ABSTRACT Current geographic information systems tend to follow an inherently static approach to geospatial information management. Small amounts of information are typically synthesized into map-like application-specific data snapshots.... more
ABSTRACT Current geographic information systems tend to follow an inherently static approach to geospatial information management. Small amounts of information are typically synthesized into map-like application-specific data snapshots. This static approach leaves large amounts of information unused and offers limited communication capabilities. Accordingly, it is unsuitable for today's applications, where geospatial information becomes increasingly dynamic and spatiotemporal in nature.
Background This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the... more
Background This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the proposed MSRBF network relies on the integration of both local and global error statistics in the node selection process.
Abstract Geospatial datasets are typically available as distributed collections contributed by various government or commercial providers. Supporting the diverse needs of various users that may be accessing the same dataset for different... more
Abstract Geospatial datasets are typically available as distributed collections contributed by various government or commercial providers. Supporting the diverse needs of various users that may be accessing the same dataset for different applications remains a challenging issue. In order to overcome this challenge there is a clear need to develop the capabilities to take into account complicated patterns of preference describing user and/or application particularities, and use these patterns to rank query results in terms of suitability.
One of the major tools used to model accurately the real world is a geographic information system (GIS). In such a system and in order to capture the dynamic world, a GIS approach that handles change information should be employed. Such a... more
One of the major tools used to model accurately the real world is a geographic information system (GIS). In such a system and in order to capture the dynamic world, a GIS approach that handles change information should be employed. Such a model is useful in many application domains: historical geography, meteorology, physical geography, and engineering fields like city planning, landscape architecture, cadastral systems and transportation.
Abstract Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models.... more
Abstract Urbanization changes have been widely examined and numerous urban growth models have been proposed. We introduce an alternative urban growth model specifically designed to incorporate spatial heterogeneity in urban growth models. Instead of applying a single method to the entire study area, we segment the study area into different regions and apply targeted algorithms in each subregion.
Abstract A SpatioTemporal Gazetteer as a model to manage change information at the geographic entity instance level is presented. TAe Gazetteer fromework links an image repository, that is the source of change information, to instances of... more
Abstract A SpatioTemporal Gazetteer as a model to manage change information at the geographic entity instance level is presented. TAe Gazetteer fromework links an image repository, that is the source of change information, to instances of geographic entities, and is change specific to these instances. The ability to quickly detect and extract change from image data is an essential component of the model.
ABSTRACT Mapping of architectural and archaeological objects often encounters limitations in imaging distances (interiors, narrow streets, excavations), usually tackled via large numbers of images or special camera platforms This,... more
ABSTRACT Mapping of architectural and archaeological objects often encounters limitations in imaging distances (interiors, narrow streets, excavations), usually tackled via large numbers of images or special camera platforms This, however, seriously contradicts the benefits of simple, low-cost photogrammetric procedures. In these cases, furthermore, the use of digital cameras with the currently limited area of sensitive sensors may also be impracticable.
Teaching remote sensing in higher education has been traditionally restricted in lecture and computer-aided laboratory activities. This paper presents and evaluates an engaging inquiry-based educational experiment. The experiment was... more
Teaching remote sensing in higher education has been traditionally restricted in lecture and computer-aided laboratory activities. This paper presents and evaluates an engaging inquiry-based educational experiment. The experiment was incorporated in an introductory remote sensing undergraduate course to bridge the gap between theory and application of relevant technology.
ABSTRACT: In modern geospatial applications object extraction becomes increasingly part of larger cycles of GIS updates. In such update cycles, the objective is to compare new information to older one, and to identify changes that... more
ABSTRACT: In modern geospatial applications object extraction becomes increasingly part of larger cycles of GIS updates. In such update cycles, the objective is to compare new information to older one, and to identify changes that occurred in the meantime. In this paper we present an image-based GIS updating framework and corresponding image analysis algorithms developed by our group to automate GIS updates.
Abstract: Recent climatic patterns indicate that extreme weather events will increase in frequency and magnitude. Remote sensing offers unique advantages for large-scale monitoring. In this research, Landsat 5 remotely sensed imagery was... more
Abstract: Recent climatic patterns indicate that extreme weather events will increase in frequency and magnitude. Remote sensing offers unique advantages for large-scale monitoring. In this research, Landsat 5 remotely sensed imagery was used to assess flooding caused by Hurricane Katrina, one of the worst natural disasters in the US over the past decades.
