With the turn of the century our ability to collect and store geospatial information has increased considerably. This has resulted in ever-increasing amounts of heterogeneous geospatial data, an issue that poses new challenges and opportunities. As these rich sources of data are made available, users rely, now more than ever, on the geospatial data infrastructure. The availability and accessibility of such data, as well as the ability to effectively manage, model, index and query the data is becoming a cornerstone in numerous applications. Moreover, the ability to formalize and represent data is becoming key to integration and interoperability. With the introduction of distributed geospatial data infrastructure and the implementation of web-based services, the impact of such issues is becoming even more evident. Inspired by these challenges, this book on Next Generation Geospatial Information offers a collection of original contributions from leading experts in spatial information modeling, image processing and analysis, database management, ontologies and data mining. It provides a unique insight into the current state-of-the-art and future challenges in geospatial information through four thematic chapters, each of which represents a primary research theme, namely distributed spatial infrastructure, image-based geospatial information management, indexing and querying geospatial databases, and ontology and semantics for geospatial data.

Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.

would like to express our appreciation to the authors and participants of ISD 99, who made the meeting a memorable one, and these proceedings a valuable contribution to the relevant literature. October 1999 Peggy Agouris and Anthony Stefanidis $FNQRZOHGJPHQWV This workshop was partially supported by the National Science Foundation (NSF), Directorate for Computer and Information Sciences and Engineering, Division of Information and Intelligent Systems (IIS), through CAREER grant number 9702233, and by the National Center for Geographic Information and Analysis (NCGIA). VII Preface: RUNVKRS 2UJDQL]DWLRQ: RUNVKRS &KDLU Peggy Agouris, University of Maine 3URJUDP &RPPLWWHH &KDLU Anthony Stefanidis, University of Maine 3URJUDP &RPPLWWHH Kate Beard, University of Maine Panos Chrysanthis, University of Pittsburgh Max Egenhofer, University of Maine Wolfgang Foerstner, University of Bonn, Germany Andrew Frank, Technical University of Vienna, Austria Dieter Fritsch, University of Stuttgart, Germany Mike Goodchild, University of California - Santa Barbara Armin Gruen, Swiss Federal Institute of Technology, Switzerland Thanasis Hadzilacos, Computer Technology Institute, Greece Marinos Kavouras, National Technical University of Athens, Greece David Mark, State University of New York at Buffalo Dave McKeown, Carnegie Mellon University Martien Molenaar, ITC, The Netherlands Dimitris Papadias, University of Science and Technology, Hong Kong, China Hanan Samet, University of Maryland - College Park Tapani Sarjakoski, Finnish Geodetic Institute, Finland Timos Sellis, National Technical University of Athens, Greece Shashi Shekhar, University of Minnesota Nektaria Tryfona, Aalborg University, Denmark Vassilis Tsotras, University of California - Riverside Marc van Kreveld, Utrecht University, The Netherlands /RFDO $UUDQJHPHQWV Blane Shaw, University of Maine 2UJDQL]LQJ &RPPLWWHH"

Advancements in digital sensor technology, digital image analysis techniques, as well as computer software and hardware have brought together the fields of computer vision and photogrammetry, which are now converging towards sharing, to a great extent, objectives and algorithms. The potential for mutual benefits by the close collaboration and interaction of these two disciplines is great, as photogrammetric know-how can be aided by the most recent image analysis developments in computer vision, while modern quantitative photogrammetric approaches can support computer vision activities. Devising methodologies for automating the extraction of man-made objects (e.g. buildings, roads) from digital aerial or satellite imagery is an application where this cooperation and mutual support is already reaping benefits. The valuable spatial information collected using these interdisciplinary techniques is of improved qualitative and quantitative accuracy. This book offers a comprehensive selection of high-quality and in-depth contributions from world-wide leading research institutions, treating theoretical as well as implementational issues, and representing the state-of-the-art on this subject among the photogrammetric and computer vision communities.