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This paper proposes a novel speckle reduction method that combines an advanced statistical distribution with spatial contextual information for SAR data. The method for despeckling is based on a Markov random field (MRF) that integrates a K-distribution for the SAR data statistics and a Gauss-MRF model for the spatial context. These two pieces of information are combined based on weighted summation...
Focusing on the issue of echo data acquire approach in bistatic SAR system. In this paper, the key technology of echo sampling window synchronization is introduced, the effect of echo sampling window synchronization error to the echo data and image performance are analyzed, an adaptive echo sampling window synchronization approach based on amplitude demodulation and phase compare is proposed, which...
The quality of Synthetic Aperture Radar image is affected by the deviation of radar platforms from the nominal straight line which is usually measured based on hardware such as Inertial Measurement Unit and Global Position System with high accuracy. Because of limited budget, many SAR systems cannot carry those expensive equipments. Based on the 3-D Geometry model of the motion error analysis, a new...
The discrepancies caused by different cluster merging algorithms in fully polarimetric SAR classification are analyzed here. There are two often-used merging schemes, i.e., merging first to desirable cluster numbers and then iterative clustering and, the agglomerative hierarchical clustering, both using three different between-cluster distance measures herein. One sub-image of RadarSat-2 SAR SLC image...
This paper addresses the problem of object localization using only angle-of-arrival (AoA) data from satellites. Traditionally, this is performed by a triangulation algorithm (TA) that minimizes the distances between the estimated object location to all lines-of-sight representing measurements of the object. However, when observing objects from satellites, the differences in distance from each satellite...
A prominent issue with the state of current terrestrial biosphere models pertains to unrealistic parameterizations of model parameters in space and time. Key biochemical controls on carbon uptake by vegetation canopies are typically assigned fixed literature-based values for broad categories of vegetation types despite the fact that these are affected by a complex interplay of environmental and physiological...
Two field experiments have been conducted in Sweden to allow an evaluation of the backscatter signatures of wind-thrown forest from L-band, C-band and X-band Synthetic Aperture Radar. When the trees are felled the backscattered signal from TerraSAR-X (X-band) increase with about 1.5 dB, while for ALOS PALSAR (L-band) a decrease with the same amount is observed. Radar images with fine spatial resolution...
A method based on radiative transfer models (RTM) incorporating multi-angle data is used to estimate LAI. The estimation of LAI from inversion will be based on Look Up Tables (LUT) approach. The usefulness of the method was verified using the data of Spectral database of Chinese typical features. The determination coefficient R2 between estimated result and measurement data is high to 0.6046. The...
Vegetation productivity is the basis of all the biosphere activities on the land surface that relate to global biogeochemical cycles of carbon and nitrogen. The accurate quantification of gross primary production (GPP) in crops is important for regional and global studies of carbon budgets. Many flux observation nets have been established to help us monitoring the carbon cycling. However, estimation...
Polarimetric Synthetic Aperture Radar (PolSAR) images are widely used for agricultural fields monitoring and change detection applications due to their all-weather acquisition possibilities and inherent properties including phase and amplitude information. The techniques used for such temporal applications can be cast in two groups: polarimetric (incoherent) and polarimetric-interferometric (coherent)...
This paper focuses on the detection of land cover change from 2002, 2006 to 2010 combining TM, ETM+ and ASTER data. Our results indicate that most of the land covered by vegetation or water body previously within the fifth ring road around old city of Beijing has been replaced by urban construction land. The size of urban areas is expanded outside as a form of establishment of ring roads surrounding...
Drought is a main meteorological disaster leading to significant environmental, social and economic consequences due to its high frequency and large influence. Traditional methods of drought monitoring are to simplify drought into drought indices derived from weather station data. With the development of remote sensing, It is necessary to assess the potential of such indices derived from a specific...
This paper quantifies the probable impacts of ionospheric scintillation on the proposed European Space Agency BIOMASS synthetic aperture radar (SAR). BIOMASS is a 435 MHz quad-polarised.SAR in a dawn-dusk orbit, with a primary objective of measuring woody biomass density and tree heights with near-global coverage. The climatological model WBMOD is used to generate multiple random ionospheric phase...
Wildfires plays a fundamental intervention in global biogeochemical cycle, by the chemical reaction occurring in the combustion process, and the organic compounds present in vegetation returns to the atmosphere and soil in a cyclical behavior. Therefore, the main objective of this work is to develop a method to estimate the instantaneous fire size in Brazil using Thematic Mapper (TM) aboard of Landsat...
In this paper we propose an unsupervised approach for SAR image change detection task. A new method based on compressed sensing is applied. First using the PPB method for the speckle reduction, and then the logarithm ratio method is applied to generate a simple change map, and then the compressed sensing-based method is used to part the change map into a low rank part and a sparse part, where the...
Evaluation of ALOS PALSAR polarimetric data for land-cover classification was made for test area located in the northern part of Timan-Pechorian petroleum province (North-West of Russia). Different methods of classification have been made and compared. Results of land-cover classification have allowed to reveal different types of landscape and to estimate deep of bogs. Application of PALSAR PLR data...
This paper presents a novel interactive domain-adaptation technique based on active learning for the classification of remote sensing (RS) images. The proposed method aims at adapting the supervised classifier trained on a given RS source image to make it suitable for classifying a different but related target image. The two images can be acquired in different locations and/or at different times,...
The research into automatic cartographic mapping is a current topic due to today's availability of high resolution remote sensing data. In order to get as much reliable information as possible, it is recommendable to fuse different image data of the same scene. No matter if the images are acquired by different sensors, from different directions (i.e. multi-aspect data), or are multi-temporal, a careful...
In this paper, we improve the traditional bag-of-words-based image representation method in two aspects: preserving the semantics in vocabulary generation and incorporating spatial relations in image representation. Based on that, we present a novel context-aware information modeling method for high resolution synthetic aperture radar image scene interpretation. We compare the proposed method with...
We describe an interactive framework for man-made structure classification. Our system is able to help an image analyst to define a query that is adapted to various image and geographic contexts. It offers a GIS-like interface for visually selecting the training region samples and a fast and efficient sample description by histogram of oriented gradients and local binary patterns. To learn a discrimination...
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