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This study aims to characterize the spatial arrangement of land cover features and integrate the spatial arrangement information with other commonly used land use indicators. The characterization is conducted at object level, corresponding to land cover objects. At the local urban level, a VHR image is dominated by buildings. Therefore, the characterization of spatial arrangement of land cover elements...
The database helps to better understand and quantify the effect of F/T and snow on the L-Band signal. The information will be useful for the validation and calibration of satellite based products. The database will also be used to validate and calibrate different L-Band snow emission models [3–4–5].
In this paper, we propose a new approach for improving boreal forest soil moisture estimation using L-band microwave radiometer. The effect is achieved by introducing improved description of forest canopy contribution from multisensor SAR measurements.
Remote sensing plays an important role in the investigation of deep sea bottom [1]. However, the optical and lidar remote sensing technologies are only suitable for the seabed study in shallow and clear coastal waters due to rapid light attenuation with water depth [2]. The development of the acoustic remote sensing techniques such as multibeam echo-sounders system, becomes the only effective way...
The target of sustainable water sensitive cities can be accomplished by re-configuration of current urban water systems. Stormwater speaks to a significant option for urban water source so as to minimize the load on crisp water assets, and to alleviate the environmental effect of urban stormwater runoff. Suitable site selection for urban stormwater harvesting is for the most part taking into account...
This paper presents a hyperspectral image classification method based on deep network, which has shown great potential in various machine learning tasks. Since the quantity of training samples is the primary restriction of the performance of classification methods, we impose a new prior on the deep network to deal with the instability of parameter estimation under this circumstances. On the one hand,...
Supervised classification of hyperspectral images is a challenging task due to the relatively low ratio between the number of training samples and the number of spectral channels. Subspace-based classification methods deal with this difficulty by assuming that feature vectors lie in a low-dimensional subspace. Based on the fact that a class in a hyperspectral image may be composed of a number of different...
Recently, compressive sensing theory has been successfully applied in inverse synthetic aperture radar (ISAR) imaging. However, the issue of maneuvering target imaging from compressive sampling data has not been sufficiently addressed because it is difficult to jointly deal with both sparse imaging and motion compensation under compressive sampling. In this paper, we develop a novel algorithm of high-resolution...
Soil temperature is one of the essential variables governing the land atmosphere interaction. In this study, we proposed a statistical algorithm to retrieve the surface soil temperature from AMSR-E brightness temperature (TB) observations. The algorithm was developed based on the regression relationship between AMSR-E TB and corresponding in situ soil temperature observed at the Naqu network in the...
Target image database is of great significance in SAR automatic target recognition (ATR). Recently, some convenient and low cost approaches of database simulation were proposed. However, the similarity between virtual SAR images obtained by these simulation approaches and real SAR images is still under study. To solve this problem, we will model the virtual target with three-dimensional (3D) modeling...
Authors in this work aim to present new analysis methods for Earth Observation, developed by processing Sentinel-1 and Landsat-8 satellite data and combining them in an original way. Comparing SAR and Optical/Multispectral data is a procedure already in use because they are two acquisition systems that provide very different and therefore complementary and useful information. Even if the combination...
Extracting and identifying objects in very high resolution imagery has been a popular research topic in remote sensing. Since the beginning of this decade, deep learning techniques have revolutionized computer vision providing significant performance gains compared to traditional “shallow” techniques in various challenging vision problems. The training of deep neural networks usually requires very...
Scattering structure features of targets is of great importance for Synthetic Aperture Radar (SAR) image analysis. In this paper, a novel algorithm for aircraft recognition in high resolution apron area of SAR images is proposed. The algorithm combines the strength of gradient saliency map and scattering structure features to improve accuracy and efficiency. Specially, Constant False-Alarm Rate (CFAR)...
The existing SAR image quality assessment method could not be effectively used for assessing the performance of object detection. Thus, it is difficult to select SAR images and corresponding detection algorithms for SAR object detection. By analyzing the relationship between object detection results and basic image quality indicators, this paper studies the image quality assessment for image object...
The commonly applied triangular method was used to estimate regional evapotranspiration(ET). Based on the parameters of land surface, the applicability of NDVI-land surface temperature(NDVI-LST) and NDVI-albedo triangular methods were validated using the landsat7 data and the Heihe Watershed Allied Telemetry Experimental Research(HiWATER) observed data. Considering the affecting of soil moisture and...
Near real-time satellite data is very useful in the research and development activities for land, ocean, and atmospheric processes, environmental monitoring and assessment, weather prediction, and so on. The quality, completeness, and timeliness of this satellite data are great concerns to researchers. How to monitor and collect this information presents them with technical challenges. This paper...
In this paper the calibration of sensors in polar orbiter satellites in the GPM constellation has been addressed. Since the lunch of TRMM at 1998, AMSU-B sensors flown on NOAA-15, NOAA-16, NOAA-17, and the MHS sensors flown on NOAA-18, NOAA-19, MetOp-A and MetOp-B have provided an invaluable datasets of full coverage of earth which have been extensively used in weather prediction. Here, the calibration...
A robust XCAL double difference (DD) approach for radiometric calibration has been successfully applied between the TRMM Microwave Imager, TMI, (previous calibration transfer standard for NASA's Precipitation Measuring Mission) and a number of precipitation measuring radiometers in polar sun-synchronous orbits. Now that the TRMM Mission has ended (April 2015), the radiometric transfer standard was...
The Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) had been operated in special slow rotation mode to obtain continuous brightness temperatures for the inter-comparison with those of AMSR2 on the Global Change Observation Mission-Water (GCOM-W) for three years. Although its observation coverage is sparse and some calibration uncertainties exist, the data are still very...
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