Identification of Land-Cover Characteristics Using MODIS Time Series Data: An Application in the Yangtze River Estuary
Author(s) -
Mo-Qian Zhang,
Haiqiang Guo,
Xiao Xie,
Tingting Zhang,
Zutao Ouyang,
Bin Zhao
Publication year - 2013
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0070079
Subject(s) - land cover , vegetation (pathology) , ecosystem , time series , environmental science , estuary , land use , series (stratigraphy) , remote sensing , hyperspectral imaging , ecology , geography , computer science , machine learning , biology , medicine , paleontology , pathology
Land-cover characteristics have been considered in many ecological studies. Methods to identify these characteristics by using remotely sensed time series data have previously been proposed. However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics. In this study, a method for identifying these characteristics was proposed from the ecological perspective of sustained vegetation growth trend. Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position. Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis. The results show that the extracted parameters can reflect ecosystem growth patterns and portray ecosystem traits such as vegetation growth strategy and ecosystem growth situations.
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