Its application for flood monitoring has been studied and its near real time(NRT) application can be realized on the basis of real-time delivery of image. During the 2005, 2006 and 2007 flood seasons, over the 31 NRT flood monitoring based on Envisat, had been carried out in Yangtze, Songua, Huaihe, pearl river basin. The result shows that Envisat SAR is very useful data source for flood disaster monitoring and assessment.

• 자원환경지질
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• 제32권1호
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• pp.19-31
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• 1999

In this study, we have estimated lineaments in the Euiseong area, Kyungbuk Province, from Landsat TM by applying the algorithm developed by Kim and Won et al. which can effectively reduce the look direction bias associated with the Sun's azimuth angle. Fratures over the study area were also mapped in the field at 57 selected sites to compare them with the results from the satellite image. The trends of lineaments estimated from the Landsat TM images are characterized as $N50^{\circ}$~70W, NS~$N10^{\circ}$W, and $N10^{\circ}$~$60^{\circ}$E trends. The spatial distribution of lineaments is also studied using a circular grid, and the results show that the area can be divided into two domains : domain A in which NS~$N20^{\circ}$E direction is dominant, and domain B in which west-north-west direction is prominent. The trends of lineaments can also be classified into seven groups. Among them, only C, D and G trends are found to be dominant based upon Donnelly's nearest neighbor analysis and correlations of lineament desities. In the color composite image produced by overlaying the lineament density map of these C-, D-, and G-trends, G-trend is shown to be developed in the whole study area while the eastern part of the area is dominated by D-trend. C-trend develops extensively over the whole are except the southeastern part. The orientation of fractures measured at 35 points in the field shows major trends of NS~$N30^{\circ}$E, $N50^{\circ}$~$80^{\circ}$W, and N80$^{\circ}$E~EW, which agree relatively well with the lineaments estimated form the satellite image. The rose diagram analysis fo field data shows that WNW-ESE trending discontinuities are developed in the whole area while discontinuities of NS~$N20^{\circ}$E are develped only in the estern part, which also coincide with the result from the satellite image. The combined results of lineaments from the satellite image and fracture orientation of field data at 22 points including 18 minor faults in Sindong Group imply that the WNW-ESE trend is so prominent that Gumchun and Gaum faults are possibly extended up to the lower Sindong Group in the study area.

• 한국지리정보학회지
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• 제18권2호
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• pp.135-148
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• 2015

본 연구는 LiDAR DEM(Digital Elevation Model)과 다중시기에 촬영된 Landsat 영상을 이용하여 4대강 정비사업이 시행되기 이전 및 이후에 낙동강 유역 내 발생한 토지피복 변화를 탐지 및 분석하기 위하여 수행되었다. 우선 LiDAR DEM으로부터 추출된 제방경계선을 이용하여 하천유역 폴리곤을 생성하고, 하천유역 폴리곤을 이용하여 다중시기에 촬영된 Landsat-5 TM(Thematic Mapper) 영상과 Landsat-8 OLI(Operational Land Imager) 영상으로부터 4개의 하천유역 영상을 각각 추출하였다. 그리고 영상분류방법을 적용하여 각 하천유역 영상으로부터 하천유역의 주요 토지피복인 하천, 나지, 초지를 각각 분류하였고, 전체 면적에서 각 토지피복이 차지하는 비율을 계산하였다. 다중시기에 촬영된 하천유역 영상으로부터 분류된 각 토지피복의 변화량을 분석한 결과, 4대강 정비사업이 시행되기 이전과 4대강 정비사업이 완공된 이후에는 계절의 변화에 의해 나지와 초지의 면적은 큰 폭으로 변화하였으나, 하천의 면적은 큰 변화가 없었다. 반면에 4대강 정비사업 전후로, 낙동강 유역 내 저수량의 증가로 인해 하천의 면적이 큰 폭으로 증가하였다. 본 논문은 LiDAR DEM과 4대강 정비사업 이전과 이후에 촬영된 위성영상들을 이용하여 4대강 정비사업으로 인해 발생한 하천 유역 내 토지피복 변화를 탐지할 수 있는 효과적인 방법을 제시하였다는데 의의가 있다.

• 대한원격탐사학회지
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• 제20권3호
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• pp.197-205
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• 2004

Wetlands are lands with a mixture of water, herbaceous or woody vegetation and wet soil. And linear spectral mixture analysis (LSMA) is one of the most often used methods in handling the spectral mixture problem. This study aims to test LSMA is an enhanced routine for classification of wetland land-covers in Paldang reservoir and vicinity (paldang Reservoir) using Landsat TM and ETM+ imagery. In the LSMA process, reference endmembers were driven from scatter-plots of Landsat bands 3, 4 and 5, and a series of endmember models were developed based on green vegetation (GV), soil and water endmembers which are the main indicators of wetlands. To consider phenological characteristics of Paldang Reservoir, a soil endmember was subdivided into bright and dark soil endmembers in spring and a green vegetation (GV) endmember was subdivided into GV tree and GV herbaceous endmembers in fall. We found that LSMA fractions improved the classification accuracy of the wetland land-cover. Four endmember models provided better GV and soil discrimination and the root mean squared (RMS) errors were 0.011 and 0.0039, in spring and fall respectively. Phenologically, a fall image is more appropriate to classify wetland land-cover than spring's. The classification result using 4 endmember fractions of a fall image reached 85.2 and 74.2 percent of the producer's and user's accuracy respectively. This study shows that this routine will be an useful tool for identifying and monitoring the status of wetlands in Paldang Reservoir.

• 대한토목학회논문집
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• 제9권4호
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• pp.113-124
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• 1989

인공위성 데이타 정보의 용용분야는 여러가지가 있으나, 본 연구에서는 LANDSAT MSS데이타와 TM데이타를 처리 분석하여 서울시 토지이용정보를 경년변화에 따라 추출하고자 하였다. 사용 데이터는 MSS(72, 79, 81, 83년), TM(85년)이며 입수된 데이타를 전처리를 통해 기하보정, 디지타이징(행정구역에 따라) 등을 하고, 유효 band 선정 및 filtering을 통하여 정확도를 높인 후 MLC(Maximum Likelihood Classifier)로 토지이용분류를 실시하였다. 토지이용분류시 training field 선정 자료로는 현지조사자료, 지형도, 항공사진을 참조하였고, 분류결과의 정확도는 각각 그 당시의 통계자료를 토대로 하여 비교해 보았다. 분석결과, 서울시의 도시지역은 72년 (25.3 %), 81년 (43.0 %), 85년 (51.9 %)로 증가되었고, 이에 대해 삼림은 72년(39.0 %)에서 85년(28.4 %)로 점차 감소되고 있었다. 이상과 같이 토지이용 경년변화를 추출함으로써 도시의 토지 이용상황 monitoring에는 반복 주기를 가지는 인공위성 데이터의 활용이 경제적이며 효과적임을 알 수 있었다.