Geographic Data Models and Remote Sensing

Raster Data Model

• Represents geographic data as a grid of pixels, each with an associated attribute (e.g., color, elevation).
• Best for continuous data like temperature or satellite imagery.
• Generally results in larger file sizes due to high pixel resolution.
• Facilitates overlay and surface modeling analysis.

Vector Data Model

• Represents geographic features (points, lines, polygons) defined by coordinates.
• Ideal for discrete data like roads, borders, and city boundaries.
• Usually has smaller file sizes compared to raster, representing features with fewer data points.
• More effective for network analysis and attribute-based queries.

Remote Sensing

• Acquisition of information about objects or areas from a distance, typically using sensors on satellites or aircraft.
• Data collection of Earth's surface without physical contact.
• Enables large-area observations.
• Application areas include land use, environmental monitoring, and resource management.

Geographic Information Systems (GIS) Components

• Hardware: Physical devices for data collection, storage, and analysis (e.g., computers, servers).
• Software: Programs for GIS functions like mapping, spatial analysis, and data management (e.g., ArcGIS, QGIS).
• Data: Geographic and attribute information crucial for GIS analysis (raster or vector).
• People: Users managing, manipulating, and analyzing GIS data (specialists and decision-makers).
• Procedures: Standard methods for collecting, managing, and analyzing spatial data.