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The Separability and Thresholds (SEaTH) algorithm calculates the the SEparability and the corresponding THresholds of object classes for any number of given features. However, it is applicable only to the normally distributed training data. To cope with the problem, The Classification And Regression Tree (CART) coupled with SEaTH for object-based classification approach is proposed in the paper. The...
The parcel-based changed detection by adopting the holistic feature can extract the changed parcels in land-use maps[1]. This method of parcel-based change detection uses the holistic feature, which represents each land use parcels clipped by polygons in the land use map with the energy spectrum of WFT and extracts the changed parcels according to the distance threshold between feature vectors associated...
Multi-scale spatial context which integrates spatial metrics and textural metrics is used to characterize land-use parcel and a hybrid land-use mapping approach is proposed in this paper. In terms of land-use characterization, the contributions of textural and spatial metrics are evaluated quantitatively. In terms of land-use categorization, a hybrid land-use classification scheme which combines Pairwise...
Monitoring snow distribution area plays an important role in researching climate change and energy exchange process. Chinese small satellite constellation (abbreviated HJ constellation) is special for environment and disaster continuously monitoring or forecasting. By using HJ-1B CCD and infrared data or only using its infrared data, it can construct NDSI (Normalized Difference Snow Index) or MNDSI...
Road traffic volume monitoring plays an important role in transportation planning and spatial development, particularly in urban areas. The high-resolution satellite imagery provides a new data source to detect vehicles. Meanwhile, Satellite image covers large areas instantaneously, providing a possibility for snapshotting road traffic conditions. In this paper, we proposed an approach based on watershed...
In object-oriented classification approaches, small sample size and high dimensionality of features are the two main characteristics. In order to effectively use the rich features of the image objects, in this study, the Relief algorithms were improved in terms of aspects of randomly drawing samples, the influence of sample quantity variance, and iteration times to evaluate the features. Through experiments...
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