• 한국산림과학회지
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• 제112권3호
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• pp.267-279
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• 2023

본 연구는 IPCC에서 제시하고 있는 Approach 3 수준의 토지이용 및 토지피복 면적 추정을 위해 고해상도 항공사진에 딥러닝 알고리즘과 Sampling method를 적용하였으며, 표본강도에 따라 토지피복 면적을 산출하고 최적의 표본강도를 도출하는 것을 목적으로 하였다. 원격탐사자료로는 51 cm급의 고해상도 칼라 항공 이미지를 사용하였으며, 딥러닝 알고리즘은 전이 학습이 적용된 VGG16 아키텍처를 활용하였다. 딥러닝 기반 토지피복 분류모델의 학습과 검증은 육안판독을 통해 선별된 데이터를 이용하였다. 최적의 표본강도를 도출하기 위한 평가는 7개의 표본강도(4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, 250 × 250 m)에 따른 토지이용 및 토지피복 면적을 추정하고 환경부에서 제시한 토지피복지도와 비교하였다. 본 연구 결과, 딥러닝 기반의 토지피복 분류 모델의 전체정확도와 카파계수는 각각 91.1% 와 88.8%였다. F-Score는 초지를 제외한 모든 범주가 90% 이상으로 구축되어 모델의 정확도가 우수하였다. 표본강도별 적합도 검정은 유의수준 0.1에서 4 × 4 km를 제외한 모든 표본강도에서 환경부에서 제시한 토지피복지도의 면적 비율과 유의한 차이를 보이지 않았다. 또한, 표본강도가 증가할수록 상대표준오차와 상대효율은 감소하였으며, 상대표준오차는 1 × 1 km 표본강도에서 모든 토지피복범주가 15% 이하로 감소하였다. 따라서, 지역 단위의 토지피복 면적 산정을 위해서는 표본강도를 1 × 1 km보다 상세하게 설정하는 것이 적합하다고 판단된다.

• 한국조경학회지
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• 제26권3호
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• pp.237-248
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• 1998

Landcover has been largely influenced by human activities, especially in recent days. The analysis of the change of land use by urbanized development is useful for determining development plan hereafter. This study aimed to the quantitative analysis about the urban sprawl within 12 years from 1985 to 1996, at Chonan, and for extracting the characteristics of change. For this purpose, this study performed land cover classifications using Landsat TM data . A hybrid classification method was used to classify satellite images into seven types of land cover. Road network digitied from 1:25,000 topographic map was rasterized and overlaid on the landcover map. A result of this study showed that area of forest and paddy decreased due to urban sprawl. Especially from 1993 to 1996, the change of land use progressed rapidly because of merging a city and a country in Chonan. The size of patch in forest had been smaller and irregular form. It is a general progress that size of patch in forest had been smaller and irregular form. It is a general progress that the forest have changed the paddy and bare land paddy and bare land have changed low-density urban or high-density urban. This explained how urbanized Chonan was and applied the suggeston of plan in landuse with the result of this study.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 춘계학술대회 논문집
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• pp.113-119
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• 2007

This article deals mainly with two objectives viz, 1) the potentiality of very high-resolution(VHR) multi-spectral and pan chromatic QuickBird satellite data in resources mapping over moderate resolution satellite data (IRS LISS III) and 2) the advantages of using object oriented classification method of eCognition software in land use and land cover analysis over the ISODATA classification method. These VHR data offers widely acceptable metric characteristics for cartographic updating and increase our ability to map land use in geometric detail and improve accuracy of local scale investigations. This study has been carried out in the Sukkalampatti mini-watershed, which is situated in the Eastern Ghats of Tamil Nadu, India. The eCognition object oriented classification method succeeded in most cases to achieve a high percentage of right land cover class assignment and it showed better results than the ISODATA pixel based one, as far as the discrimination of land cover classes and boundary depiction is concerned.

• 디지털콘텐츠학회 논문지
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• 제18권7호
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• pp.1367-1375
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• 2017

최근 토지피복도는 경관 모자이크의 공간적 구성, 기능 및 변화와 같은 공간 패턴을 분석하기 위해 그 활용도가 지속적으로 증가하고 있다. 본 논문에서는 토지피복도를 활용한 경관 모자이크 패턴 분석 시스템을 제안하기 위해서 영역기반 영상처리 기법으로 경관 모자이크의 요소인 패치를 추출하고, 추출된 패치의 경관분석 측정요소를 패치 레벨과 클래스 레벨에서 계산하였다. 계산된 측정요소로 공간관계를 표현할 수 있는 패치기반의 공간 패턴을 제안한다. 제안된 시스템은 시스템의 유효성을 확인하기 위하여 광주광역시의 범례별 토지이용 현황 및 패치의 공간패턴을 확인한다.

