By Topic

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Date July 31 2006-Aug. 4 2006

Filter Results

Displaying Results 1 - 25 of 1083
  • 2006 IEEE International Sensing Symposium Geoscience and Remote - Cover

    Page(s): c1
    Save to Project icon | Request Permissions | PDF file iconPDF (43 KB)  
    Freely Available from IEEE
  • 2006 IEEE International Sensing Symposium Geoscience and Remote - Copyright notice

    Page(s): ii
    Save to Project icon | Request Permissions | PDF file iconPDF (45 KB)  
    Freely Available from IEEE
  • 2006 IEEE International Sensing Symposium Geoscience and Remote - Copyright notice

    Page(s): iii - vi
    Save to Project icon | Request Permissions | PDF file iconPDF (160 KB)  
    Freely Available from IEEE
  • 2006 IEEE International Sensing Symposium Geoscience and Remote - Table of contents

    Save to Project icon | Request Permissions | PDF file iconPDF (245 KB)  
    Freely Available from IEEE
  • A Self-Organizing Map Framework for Detection of Man-Made Structures and Changes in Satellite Imagery

    Page(s): 1 - 4
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (314 KB) |  | HTML iconHTML  

    Content-based querying allows efficient retrieval of images based on the information they contain, rather than acquisition date or geographical extent. We extend the potential of a content-based image retrieval (CBIR) system based on Self- Organizing Maps (SOMs), to the analysis of remote sensing data. A database was artificially created by splitting each satellite image to be analyzed into small images. After training the CBIR system on this imagelet database, both interactive and off-line queries were made to detect man-made structures, as well as changes. Experimental results suggest that this new approach is suitable for analyzing very high-resolution optical satellite imagery. Possible applications include interactive detection of man-made structures and supervised monitoring of sensitive sites. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Simple and Efficient Feature Extraction Algorithm for Geophysical Phenomena

    Page(s): 5 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (445 KB) |  | HTML iconHTML  

    A phenomenon is defined as any state or process known through the senses rather than by intuition or reasoning, and thus is an observable event, especially something special or unusual. A geophysical phenomenon in the context of geoscience data can be characterized as a spatial region which is significantly different from the rest of the image; having higher/lower than average background intensity value; and having higher variation in intensity when compared to the remaining data points. This paper will describe two variations of the Phenomena Extraction Algorithm (PEA). The PEA consists of three components: a hierarchical splitting to efficiently decompose geoscience data into smaller regions; a set of statistical tests to determine whether decomposed region meets the definition of a geophysical phenomenon and an optimization algorithm to determine the best thresholds needed by these statistical tests. The two variations of the algorithm were tested on a synthetic dataset in a series of experiments. The results from these experiments will be presented in this paper. The use of PEA in a proof-of-concept effort within Linked Environment for Atmospheric Discovery (LEAD), a large NSF funded Information Technology Research project, will also be described. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Coalescing ICA and Wavelets Coefficients for Image Information Mining in Earth Observation Data Archives

    Page(s): 9 - 12
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (485 KB) |  | HTML iconHTML  

    Reflectance pattern and spatial pattern characterize the geospatial data. Current semantic-enabled framework retrieval system extract primitive features based on color, texture (Spatial Gray Level Dependency - SGLD matrices), and shape from the segmented homogenous region. This system can use only three bands (true color or false color) at a time to capture color information as it converts RGB space into HSV space. Thus it fails to capture the complete reflectance pattern, an important characteristic of geospatial data. This paper describes a new method to perform image segmentation using the features obtained by coalescing of Independent Component Analysis and Wavelet transform, which are later on used for the region-based retrieval in the earth observation data archives. Experimental results show effectiveness of the proposed method for image information mining in Earth observation data archives. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Categorization based Relevance Feedback Search Engine for Earth Observation Images Repositories

    Page(s): 13 - 16
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (494 KB) |  | HTML iconHTML  

