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Supervised classification in remote sensing imagery is receiving increasing attention in current research. In order to improve the classification accuracy, a lot of spatial-features (e.g., texture information generated by GLCM) are often utilized. Unfortunately, too many spatial-features usually reduce the computation speed of remote sensing classification, that is, the time complexity may be increased...
In recent years, various kinds of satellite-derived aerosol products have been used to air quality monitoring. However, satellites are not sensitive to the near surface aerosol which impacts human health but the entire aerosol column. In this paper, we establish an artificial neural network (ANN) instead of multiple regression technique to lessen the surface PM2.5 estimation uncertainty from remote...
In order to improve water quality evaluation of multi-spectral image accurately,this paper puts forward a model for water quality evaluation based on RBF Neural Network with parameters optimized by particle swarm optimization algorithms. The model uses High-resolution multi-spectral remote SPOT-5 data and the water quality field data, chose four representative water quailty parameters, RBF Neural...
Partial cloud removal from remote sensing images composed of three sequential steps: accurate cloud and cloud shadow detection of the remote sensing image and corresponding cloud mask generation, phenology simulation for adjacent temporal images, fusion for blending artificial effects of composite image. Phenology simulation predicts what the surface features would look like in fields beneath clouds...
This paper addresses the problem of remote sensing image multi-scale classification by: (i) showing that using multiple scales does improve classification results, but not all scales have the same importance; (ii) showing that image descriptors do not offer the same contribution at all scales, as commonly thought, and some of them are very correlated; (iii) introducing a simple approach to automatically...
In this paper, we propose a new method for remote sensing image pan-sharpening which is based on weighted red-black (WRB) wavelet and adaptive principal component analysis (PCA), where the adaptive PCA is used to reduce spectral distortions and the utilization of WRB wavelet is used to extract the spatial details in PAN images. To reduce the artifacts and spectral distortions in the pan-sharpened...
As a reliable and effective feature descriptor, SIFT garners more and more attention in image registration for its capability of scale and rotation invariance. This paper proposes a novel image registration method to utilize SIFT in spectrum disparity cases. The new method uses the local correlation based on phase congruency and is introduced to reinforce original similarity measurement and obtain...
Based on SPOT5 remote sensing image in 2008, we selected two golf courses — one in urban area of Shenzhen and the other in the forest area of Shenzhen, as the two study areas. First, we made principal components analysis of the two areas for data compression and enhancing geometric information. Second, we processed the image and filtered the noise by the wavelet transformation, and the textures of...
Concept and method of energy-morphological operations are simply expounded. The paper studies properties in hyper-spectral remote sensing data. The optimal bands are obtained by the correlation and information quantity, then gradient and edge are acquired by energy-morphological function, and then we can gain image constructed by gradients map overlaying edge map. Finally, by local minima values and...
Poyang Lake wetland is an important ecological functional areas against floods, improve the climate and achieve sustainable development in Poyang Lake Ecological Economic Region(PLEER). Wetland monitoring is the basis for its protection and exploitation. This article discusses wetland monitoring remote sensing technology in the PLEER. After analysis of remote sensing images using Landsat-7 specific...
This paper researched the spatial pattern dynamic change of vegetation on China-Russian border area form 1998 to 2007 using NDVI data of 10-day synthesis. Then the analysis had been made on the relationship between vegetation coverage change and economic factors using data from local statistical yearbook. Results showed that that mostly research areas were well covered and vegetation coverage trend...
Aim to the difficulty of acquisition of conjugate points from multi-source remote sensing imagery, a novel matching method based on SIFT and CRA similarity measure is proposed. Firstly, the SIFT operator is adopted to extract feature points and coarse match is performed, the approximate transformation relationship and the rotation angle between the matched images are estimated by the above matching...
An artificial neural network (ANN) was applied to predict monthly shoreline changes at various locations along 25km of the Noor Bay, southern Caspian Sea. The shoreline variations in 8 stations for a period of about 11 years were studied using ANN. The model results were compared with field data. The properties of the wave (height, period, energy by different equations) and wind data were fed to a...
In this paper we discuss some relevant features observed concerning wave penetration at P-band in boreal and tropical forests. The discussion will be based on results obtained from the multi-polarimetric and multi-baseline data-sets relative to the forest sites within the Krycklan river catchment, Sweden, and the area of Paracou in French Guyana, collected in the frame of the ESA campaign BioSAR 2008...
The accuracy of the digital elevation model (DEM) generated by the interferometric synthetic aperture radar (SAR) partly depends on the accuracy of system parameters, so it is necessary to calibrate the system parameters. The traditional calibration method models the elevation error as a linear function of parameter biases, and solves the biases through the sensitivity equations. This paper presents...
This paper presents an algorithm for locally adaptive template sizes in normalized cross-correlation (NCC) based image matching for measuring surface displacement of mass movements. After adaptively identifying candidate templates based on the image signal-to-noise ratio (SNR), the algorithm iteratively looks for the size at which the maximum cross-correlation coefficient attains a local peak and...
In this paper, we set to investigate the orientation and structure parameters retrieved from POLSAR observations for canopy scattering and evaluate their capability to improving physical retrievals for vegetation and forest targets. Both the orientation and structure parameters of the canopy can be described as a cloud of spheroids with independent orientation distribution and shape distribution....
The German joint project DeCover 2 is developing a methodological framework to cope with the increasing demand for up-to-date land cover information using remote sensing techniques. New satellite systems like RapidEye provide both data of high geometric resolution and high repetition rates. Because of the Germany-wide diversity of natural conditions, same acquisition dates don't correspond to same...
This paper presents a novel active-learning (AL) technique in the context of the cascade classification of multitemporal remote-sensing images for updating land-cover maps. The proposed AL technique is based on the selection of unlabeled samples that have maximum uncertainty on their labels assigned by cascade classification, and explicitly exploits temporal correlation between multitemporal images...
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