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Journal of Plant Ecology 2008 1(1):9-23; doi:10.1093/jpe/rtm005
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© The Author 2008. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

Remote sensing imagery in vegetation mapping: a review

Yichun Xie1,*, Zongyao Sha1,2 and Mei Yu3

1 Department of Geography and Geology, Eastern Michigan University, Ypsilanti, MI 48197, USA
2 International Software School, Wuhan University, Wuhan, Hubei Province 430079, China
3 Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China

* Correspondence address. Department of Geography and Geology, Eastern Michigan University, Ypsilanti, MI 48197, USA. Tel: +1-734-487-0218; Fax: +1-734-487-6979; E-mail: yxie{at}emich.edu

Aims: Mapping vegetation through remotely sensed images involves various considerations, processes and techniques. Increasing availability of remotely sensed images due to the rapid advancement of remote sensing technology expands the horizon of our choices of imagery sources. Various sources of imagery are known for their differences in spectral, spatial, radioactive and temporal characteristics and thus are suitable for different purposes of vegetation mapping. Generally, it needs to develop a vegetation classification at first for classifying and mapping vegetation cover from remote sensed images either at a community level or species level. Then, correlations of the vegetation types (communities or species) within this classification system with discernible spectral characteristics of remote sensed imagery have to be identified. These spectral classes of the imagery are finally translated into the vegetation types in the image interpretation process, which is also called image processing. This paper presents an overview of how to use remote sensing imagery to classify and map vegetation cover.

Methods: Specifically, this paper focuses on the comparisons of popular remote sensing sensors, commonly adopted image processing methods and prevailing classification accuracy assessments.

Important findings: The basic concepts, available imagery sources and classification techniques of remote sensing imagery related to vegetation mapping were introduced, analyzed and compared. The advantages and limitations of using remote sensing imagery for vegetation cover mapping were provided to iterate the importance of thorough understanding of the related concepts and careful design of the technical procedures, which can be utilized to study vegetation cover from remote sensed images.

Keywords: vegetation mapping • remote sensing sensors • image processing • image classification


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