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Heterogeneous Spatial Data - Fusion, Modeling, and Analysis for GIS Applications (Paperback)
Loot Price: R1,320
Discovery Miles 13 200
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Heterogeneous Spatial Data - Fusion, Modeling, and Analysis for GIS Applications (Paperback)
Series: Synthesis Lectures on Visual Computing: Computer Graphics, Animation, Computational Photography and Imaging
Expected to ship within 10 - 15 working days
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New data acquisition techniques are emerging and are providing fast
and efficient means for multidimensional spatial data collection.
Airborne LIDAR surveys, SAR satellites, stereo-photogrammetry and
mobile mapping systems are increasingly used for the digital
reconstruction of the environment. All these systems provide
extremely high volumes of raw data, often enriched with other
sensor data (e.g., beam intensity). Improving methods to process
and visually analyze this massive amount of geospatial and
user-generated data is crucial to increase the efficiency of
organizations and to better manage societal challenges. Within this
context, this book proposes an up-to-date view of computational
methods and tools for spatio-temporal data fusion, multivariate
surface generation, and feature extraction, along with their main
applications for surface approximation and rainfall analysis. The
book is intended to attract interest from different fields, such as
computer vision, computer graphics, geomatics, and remote sensing,
working on the common goal of processing 3D data. To this end, it
presents and compares methods that process and analyze the massive
amount of geospatial data in order to support better management of
societal challenges through more timely and better decision making,
independent of a specific data modeling paradigm (e.g., 2D vector
data, regular grids or 3D point clouds). We also show how current
research is developing from the traditional layered approach,
adopted by most GIS softwares, to intelligent methods for
integrating existing data sets that might contain important
information on a geographical area and environmental phenomenon.
These services combine traditional map-oriented visualization with
fully 3D visual decision support methods and exploit
semantics-oriented information (e.g., a-priori knowledge,
annotations, segmentations) when processing, merging, and
integrating big pre-existing data sets.
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