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Geographical Information Systems A Practical Approach 2nd Edition By Xuan Zhu

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584
File size
23.88 MB
Format
Digital PDF
Category
eBook[PDF]
About this ebook
The Geographical Information Systems: A Practical Approach (2nd Edition) by Xuan Zhu, published by Routledge, acts as a comprehensive, hands-on introduction to GIS technology and spatial data science.
The primary concepts, methodologies, and technical workflows covered throughout the book are organized into the following areas:
Core Concepts & Fundamentals
  • GIS Overview: Basic definitions, historical evolution, and scope of geographical information systems.
  • System Components: Analysis of hardware, software platforms (specifically ArcGIS Pro and QGIS), data types, and organizational methods.
  • Data Sources & Capture: Methods for gathering spatial information via satellite imagery, GPS, digital/analogue map conversion, and agency reports.
Spatial Data Management & Structure
  • Vector & Raster Formats: Deep dive into discrete vector geometries and continuous raster/grid data models.
  • Attribute Integration: Linking geographic coordinate data with non-spatial attributes (such as population statistics or environmental metrics).
  • Data Integrity: Addressing system limitations, data quality, error margins, and transparency.
Data Analysis & Geoprocessing
  • Spatial Manipulation: Hands-on application of buffering, clipping, intersection, and interpolation.
  • Spatial Statistics & Modelling: Core techniques in spatial data science, including machine learning modules and 3D mapping.
  • Automation Workflow: Implementing ModelBuilder and scripting methods to streamline repetitive geoprocessing tasks.
Visualization & Practical Applications
  • Cartographic Visualization: Principles of map design, presentation, and data dissemination.
  • Socio-Environmental Applications: Case studies detailing how GIS models processes across urban planning, public health, natural resource management, and economic development.
  • Modern Technical Trends: Explores the modern fusion of big data analytics, remote sensing, and PGIS alongside modern privacy and ethics constraints.

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