Jianguang Liu
College of Natural Resources and Environmental Science, China Agricultural University, Beijing, China
Danfeng Sun
College of Natural Resources and Environmental Science, China Agricultural University, Beijing, China
Feng He
College of Natural Resources and Environmental Science, China Agricultural University, Beijing, China
Weiwei Zhang
College of Natural Resources and Environmental Science, China Agricultural University, Beijing, China
Xiaoke Guan
College of Natural Resources and Environmental Science, China Agricultural University, Beijing, China
ABSTRACT
This study attempted to develop a low-cost, high-precision method to acquire land use/cover data by combining multi-temporal and multi-spectral Moderate Resolution Imaging Spectroradiometer (MODIS). The results indicate that Classification and Regression Tree (CART) algorithm clearly outperforms the Maximum Likelihood (ML) in land use/cover classification using MODIS and the first principal component (PC1) with multi-spectral MODIS image that reflected more soil information can efficiently improve the accuracy of classification based on MODIS NDVI time series.
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How to cite this article
Jianguang Liu, Danfeng Sun, Feng He, Weiwei Zhang and Xiaoke Guan, 2013. Land Use/cover Classification with Classification and
Regression Tree Applied to MODIS Imagery. Journal of Applied Sciences, 13: 3770-3773.
DOI: 10.3923/jas.2013.3770.3773
URL: https://scialert.net/abstract/?doi=jas.2013.3770.3773
DOI: 10.3923/jas.2013.3770.3773
URL: https://scialert.net/abstract/?doi=jas.2013.3770.3773
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