Deriving Planform Morphology and Vegetation Coverage From Remote Sensing to Support River Management Applications

摘要: With the increasing availability of big geospatial data (e.g., multi-spectral satellite imagery) and access to platforms that support multi-temporal analyses cloud-based computing, Geographical Information Systems, GIS), use remotely sensed information for monitoring riverine hydro-morpho-biodynamics is growing. Opportunities map, quantify detect changes in wider riverscape (i.e., water, sediment vegetation) at an unprecedented spatiotemporal resolution can flood risk river management applications. Focusing on a reach Po River (Italy), imagery from Landsat 5, 7 8 period 1988-2018 were analyzed Google Earth Engine (GEE) investigate planform morphology vegetation dynamics associated with transient hydrology. An improved understanding these correlations help managing transport riparian reduce risk, where biogeomorphic processes are commonly overlooked mapping. In study, two established indices analyzed: Modified Normalized Difference Water Index (MNDWI) wetted morphology, inferring about dynamics, Vegetation (NDVI) evaluating coverage. Results suggest highly localized most parts remaining stable. Using channel occurrence as measure stability, almost two-thirds extent (total area = 86.4 km2) had frequency > 90% (indicating stability). A loss complexity coincided position former secondary channels, or zones active narrowed. Time series analysis showed NDVI maxima recorded May/June first peak hydrological regime (occurring late spring snowmelt). Seasonal variation coverage potentially important local hydrodynamics, influencing risk. We provide scientists new insights anthropized watercourses.