• Journal of Forest and Environmental Science
• /
• 제36권3호
• /
• pp.187-198
• /
• 2020

This study extracted deforestation area and degraded forestland area, which are potential REDD+ (Reducing Emissions from Deforestation and Forest Degradation) project candidate areas in Paraguay using Land Cover Map (LCM) and Tree Cover Map (TCM). The REDD+ project objectives scenarios were set three stages: 'afforestation and economic efficiency scenario', 'local capacity reinforcement scenario', and 'Infrastructure-oriented scenario'. And then, we evaluated the project unit suitable area of the REDD+ project. All scenarios selected the evaluation factors for each scenario in addition to the area ratio factors for deforestation area and degraded forestland area and weighted values were extracted by assigning category scores. As a result of the three scenarios comparison analysis, Concepcion state score was the highest. Within Concepcion state, the Belon district had the highest score, making it appropriate as a project unit REDD+ project candidate area in Paraguay, while the San Carlos district had the lowest score. This study can be used as basic data for selecting REDD+ project candidate area in Paraguay, and it is expected to contribute sufficiently to REDD+ project if additional data or information of social, cultural and economic sectors are secured.

• 한국지리정보학회지
• /
• 제13권1호
• /
• pp.89-100
• /
• 2010

본 연구는 다양한 고해상도 위성영상을 사용하여 토지피복도를 제작하고 영상종류와 피복도의 분류에 따른 정확도를 비교함에 목적이 있다. 토지피복도 작성시 세분류의 다양함을 위해 시가지와 농지, 수역 등을 포함하는 낙동강 하구 일대를 연구지역으로 선정하였고, 1m 이상의 해상도를 가지는 KOMPSAT2, QuickBird, IKONOS, 항공사진등을 육안판독 후 분류 하였다. 영상과 피복분류에 따른 토지피복도를 작성 후 상호 비교 한 결과 영상별 정확도는 항공사진과 QuickBird가 KOMPSAT2와 IKONOS 보다 상대적으로 높은 것으로 나타났고, 분류방법에 따른 일치도는 대분류의 경우 0.934~0.956, Kappa value는 0.905~0.937, 중분류의 일치도는 0.888~0.913, Kappa value는 0.872~0.901, 세분류의 일치도는 0.833~0.901, Kappa value는 0.813~0.888로 나타났다. 또한 영상별 혼돈발생 정도는 분류 항목에 따라 대분류의 경우 시가화 건조지역과 나지의 혼돈이 발생했고, 중분류는 논, 밭, 하우스 재배지, 인공초지에서 주로 발생하며, 세분류의 경우 자연녹지, 시설물 경작지, 간석지와 해수면으로 주로 나타났다. 본 연구를 통해 토지피복도 작성시 육안판독에 의한 고해상도 영상분류는 전체 80% 이상의 일치도를 나타내어 활용이 가능했고, 고해상도 영상을 사용할수록 정확한 분류가 가능하며 영상의 촬영시기가 토지피복도 작성에 중요함을 알 수 있었다.

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

• 한국수자원학회논문집
• /
• 제53권3호
• /
• pp.215-223
• /
• 2020

본 연구의 목적은 국내 하천을 대상으로 데이터 마이닝의 분류 및 예측 기법을 활용하여 비유사량 추정 모델을 개발하는 것이다. 이를 위해 유사이송에 영향을 미치는 요소들을 전반적으로 고려하여 유역인자를 추출하였으며, 유역의 지형학적 요소, 강우, 토지 피복, 토지 이용, 하상 재료 등이 고려되었다. 추출된 인자를 활용하여 모델을 도출한 결과 유역 형태학적 특성인자 중 평균 면적비에서 유역고도 및 토지피복인자 중 도시화 비율과 전체 유역 중 습지와 수역의 비율이 조건인자로 활용되었다. 도출된 모델은 실측값과의 비교를 통해 실측 비유사량의 발생 패턴이 유사하게 재현됨을 확인하였다. 또한 기존의 사용되던 산정 공식과 비교하였으며, 국외의 데이터를 기반으로 도출된 모델은 개발 배경 및 국내 하천 환경과의 차이로 인해 국내 하천 데이터 적용에 한계가 있는 것으로 나타났다. 이에 본 연구에서는 개발 및 적용 환경, 데이터 범위의 차이 등으로 인해 발생하던 기존 공식의 한계를 개선하고자 하였다.

• 한국측량학회지
• /
• 제31권6_2호
• /
• pp.521-527
• /
• 2013

Rule set is an important step which impacts significantly on accuracy of object-oriented classification result. Therefore, this paper proposes a rule set to extract land cover from Landsat Thematic Mapper (TM) imagery acquired in Donganh, Hanoi, Vietnam. The rules were generated to distinguish five classes, namely river, pond, residential areas, vegetation and paddy. These classes were classified not only based on spectral characteristics of features, but also indices of water, soil, vegetation, and urban. The study selected five indices, including largest difference index max.diff; length/width; hue, saturation and intensity (HSI); normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) based on membership functions of objects. Overall accuracy of classification result is 0.84% as the rule set is used in classification process.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
• /
• pp.840-843
• /
• 2006

The aim of this study was to detect landslide using satellite image and apply the landslide to probabilistic landslide-susceptibility mapping at Gangneung area, Korea using a Geographic Information System (GIS). Landslide locations were identified by change detection technique of KOMSAT-1 (Korea Multipurpose Satellite) EOC (Electro Optical Camera) images and checked in field. For landslide-susceptibility mapping, maps of the topography, geology, soil, forest, lineaments, and land cover were constructed from the spatial data sets. Then, the sixteen factors that influence landslide occurrence were extracted from the database. Using the factors and detected landslide, the relationships were calculated using frequency ratio, one of the probabilistic model. Then, landslide-susceptibility map was drawn using the frequency ration and finally, the map was verified by comparing with existing landslide locations. As the verification result, the prediction accuracy showed 86.76%. The landslide-susceptibility map can be used to reduce hazards associated with landslides and to land cover planning.

