• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.4
• /
• pp.21-27
• /
• 2013

Recently, It is increasing that importance of systematic management by carbon sinks in forest resources. Especially, in terms of social, Forest resources in urban areas are important role as well as carbon sinks, and improvement of the natural environment of the city. In this study, through ANOVA analysis that a total of nine different vegetation index from rearranged NIR band of images to Forest tree species classified in urban areas using high-resolution aerial images and satellite images of KOMPSAT-2. And various vegetation indices such as NDVI are divided a species by forest units through statistical analysis. Also, separated species are compared to forest type map by the Forest Service. As a result, it is built as basis for vegetation management in urban areas.

• Journal of Korea Spatial Information System Society
• /
• v.12 no.1
• /
• pp.57-65
• /
• 2010

In this study, disaster damage investigation system was developed using high resolution satellite images and GIS technique to afford effective damage investigation system for widely disaster damaged area. Study area was selected in Bonghwa, Gyungsangbukdo where high magnitude of damages from torrential rain has occurred at July in 2008. GIS DB was built using 1:5,000 topographic map, cadastral map, satellite image and aerial photo to apply for investigation algorithm. Disaster damage investigation system was developed using VB NET languages, ArcObject component and MS-SQL DBMS for effective management of damage informations. The system can finding damaged area comparing pre- and post-disaster images and drawing damaged area according to the damage item unit. Extracted object was saved in Shape file format and overlayed with background GIS DB for obtaining detail information of damaged area. Disaster damage investigation system using high resolution spatial images can extract damage information rapidly and highly reliably for widely disaster areas. This system can be expected to highly contributing to enhance the disaster prevention capabilities in national level field investigation supporting and establishing recovery plan etc. This system can be utilized at the plan of disaster prevention through digital damage information and linked in national disaster information management system. Further studies are needed to better improvement in system and cover for the linkage of damage information with digital disaster registry.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.4 no.3
• /
• pp.61-70
• /
• 2001

This paper presents a new method to extract semi-automatically roads from high spatial resolution satellite imagery. This method is based both on wavelet transform and on multiresolution analysis combined in the "$\grave{a}$ trous" algorithm. As an urban road network consists on different classes of streets, multiresolution processing allows to extract the streets class by class. The method was applied to a KVR-1000 image on a part of Busan Metropolitan City. The method was carried out for the road extraction of three different widths and it succeeded in extracting good fitted strips. The accuracy analysis for three types of streets was also performed. The overall accuracy in 4 pixels of width is 80.5%. The result suggests that this method can be used to update road networks in the studied urban network. In summary, the multiresolution approach based on the wavelet transform, used in this study, is regarded as one of effective methods to extract urban road network from high spatial resolution satellite images.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2004.03a
• /
• pp.347-347
• /
• 2004

임상도는 항공사진을 판독하여 얻어진 산림에 관한 정보를 지형도(1/25,000)에 도화 작성한 도면으로 전국 산림조사와 연계하여 10년을 주기로 순환제작 되며, 현재 제 4차 수치임상도가 제작 중에 있다 임상도는 여러 산림관련 주제도 중 가장 많이 활용되는 도면으로 산림 분야뿐만 아니라 다른 분야에서도 널리 활용되고 있다. 그러나 10년을 주기로 제작되므로 부분적으로 현실과 부합하지 않는 내용이 포함되어 있어 각종 계획수립 및 활용에 장애요인으로 작용하고 있다. 따라서 실제 임상정보를 획득할 수 있도록 지속적인 갱신이 필요하다. 그러나 임상도의 부분적 갱신을 위하여 별도의 항공사진을 촬영하는 것은 현실적인 어려움이 있으며, 최근 고해상도 위성영상이 활용 가능하게 됨에 따라 임상도의 갱신에도 활용될 수 있을 것으로 기대되고 있다. 본 연구에서는 고해상도 위성영상인 IKONOS를 이용하여 수치임상도를 갱신하는 방법을 제시하였다. 연구대상지는 제 4차 임상도의 수치화가 완료된 전라북도 완주 지역으로 1:25000 지형도의 도엽명 대아와 읍내의 일부지역이다. 영상자료는 2001년 8월 18일에 촬영된 IKONOS Multispectral 자료를 이용하였다. 영상의 기하보정을 위하여 RPC Model과 1:25000 수치지형도로부터 만들어진 DEM을 사용하였다. 기하보정된 영상을 이용하여 영상분할(Segmentation)을 실시하여 서로 중복되지 않는 동질한 지역으로 구분하였다. 이때 기존의 수치임상도를 Super-Object로 사용하여 영상을 분할할 때 형성될 수 있는 가장 큰 Segment로 제한하였으며 Super-Object의 경계를 벗어나지 않는 보다 작은 Sub-Object를 만들도록 하여 분할영상의 계층적 구조를 형성하였다. 어느 한 임상내에서 변화가 발생하면 변화가 발생한 지역은 변화가 발생하지 않은 지역과 서로 다른 분광특성을 나타내므로 별도의 Segment를 형성하게 된다. 따라서 임상도의 경계선으로부터 획득된 Super-Object의 분광반사 값과 그 안에서 형성된 Sub-Object의 분광반사값의 차이를 이용하여 임상도의 갱신을 위한 변화지역을 탐지하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.2
• /
• pp.149-156
• /
• 2008

