Application of Spot 5 Satellite Image and GIS for Updating Road Network: Towards Building Landslide Spatial Database

Rapid development in urbanization is usually followed by development in transportation network. As the consequence, latest developed road networks are not found on the existing topographic map. As the topographic map-derived road network is not updated in short period, it is important to short...

全面介紹

Saved in:
書目詳細資料
Main Authors: Basith, Abdul, Matori, Abdul Nasir, Cahyono, Bambang Kun
格式: Conference or Workshop Item PeerReviewed
語言:English
出版: 2008
主題:
在線閱讀:https://repository.ugm.ac.id/277798/1/2008%20ganjil-%20paper%20ICBEDC%20road%20network%20extraction%20from%20cameron%20Highlands.pdf
https://repository.ugm.ac.id/277798/
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:Rapid development in urbanization is usually followed by development in transportation network. As the consequence, latest developed road networks are not found on the existing topographic map. As the topographic map-derived road network is not updated in short period, it is important to shorten the map updating cycles. SPOT 5 satellite image offers a cost effective way for updating the map compared to a conventional mapping method. The image, acquired in 2005, is used for updating road network on topographic map scaled at 1:50000, sheet 74, issued by JUPEM which was derived from aerial photograph taken in 1981. The road connecting Simpang Pulai cross and Kampung Raja, Cameron Highlands, is selected due to its considerably rapid development and susceptibility to landslide. Since most landslide occurrences take place along the road, updating road map as part of landslide geo-database becomes necessary. SPOT5 image is registered into Malaysian Coordinate System, RSO, to conform to the existing registered topographic map. Both image classification and on screen digitization methods are used to extract road network feature. The latest method is applied to complement to the first one in case of facing uncertainty in image classification. The quality of extracted road network from image classification is discussed. The extracted road network is stored into landslide spatial database. In regard to landslide aspects, features such as barren land, vegetation coverage, are also extracted. DEM derived from topographic map is used to generate slope risk map. GIS analysis is performed to locate high risk areas that prone to landslide based on two criteria. Those areas having high risk slope (200-350) and occupy barren/un-vegetated land are considered as high risk area. From this study, only 0.1% of areas occupy high risk locations. Some of which is located at existing slope failure area at Pos Slim.