• Title/Summary/Keyword: 토지이용 및 피복 변화

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Hotspot Detection for Land Cover Changes Using Spatial Statistical Methods (공간통계기법을 이용한 토지피복변화의 핫스팟 탐지)

  • Lee, Jeong-Hun;Kim, Sang-Il;Han, Kyung-Soo;Lee, Yang-Won
    • Korean Journal of Remote Sensing
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    • v.27 no.5
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    • pp.601-611
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    • 2011
  • Land cover changes are occurring for a variety of reasons such as urbanization, infrastructure construction, desertification, drought, flood, and so on. Many researchers have studied the cause and effect of land cover changes, and also the methods for change detection. However, most of the detection methods are based on the dichotomy of "change" and "not change" according a threshold value. In this paper, we present a change detection method with the integration of probability, spatial autocorrelation, and hotspot detection. We used the AMOEBA (A Multidirectional Ecotope-Based Algorithm) and developed the AMOEBA-CH (core hotspot) because the original algorithm tends to produce too many clusters. Our method considers the probability of land cover changes and the spatial interactions between each pixel and its neighboring pixels using a local spatial autocorrelation measure. The core hotspots of land cover changes can be delineated by a contiguity-dominance model of our AMOEBA-CH method. We tested our algorithm in a simulation for land cover changes using NDVI (Normalized Difference Vegetation Index) data in South Korea between 2000 and 2008.

Multi-temporal NDVI Change Patterns and Global Land Cover Dynamics (다중시기 NDVI 변화 패턴과 토지 피복상태의 변화에 관한 연구)

  • Seong, Jeong-Chang
    • Journal of the Korean Association of Geographic Information Studies
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    • v.3 no.3
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    • pp.20-30
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    • 2000
  • Average annual NDVI values from the NOAA/NASA Pathfinder AVHRR Land Data Sets from 1982 to 1994 showed comprehensive systematic displacement patterns in Asia. Inter-annual growing season data, however, did not show such systematic patterns. The most likely cause for the abrupt displacements, which appear especially in 1982, 1989 and 1990, may be changes in satellite sensors, although global warming, El Ni$\tilde{n}$o-Southern Oscillation events, changes in processing algorithms, and changes in land-use patterns in various parts of Asia may also play some role. The results suggest that researchers must be extremely careful in their inter-annual global change research, since direct use of the raw data could cause unexpected results. Growing-season NDVI shows decreases throughout most of Southeast Asia and modest gains in northern China and some parts in India, which could be related to land-use and land-cover changes.

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Land-Cover Change Detection of Western DMZ and Vicinity using Spectral Mixture Analysis of Landsat Imagery (선형분광혼합화소분석을 이용한 서부지역 DMZ의 토지피복 변화 탐지)

  • Kim, Sang-Wook
    • Journal of the Korean Association of Geographic Information Studies
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    • v.9 no.1
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    • pp.158-167
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    • 2006
  • The object of this study is to detect of land-cover change in western DMZ and vicinity. This was performed as a basic study to construct a decision support system for the conservation or a sustainable development of the DMZ and Vicinity near future. DMZ is an is 4km wide and 250km long and it's one of the most highly fortified boundaries in the world and also a unique thin green line. Environmentalists want to declare the DMZ as a natural reserve and a biodiversity zone, but nowadays through the strengthening of the inter-Korean economic cooperation, some developers are trying to construct a new-town or an industrial complex inside of the DMZ. This study investigates the current environmental conditions, especially deforestation of the western DMZ adopting remote sensing and GIS techniques. The Land-covers were identified through the linear spectvral mixture analysis(LSMA) which was used to handle the spectral mixture problem of low spatial resolution imagery of Landsat TM and ETM+ imagery. To analyze quantitative and spatial change of vegetation-cover in western DMZ, GIS overlay method was used. In LSMA, to develop high-quality fraction images, three endmembers of green vegetation(GV), soil, water were driven from pure features in the imagery. Through 15 years, from 1987 to 2002, forest of western DMZ and vicinity was devastated and changed to urban, farmland or barren land. Northern part of western DMZ and vicinity was more deforested than that of southern part. ($52.37km^2$ of North Korean forest and $39.04km^2$ of South Korean were change to other land-covers.) In case of North Korean part, forest changed to barren land and farmland and in South Korean part, forest changed to farmland and urban area. Especially, In North Korean part of DMZ and vicinity, $56.15km^2$ of farmland changed to barren land through 15 years, which showed the failure of the 'Darakbat' (terrace filed) project which is one of food increase projects in North Korea.

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Land Cover Monitoring of the Korean Peninsula Using Multi-Temporal NOAA-AVHRR Data (NOAA-AVHRR 자료분석에 근거한 한반도 지표피복의 변화)

  • 구자민;홍석영;윤진일
    • Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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    • 2001.06a
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    • pp.147-150
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    • 2001
  • 최근 넓은 지역을 대상으로 토지이용 및 식생분포 등을 조사하기 위하여 인공위성 원격탐사기술이 활발히 사용되고 있다. 위성화상자료를 이용한 토지이용분석 사례는 다양한 분야에서 발견되는데, 미국지질청(USGS)의 EROS 데이터센터, 네브라스카 대학, 유럽공동체에서는 NASA의 도움을 받아 전 지구의 지표피복을 1km 해상도로 분류한 바 있다(http://edcdaac.usgs.gov).(중략)

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Change Detection of Land Cover Environment using Fuzzy Logic Operation : A Case Study of Anmyeon-do (퍼지논리연산을 이용한 토지피복환경 변화분석: 안면도 사례연구)

