Modeling of landscape visibility using digital data offers an efficient way to assess a geographic area systematically. This approach has been widely used in historical and archeological studies, renewable energy such as solar and wind farm, telecommunications tower assessments, military use, landscape architecture, landscape planning and management, spatial planning, among others. Disaster events such as flooding and landslides as a result weather disturbance has significantly changed our landscapes affecting population and resources. With the availability of Digital Elevation Models (DEMs) of various spatial scales, visibility analyses can be carried out for rapid landscape assessment. This study was done in a 46km2 area in Bongabong, Oriental Mindoro, Philippines. Visibility analyses used: 1) Light Detection and Ranging (LiDAR) derived Digital Terrain Model (DTM) and Digital Surface Model (DSM) at 1m spatial resolution; 2) Synthetic Aperture Radar (SAR) DEM at 10m spatial resolution; 3) Advanced Land Observing Satellite (ALOS) DSM at 30m spatial resolution; and 4) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2). Observer location was randomly established along major roads and compared with the observer location at ecotourism sites. Results showed that LiDAR-derived elevation models offer greater details concerning the visibility of landscapes along the main roads compared to SAR DEM, ALOS DSM, and ASTER GDEM, respectively. On the other hand, regardless of spatial resolution, visible areas of the study area along the main roads using SAR DEM (30.07 km2), ALOS DSM (30.16 km2) and ASTER GDEM (30.18 km2) is comparable to LiDAR-derived DTM (25.77 km2). Computationally, LiDAR DTM took about 28 mins to complete the visibility analysis compared to about 19 sec. for SAR DEM, and about 3 sec. for ALOS DSM and ASTER GDEM, respectively. Further investigation reveals that the visible areas of the landscapes are predominantly agricultural lands, and prone to flooding. High spatial resolution elevation/surface data offer greater detail when it comes to visibility analysis of the landscape. In areas where these data are not available, medium resolution elevation data can be used for landscape assessments.
|出版狀態||Published - 2020|
|事件||40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019 - Daejeon, Korea, Republic of|
持續時間: 2019 十月 14 → 2019 十月 18
|Conference||40th Asian Conference on Remote Sensing: Progress of Remote Sensing Technology for Smart Future, ACRS 2019|
|國家/地區||Korea, Republic of|
|期間||19-10-14 → 19-10-18|
All Science Journal Classification (ASJC) codes