REMOTE SENSING TECHNIQUES TO ASSESS POST-FIRE EFFECTS AT THE HILLSLOPE AND SUB-BASIN SCALES VIA MULTI-SCALE MODEL
A. Brook1,M. Polinova1,D. Kopel1,D. Malkinson2,L. Wittenberg2,D. Roberts3,and N. Shtober-Zisu4A. Brook et al.A. Brook1,M. Polinova1,D. Kopel1,D. Malkinson2,L. Wittenberg2,D. Roberts3,and N. Shtober-Zisu4
1Spectroscopy & Remote Sensing Laboratory, Center for Spatial Analysis Research (UHCSISR), Department of Geography and Environmental Studies, University of Haifa, Mount Carmel, 3498838, Israel
2Geomorphology Laboratory, Department of Geography and Environmental Studies, University of Haifa, Israel
3Geography Department, University of California Santa Barbara, Santa Barbara, CA, USA
4Department of Israel Studies, University of Haifa, Israel
1Spectroscopy & Remote Sensing Laboratory, Center for Spatial Analysis Research (UHCSISR), Department of Geography and Environmental Studies, University of Haifa, Mount Carmel, 3498838, Israel
2Geomorphology Laboratory, Department of Geography and Environmental Studies, University of Haifa, Israel
3Geography Department, University of California Santa Barbara, Santa Barbara, CA, USA
4Department of Israel Studies, University of Haifa, Israel
Abstract. Post-fire environmental footprint is expected at varying scales in space and in time and demands development of multi-scale monitoring approaches. In this paper, a spatially and temporally explicit multi-scale model that reveals the physical and morphological indicators affecting hillslope susceptibility at varying scales, is explained and demonstrated. The qualitative and quantitative suitability classification procedures are adapted to translate the large-scale space-borne data supplied by satellite systems (Landsat OLS8 and Sentinel 2 and 3) to local scale produced by a regional airborne survey performed by unmanned aerial vehicle (UAV). At the smallest spatial and temporal resolution, a daily airborne imagery collection by UAV is linked to micro-topography model, using statistical and mathematical approaches.
