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River floodplain vegetation scenario development using imaging spectroscopy derived products as input variables in a dynamic vegetation model


Schaepman, Michael E; Wamelink, G W W; van Dobben, H F; Gloor, M; Schaepman-Strub, Gabriela; Kooistra, L; Clevers, J G P W; Schmidt, A; Berendse, F (2007). River floodplain vegetation scenario development using imaging spectroscopy derived products as input variables in a dynamic vegetation model. Photogrammetric Engineering and Remote Sensing, 73(10):1179-1188.

Abstract

River floodplains are becoming increasingly subject to multifunctional land-use. In this contribution, we are linking imaging spectrometer derived products with a dynamic vegetation model to improve the simulation
and evaluation of scenarios for a river floodplain in the Netherlands. In particular, we are using airborne HyMap imaging spectrometer data to derive Leaf Area Index (LAI), spatial distribution of Plant Functional Types (PFT), and model dominant species abundances as input for the ecological model. We use the dynamic vegetation model (DVM) SMART2-SUMO to simulate vegetation succession under scenarios of changing abiotic conditions and man- agement regimes. SMART2 is a soil chemical model whereas SUMO describes plant competition and resulting vegetation succession. We validate all remote sensing derived products and the DVM calibration independently using extensive field sampling. We conclude that the dynamic vegetation models can be successfully initialized using imaging spectrometer data at currently unprecedented accuracy. However, all efforts undertaken for validation in this contribution may significantly exceed capacities for national or continental scale application of the proposed method.

River floodplains are becoming increasingly subject to multifunctional land-use. In this contribution, we are linking imaging spectrometer derived products with a dynamic vegetation model to improve the simulation
and evaluation of scenarios for a river floodplain in the Netherlands. In particular, we are using airborne HyMap imaging spectrometer data to derive Leaf Area Index (LAI), spatial distribution of Plant Functional Types (PFT), and model dominant species abundances as input for the ecological model. We use the dynamic vegetation model (DVM) SMART2-SUMO to simulate vegetation succession under scenarios of changing abiotic conditions and man- agement regimes. SMART2 is a soil chemical model whereas SUMO describes plant competition and resulting vegetation succession. We validate all remote sensing derived products and the DVM calibration independently using extensive field sampling. We conclude that the dynamic vegetation models can be successfully initialized using imaging spectrometer data at currently unprecedented accuracy. However, all efforts undertaken for validation in this contribution may significantly exceed capacities for national or continental scale application of the proposed method.

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12 citations in Web of Science®
13 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:2007
Deposited On:20 Mar 2013 16:28
Last Modified:05 Apr 2016 16:42
Publisher:American Society for Photogrammetry and Remote Sensing
ISSN:0099-1112
Free access at:Official URL. An embargo period may apply.
Official URL:http://www.asprs.org/a/publications/pers/2007journal/october/2007_oct_1179-1188.pdf
Permanent URL: https://doi.org/10.5167/uzh-76786

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