AI Article Synopsis
- Researchers have acknowledged the importance of land-cover characteristics in ecological studies and have previously proposed methods to identify them through remotely sensed time series data.
- Previous methods were often mathematically focused, prompting the need for a more ecological interpretation of land-cover characteristics.
- This study introduces a new method based on sustained vegetation growth trends, utilizing MODIS time series data to analyze five land-cover types, revealing insights into ecosystem growth patterns and traits.
Article Abstract
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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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3722099 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0070079 | PLOS |
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