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What Is Raster Data in GIS?

  • Writer: Anvita Shrivastava
    Anvita Shrivastava
  • Nov 17
  • 3 min read

Raster data is one of the two main ways to represent spatial information in Geographic Information Systems (GIS). Understanding raster data is vital for GIS practitioners, remote sensing scientists, and data scientists working with geospatial datasets. In this article, we will explore the technical details of raster data, including what it is, its structure, how it can be used, its advantages, and its limitations.


Raster Data in GIS
Raster Data in GIS

What is Raster Data in GIS?


Raster data, or grid-based data, represents the world as a matrix of cells or pixels that are organized in rows and columns. Each cell is awarded a value that represents something about a certain geographic area. Raster data is unlike vector data, which represents features with points, lines, and polygons. Raster data is particularly suited for representing continuous features, such as:



Because raster data allows each geographic location to be represented with a numeric value, it is a key data structure for modeling, analyzing, and visualizing continuous spatial phenomena.


Technical Structure of Raster Data


Raster data has three main components:


  1. Cells/Pixels: The basic unit of a raster layout. Cells store a value that signifies a feature or attribute.

  2. Resolution: Indicates the size of each cell. If a raster has a higher resolution, cells are smaller and represent spatial information more accurately. For example, a 30m resolution raster has pixels that represent a 30m x 30m area on the surface of the land.

  3. Extent: The geographic area that the raster covers, which is determined by the boundary coordinates.


Raster data can be single-band or multi-band:


  • Single-band raster: has one value per cell (e.g., elevation).

  • Multi-band raster: has more than one value per cell, typically used regarding a geographic area of interest or regarding satellite images (e.g., Red, Green, Blue and Infrared bands).


Common Raster Data Formats


Depending on the use case, GIS professionals work with several raster file formats:


  • GeoTIFF: a georeferenced TIFF image that is quite popular in a GIS environment.

  • ASCII Grid: a text-based raster format that is often used for interoperability.

  • ERDAS Imagine (IMG): a raster format designed for high-performance raster operations for the remote sensing community.

  • JPEG2000: a compressed raster format that has support for multi-band imagery.


Regardless of the raster file format, all can contain georeferencing information, so a raster file can be aligned with the coordinate system of the real world.


Sources of Raster Data


Raster data may have originated from the following sources:


  1. Satellite Imagery: Landsat, Sentinel, and MODIS

  2. Aerial Photography: capturing images using drones and aircraft

  3. Remote sensing sensors: LiDAR and RADAR

  4. Digital Elevation Models (DEMS): created from either topographic surveys or photogrammetry.


Uses of Raster Data in GIS


Raster data has a broad array of uses in spatial analysis and modeling, including:


  • Terrain Analysis: Using digital elevation models (DEMs) to determine slope, aspect, and watershed.

  • Environmental Monitoring: Monitoring forest health, deforestation, and pollutants.

  • Hydrological Modeling: Assessing flood risk, modeling the flow of water.

  • Urban Planning: Mapping land use and land cover, including urban heat island mapping.

  • Remote Sensing Analysis: Classification, calculation of NDVI, and change detection.


Strengths of Raster Data


  • Efficient representation of continuous data.

  • Facilitates the ease of processing analytical data and statistics.

  • It can be used for remote sensing data and satellite images.

  • Can simplify complex spatial analysis.


Drawbacks of Raster Data


  • Large storage needs for high-definition datasets

  • Lost accuracy compared to vector data when storing discrete objects

  • Inability to represent linear objects precisely

  • Processing-intensive with large datasets


Raster vs. Vector Data: Key Differences

Feature

Raster Data

Vector Data

Representation

Grid of cells

Points, lines, polygons

Best for

Continuous phenomena

Discrete features

Storage

Large for high-resolution

Smaller for simple features

Analysis

Pixel-based calculations

Topology-based operations

In GIS, raster data is a fundamental resource for the study of continuous spatial phenomena. With its grid structure, compatibility with remote sensing images, and ability to work in large-scale spatial analysis, raster data serves as the backbone of geospatial intelligence. By understanding raster data, GIS professionals can conduct sophisticated spatial analysis through simulations, environmental monitoring, and the performance of predictive spatial analysis.


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