• 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.

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2004년도 GIS/RS 공동 춘계학술대회 논문집
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• pp.261-265
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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.

• 농촌계획
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• 제19권2호
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• pp.121-128
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• 2013

The greenhouse gas emission according to the energy consumption is the cause of global warming. With various climates, it is occurs the direct problems to ecosystem. The various studies are being to reduce the carbon dioxide, which accounts for more than 80% of the total greenhouse gas emissions. In this study, estimate the carbon usage using potential biomass extracted from forest type map according to land-use by satellite image, and estimate the amount of carbon dioxide, according to the energy consumption of urban area. The $CO_2$ adsorption is extracted by the amount of forest based on the direct absorption of tree, the other used investigated value. The $CO_2$ emission in Jecheon was 3,985,900 $TCO_2$ by energy consumption. At the land cover classification, the forest is analyzed as 624,085ha and the farmland is 148,700ha. The carbon dioxide absorption was estimated at 1,834,850 Tons from analyzed forest. In case of farmland, it was also estimated at 706,658 Tons.

• 한국환경복원기술학회지
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• 제21권3호
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• pp.13-26
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• 2018

This study estimated the carbon sequestration from urban green spaces in Ansan City using environmental spatial information. We examined study results of carbon sequestration from existing urban green spaces, using a land cover map (level 3). In particular, the carbon sequestration of trees by land use and the IPCC Global default value were linked with the land cover map level 3. Domestic research showed that carbon storage in urban green spaces in Ansan City was 17,927.2 tC, and the annual carbon sequestration was calculated as 2,680.5 tC/yr. On the other hand, applying the IPCC Global Default value resulted in annual carbon sequestration of 5,287.8 tC/yr, which was 2,607.3 tC/yr more that the domestic research value. This resulted from difference in detailed methodologies such as background data, sample size for on-site investigation, and measurement of tree species. The study presented a consistent assessment method to assess the sequestration of carbon from municipal urban green spaces. Furthermore, we provided basic data that could be useful in urban green space policies.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.378-381
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• 2008

The regulating and relaxing targets in the Land Use Regulation and Total Maximum Daily Loads are influenced by Land cover information. For the providing more accurate land information, this study attempted to generate an impervious surface map using KOMPSAT-2 image which a Korea manufactured high resolution satellite image. The classification progress of this study carried out by tasseled-cap spectral enhancement through each class extraction technique neither existing classification method. KOMPSAT-2 image of this study is enhanced by Soil Brightness Index(SBI), Green vegetation Index(GVI), None-Such wetness Index(NWI). Then ranges of extracted each index in enhanced image are determined. And then, Confidence Interval of classes was determined through the calculating Non-exceedance Probability. Spectral distributions of each class are changed according to changing of Control coefficient(${\alpha}$) at the calculated Non-exceedance Probability. Previously, Land cover classification map was generated based on established ranges of classes, and then, pervious and impervious surface was reclassified. Finally, impervious ratio of reclassified impervious surface map was calculated with blocks in the study area.

• 대한공간정보학회지
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• 제1권1호
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• pp.181-192
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• 1993

영상은 어떤 현상이나 대상물의 종류와 현상조건에 대한 정보를 포함하고 있는 화소값으로 구성되며, 화소값은 전처리 과정인 기하보정으로 변화된다. 이러한 화소값의 변화는 토지피복 분류 결과에 영향을 미친다. 본 논문에서는 기하보정으로 재구성된 영상을 이용하여 토지피복 분류를 함으로서 재배열의 영향을 알고자 한다. 연구대상 지역은 북한강 수계 중에서 가장 다양한 피복형태를 가지고 있는 춘천시를 중심으로 하는 춘천유역을 선정하였고, 전처리과정에서 재배열된 RESTEC 데이타가 이용되었다. 토지피복 분류는 최대우도법을 사용하여 LEVEL I 수준인 여섯개의 분류항목으로 분류되었다. 본 연구에서 두 가지 방법으로 재배열된 영상을 이용하여 토지피복 분류를 실시하였다. 각각의 분류항목을 지형도와 비교한 결과 Bilinear Interpolation법이 나지(BARE-LAND)를 제외한 다섯개의 분류항목에서 정확도가 좋았다. 결론적으로 기하보정의 영상 재배열은 어떤 분류항목에 중점을 두고 분류를 행하느냐에 따라서 재배열 방법을 선택해야 하며 논과 밭의 경우와 같은 분류항목간의 혼돈은 사계절 영상을 이용하면 더욱 더 정확하게 분류할 수 있을 것이다.