Floodplain Roughness Mapping Synergy: Lidar and Spectral Remote Sensing

Floodplain roughness parameterization is one of the key elements of hydrodynamic modeling of river flow, which is directly linked to safety level estimation of lowland fluvial areas. Necessary input parameters are median grain size for unvegetated areas, vegetation density for forest and vegetation height and density for herbaceous vegetation. This paper presents a method for spatially distributed roughness parameterization, in the entire floodplain by fusion of CASI multispectral data with airborne laser scanning (ALS) data. The method consists of two stages: (1) image segmentation of the fused dataset and classification into the most important land cover classes (overall accuracy = 81 percent, and (2) determination of hydrodynamic surface characteristics for each class separately. In stage two, a lookup table provides numerical values that enable roughness computation for water, sand, paved area, meadows and built-up areas. For the other classes, forest and herbaceous vegetation, ALS data enabled spatially detailed analysis of vegetation height and density. The vegetation density of forest is mapped using a calibrated regression model. Herbaceous vegetation was further subdivided in single trees and non-woody vegetation. Single trees were delineated using a novel iterative cluster merging method, and their height is predicted (R = 0.41). The vegetation density of single trees was determined identically to forest Vegetation height and density of non-woody herbaceous vegetation was determined using calibrated regression models. This method provides hydrodynamic modelers with a highly automized procedure for roughness mapping with much spatial detail.