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RESEARCH PRODUCT
Mapping Vegetation Density in a Heterogeneous River Floodplain Ecosystem Using Pointable CHRIS/PROBA Data
Lammert KooistraE. RomijnJochem Verrelstsubject
010504 meteorology & atmospheric sciencesFloodplainWater flowpointable sensors; CHRIS/PROBA; leaf area index (LAI); inversion; radiative transfer (RT) model; FLIGHT; river floodplain ecosystem; vegetation density; hydraulic roughnessleaf area index (LAI)0211 other engineering and technologiesClimate change02 engineering and technologyCHRIS/PROBA01 natural sciencesforestinversionLaboratory of Geo-information Science and Remote SensingLaboratorium voor Geo-informatiekunde en Remote SensingLeaf area indexcoverlcsh:ScienceZenithriver floodplain ecosystem021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensinggeographychris-proba datahyperspectral brdf datageography.geographical_feature_categoryFLIGHTFlood mythrhine basinradiative-transfer modelHyperspectral imagingEnhanced vegetation index15. Life on landpointable sensorsPE&RCradiative transfer (RT) modelsugar-beetclimate-changeGeneral Earth and Planetary SciencesEnvironmental sciencehydraulic roughnesslcsh:Qflow resistanceleaf-area indexvegetation densitydescription
River floodplains in the Netherlands serve as water storage areas, while they also have the function of nature rehabilitation areas. Floodplain vegetation is therefore subject to natural processes of vegetation succession. At the same time, vegetation encroachment obstructs the water flow into the floodplains and increases the flood risk for the hinterland. Spaceborne pointable imaging spectroscopy has the potential to quantify vegetation density on the basis of leaf area index (LAI) from a desired view zenith angle. In this respect, hyperspectral pointable CHRIS data were linked to the ray tracing canopy reflectance model FLIGHT to retrieve vegetation density estimates over a heterogeneous river floodplain. FLIGHT enables simulating top-of-canopy reflectance of vegetated surfaces either in turbid (e.g., grasslands) or in 3D (e.g., forests) mode. By inverting FLIGHT against CHRIS data, LAI was computed for three main classified vegetation types, ‘herbaceous’, ‘shrubs’ and ‘forest’, and for the CHRIS view zenith angles in nadir, backward (-36°) and forward (+36°) scatter direction. The -36° direction showed most LAI variability within the vegetation types and was best validated, closely followed by the nadir direction. The +36° direction led to poorest LAI retrievals. The class-based inversion process has been implemented into a GUI toolbox which would enable the river manager to generate LAI maps in a semiautomatic way.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2012-09-24 | Remote Sensing |