    Presently Earth observation (EO) satellites acquire huge volumes of high resolution images very much over-passing the capacity of the users to access the information content of the acquired data. Thus, in addition to the existing methods for EO data and information extraction, new methods and tools are needed to explore and help to discover the information hidden in large EO image repositories. This article presents a categorisation based Relevance Feedback (RF) search engine for EO images repositories The developed method is presented as well results obtained for a SPOT5 satellite image database. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Knowledge Discovery by Mining Association Rules and Temporal-Spatial Information from Large-Scale Geospatial Image Databases

    Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (293 KB) |  | HTML iconHTML  

    Discovering relevant knowledge from large-scale geospatial image databases is challenging because of the complexity of describing visual semantics, the computational cost of processing petabytes of data, and the difficulty in summarizing and presenting knowledge. In this paper, we revisit a selective set of core data mining algorithms, namely association rules mining, spatial mining, and temporal mining. We then customize these algorithms using visual content and potential objects extracted from geospatial image databases with other relevant information, such as text-based annotations. Queries utilizing the mining results are also discussed in this paper. These mining and query processing algorithms play an important role in GeoIRIS- Geospatial Information Retrieval and Indexing System. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mining Visual Associations from User Feedback for Weighting Multiple Indexes in Geospatial Image Retrieval

    Page(s): 21 - 24
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (172 KB) |  | HTML iconHTML  

    Geospatial content-based image retrieval (CBIR) systems can be used to query for visually similar images by identifying similar patterns between a query image and those in the database. When several different classes of features are used, some queries require that each class should be given a different degree of weight; to this end, CBIR indexes are built for each class of features. This paper proposes an approach for weighting multiple indexes in a geospatial CBIR system by mining information from user feedback. After a small number of iterations of relevance feedback and data mining, index weights can be determined dynamically per query. Using this technique geospatial retrieval system precision of results increased from 70% to 79% after 5 iterations of feedback. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Semantics-Enabled Knowledge Management for Global Earth Observation System of Systems

    Page(s): 25 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (292 KB) |  | HTML iconHTML  

    The Global Earth Observation System of Systems (GEOSS) is a distributed system of systems built on current international cooperation efforts among existing Earth observing and processing systems. The goal is to formulate an end-to-end process that enables the collection and distribution of accurate, reliable Earth Observation data, information, products, and services to both suppliers and consumers worldwide. Earth Observations (EO) are obtained from a multitude of sources and requires tremendous efforts and coordination among different agencies and user groups to come to a shared understanding on a set of concepts involved in a domain. Semantic metadata plays a crucial role in resolving the differences in meaning, interpretation, usage of the same or related data. Also the knowledge about the geopolitical background of the originating datasets could be encoded in the metadata that would address the diversity on a global scale. In distributed environments like GEOSS modularization is inevitable. In this paper we propose a framework for modular ontologies based knowledge management approach for GEOSS in which we explore approaches on formulating smaller interconnected ontologies. This analysis is exercised in a coastal zone domain. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Development and Validation of Spaceborne Dualfrequency Precipitation Radar for GPM

    Page(s): 29 - 31
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB) |  | HTML iconHTML  

    After the great success of the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM) started as an international mission and follow-on mission of the TRMM project to obtain more accurate and frequent observations of precipitation. The accurate measurement of precipitation will be achieved by the DPR installed on the GPM core satellite. In order to estimate accurate precipitation rate value, calibration and validation of the DPR algorithms and products are essential. From the experiences of TRMM validations, it is important for the DPR algorithm validation to compare between precipitation rate through the calculation of DPR algorithm and that of the directly observed precipitation rate over the validation site. For this purpose, the most important and difficult issue is to construct the database of the physical parameters for the precipitation retrieval algorithms of DPR from the ground-based data using well-calibrated instruments. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • The Role of C-band Dual Polarization Radars for GPM Ground Validation

    Page(s): 32 - 35
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (225 KB) |  | HTML iconHTML  