In this paper, we propose a method aiming at updating the building information of the digital maps using single high resolution satellite image and digital map. Firstly we produced a digital orthoimage through the automatic co-registration of QuickBird image and 1:1,000 digital map. Secondly we extracted building height information through the template matching of digital map's building vector data and the image's edges obtained by Canny operator. Finally we refined the shape of some buildings by using the result from template matching as the seed polygon of the greedy snake algorithm. In order to evaluate the proposed method's effectiveness, we estimated accuracy of the extracted building information using LiDAR DSM and 1:1,000 digital map. The evaluation results showed the proposed method has a good potential for extraction and revision of building information.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.1
• /
• pp.80-93
• /
• 2016

Parcel boundary demarcation in agricultural area is commonly performed by terrestrial surveying methods, which have been pointed out as drawbacks to require consuming too much time and heavy expenditure. With the developments of high performance digital aerial cameras, however, studies on cadastral boundary demarcation with an aerial photogrammetric method attract a great attention in recent years. In this paper, an approach is presented to rapidly demarcate parcel boundaries coinciding with real ground ones in agricultural areas by extracting boundaries from the high resolution aerial orthoimages based on aerial targets. In order to investigate the feasibility of the proposed method, the accuracy of coordinates and area of parcel boundaries extracted from the aerial targets appeared in orthoimages compared with that of terrestrial boundary surveying results over the selected two test agricultural areas. Aerial image data were processed taken by a ADS80 digital camera with a GSD of 8cm in Changwon region, and by a DMCII camera with a GSD of 5cm in Suwon respectively. The result shows that the accuracy of parcel demarcation using aerial images is within the tolerance limits of coordinates and areas compared with that of terrestrial surveying. The proposed method using aerial target-based high resolution aerial images is therefore expected to be usefully applied in the agricultural parcel demarcation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.32 no.4_1
• /
• pp.319-326
• /
• 2014

The accurate geo-referencing processes that apply ground control points is prerequisite for effective end use of HRSI (High-resolution satellite imagery). Since the conventional control point acquisition by human operator takes long time, demands for the automated matching to existing reference data has been increasing its popularity. Among many options of reference data, the airborne LiDAR (Light Detection And Ranging) data shows high potential due to its high spatial resolution and vertical accuracy. Additionally, it is in the form of 3-dimensional point cloud free from the relief displacement. Recently, a new matching method between LiDAR data and HRSI was proposed that is based on the image projection of whole LiDAR data into HRSI domain, however, importing and processing the large amount of LiDAR data considered as time-consuming. Therefore, we wmotivated to ere propose a local LiDAR chip generation for the HRSI geo-referencing. In the procedure, a LiDAR point cloud was rasterized into an ortho image with the digital elevation model. After then, we selected local areas, which of containing meaningful amount of edge information to create LiDAR chips of small data size. We tested the LiDAR chips for fully-automated geo-referencing with Kompsat-2 and Kompsat-3 data. Finally, the experimental results showed one-pixel level of mean accuracy.

• Journal of the Society of Disaster Information
• /
• v.14 no.4
• /
• pp.501-509
• /
• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.223-227
• /
• 2006

최근 위성기술의 발전은 크게 두 가지 방향으로 진행되고 있다. 하나는 고해상도(High Resolution)라는 말로 대표되는 공간해상도(Spatial Resolution)의 향상이고, 다른 하나는 초분광(Hyperspectral)으로 대표되는 분광해상도(Spectral Resolution)의 향상이다. 특히 초분광영상(Hyperspectral Image)은 지상피복 및 대상물에 대해 실험실에서 얻을 수 있을 정도의 연속적이고 좁은 파장 간격의 분광정보를 제공하고 있어, 기존에 사용하던 다중분광영상(Multispectral Image) 보다 많은 양의 정보를 사용자에게 제공한다. 본 논문에서는 다중분광영상과 초분광영상의 분광 정보를 활용한 영상분류능력을 비교분석하고 그 결과를 평가하였다. 분석결과는 다중분광영상에서 식별이 어려웠던 초지, 농지, 나지에 대한 분석 능력이 초분광영상에서 상당히 향상됨으로써 감독분류에서 약 20% 정도의 정확도 향상을 가져왔으며, 무감독분류의 경우에는 미소한 차이로 그 정확도가 향상된다는 것이다. 이런 결과는 향후 초분광영상의 토지 피복분류 및 대상물 탐사에 긍정적인 활용 방안을 제시할 수 있음을 알려주고 있다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.3
• /
• pp.63-71
• /
• 2013

This study calculated vegetation indexes such as SR, NDVI, SAVI, and LAI to figure out correlations regarding vegetation by using high resolution KOMPSAT-2 images and LANDSAT images based on the forest biomass distribution map that utilized field survey data, satellite images and LiDAR data and then analyzed correlations between their values and forest biomass. The analysis results reveal that the vegetation indexes of high resolution KOMPSAT-2 images had higher correlations than those of LANDSAT images and that NDVI recorded high correlations among the vegetation indexes. In addition, the study analyzed the characteristics of hyperspectral images by using the COMIS of STSAT-3 and Hyperion images of a similar sensor, EO-1, and further the usability of biomass estimation in hyperspectral images by comparing vegetation index, which had relatively high correlations with biomass, with the vegetation indexes of LANDSAT with the same GSD conditions.