Comparison of land cover classification methods based on single-temporal MODIS data

Tao Han; Xiaotao Xu; Yaohui Li; Yaowen Xie

doi:10.1117/12.813218

7 November 2008 Comparison of land cover classification methods based on single-temporal MODIS data

Tao Han, Xiaotao Xu, Yaohui Li, Yaowen Xie

Proceedings Volume 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images; 71470H (2008) https://doi.org/10.1117/12.813218
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Based on single-temporal MODIS data of Gansu province, mainly using its spectra information, three classifiers - the Maximum likelihood, BP neural network and decision tree based on data mining software See 5.0 are applied in the Land cover classification research. The validated results show that decision tree algorithm has the best performance of extraction with an overall accuracy of 82.13 percent, followed by the BP network algorithm, and that of the maximum likelihood classifier is worst; the accuracy of low vegetation area is improved with the indexes of TVA and TVD; Data mining software of See 5.0 with boosting technique can build decision tree quickly and improve the precision of miscible classes.

Citation Download Citation

Tao Han, Xiaotao Xu, Yaohui Li, and Yaowen Xie "Comparison of land cover classification methods based on single-temporal MODIS data", Proc. SPIE 7147, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images, 71470H (7 November 2008); https://doi.org/10.1117/12.813218

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