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标题：REGIONAL MAPPING OF PLANT FUNCTIONAL TYPES IN RIVER FLOODPLAIN ECOSYSTEMS USING AIRBORNE IMAGING SPECTROSCOPY DATA
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作者：L. Kooistra ; L. Sanchez-Prieto ; H.M. Bartholomeus 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2007
卷号：XXXVI-7/C50
出版社：Copernicus Publications
摘要：Monitoring and forecasting of natural vegetation succession is essential for optimal management of river floodplain ecosystems in Western Europe. For example the development of woody vegetation types (e.g., softwood forest) increases the hydraulic resistance of the floodplain and can have negative effects on the discharge capacity of the river. However, from a biodiversity point-of-view this development results in higher valued nature reserves. The current challenge for river managers is therefore how to combine sustainable flood protection and floodplain rehabilitation in the best possible way. Natural vegetation in these floodplain ecosystems consists of a continuum between grassland and forest. Ground coverage by woody plants (trees and shrubs) ranges from non-existent to complete and forms a mosaic pattern within the ecosystem. Dynamic vegetation modeling becomes an increasingly important tool to assess the current and future state of these complex ecosystems. In this approach, remote sensing is used to derive spatial continuous input date of the state of the ecosystem to initialize these models at simulation start. Also site-specific remote sensing derived variables (e.g., LAI, biomass, canopy N) are assimilated in these models resulting in more reliable and accurate predictions. Interfacing between remote sensing and dynamic vegetation models requires a proper representation of the grassland-forest continuum. For global scale modeling, plant functional types (PFT), i.e., groups of plant species that share similar functioning are adopted to represent vegetation distribution and derived using remote sensing based methods. Also on a regional scale the use of PFTs could be of interest to map vegetation heterogeneity through separately specifying the composition and structure of PFTs within a grid cell. In this study we investigate the possibilities to derive the spatial distribution of PFTs for floodplain ecosystems from imaging spectroscopy data at the regional level. Field and airborne data (HyMap) were acquired for a floodplain along the river Rhine in the Netherlands and used to derive spatial continuous PFT maps. Spectra of main PFTs (grass, herbs, shrub, and trees) were selected from the image data and identified as endmembers using a site-specific library. The results show that spectral unmixing analysis can be used for mapping plant functional types to characterize the complex structure and composition of a natural floodplain ecosystem. Spatial distributions of herbaceous and tree PFTs are well in agreement with actual situation as observed in the field. Modelled fractional coverage of the herbaceous PFTs agreed reasonable well with field observed abundances (R 2 between 0.35 and 0.56). Further work is required to upscale the approach from the floodplain level to the river catchment scale using medium-resolution sensors like MODIS and MERIS
关键词：imaging spectroscopy; spectral mixture analysis; plant functional types; plant traits; dynamic vegetation model