  • 장동호;지광훈;이현영
    • Korean Journal of Remote Sensing
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    • v.18 no.6
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    • pp.305-317
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    • 2002
  • The purpose of this study is to analyze the land cover environmental changes in the Anmyeon-do. Especially, it centers on the changes in the land cover environment through methods of GIS and remote sensing. The land cover environmental change areas were detected from remote sensing data, and geographic data sets related to land cover environment change were built as a spatial database in GIS. Fuzzy logic was applied for data representation and integration of thematic maps. In the natural, social, and economic environment variables, the altitude, population density, and the national land use planning showed higher fuzzy membership values, respectively. After integrating all thematic maps using fuzzy logic operation, it is possible to predict the change quantitatively. In the study area, a region where land cover change will be likely to occur is the one on a plain near the shoreline. In particular, the hills of less than 5% slope and less than 15m altitude, adjacent to the ocean, were quite vulnerable to the aggravation of coastal environment on account of current, large-scale development. In conclusions, it is expected that the generalized scheme used in this study is regarded as one of effective methodologies for land cover environmental change detection from geographic data.

Impervious Surface Estimation Area of Seom River Basin using Satellite Imagery and Sub-pixel Classifier (위성영상과 Sub-pixel 분류에 의한 섬강유역의 불투수율 추정)

  • Na, Sang-Il;Park, Jong-Hwa;Shin, Hyoung-Sub;Park, Jin-Ki;Baek, Shin-Chul
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.744-744
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    • 2012
  • 불투수층은 자연적인 침투를 허용하지 않는 인위적인 토지피복상태로 도시화율 추정 및 유역의 환경변화 정도를 분석하기 위한 척도로 사용되어 왔다. 특히, 수문학적 관점에서 불투수층은 단기 유출현상에 큰 영향을 끼치는 요소로 불투수율이 증가할수록 침투량이 감소하여 첨두유출량은 증가하고 도달시간은 짧아진다. 최근에는 급속한 도시화로 인해 불투수층의 영향이 더욱 커짐에 따라 불투수율의 추정에 대한 필요성이 증가하고 있다. 현재까지 위성영상을 이용한 불투수층의 추정은 고해상도 영상을 이용하여 피복분류를 수행하였다. 즉, 분류된 토지피복에 근거하여 불투수율을 산술적으로 계산하거나 분광혼합기법 및 회귀 트리기법 등 다양한 방법에 적용되어 왔다. 본 연구에서는 Sub-pixel 분류기법을 위성영상에 적용하여 섬강유역의 불투수율을 추정하고자 한다. Sub-pixel 분류는 기존 분류기법들이 다양한 토지피복이 혼합된 화소에 대해서도 가장 비중이 높은 토지피복 하나로 분류하던 것을 개선한 방법으로 fuzzy 이론을 적용하여 최소 20% 이상의 비율을 점유하는 항목 모두를 구분하여 분류하는 기법이다. 이를 위해 섬강유역의 Landsat TM 영상을 수집하고 환경부의 토지피복도와 지질도를 참조하여 트레이닝 자료를 수집하였다. 또한 결과에 영향을 미칠 수 있는 구름은 전처리를 통하여 제거하고 수집된 트레이닝 자료에 Sub-pixel 분류기법을 적용하여 섬강유역의 불투수율을 공간분포도로 작성하였다.

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Analysis of Land Cover Change in the Waterfront Area of Taehwa River using Hyperspectral Image Information (초분광 영상정보를 이용한 태화강 수계지역의 토지피복 변화분석)

  • KIM, Yong-Suk
    • Journal of the Korean Association of Geographic Information Studies
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    • v.24 no.1
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    • pp.12-25
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    • 2021
  • Land cover maps are used in various fields in urban expansion and development. This study analyzed the amount of land cover change over time using multi-sensor information, focusing on the waterfront area of the Taehwa River. In order to apply high-accuracy aerial hyperspectral images, patterns with Field-spectral were reviewed and compared with time series Digital map. The hyperspectral image was set as 13 land cover grades, and the time series digital map was classified into 7 and the waterfront area was classified into 5-6 grades and analyzed. As a result of analysis of the change in land cover of the digital map from the 1990s to 2010, it was found that forest areas were rapidly decreasing and Farmland and grassland were becoming urban. As for the land cover change(2010~2019) in the waterfront area(set 500m) analyzed through hyperspectral images, it was found that Farmland(1.4㎢), Forest(1.0㎢), and grassland (0.8㎢) were converted into urbanized and dried areas, and urbanization was accelerating around the Taehwa River waterfront. Recently, a lot of research has been conducted on the production of land cover maps using high-precision satellite images and aerial hyperspectral images, so it is expected that more detailed and precise land cover maps can be produced and utilized.

Time series Analysis of Land Cover Change and Surface Temperature in Tuul-Basin, Mongolia Using Landsat Satellite Image (Landsat 위성영상을 이용한 몽골 Tuul-Basin 지역의 토지피복변화 및 지표온도 시계열적 분석)

  • Erdenesumbee, Suld;Cho, Gi Sung
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.3
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    • pp.39-47
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    • 2016
  • In this study analysis the status of land cover change and land degradation of Tuul-Basin in Mongolia by using the Landsat satellite images that was taken in year of 1990, 2001 and 2011 respectively in the summer at the time of great growth of green plants. Analysis of the land cover change during time series data in Tuul-Basin, Mongolia and NDVI (Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and LST (Land Surface Temperature) algorithm are used respectively. As a result shows, there was a decrease of forest and green area and increase of dry and fallow land in the study area. It was be considered as trends to be a land degradation. In addition, there was high correlation between LST and vegetation index. The land cover change or vitality of vegetation which is taken in study area can be closely related to the temperature of the surface.