D
Dengsheng Lu
Researcher at Fujian Normal University
Publications - 169
Citations - 19643
Dengsheng Lu is an academic researcher from Fujian Normal University. The author has contributed to research in topics: Thematic Mapper & Impervious surface. The author has an hindex of 54, co-authored 158 publications receiving 16579 citations. Previous affiliations of Dengsheng Lu include Michigan State University & Indiana University.
Papers
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Change detection techniques
TL;DR: This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature and summarizes and reviews these techniques.
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A survey of image classification methods and techniques for improving classification performance
Dengsheng Lu,Qihao Weng +1 more
TL;DR: It is suggested that designing a suitable image‐processing procedure is a prerequisite for a successful classification of remotely sensed data into a thematic map and the selection of a suitable classification method is especially significant for improving classification accuracy.
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Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies
TL;DR: In this article, the applicability of vegetation fraction derived from a spectral mixture model as an alternative indicator of vegetation abundance was investigated based on examination of a Landsat Enhanced Thematic Mapper Plus (ETM+) image of Indianapolis City, IN, USA, acquired on June 22, 2002.
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The potential and challenge of remote sensing‐based biomass estimation
TL;DR: In this article, a review of previous research on remote sensing-based biomass estimation approaches and a discussion of existing issues influencing biomass estimation are valuable for further improving biomass estimation performance, especially in those study areas with complex forest stand structures and environmental conditions.
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Use of impervious surface in urban land-use classification
Dengsheng Lu,Qihao Weng +1 more
TL;DR: In this article, the authors explored extraction of impervious surface information from Landsat Enhanced Thematic Mapper data based on the integration of fraction images from linear spectral mixture analysis and land surface temperature.