Texture and shape analysis offer interesting possibilities to characterize the structural heterogeneity of classes in the high spatial resolution satellite imagery. In this paper, texture features are generated based ...
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Texture and shape analysis offer interesting possibilities to characterize the structural heterogeneity of classes in the high spatial resolution satellite imagery. In this paper, texture features are generated based on the Gaussian Markov random field (GMRF) model, and shape features are measured using geometric moments. Then feature selection is implemented according to the class separability. To reduce the border blurring effect introduced by texture features, the unsupervised classification algorithm involved ordered procedures is proposed, in which linear objects are extracted using spectral and shape features firstly, then other objects are detected using the combination of spectral, texture, and shape features. The proposed classification method is implemented using QuickBird imagery. For comparison, the standard K-means method with spectral data is used as a benchmark. The experimental results show that the ordered classification method with the combination of spectral, texture, and shape information performed better than conventional methods.
Monitoring and assessing vegetative land cover change is important to resources management and the study of environmental changes. This paper, using the 1 km SPOT Normalized Difference Vegetation Index (SPOT/NDVI) (19...
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Monitoring and assessing vegetative land cover change is important to resources management and the study of environmental changes. This paper, using the 1 km SPOT Normalized Difference Vegetation Index (SPOT/NDVI) (1998 - 2006) data in growing seasons (April-September), assesses changes of vegetative land cover in Wujiang River Basin (WRB), Southwest China from 1998 to 2006. The results demonstrate that vegetative land cover shows a slight trend of amelioration in general during thees 9 years. Especially in the southwest part of WRB, the vegetations improve greatly, while in the surrounding of Guiyang and Zunyi, vegetative land cover degrades or decreases. When analyzing the relationship between vegetation and its potential driving forces, such as climate and population factors, we find out that the changes of vegetations have no obvious links to climate variation, but they show correlation with the increasing population. These findings may serve as a basis for decision making with regard to land resource management and environmental protection.
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