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The study of flood detection is significant to human life and social economy. In this paper, a completely unsupervised flood detection approach is presented, which combines spatio-temporal context and histogram thresholding. A global thresholding algorithm can be used in most of the cases to distinguish flood from non-flood pixels, but it may not distinguish local grey-level changes when the method...
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...
Compared with the single remote sensing image, the time series images provide more information of ground objects, which can greatly improve the clustering accuracy. But time series clustering also has many difficulties, such as the impacts of cloud and other sharp noise. The sharp noise impacts time series clustering by affecting the calculation of the similarity measure of sequences. Therefore, this...
This paper introduces an improved image registration method for infrared and visible remote sensing image based on NSCT and SIFT algorithm. As the infrared and visible spectral characteristics of remote sensing images are inconsistent, the gray difference between these two images are quite distinct, so there are less matching points by using SIFT algorithm directly. The method of NSCT can decompose...
This paper proposes a novel object-oriented building extraction method based on fuzzy support vector machines (SVM). The choice to adopt an SVM classification technique is motivated by the high number of parameters derived from the feature-extraction phase, which requires a classifier suitable to the analysis of hyper-dimensional features spaces. This method can be divided into two different phases:...
In the change detection of remote sensing images, the brightness and colors need to be adjusted at first in order to make two images almost have the same radiation (relative radiometric normalization (RRN)). However, hazes in images often influence the effect of relative radiometric correction. In this paper, we proposed a new approach to detect and remove hazes from high-resolution panchromatic images...
Rapid development of urban area makes data update more often than ever. Building is an important element of geographical information. So, it is important to detect building changes in urban areas timely. This paper proposes a novel technique for building change detection based upon similarity calibration. In this paper, we define the types of building changes clearly, and introduce how to analyze...
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