Spatial Data Analysis with GIS

INTRODUCTION

  • Definition of Geographical Information System (GIS):
    • A powerful set of tools for:
    • Collecting, storing, retrieving, transforming, and displaying spatial data.
    • General definition: Tools that process spatial data into information (DeMers, 1997).
    • Technical definition: Data about real-world objects stored in a database linked to onscreen maps (ESRI).
    • Geographical Information Science: Study of spatial information handling problems (Burrough, McDonnell, & Lloyd, 2015).
    • Geographical Information and Society: Examines social impacts and equity in GIS use (Burrough, McDonnell, & Lloyd, 2015).

USE OF GIS

  • Provides tools for various applications:
    • Natural resource management
    • Demographic research
    • Environmental research
    • Land use planning
    • Fleet management
    • Assessment and planning

COMPONENTS OF GIS

  1. Users:
    • Require technical and scientific knowledge.
  2. Software:
    • Data input (existing datasets, field observations).
    • Data storage and management (DBMS).
    • Data output and presentation methods.
    • Data transformation (error removal and answering questions).
    • Examples: ArcGIS, MapInfo, ERDAS, QGIS/GRASS.
  3. Hardware:
    • Provides computing capacity and access to data.
    • Includes computers, servers, and peripheral hardware (e.g., scanners).
  4. Spatial Data:
    • Four components: Geometry, Attributes, Topology, Behavior.
    • Organization into geographic databases linked by thematic layers.
  5. Database Management Systems:
    • Facilitate data organization and storage.

TYPES OF SPATIAL DATA

Vector Data:

  • Stores positional coordinates for shapes (points, lines, polygons).
  • Advantages:
    • Requires less storage space.
    • Better resolution and quality graphics.
  • Disadvantages:
    • Complex processing algorithms.
    • Requires high computational power for vectorizing.

Raster Data:

  • Uses a grid of square cells to represent continuous data.
  • Advantages:
    • Easy analysis of neighborhood relations.
    • Simpler processing algorithms.
  • Disadvantages:
    • Limited resolution due to cell size.
    • Requires more storage space than vector data.

METADATA

  • Descriptive information about spatial data (source, resolution, availability).
  • Necessary for data interpretation and credibility.

GIS OPERATIONS

  • A GIS should perform fundamental operations:
    a) Capture data
    b) Querying data (finding specific features)
    c) Data analysis (proximity, overlay, statistical methods)
    d) Outputting data (various display options)

REMOTE SENSING BASICS

  • Definition: Collection of data about objects without physical contact.
  • Types of systems:
    • Active systems (emitting radiation).
    • Passive systems (using natural radiation).
    • Sensors: Primary mechanisms to capture environmental data.

ENERGY SOURCES AND RADIATION PRINCIPLES

  • Visible Light: Specific form of electromagnetic radiation.
  • Electromagnetic Spectrum:
    • Visible, Infrared, and Microwave radiation segments.
  • Energy Content:
    • Inversely proportional to wavelength.

SPATIAL DATA ANALYSIS AND INTERPOLATION

  • Spatial Interpolation: Predicting values at unsampled sites from point measurements.
  • Interpolation Methods:
    • Global methods (trend surfaces, classifications).
    • Local methods (nearest neighbors, inverse distance weighting, splines).
    • Geostatistical methods (kriging, variogram).

CONCLUSION

  • GIS is an essential tool for spatial data analysis and management, integrating various components and methodologies to support decision-making in various fields.
  • Different types of spatial data and analysis methods allow for diverse applications in research and practical scenarios like environmental management and urban planning.
  • Understanding the underlying principles and operations of GIS is crucial for effective utilization and analysis of spatial information.