• 한국지형학회지
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• 제25권3호
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• pp.105-120
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• 2018

This study estimates possibility and limitation on production of DEM using aerial photo by comparison of DEMs using aerial photo and digital map. Mountain and urban areas show higher elevation in DEM using aerial photo than in DEM using digital map, due to height of vegetation cover and buildings, respectively. However, artificial affects due to bridge, embankment and road construction are responsible for areas with higher elevation in DEM using digital map than in DEM using aerial photo. This difference in elevation between DEMs seems to be caused by rapid change in real elevation that is not reflected in digital map. There is little difference in elevation between DEMs in plain and area with little or no vegetation cover. This study suggests that problems associated with vegetation cover and error by GCP should be fixed, although DEM using aerial photo can quantitatively and 3-dimensionally reconstruct topography with a high resolution.

• The Korean Journal of Ecology
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• 제26권2호
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• pp.75-81
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• 2003

This study was performed to prove if the high resolution satellite imagery of IKONOS is suitable for preparing digital vegetation map which is becoming increasingly important in ecological science. Seven classes for forest area and five classes for non-forest area were taken for classification. Three methods, such as the pixel based classification, the segment based classification with majority principle, and the segment based classification with maximum likelihood, were applied to classify IKONOS imagery taken in April 2000. As a whole, the segment based classification shows better performance in classifying the high resolution satellite imagery of IKONOS. Through the comparison of accuracies and kappa values of the above 3 classification methods, the segment based classification with maximum likelihood was proved to be the best suitable for preparing the vegetation map with the help of IKONOS imagery. This is true not only from the viewpoint of accuracy, but also for the purpose of preparing a polygon based vegetation map. On the basis of the segment based classification with the maximum likelihood, a digital vegetation map in which each vegetation class is delimitated in the form of a polygon could be prepared.

• The Korean Journal of Ecology
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• 제19권5호
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• pp.465-476
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• 1996

There are several environmental variables that may be influential to the spatial distribution of forest vegetation. To create a map of forest vegetation zone over southern part of Korean Peninsula, digital map layers were produced for each of environmental variables that include topography, geographic locations, and climate. In addition, an extensive set of field survey data was collected at relatively undisturbed forests and they were introduced into the GIS database with exact coordinates of survey sites. Preliminary statistical analysis on the survey data showed that the environmental variables were significantly different among the previously defined five forest vegetation zones. Classification of the six layers of digital map representing environmental variables was carried out by a supervised classifier using the training statistics from field survey data and by a clustering algorithm. Although the maps from two classifiers were somewhat different due to the classification procedure applied, they showed overall patterns of vertical and horizontal distribution of forest zones. considering the spatial contents of many ecological studies, GIS can be used as an important tool to manage and analyze spatial data. This study discusses more about the generation of digital map and the analysis procedure rather than the outcome map of forest vegetation zone.

• 산업기술연구
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• 제25권B호
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• pp.47-54
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• 2005

The goal of this study is to generate a landslide potential map using GIS(Geographic Information System) based method. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM(Digital Elevation Model) and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight value for landslide potentialities is calculated from AHP(Analytic Hierarchy Process) method. Slope and Slope-direction is extracted from DEM, and soil information is extracted from digital soil map. Also, vegetation information is extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is compared with landslide place.

• 한국지형공간정보학회:학술대회논문집
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• 한국지형공간정보학회 2005년도 아시아 태평양 국제 GSIS 학술발표회
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• pp.61-72
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• 2005

The landslide risk assessment process consists of hazard risk assessment and vulnerability analysis. landslide hazard risk is location dependent. Therefore, maps and spatial technologies such as GIS are very important components of the risk assessment process. This paper discusses the advantages of using GIS technology in the risk assessment process and illustrates the benefits through case studies of live projects undertaken. The goal of this study is to generate a map of landslide vulnerability map by analysis of static natural factors with GIS. A simple and efficient algorithm is proposed to generate a landslide potentialities map from DEM and existing maps. The categories of controlling factors for landslides, aspect of slope, soil, vegetation are defined. The weight values for landslide potentialities are calculated from AHP method. Slope and slope-direction are extracted from DEM, and soil informations are extracted from digital soil map. Also, vegetation informations are extracted from digital vegetation map. Finally, as overlaying, landslide potentialities map is made out, and it is verified with landslide place.