    Dual polarization weather radars have brought in significant advancement to precipitation observation, as rainfall rate estimation, microphysical characterization, and hydrometeor classification. The improvements have been mostly demonstrated at S-band frequency where attenuation effects are usually negligible. In Europe C-band is largely adopted in operational and research radars because of larger differential phase measurements, reduced antenna size and an overall lower cost with respect to that of S-band systems. The major disadvantage is that the signal attenuation is not negligible. In the context of GPM Ground Validation, techniques to compensate the reflectivity measurements for propagation effects are thus necessary to obtain GV products from ground-based C-band radars. The attenuation correction methodology using differential phase shift as constraint has shown a good performance. One of the advantages of polarimetric radar measurements is their self-consistency. Starting from the initial guess of attenuation correction provided by the rain profiling algorithm, self-consistency is used in an iterative technique to improve the accuracy of attenuation correction at C-band. The obtained accuracy is evaluated in terms of bias and standard error using C-band profiles generated from S-band dual polarization observations. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Rain Retrieval Performance of a Dual-Frequency Radar Technique with Differential Attenuation Constraint

    Page(s): 36 - 40
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (496 KB) |  | HTML iconHTML  

    Assessments on the performance of dual-frequency (13.6/35.5 GHz) precipitation radar (DPR) rain retrieval techniques are performed through simple vertical rain profiles synthesized with arbitrarily defined and disdrometer-measured raindrop size distribution (DSD) data. A DPR inversion technique (DPR-IT) with the estimates of differential attenuation (DA), which used to resolve the path-integrated attenuation (PIA) information instead of relying on surface reference or iterative methods, is considered mainly for the analysis. Preliminary simulation results show that the DPR-IT with DA constraint can work as an independent way to extract the DPR PIA information, hence, the DSD parameters, especially in the regions of moderate to strong rainfall rates. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Precipitation Retrieval Accuracies for Geo-Microwave Sounders

    Page(s): 41 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1255 KB) |  | HTML iconHTML  

    Only instruments on geostationary or comparable platforms can view global precipitation at the ~15-minute intervals necessary to monitor rapidly evolving convective events. This paper compares the abilities of ten such alternative passive microwave sensors to retrieve surface precipitation rates and hydrometeor water paths-five instruments observe various frequencies from 116 GHz to 429 GHz with a filled-aperture antenna, and five observe various frequencies from 52 to 191 GHz with a U-shaped aperture synthesis array. The analysis is based on neural network retrieval methods and 122 global MM5- simulated storms that are generally consistent with simultaneous AMSU observations. Several instruments show considerable promise for retrieving hydrometeor water paths and 15-minute average precipitation rates ~1-100 mm/h with spatial resolutions that vary from ~15 km to ~50 km. This space/time resolution is potentially adequate to support assimilation into cloud-resolving numerical weather prediction models. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Study of Hurricanes and Typhoons from TRMM Precipitation Radar Observations: Self Organizing Map (SOM) Neural Network

    Page(s): 45 - 48
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (864 KB) |  | HTML iconHTML  

    Precipitation radar (PR) on Tropical Rainfall Measuring Mission (TRMM) satellite provides high resolution vertical profile of reflectivity (VPR) of tropical storms. Three- dimensional downward-looking observations of tropical storms are very useful to study Hurricanes and Typhoons. The increased reflectivity measured in bright band (BB) region can lead to rainfall overestimate. It is also known that VPR of BB holds extensive information on the types of precipitation and their variability. Better knowledge of VPR of storms is important to understand cloud dynamics and microphysical processes, and to improve satellite retrieval algorithm. Because of a large number of VPR observation, it is of interesting to classify the VPR into characteristic profiles so that it can be useful in studying and comparing different vertical reflectivity profiles. In this study, Self Organizing Map (SOM) Neural Network is used as a method to study and classify VPR of Hurricanes and Typhoons. SOM is unsupervised neural network. It forms a non-linear mapping of the data to a two-dimensional map grid that can be used as an exploratory data analysis tool for generating hypotheses on the relationships of VPR. Similarity relationships within the VPR data and its vertical structure can be visualized and interpreted. Preparation of vertical profile of reflectivity used as input vectors of SOM algorithm is one of the most vital steps. In total eleven Hurricanes and forty Typhoons are studied. VPR of Hurricanes and Typhoons are classified into characteristic profiles. The result of classification shows a distribution that indicates location of each characteristic profile within a storm when viewed from the PR. Percentages of contribution of each characteristic profile to Hurricanes and Typhoons can also be determined. By using SOM, VPR can be classified into various numbers of classes up to one hundred. In this study, VPR is classified into four classes. Two simple operations were performed. Firstl- - y, SOM was applied to all VPR data regardless of rain type. Secondly, stratiform and convective portion of VPR was applied to SOM separately. For stratiform portion of Hurricanes and Typhoons, the bright band (BB) properties including the height of BB peak, BB thickness, reflectivity of BB peak and BB sharpness index of Hurricanes and Typhoons are investigated and compared to those of generic oceanic storm. Comparison of those BB properties of Hurricanes, Typhoons and generic oceanic storm reveals similarities and differences among them. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Recent Advances in Polarimetry and Polarimetric Interferometry

