Land cover mapping at sub-pixel scales using linear optimization techniques

被引:232
作者
Verhoeye, J [1 ]
De Wulf, R [1 ]
机构
[1] State Univ Ghent, Fac Agr & Appl Biol Sci, Lab Forest Management & Spatial Informat Techniqu, B-9000 Ghent, Belgium
关键词
D O I
10.1016/S0034-4257(01)00242-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Mixed pixels result when the sensor's instantaneous field-of-view includes more than one land cover class on the ground. For mixed pixels, fuzzy classifiers can be used, which assign a pixel to several land cover classes in proportion to the area of the pixel that each class covers. These fraction values can be assigned to sub-pixels, based on the assumption of spatial dependence and the application of linear optimization techniques, A newly proposed sub-pixel mapping algorithm was first applied to a synthetic data set with a 1-km resolution, derived from a 20-m resolution image. This algorithm yielded land cover maps at 500, 200, and 100 m resolution with accuracies close to 89%. Subsequent mode filtering further increased these values. When applied to a real data set. the accuracy reached 78%. While this study suggests the potential of the proposed technique. there is still ample scope for improvements and extensions. (C) 2002 Elsevier Science Inc. All rights reserved.
引用
收藏
页码:96 / 104
页数:9
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