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Open AccessArticle

A Texture-Based Land Cover Classification for the Delineation of a Shifting Cultivation Landscape in the Lao PDR Using Landscape Metrics

1
Department of Integrative Geography (DIG), Institute of Geography, and Centre for Development and Environment (CDE), University of Bern, Hallerstrasse 10, CH-3012 Bern, Switzerland
2
Centre for Development and Environment (CDE), University of Bern, Hallerstrasse 10, CH-3012 Bern, Switzerland
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Author to whom correspondence should be addressed.
Remote Sens. 2013, 5(7), 3377-3396; https://doi.org/10.3390/rs5073377
Received: 3 June 2013 / Revised: 9 July 2013 / Accepted: 9 July 2013 / Published: 15 July 2013
The delineation of shifting cultivation landscapes using remote sensing in mountainous regions is challenging. On the one hand, there are difficulties related to the distinction of forest and fallow forest classes as occurring in a shifting cultivation landscape in mountainous regions. On the other hand, the dynamic nature of the shifting cultivation system poses problems to the delineation of landscapes where shifting cultivation occurs. We present a two-step approach based on an object-oriented classification of Advanced Land Observing Satellite, Advanced Visible and Near-Infrared Spectrometer (ALOS AVNIR) and Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) data and landscape metrics. When including texture measures in the object-oriented classification, the accuracy of forest and fallow forest classes could be increased substantially. Based on such a classification, landscape metrics in the form of land cover class ratios enabled the identification of crop-fallow rotation characteristics of the shifting cultivation land use practice. By classifying and combining these landscape metrics, shifting cultivation landscapes could be delineated using a single land cover dataset. View Full-Text
Keywords: shifting cultivation; landscape metrics; remote sensing; image segmentation; texture shifting cultivation; landscape metrics; remote sensing; image segmentation; texture
MDPI and ACS Style

Hurni, K.; Hett, C.; Epprecht, M.; Messerli, P.; Heinimann, A. A Texture-Based Land Cover Classification for the Delineation of a Shifting Cultivation Landscape in the Lao PDR Using Landscape Metrics. Remote Sens. 2013, 5, 3377-3396.

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