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  • av Tao Tang
    1 426,-

    Unique and authoritative reference combining concepts, theories, and hands-on analysis in the ArcGIS Pro software environment Fundamentals of Geographic Information Systems (GIS) Analysis bridges the gap between academic discussions and research with public and private professional practices in the field. The book discusses and illustrates essential concepts and theories, with tutorials showing students how to conduct hands-on analysis in the ArcGIS Pro software environment. Supplementary material for this text includes data files for the tutorials and students exercises. All datasets are sourced from public domains, including the US Census Bureau data, the New York State ITS Geospatial Services (https: //data.gis.ny.gov/), the New York State Department of Environmental Conservation (NYSDEC), the GIS Services of Erie County New York, and others. Written by a highly qualified academic, the book covers topics such as: Digital data models representing geographic information, including vector, raster, and 3D models Methods of spatial data input in vector and raster data formats to incorporate geographic features and events with their attribute data Geographic data collections in natural sciences, engineering, and social sciences, and relational, spatial, and structural querying of a database Coordinate systems, map projection, geo-referencing, geographic analyses, and internet-enabled geographic information sharing Spatial interpolation and spatial statistical analysis, network analysis, digital mapping, and map presentations Uniquely combining academic research and discussions with professional practices in the software and data analysis environments, Fundamentals of Geographic Information Systems (GIS) Analysis is an essential reference for GIS analysts and technicians, urban planners, civil engineers, and computer scientists, along with students in related programs of study.

  • - Algorithms, Analysis and Applications
    av Jie Shen, Tao Tang & Li-Lian Wang
    1 776,-

    Along with finite differences and finite elements, spectral methods are one of the three main methodologies for solving partial differential equations on computers. This book provides a detailed presentation of basic spectral algorithms, as well as a systematical presentation of basic convergence theory and error analysis for spectral methods.

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