• The Korean Journal of Ecology
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• 제19권5호
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Journal of Ecology and Environment
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• 제41권4호
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• pp.114-119
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• 2017

This study tried to analyze error range and resolution of drone images using a rotary wing by comparing them with field measurement results and to analyze stands patterns in actual vegetation map preparation by comparing drone images with aerial images provided by National Geographic Information Institute of Korea. A total of 11 ground control points (GCPs) were selected in the area, and coordinates of the points were identified. In the analysis of aerial images taken by a drone, error per pixel was analyzed to be 0.284 cm. Also, digital elevation model (DEM), digital surface model (DSM), and orthomosaic image were abstracted. When drone images were comparatively analyzed with coordinates of ground control points (GCPs), root mean square error (RMSE) was analyzed as 2.36, 1.37, and 5.15 m in the direction of X, Y, and Z. Because of this error, there were some differences in locations between images edited after field measurement and images edited without field measurement. Also, drone images taken in the stream and the forest and 51 and 25 cm resolution aerial images provided by the National Geographic Information Institute of Korea were compared to identify stands patterns. To have a standard to classify polygons according to each aerial image, image analysis software (eCognition) was used. As a result, it was analyzed that drone images made more precise polygons than 51 and 25 cm resolution images provided by the National Geographic Information Institute of Korea. Therefore, if we utilize drones appropriately according to characteristics of subject, we can have advantages in vegetation change survey and general monitoring survey as it can acquire detailed information and can take images continuously.

• 대한지리학회지
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• 제38권5호
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• pp.667-685
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• 2003

미국 캔자스주 정부와 연방정부가 필요로 하는 상세한 지표피복 수치지도제작을 위해, Landsat Thematic Mapper 자료를 이용하여 캔자스주 전체를 대상으로 43가지로 분류된 식생군단(vegetation alliance) 수준의 자연식 생지도를 제작하였다. 지도제작 방법으로는 봄, 여름, 가을의 계절별 위성자료를 이용하여 두 단계 분류절차를 거치는 이른바 '하이브리드(hybrid)' 방식을 채택하였다. 이 접근 방법은 첫 단계로 unsupervised classification을 이용, 자연녹지를 농경지로부터 분리해 낸 다음. 두 번째 단계에서 supervised classification, 현장확인조사. 그리고 분류 후 다양한 보강자료를 이용하여 최종적으로 자연식생을 구분ㆍ분류해 내는 것이다. 정확도 평가는 세 가지 분류 수준에서 실행되었는데, 이는 앤더슨 분류단계 I(Anderson level I), 식생군계(vegetation formation), 그리고 식생군단 수준을 포함한다. 확인결과 전반적인 정확도는 51.7%에서 89.4%에 이르는 것으로 조사되었다.

• 한국측량학회지
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• 제28권1호
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• pp.21-28
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• 2010

산불은 산림의 주요 교란요소중의 하나로써 산림 구조와 기능에 매우 큰 영향을 미치며, 산불피해강도에 따라 피해 후 식생회복 과정이 달라질 수 있다. 산불피해지의 피해강도와 식생회복 과정을 파악하기 위해서는 많은 인력과 예산이 필요하다. 위성영상자료를 이용한 산불피해지의 피해량 분석은 신속한 정보는 물론 대규모 피해지의 객관적인 결과를 원격으로 신속하게 취득할 수 있다. 이에 본 연구에서는 충청남도 청양 예산 지역의 산불발생 전 후 위성영상을 이용한 분류 기법을 통해 연구대상 지역의 산불피해 정보를 산출하고자 하였다. 이를 위해 산불발생 전 후의 다 시기 Landsat 위성영상을 이용한 영상 분류를 통해 산불피해 지역의 면적을 산출하였으며 수치임상도와의 중첩분석을 통해 피해지역 삼림의 수종, 영급, 경급 및 수관밀도별 피해량을 효과적으로 산정할 수 있었으며 분류결과와 NDVI를 이용하여 식생회복을 모니터링 할 수 있었다.

• 한국환경복원기술학회지
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• 제19권5호
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• pp.11-17
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• 2016

The purposes of this research are to estimate area of greenable roof and to monitor maintaining of green roofs using World-View 2 images. The contents of this research are development of World-View 2 application technologies for estimation of green roof area and development of monitoring and maintaining of green roofs using World-View 2 images. The available green roof areas in Gwangjin-gu Seoul, a case for this study, were estimated using digital maps and World-View 2 images. The available green roof area is approximately 12.17% ($2,153,700m^2$) of the total area, and the roof vegetation accounts for 0.46% ($80,660m^2$) of the total area. For verification of the extracted roof vegetation, Vworld 3D Desktop map service was applied. The study results may be used as a decision-making tool by the government and local governments in determining the feasibility of green roof projects. In addition, the project implementer may periodically monitor to see whether roof greening has maintained for efficient management of projects, and a vast amount of World-View 2 images may be regularly used before and after the projects to contribute to sharing of satellite images information.