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The RF method based on grid-search parameter optimization could achieve a classification accuracy of 88.16 % in the classification of images with multiple feature variables. This classification ...
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...
Residential areas show plenty of texture information on high resolution remotely sensed imagery. Appropriate description about this texture information for discriminating residential class and its bac...
Road tracking is a promising technique to increase the efficiency of road mapping. In this paper an improved road tracker, based on cooperation between angular texture signature and template matching,...
The remote sensing community has long been active in developing, evaluating, and comparing different classification algorithms using a variety of remotely sensed imagery. As an integral component of i...
Using high-resolution remotely sensed imagery to timely detect distribution and expansion of residential area is one of most important jobs of national 1:5 spatial database updating. In view of comp...
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...
In order to understand causes and effects of disturbance and fragmentation on flora and fauna, a time series on land cover change is needed as basis for the BIOTA-East Africa project partners working ...
Applying the region growing to the Kohonen’s self-organizing feature map, a non-supervised classifier for remotely sensed imagery data is proposed. If the self-organizing feature map is made large e...

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