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This paper studies the potential interest of the multivariate Pearson system for the statistical modeling of images acquired by different sensors. These images include optical and synthetic aperture radar (SAR) remote sensing images. The univariate Pearson system has shown good capacities to capture the statistical properties of SAR images. This paper introduces a generalization of this system to...
Optimal segmentation results can be obtained by synthetic aperture radar (SAR) image segmentation based on the Markov Random Field (MRF) model. However, MRF segmentation is very time-consuming because of employing the simulated annealing algorithm to optimize energy function. To speed up SAR image segmentation based on the MRF model, this paper investigates a fast segmentation approach for SAR imagery...
Urban areas are highly complex scenes and thus single buildings are often hard to extract. A combination of complementary features of high-resolution interferometric SAR (InSAR) data and optical imagery can add valuable information in case one data source leads to ambiguous results. In addition, contextual information like the sun shadow, front yards, and driveways can act as hints for buildings....
A method to calibrate the geo-location accuracy of optical sensors is presented which is based on a novel multi-modal image matching strategy. This concept enables to transfer points from highly accurate TerraSAR-X imagery to optical images. These points are then used to register the images or to update the optical sensor models. The potential of the methodology is demonstrated on Spot 5, Ikonos and...
A novel approach for building extraction in high resolution optical and SAR images and its application to building change detection are presented in this paper. The proposed object-based building extraction technique relies on an hypothesis generation-optimization-validation scheme, whose estimation and detection performances are characterized on Quickbird and TerraSAR-X semi-urban images. The introduced...
We propose a robust and reasonably fast approach to provide phase estimation and stable target (Persistent Scatterers, PS) detection from a set of repeated pass interferometric acquisitions. The major assumption is that, locally, the PS phase model is decomposed into the separable product of the intrinsic target phase times the optical path, that is common to all the targets in the estimation window...
In the tropical regions, due to frequent cloud cover, optical remote sensing usually does not have adequate multi-temporal high resolution imagery to monitor phenology of forest. This paper seeks to improve mapping of tropical forest by combination of optical and microwave imagery. The study area is located in the southern part of Vietnam. Firstly, ALOS/AVNIR-2 images were used to create a forest...
Given the different nature of optical and radar data, it is reasonable the idea that each type of data can contribute in complementary ways for different applications. This paper aims at analyzing the potential joint usage of optical and Synthetic Aperture Radar (SAR) data for land use and land cover classification in a region located in the Brazilian Amazon. To achieve this objective, we evaluated...
In this paper,we propose a hierarchical Markovian framework to extract the road network with optical and synthetic aperture radar (SAR) data. We propose a generalization of a previous method based on a low-level step (features extraction) and a high-level step (use of contextual information). The main novelties of the proposed approach are the use of more general elements to represent road candidates,...
The work presented in this paper is devoted to the analysis of SAR images in order to produce at first a human settlements map, followed by a refined classification of the same dataset in order to extract a Land Use Land Cover (LU/LC) map based on CORINE nomenclature. The urban extents are computed using an approach based on Local Indicators of Spatial Association and textural features while the LU/LC...
This work aims to assess the potential of Synthetic Aperture Radar (SAR) data combined with optical data to support local administrations in the knowledge of the land use and land cover at regional scale. In particular, the contribution of data available in the future through the SIASGE project, combining L-band and X-band radar imagery, is assessed in order to produce thematic maps. Moreover, the...
In this paper, an advanced synergetic algorithm for aerosol retrieval from small satellite data is presented and applied on MODerate resolution Imaging Spectroradiometer (MODIS) and the Hyper-Spectral Imager (HSI) data from China HJ-1A satellite of the Environment and Disasters Monitoring Microsatellite Constellation. Using this algorithm, 500m MODIS data are downscaled to 100m based on maximal mutual...
Urban areas grow and change rapidly all over the world. Hence, regular and up-to-date information on urban changes is required for urban planning and disaster management. In this study, two temporal TerraSAR-X images are used to monitor urban changes. The study area is focused on a part of central Tokyo, Japan. Firstly, the changes between two images are checked by color composition. Then the difference...
Automatic detection and recognition of ship in satellite images is very important and has a wide array of applications. This paper concentrates on optical satellite sensor, which provides an important approach for ship monitoring. Graph-based fore/background segmentation scheme is used to extract ship candidant from optical satellite image chip after the detection step, from course to fine. Shadows...
Unlike PAN sharpening, the fusion of SAR with multispectral data involve use of non-overlapping spectral bands which poses certain inconsistencies viz. 1) radiometric differences due to their acquisition in entirely different spectral bands 2) geometric differences due to range and angular imaging of SAR and Optical sensors respectively. Apart from these, speckle noise and registration related factors...
The main missions of HJ-1 satellite are to monitor pollution, ecosystem destruction and natural disasters. In recent years, Inhalable particle (PM10) has become the primary pollutant of major cities in China, which seriously affects the living environment of its residents. In this paper, we made use of high-resolution CCD data of HJ-1 satellite to monitor atmospheric inhalable particle (PM10) in Shenzhen...
The accuracy of rainforests classification is generally improved by the input of multisensory data since complex vegetation type identification benefits from complementary information. However, in some cases, multisource fusion can also deteriorate accuracy when irrelevant sources are added. Thus, we introduce a fusion method for classes “in difficulty”. Our method outperforms the classical global...
The integration of optical and radar sensors in a common area is an important task in data fusion as well as other applications. The objective of this study is to perform the feature-based registration of ALOS PALSAR and AVNIR-2 images. The proposed method iteratively minimizes the discrepancy between the feature edges in PALSAR and AVNIR-2 images. A coarse-to-fine strategy is also adopted by applying...
The registration of synthetic aperture radar imagery to other images is difficult, especially in mountainous terrain. We introduce a new approach to this problem that registers radar images to digital elevation models derived from LIDAR. The algorithm generates a predicted image from the elevation model using the radar geometry and then registers the predicted image to the radar image with normalized...
The radiation from the sun to satellites in the sky is always modulated twice by atmosphere. Aerosol is one of the most active components in atmosphere and it usually contaminates the remotely sensed imagery severely so that most remotely sensed imagery cannot be used without atmospheric effect correction. However, the remotely sensed imagery is always the coupling of atmosphere and land surface information,...
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