• 한국관개배수논문집
• /
• 제14권2호
• /
• pp.236-244
• /
• 2007

Agricultural water demand in North Korea must be considered for the near-future investment in agricultural consolidation projects and to prepare for the future unification. Thus, the objective of this study is to estimate the agricultural water demand of paddy fieldss in North Korea. GIS data including land cover classification map, Thiessen network and administration maps of North Korea, and meteorological data were synthesized. In order to estimate paddy water demand for a 10-year return period, the FAO Blaney-Criddle method and the fixed effective rainfall ratio method were used. The results showed that 4.77 billion $\beta$(c)/year paddy water demand is required for the 512,400 ha of paddy fieldss. Paddy water demand in the three major regions - Hwanghaedo, Pyeongando, Hamgyeongnamdo - was estimated chargong 81.7 percent of total paddy water demand in North Korea.

• 한국습지학회지
• /
• 제14권4호
• /
• pp.561-569
• /
• 2012

본 연구에서는 경안천 유역을 대상으로 1975년부터 2000년까지의 토지피복상태에 따른 불투수면과 투수면을 재분류하여 경관분석 프로그램을 이용하여 경관 지수를 산정하였다. 경관 지수 중 총 중심지면적인 TCA(Total Core Area)를 생물종 다양성 지표로 이용하였다. 선정된 경관 지표 TCA와 불투수면 모델인 ICM(Impervious Cover Model)을 이용하여 실제 경안천 유역의 어류 출현종수와 비교하였다. TCA와 불투수면 비율의 관계에서는 불투수면 비율 증가에 따라 TCA값이 점차 감소하는 추세를 보였다. 이는 도시화와 인위적인 개발로 인해 경관에서 불투수면 면적이 차지하는 비율이 커지면서 생물종이 외부로부터의 격리를 필요로 하는 임계면적이 점차 감소하였음을 나타낸다. 또한, 경안천에 서식하는 출현 어류종의 종류를 모니터링 해 본 결과 불투수면 비율이 낮은 지역에서 청정수에 서식하는 종의 출현빈도가 높음을 알 수 있었다. 경안천 유역은 하천상태가 Impacted Stream(손상하천) 위에 해당하여 유역의 상태가 나빠지는 단계에 있는 것으로 파악되었으며, 이 구간에서 유역은 불투수면 비율에 민감하게 반응하므로, 계속적으로 집중적인 유역관리가 필요하며, 지역에 출현하는 어류다양성을 증가시키기 위해 유역상태를 개선시킬 필요성이 있다.

• 대한원격탐사학회지
• /
• 제24권1호
• /
• pp.45-55
• /
• 2008

The impact on streamflow and groundwater recharge considering future potential climate and land use change was assessed using SLURP (Semi-distributed Land-Use Runoff Process) continuous hydrologic model. The model was calibrated and verified using 4 years (1999-2002) daily observed streamflow data for a $260.4km^2$ which has been continuously urbanized during the past couple of decades. The model was calibrated and validated with the coefficient of determination and Nash-Sutcliffe efficiency ranging from 0.8 to 0.7 and 0.7 to 0.5, respectively. The CCCma CGCM2 data by two SRES (Special Report on Emissions Scenarios) climate change scenarios (A2 and B2) of the IPCC (Intergovemmental Panel on Climate Change) were adopted and the future weather data was downscaled by Delta Change Method using 30 years (1977 - 2006, baseline period) weather data. The future land uses were predicted by CA (Cellular Automata)-Markov technique using the time series land use data of Landsat images. The future land uses showed that the forest and paddy area decreased 10.8 % and 6.2 % respectively while the urban area increased 14.2 %. For the future vegetation cover information, a linear regression between monthly NDVI (Normalized Difference Vegetation Index) from NOAA/AVHRR images and monthly mean temperature using five years (1998 - 2002) data was derived for each land use class. The future highest NDVI value was 0.61 while the current highest NDVI value was 0.52. The model results showed that the future predicted runoff ratio ranged from 46 % to 48 % while the present runoff ratio was 59 %. On the other hand, the impact on runoff ratio by land use change showed about 3 % increase comparing with the present land use condition. The streamflow and groundwater recharge was big decrease in the future.

• 한국GIS학회:학술대회논문집
• /
• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
• /
• pp.63-63
• /
• 2003

The aim of this study is to apply and verify of Bayesian probability model, the likelihood ratio and statistical model, at Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite images, field surveys, and maps of the topography, soil type, forest cover, geology and land use were constructed to spatial database. The factors that influence landslide occurrence, such as slope, aspect and curvature of topography were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, diameter and density of forest were extracted from the forest database. Land use was classified from the Landsat TM image satellite image. As each factor's ratings, the likelihood ratio coefficient were overlaid for landslide susceptibility mapping, Then the landslide susceptibility map was verified and compared using the existing landslide location. The results can be used to reduce hazards associated with landslides management and to plan land use and construction.