Typical reclamation vegetation classification based on phenological feature parameters for coalfields in Shanxi Province
ZHANG Yanbin1, AN Nan2, LIU Peiyan1, JIA Kun3, YAO Yunjun3
1. Shanxi Automation Research Institute, Taiyuan 030012, China;
2. Ecology & Agriculture Spatial Analysis Laboratory, Department of Agronomy, Kansas State University, Kansas 66506, USA;
3. School of Geography, Beijing Normal University, Beijing 100875, China
In this paper, the authors reconstructed MOD13Q1 time-series NDVI data from 2001 to 2013 using Savitzky-Golay filter and Chebyshev Polynomial methods for classifying vegetation types in the six coalfields in Shanxi Province. The key phenological parameters were extracted from the reconstructed NDVI data, such as the beginning dates of the growing season, length of the growing season, the ending dates of the growing season, the maximum NDVI value and the responding dates. The results show that different vegetation types of the six major coalfields in Shanxi have different phenological features. Cropland has distinguishable differences from grass and forest. Similarly, forest is distinguished from grass and cropland by integration of total growth. It is shown that the classification of vegetation types can achieve better results by extracting and analyzing the phonological parameters compared with multi-temporal unsupervised classification. The overall classification accuracy reaches 89.67%. This study provides a robust method for assessing long-term ecological conditions and monitoring vegetation coverage changes of the six major coalfields in Shanxi Province.
张彦彬, 安楠, 刘佩艳, 贾坤, 姚云军. 基于物候特征参数的山西煤矿区典型复垦植被分类[J]. 国土资源遥感, 2017, 29(1): 170-177.
ZHANG Yanbin, AN Nan, LIU Peiyan, JIA Kun, YAO Yunjun. Typical reclamation vegetation classification based on phenological feature parameters for coalfields in Shanxi Province. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(1): 170-177.
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