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

被引：33

作者：

Hurni, Kaspar ^{[1
,2
]}

Hett, Cornelia ^{[2
]}

Epprecht, Michael ^{[2
]}

Messerli, Peter ^{[2
]}

Heinimann, Andreas ^{[1
,2
]}

机构：

[1] Univ Bern, DIG, Inst Geog, CH-3012 Bern, Switzerland

[2] Univ Bern, CDE, CH-3012 Bern, Switzerland

来源：

REMOTE SENSING | 2013年 / 5卷 / 07期

基金：

瑞士国家科学基金会;

关键词：

shifting cultivation; landscape metrics; remote sensing; image segmentation; texture; SATELLITE IMAGERY; CARBON STOCK; SWIDDEN; METHODOLOGY; ACCURACY; FORESTS; PATTERN; BIOMASS; SYSTEMS; DEM;

D O I：

10.3390/rs5073377

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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.

引用

页码：3377 / 3396

页数：20

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