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The SCA instrument is a C-band wind scatterometer that forms part of the EUMETSAT Polar System Second Generation (EPS-SG) mission. The paper presents an overview on the current development status of the SCA instrument and of its key equipment.
Vegetation indices derived from optical and multispectral data, such as Enhanced Vegetation Index (EVI), have been widely used to monitor the health and productivity of vegetation. However, their use is limited in areas with persistent cloud-cover and inclement weather. Due to the all-weather observations provided by Synthetic Aperture Radar (SAR) sensors, an alternative would be to derive vegetation...
We investigated the use of phenological information extracted from satellite imagery and supported by agro-ecological zoning (AEZ) in accurate crop classification and monitoring. Vegetation indices extracted from Landsat 8 imagery are capable to track the vegetation development through the year and from them the phenological profile can be extrapolated and implemented into a multi-temporal automatic...
Area Sampling Frames are used for surveys including crop acreage and yield, forests, and natural resource inventories and are the foundation of the statistical program of the USDA National Agricultural Statistics Service (NASS) and many statistical survey programs around the world. An automated area frame stratification method was recently implemented into NASS operations, which is based on the objective...
Recently, deep learning has been introduced to classify hyperspectral images (HSIs) and achieved effective performance. In general, the previous networks are not enough deep, which might not extract very discriminant features for classification. In addition, they do not consider strong correlations among different hierarchical layers. Due to the two problems, a hybrid deep residual network is presented...
Classification of Synthetic Aperture Radar (SAR) images is a complex task because of the presence of speckle, which affects images in a way similar to a strong noise. In this study, we investigate the use of Convolutional Neural Networks (CNNs) which can effectively learn a bank of spatial filters to simultaneously 1) reduce speckle noise, and 2) extract spatial-contextual features to characterize...
In this work, we develop a new framework to combine ensemble learning and composite kernel learning for hyperspectral image classification. We refer it as the multiple composite kernel learning, which is based on an iterative architecture. More specifically, in each iteration, we use the rotation-based ensemble to create rotation matrix, which is used to generate rotated features for both spectral...
We show that indications of spatial dispersion effects on mineral oil slicks are observed by space-borne multipolarization synthetic aperture radar. This is readily perceived by eye when correlating multipolarization synthetic aperture radar observables with the ship track of the dispersion vessel. We investigate real full-polarimetric (linear transmit/linear receive) as well as simulated and real...
This paper describes a new technique for generating bistatic sea clutter returns based on the compound K-distribution model for clutter amplitude statistics. The technique adopts the computational electromagnetic (CEM) method to calculate bistatic sea clutter reflectivity by the given bistatic geometrical relationship, aiming at obtaining the parameters of the distribution. Then the theory of spherically...
The passive Synthetic Aperture Radar with Global Navigation Satellite System (GNSS) employs GNSS satellites as transmitters and receivers mounted near the ground. Since GNSS constellations are designed for global, reliable and persistent operation, the most important advantage of such a system is the potential of permanent monitoring on the area which is overlooked by a fixed receiver. In the paper,...
The TRMM Microwave Imager has provided a nearly two-decade satellite remote sensing data set for studying climate change, and the legacy data processing is in progress and will be released in late 2017. During this reprocessing, it was discovered that the hot-load suffers an occasional transient solar intrusion, which resulted in a small systematic brightness temperature error. This paper describes...
This paper concerns the measurement of brightness temperature using the TRMM Microwave Imager (TMI) satellite microwave radiometer. Specifically, the development of an algorithm for correcting the effects of a slightly emissive reflector antenna on the measured earth scene radiance is presented. This algorithm is based upon rigorous radiative transfer theory and on-orbit reflector emissivity measurements...
In order to improve the low spatial resolution of remote sensed LST, two methods based on multiple scale factors are proposed. Considering the optimal scale factor is usually not unique under environment of different land cover types, a stratified linear regression model is built, which shows a higher accuracy than global linear regression with one scale factor. In view of the relationship between...
Nuri Cu polymetallic deposit locates in south rim of Eastern of Gangdise in Tibet. It is presented for large metallogenic scale and special mineralized combination. Using the ASTER imagery band ratio methods, the content and composition distribution of micas were implemented. And from measuring the spectral of rock and mineral using SVC portable spectrograph, it derived consequence of exists some...
Morphological attribute profiles (MAPs) are one of the most effective methodologies to characterize the spatial information in remote sensing images. This technique extracts components able to accurately describe objects in the surface of the Earth. In this work, we present a new method for impervious surface extraction from multispectral images using morphological attribute profiles. The proposed...
Changes in land use and land cover (LULC) are the critical driving forces of change in atmospheric, climatic and ecological systems. The purposes of this study are thus aiming to understand the relationship between land cover changes and thermal properties of urban heat island effects using Landsat images spanning from 1991 to 2007. On basis of the images of 17 years, the temperature differences between...
Remote sensing is widely used for alteration mineral recognition and mapping. Since it covers spectral features of hydroxyl-bearing minerals as well as C-O bearing minerals like phylosilicates, sulfates, and carbonates, ASTER SWIR region allows detailed spectral characterization of alteration minerals. This study focuses on investigating the ability of ASTER SWIR data for mapping alteration minerals...
With the rapid development of remote sensing data, the instant and high-efficient analysis on remote sensing image become a challenge. In our research, we adopt the main idea of Merkle Tree and incorporate it with the regular quad-tree to generate an advanced Merkle Quad-Tree structure to assist the remote sensing image analysis. A series of experiments are conducted to authenticate the advantages...
Identification of runoff generation areas and erosion prone zones of a watershed are important for the efficient and effective implementation of the greatest management practices for preserving the natural resources. In the present study, an effort is completed to recognize the critical erosion-prone zones of the study area by using the spatially distributed parameters liable for hazards of erosion...
Temporal sequences of images called Satellite Image Time Series (SITS) allow land cover monitoring and classification by affording a large amount of images. Many approaches attempt to exploit this multi-temporal data in order to extract relevant information such as classification-based techniques. In this paper we compare low and high levels classification-based approaches that aim to reveal the SITS...
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