The increasing uses of Unmanned Aerial Vehicles (UAV) and the producing of high resolution Digital Surface Models (DSMs) is leading to a multi-scale result in terrain analysis, prompting new solutions to cope with multi-scale analysis. In this paper we tested three indices-the local variance, texture and fractal dimensions of a same study area with six different spatial resolutions DSM processed from different UAV flights height datasets at 20, 40, 60,120,240 and 360 meters. The higher spatial resolution DSM extracted from 20 meters flight height was set as a base for a series of correlation analysis of the between the three indices to study the generalization at different scales. This approach could help in understanding the spatial resolution changing with scale and it could be used for developing hierarchical DSM scale classifications.
The advance uses of Unmanned Aerial Vehicles (UAV)
Structure from motion (SFM) algorithms greatly facilitates the production of detailed 3D models from photographs we applied this technology for the purposes of Building Information Modeling (BIM) of a historic fortress in Lebanon. Aerial and terrestrial imagery processed in SFM-based software for exterior and interior 3D modeling of the fortress. In this paper, we applied new geospatial technologies, aerial and terrestrial photogrammetry for Historic Building Information Modeling HBIM database construction. The UAV used for aerial photogrammetry, a DJI Phantom 4 pro with a camera of 20 megapixels for building facades capturing and a DSLR camera for the terrestrial photogrammetry inside the fortress. Aerial and terrestrial images processed in Agisoft Photoscan for the construction of Toron fortress HBIM of a block Geographical Information System constituted from points cloud, Digital Surface Models (DSM) and Digital Ortho Models (DOM). HBIM is a novel prototype library of parametric objects, based on historic architectural and archeological data and a system for mapping parametric objects on to point clouds database. As a result, the production of Toron fortress HBIM database containing Geographical Information Systems (GIS) and Computer Aided Design (CAD) features and entities in the form of sections plans and 3D models for both the analysis and conservation of historic objects, structures, and environments.
An important remote sensing task is to delineate snow cover. The global significance of snow patterns constitutes an important part of the climate and bio system of the Earth. Snow contributes to the hydrologic cycle through precipitation storage and melting. It is also important to monitor snow cover lands, and detect its boundaries from the Normalized Difference Snow Index (NSDI). In this work, based on remote sensing methods we delineate the snow cover on Mount Lebanon from 2013 till 2018 basing on sequential Landsat OLI/TIRS data. Beside snow cover delineation we extracted terrain characteristics of these snow boundaries from the Digital Elevation Model AW3D30, elevation interval, slope, aspects, insolation calculated for a climatological snow melt analysis and understanding. The relation of snow covers with terrain morphology is an important climatological factor influencing on the snow position, duration and melting. In this study we are seeking a link between the available snow covers and the terrain parameters. As a final result of this study based on NDSI index of the Landsat Oli images, a snow duration map of mount Lebanon was built, and the analysis showed that the surface of the snow-cover decreases around spring and it depends directly on the orientation of the slopes especially them which are in full sun and those which are with the shelters.
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