Land cover classification based on the MODIS-EVI time-series using decision tree method

Ran Meng; Zhiqiang Gao

doi:10.1117/12.824096

20 August 2009 Land cover classification based on the MODIS-EVI time-series using decision tree method

Ran Meng, Zhiqiang Gao

Proceedings Volume 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI; 745410 (2009) https://doi.org/10.1117/12.824096
Event: SPIE Optical Engineering + Applications, 2009, San Diego, California, United States

Abstract

The MODIS data has high temporal resolution but rather coarse spatial resolution, therefore, the MODIS-EVI data, which was more sensitive towards the phonological information than the MODIS-NDVI data, was chosen to build up the time series of studying area, in order to monitor and depict the original phonological characteristics of land cover. Moreover, the DEM, SLOPE, Homogeneity data, which all represent the differences of geographical distribution, and LST data, which represents the differences of earth-atmosphere interaction, were combined as ancillary data together with MODIS-EVI to build a decision tree. After the classification validation, the overall accuracy attainted to 71.9% and Kappa coefficient is 0.66. Therefore, it is proved that the land cover classification with high accuracy but low cost in regional scale is possible.

Citation Download Citation

Ran Meng and Zhiqiang Gao "Land cover classification based on the MODIS-EVI time-series using decision tree method", Proc. SPIE 7454, Remote Sensing and Modeling of Ecosystems for Sustainability VI, 745410 (20 August 2009); https://doi.org/10.1117/12.824096

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KEYWORDS

MODIS

Vegetation

Spatial resolution

Remote sensing

Data modeling

Denoising

Ecosystems

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