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considerably increased. For flood disaster risk reduction, it is important to identify and characterize flood area, locations (particularly lowland along rivers), and durations. For this purpose, floo...
To serve seamless mapping, airborne LiDAR data are usually collected with multiple parallel strips with one or two cross strip(s). Nevertheless, the overlapping regions of LiDAR data strips are usuall...
Thee rapid advances in hyperspectral sensing technology have made it possible to collect remote sensing data in hundreds of bands. However, the data analysis methods which have been successfully appli...
A new dynamical dimensional reduction model (HDRM) for hyperspectral images is proposed based on clone selection algorithm which is inspired from nature immune system in this paper. In existing dimens...
A dimensionality reduction algorithm based on feature extraction of the spectral curve using fractal analysis which considering both the spatial characteristic and spectral characteristic of hyper spe...
Synthetic aperture radar (SAR) images always suffer from strongly speckle noise, which is a great obstacle to coherence (or correlation coefficient) estimation and interferometric phase, furthermore h...
Atmospheric water vapour effects represent a major limitation of repeat-pass Interferometric SAR (InSAR) techniques including InSAR time series approaches (e.g. permanent scatterers (PS) and small bas...
Noise is an important factor that influences image quality, which is mainly produced in the processes of image acquirement and transmission. Noise reduction is necessary for us to do image processing ...
Position information obtained from standard GPS receivers is known to be corrupted with noise. To make effective use of GPS information in a navigation system it is essential to model this noise and t...
Over the past thirty years, the hyperspectral remote sensing technology is attracted more and more attentions by the researchers. The dimension reduction technology for hyperspectral remote sensing im...
Limitations and deficiencies of different remote sensing sensors in extraction of different objects caused fusion of data from different sensors to become more widespread for improving classificatio...
The need for variety and better accuracy of the map products used in the rapidly evolving GIS technology has necessitated the use of analytical techniques in photogrammetric data processing. The ready...
The processing of hyperspectral remote sensing data, for information retrieval, is challenging due to its higher dimensionality. Machine learning based algorithms such as Support Vector Machine (SVM) ...
This paper combine two conventional feature extraction methods (NWFE&NPE) in a novel framework and present a new semi-supervised feature extraction method called Adjusted Semi supervised Discriminant ...
Nowadays lidar has become a leading edge technology for photogrammetry and remote sensing. A new lidar with two detection wavelengths was presented in this paper. The two-wavelength lidar can obtain s...

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