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Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and mode...
The main aim of the study was to assess the potential of a time series of remotely sensed data for the change detection of wetland in Hongze Lake in the Northern Jiangsu Province. The raw data compris...
Remotely sensed data is the most important data source for environmental change study over the past 40 years. Since large collections of remote sensing imagery have been acquired in a time frame of su...
Remote sensing has been increasingly used to derive land cover information by manual interpretation or automated classification. As promising automated classifiers, artificial neural networks are diff...
For the significance of road information to the city management, urban roads are subjects of great concern to be extracted from remotely sensed images. With the availability of high spatial resolution...
The main aim of the study was to assess the potential of a time series of remotely sensed data for the change detection of wetland in Hongze Lake in the Northern Jiangsu Province. The raw data compr...
Geometric co-registration errors and results of object extraction (such as classification and pattern recognition) are the two main factors, which greatly affect the results of change detection in tr...
The recent trend in image classification of agricultural areas is towards the use of per-field approaches that work in a manner that a crop label is assigned to each field. The existing field bounda...
The success of the object-based image analysis (OBIA) paradigm can be attributed to the fact that regions obtained by means of segmentation process are depicted with a variety of spectral, shape, text...

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