    Page(s): 49 - 51
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (226 KB) |  | HTML iconHTML  

    Radar polarimetry radar Interferometry and polarimetric SAR interferometry represent the current culmination in 'microwave remote sensing' technology, but we still need to progress very considerably in order to reach the limits of physical realizability. Whereas with radar polarimetry the textural fine-structure, target orientation, symmetries and material constituents can be recovered with considerable improvement above that of standard 'amplitude-only' radar; by implementing 'radar interferometry' the spatial (in depth) structure can be explored. With polarimetric interferometric synthetic aperture radar (POL-IN-SAR) imaging, it is possible to recover such co-registered textural and spatial information from POL-IN-SAR digital image data sets simultaneously, including the extraction of digital elevation maps (DEM) from either polarimetric (scattering matrix) or interferometric (dual antenna) SAR systems. Simultaneous polarimetric-plus-interferometric SAR imaging offers the additional benefit of obtaining co-registered textural-plus-spatial three-dimensional POL-IN-DEM information, which when applied to repeat-pass image-overlay interferometry provides differential background validation and environmental stress-change information with highly improved accuracy. Then, by either designing multiple dual polarization antenna POL-IN-SAR systems or by applying advanced POL-IN-SAR image compression techniques, will result in 'POL-arimetric TOMO-graphic' (multi-interferometric) SAR or POL-TOMO-SAR imaging. By advancing these EWB-D-POL-IN/TOMO-SAR imaging modes, we are slowly but steadily approaching the ultimate goal of eventually realizing airborne and spaceborne 'geo-environmental background validation, stress assessment, and stress-change monitoring and wide-area military surveillance of the terrestrial and planetary covers'. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Monte Carlo Evaluation of Multi-Look Effect on Entropy/Alpha /Anisotropy Parameters of Polarimetric Target Decomposition

    Page(s): 52 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (468 KB) |  | HTML iconHTML  

    Entropy, alpha and anisotropy (H/alpha/A) of the polarimetric target decomposition of Cloude and Pettier has been an effective and popular tool for polarimetric SAR image analysis and geophysical parameter estimation. However, multi-look processing can severely affect the values of these parameters. In this paper, a Monte Carlo method is used to evaluate the multi- look effect on these parameters for various media of grass, forest and urban. The effect of pixel correlation due to over sampling, and the mixed pixel effects will also be investigated. DLR/E-SAR and JPL/AIRSAR L-band data are used in this study. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Extended Multidimensional Speckle Noise Model and its Implications on the Estimation of Physical Information

    Page(s): 56 - 59
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (265 KB) |  | HTML iconHTML  

    The presence of speckle noise in Synthetic Aperture Radar images prevents a correct interpretation, as well as, the information retrieval processes. It has been recently demonstrated that speckle noise may introduce biases into the retrieved physical information when multidimensional data is considered. In case of multidimensional SAR systems, for single-look data, it has been proved that speckle noise is due to the combination of multiplicative and additive noise sources. This paper details the extension of this noise model to multilook, multidimensional SAR data. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Time Series Approach for Soil Moisture Estimation

    Page(s): 60 - 62
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (192 KB) |  | HTML iconHTML  