Similarity learning in database queries is intrinsically connected with the data types stored. Geospatial data have important differences to online analytical processing (OLAP) data, general multi-dimensional data, traditional relational... more
Similarity learning in database queries is intrinsically connected with the data types stored. Geospatial data have important differences to online analytical processing (OLAP) data, general multi-dimensional data, traditional relational data or transactional data (Gunopulos, 2001). This uniqueness is partially attributed to the integrative nature of GISs. Many of the issues arise from the fact that geographic data span a wide range of perspectives and interests from the social to the physical aspects of the problem (Gahegan, 2001).
ABSTRACT Human population continues to aggregate in urban centers. This inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have... more
ABSTRACT Human population continues to aggregate in urban centers. This inevitably increases the urban footprint with significant consequences for biodiversity, climate, and environmental resources. Urban growth prediction models have been extensively studied with the overarching goal to assist in sustainable management of urban centers. Despite the extensive body of research, these models are not frequently included in the decision making process.
In much of the world, rapidly expanding areas of impervious surfaces due to urbanization threaten water resources. Although tools for modeling and projecting land use change and water quantity and quality exist independently, to date it... more
In much of the world, rapidly expanding areas of impervious surfaces due to urbanization threaten water resources. Although tools for modeling and projecting land use change and water quantity and quality exist independently, to date it is rare to find an integrated, comprehensive modeling toolkit to readily assess the future course of urban sprawl, and the uncertainties of its impact on watershed ecosystem health.
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Abstract Remote sensing as a field of study has reached its adulthood; computer-assisted classifi ers have been in development for more than two decades. The complexity of remote sensing classifi cation has led to a variety of methods,... more
Abstract Remote sensing as a field of study has reached its adulthood; computer-assisted classifi ers have been in development for more than two decades. The complexity of remote sensing classifi cation has led to a variety of methods, some of them based on artifi cial intelligence (AI), and provides motivation for this special issue. AI techniques range from simple out-of-the-box implementations to algorithms tailored to the specifi cs of remote sensing classifi cation. Recently, we have also observed a significant increase in parallel ...
Research Interests: Information Systems, Animal Movement, Seasonality, Environmental Concern, Case Study, and 11 moreGeographical Information Science, Statistical Significance, Space Time, Geomatic Engineering, Spatial Scale, North America, Moose, Spatial Clustering, High Density Concrete, Geographical, and Kernel Estimate
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Research Interests: Algorithms, Statistics, Statistical Analysis, Image, Hybrid, and 16 moreClassification, Data, Statistical Significance, Estimation, Geomatic Engineering, Remote Sensing of the Nearshore Environment, Aptitude, Accuracy, Texture, Implementation, Utilization, Multiple, Precision, Classifier, Optimum, and Impervious surfaces
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An optimized artificial immune network-based classification model, namely OPTINC, was developed for remote sensing-based land use/land cover (LULC) classification. Major improvements of OPTINC compared to a typical immune network-based... more
An optimized artificial immune network-based classification model, namely OPTINC, was developed for remote sensing-based land use/land cover (LULC) classification. Major improvements of OPTINC compared to a typical immune network-based classification model (aiNet) include (1) preservation of the best antibodies of each land cover class from the antibody population suppression, which ensures that each land cover class is represented by at least one antibody;(2) mutation rates being self-adaptive according to the model ...
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Background/Question/Methods Impervious surfaces associated with exurban 'sprawl'alter ecosystem functioning, resulting in potentially dramatic changes in the provision of ecosystem services that support local... more
Background/Question/Methods Impervious surfaces associated with exurban 'sprawl'alter ecosystem functioning, resulting in potentially dramatic changes in the provision of ecosystem services that support local well-being. Communities are faced with two future development alternatives, one that is highly desired by society at large (most people want to live in a big house in the suburbs) but with large impacts on water quality, and a more sustainable pattern of urban in-fill that leaves the rest of the watershed to exist in a more ...
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Abstract In this chapter we review similarity learning in spatial databases. Traditional exact-match queries do not conform to the exploratory nature of GIS datasets. Non-adaptable query methods fail to capture the highly diverse needs,... more
Abstract In this chapter we review similarity learning in spatial databases. Traditional exact-match queries do not conform to the exploratory nature of GIS datasets. Non-adaptable query methods fail to capture the highly diverse needs, expertise and understanding of users querying for spatial datasets. Similarity-learning algorithms provide support for user preference and should therefore be a vital part in the communication process of geospatial information. More specifically, we address machine learning as applied in the optimization ...
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* Available as a photocopy reprint only. Allow two weeks reprinting time plus standard delivery time. No discounts or returns apply. ... Standard delivery in the US is 7 to 10 business days and outside the US delivery is 4 to 6 weeks or longer. For further details, please see shipping policy. ... Listed below are the papers found in this volume. Click the paper title to view an abstract or to order an individual paper. ... Sign up for monthly alerts of new titles released.