The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The hyperspectral image has the advantages of wide spectral range and the high spectral resolution, and is widely applied in the terrain classification. In this paper, we study the airborne hyperspectral image classification methods using the airborne hyperspectral image. Considering the hyperspectral image has amounts of bands and there is redundancy among the bands, the principle component analysis...
An algorithm to simulate the reflectance of clouds using visible bands was developed based on the simplified radiative transfer equation and two assumptions. The assumptions and algorithm were evaluated using a Landsat 8 sub-image of 015/035 (path/row) acquired on 27 August 2013. The relationship of visible bands in clear regions was verified to be linear. The effects of clouds in visible bands were...
As a close proxy of the GOES-R Advanced Baseline Imager (ABI) instrument, the on-board 16-band Advanced Himawari Imager (AHI) brings an unprecedented opportunity to exercise the ABI algorithms developed for GOES-R in the STAR Algorithm Processing Framework (SAPF). STAR has been collaborating with JMA and NASA since AHI's post launch checkout and has been acquiring the full resolution AHI data form...
In this paper the Supervised Locally Linear Embedding (SLLE) algorithm is introduced into polarimetric SAR (PolSAR) feature dimensionality reduction (DR) and land cover classification. SLLE technique, as a supervised nonlinear manifold learning method, can obtain a low-dimensional embedding space which preserves both the local geometric property of high-dimensional data and discriminative information...
A targets detection algorithm is proposed for maritime surveillance by single-channel SAR images. It foresees a preliminary prescreening step, carried out using an adaptive threshold algorithm, followed by a discrimination phase, performed by sub-look analysis. The latter discriminates the pixels detected by the former step in three classes, i.e. targets, sea, and azimuth ambiguity. The algorithm...
AfriSAR is an ESA-funded airborne P-band SAR campaign over the African tropical forests of Gabon that is being carried out by ONERA (July 2015) and DLR (February 2016) in support of the development of the geophysical algorithms of the future BIOMASS mission. Multibaseline fully-polarimetric acquisitions have been designed over four test sites in order to further develop and validate algorithms for...
Spectral unmixing is an important technique to exploit mineral distribution through remote sensing image. In this paper, we propose an unmixing algorithm combining clustering-aware method with the sparsity-constrained nonnegative matrix factorization (SNMF) algorithm. Pixels with similar spectra have high possibility to share similar typical endmembers, therefore we preprocess the image using K-means...
Most nonlinear unmixing algorithms are based on the nonlinear mixing models with different forms. This paper focuses on the well-known generalized bilinear model (GBM). Though the GBM has shown interesting and promising for nonlinear unmixing, currently almost all the GBM-based unmixing algorithms are supervised. That is, the endmembers must be assumed known in advance. This paper develops an unsupervised...
This paper presents a new approach to post temperature and emissivity separation processing for thermal infrared hyperspectral remote sensing data, based upon sparse signal representation. We address the denoising of emissivity product, where the atmospheric correction error, temperature and emissivty separation error and data noise are to be removed from a given emissivity product. The approach taken...
Downward surface shortwave radiation (DSSR) is influenced by the atmosphere and mountainous topography. DEM scale is the key factor to affect the spatial distribution of DSSR in mode scale. In this paper, sensitivity of estimating DSSR to DEM scale is explored with six DEMs resolutions from 5-to 500-m based on our mountainous radiation algorithm published. According to the difference between the model...
In this paper, we propose a Spark-based fuzzy local information C-Means (FLICM) algorithm that provides synthetic aperture radar (SAR) image change detection. With the volume and resolution of SAR images increasing, current serial clustering algorithms are not suitable to handle big data, scalable solutions are indispensable. The proposed algorithm based on Spark framework implements FLICM algorithm...
Mass-weighted mean diameter Dm is explicitly estimated in the GPM/DPR algorithms. The spatial and temporal variations of Dm are analyzed by fixing the range of precipitation rates R. Generally, Dm is higher over land than over ocean. In India, the seasonal variation in Dm is shown. Such spatial and temporal variations are clearly seen for heavy precipitation. Compared with the TRMM/PR algorithm, KuPR...
This paper describes the rain gauge adjusted algorithm for the Global Satellite Mapping of Precipitation (GSMaP_Gauge_NRT) that estimates the surface rainfall rate with the resolution of 0.1 degree and 1 hour resolution over the globe in near realtime. Precipitation is one of the most important parameters on the earth system, and the global distribution of precipitation and its change are essential...
This paper proposes a novel solution to solve the problem of imbalanced training samples in hyperspectral image classification. It consists of two parts: one is for large-size sample sets and the other is for small-size sets. We exploit an orthogonal projection based algorithm to select samples from large-size ones; meanwhile, we propose an algorithm based on the orthogonal complementary subspace...
The Algorithm Scientific Software Integration and System Transition Team (ASSISTT) at NESDIS STAR (National Environmental Satellite Data and Information Service, Center for Satellite Applications and Research) has designed, developed and implemented a Near Real-Time (NRT) processing system to process algorithms for scientists and other stakeholders. The system generates products using the STAR Algorithm...
Comparing to the original backprojection (BP) algorithm, the fast factorized backprojection algorithm accelerates enormously by dividing the synthetic aperture into many small pieces and finishes the BP integral in many stages. Numerous two-dimensional (2-D) image interpolation operations are utilized to raise accuracy. In this letter, a new factorized backprojection algorithm is proposed where no...
Herein, we explore both a new supervised and unsupervised technique for dimensionality reduction or multispectral sensor design via band group selection in hyperspectral imaging. Specifically, we investigate two algorithms, one based on the improved visual assessment of clustering tendency (iVAT) and the other based on the automatic extraction of “blocklike” structure in a dissimilarity matrix (CLODD...
Traditional joint sparse representation based hyperspectral classification methods define a local region for each pixel. Through representing the pixels within the local region simultaneously, the class of the central pixel is able to be decided. A common limitation of this kind of methods is that only local pixels are considered in such methods, and thus, non-local information will be ignored. In...
Individual tree crown delineation (ITCD), which includes treetop detection and/or tree crown delineation, plays a significant role in modern forest resources management and precise forestry. Recent years, amount of ITCD algorithms have been proposed based on passive and active remotely sensed data. However, since there is no standardized accuracy assessment procedure for ITCD, it is extremely difficult...
Marginal Fisher analysis (MFA) exploits the margin criterion to compact the intraclass data and separate the interclass data, and it is very useful to analyze the high-dimensional data. However, MFA just considers the structure relationship of neighbor points, and it cannot effectively represent the intrinsic structure of hyperspectral image (HSI) that possesses many homogenous areas. In this paper,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.