    Soil moisture is a key parameter in understanding the global water cycle and in predicting natural hazards. Polarimetric radar measurements have been used for estimating soil moisture of bare surfaces. In order to estimate soil moisture accurately, the surface roughness effect must be compensated properly. In addition, these algorithms will not produce accurate results for vegetated surfaces. It is difficult to retrieve soil moisture of a vegetated surface since the radar backscattering cross section is sensitive to the vegetation structure and environmental conditions such as the ground slope. Therefore, it is necessary to develop a method to estimate the effect of the surface roughness and vegetation reliably. One way to remove the roughness effect and the vegetation contamination is to take advantage of the temporal variation of soil moisture. In order to understand the global hydrologic cycle, it is desirable to measure soil moisture with one- to two-days revisit. Using these frequent measurements, a time series approach can be implemented to improve the soil moisture retrieval accuracy. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Full text access may be available. Click article title to sign in or learn about subscription options.
  • Polarimetric Characteristics of Radar Echoes from the Sea Surface as a Function of Incidence Angle

    Page(s): 67 - 70
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (356 KB) |  | HTML iconHTML  

    This paper presents some initial results of polarimetric radar measurements made over a range of look-down angles using the DSTO high resolution multi-band radar. Specifically, X-band polarimetric measurements of the sea were made from 95 m high cliffs along the Great Australian Bight, for look-down angles of 3deg, 4deg, 5deg, 10deg, 15deg, 20deg, 25deg and 30deg. The analysis is addressing scattering matrix element statistics, entropy-alpha space distributions and correlation with visible spectrum imagery. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Structural Parameter Estimation of Australian Flora with a Ground-based Polarimetric Radar Interferometer

    Page(s): 71 - 74
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (774 KB) |  | HTML iconHTML  

    The application of polarimetric SAR interferometry technology is extended to ground based radar imaging (GB-POLInSAR), which has a limited field of view but provides wide band coverage. It also provides for easier deployment of broadband and multi-baseline techniques, from which we can estimate vegetation structure and extinction propagation using model based techniques. This micro-scale multi-parameter combination with good temporal resolution is a unique feature of ground- based sensors. In this paper we present both polarimetric and interferometric coherence calibration results for such a GB-POLInSAR system we have developed at the University of Adelaide. We then show an initial study of height estimation of Australian native plants based on the coherence parameter retrieval models of the polarimetric SAR interferometry technique using the broadband GB-POLInSAR system. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Study of the Influence of Vessel Motions and Sea-Ship Interaction on Classification Algorithms Based on Single-Pass Polarimetric SAR Interferometry

    Page(s): 75 - 78
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (562 KB) |  | HTML iconHTML  

    This paper analyzes the worsening effects the sea surface can induce on vessel classification algorithms working with SAR imagery. Two issues will be tackled, the complex motion history of ships and the polarimetric scattering mechanisms generated by the sea-hull interaction. Both can modify the information that allows to infer the geometry of ships dropping the classification capability. The current analysis will introduce a new classification approach based on polarimetric SAR interferometry that presents a low sensitivity respect the main distortions caused by the sea surface. Simulated SAR images obtained from GRECOSAR, a SAR simulator of complex targets, will show trustworthy vessel classification almost independent on the environmental conditions could be possible for incoming system configurations as Tandem TerraSAR-X. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Polarimetric Temporal Decorrelation Studies by Means of GBSAR Sensor Data

    Page(s): 79 - 82
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (702 KB) |  | HTML iconHTML  

    In this paper, a study of the temporal evolution of the elements of 3 x 3 covariance matrix using an X-band polarimetric ground-based SAR sensor is proposed. Although the heterogeneity of the scenario allows to select different target typologies, the study is mainly focused on the analysis of azimuthally symmetric distributed targets. The fluctuations of the most representative elements of [C] as a function of time and the decorrelation among the polarimetric channels are investigated. A relation with atmospheric parameters like temperature, humidity and wind is considered in order to make out the weight these parameters can influence the polarimetric signature of the observed area. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.