A comparison between cluster busting technique and a classification tree algorithm of a moderate resolution imaging spectrometer (MODIS) land cover map of Honduras

Rivera, S. and Lowry, John and Hernandez, A.J. and Ramsey, R.D. and Lezama, R. and Velasquez, M.A. (2012) A comparison between cluster busting technique and a classification tree algorithm of a moderate resolution imaging spectrometer (MODIS) land cover map of Honduras. Geocarto International, 27 (1). pp. 17-29. ISSN 1010-6049

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Abstract

A national land cover map derived from moderate resolution imaging spectrometer (MODIS) imagery products was developed for Honduras, Central America. We compared two methods of image classification: a cluster busting (CB) classification technique and a classification and regression tree (CART) algorithm. Field data samples were used to validate the resulting classifications. In the classification process, we used: a Google Earth™ sampling scheme, a time series of MODIS's Enhanced Vegetation Index (EVI) and digital elevation data(shuttle radar topography mission, SRTM). The CART classification method provided a more accurate classification (Kappa coefficient, K = 74%, overall model accuracy = 79.6%) while compared to the CB classification (Kappa coefficient, K = 9%, overall model accuracy = 25.1%). The findings are useful to design more accurate MODIS classification protocols in tropical countries.

Item Type:	Journal Article
Subjects:	G Geography. Anthropology. Recreation > G Geography (General)
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Geography, Earth Science and Environment
Depositing User:	Ms Shalni Sanjana
Date Deposited:	02 Sep 2013 03:57
Last Modified:	16 Jan 2017 02:46
URI:	https://repository.usp.ac.fj/id/eprint/6491

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