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Raster Data Model


A raster data model represents geographic space as a grid of cells (called pixels).

Think of it like a chessboard covering the Earth.

  • Each square = cell / pixel

  • Each cell contains a value

  • That value represents information about that location

Example:

  • Elevation = 245 meters

  • Temperature = 32°C

  • Land use = Forest

The grid is arranged in:

  • Rows

  • Columns

This structure is called a matrix.

GRID Model (Cell-Based Matrix Model)

🔹 Concept

The GRID model is the most common raster structure used in GIS for spatial analysis.

It is mainly used for:

  • Continuous data (data that changes gradually)

  • Sometimes discrete/thematic data

🔹 Structure

  • A 2D matrix (rows × columns)

  • Each cell stores one numeric value

    • Integer (whole number)

    • Float (decimal number)

🔹 Key Terminologies

  • Cell Resolution → Size of each pixel (e.g., 30m × 30m)

  • Spatial Resolution → Level of detail

  • DEM (Digital Elevation Model) → Elevation grid

  • Raster Calculator → Tool for mathematical operations

  • Overlay Analysis → Combining multiple raster layers

🔹 Examples

Example 1: Elevation (DEM)

CellValue
A1250 m
A2260 m

Each pixel stores height above sea level.

Example 2: Temperature Map

Each pixel stores:

  • 28.5°C

  • 30.2°C

🔹 Where It Is Used

  • Slope calculation

  • Watershed analysis

  • Rainfall distribution

  • Land suitability analysis

🔹 Advantages

✔ Excellent for mathematical modeling
✔ Ideal for environmental modeling
✔ Easy for spatial analysis

🔹 Disadvantages

✖ Large storage if resolution is high
✖ Less precise for boundary mapping

 IMGRID / IMAGE Model (Imagery Raster)

🔹 Concept

The Image model stores satellite images, aerial photos, scanned images.

It looks like a grid, but:
👉 Each pixel can store multiple values (multi-band).

🔹 Structure

Each pixel contains:

  • One value (grayscale), OR

  • Three values (RGB), OR

  • Multiple spectral bands (Multispectral imagery)

🔹 Key Terminologies

  • Pixel Intensity

  • Spectral Band

  • Multispectral Image

  • RGB (Red, Green, Blue)

  • GeoTIFF

  • World File (.tfw) → Stores georeferencing info

🔹 Example

Example 1: RGB Image

Each pixel stores:

  • Red = 120

  • Green = 90

  • Blue = 60

These combine to produce a color.

Example 2: Sentinel-2 Image

Each pixel stores:

  • Band 2 (Blue)

  • Band 3 (Green)

  • Band 4 (Red)

  • Band 8 (NIR)

Used for:

  • NDVI calculation

  • Vegetation analysis

  • Urban mapping

🔹 Where It Is Used

  • Remote sensing

  • Image classification

  • Change detection

  • Land cover mapping

🔹 Advantages

✔ Good for visualization
✔ Supports multiple bands
✔ Essential for remote sensing

🔹 Disadvantages

✖ Large file size
✖ Requires preprocessing

MAP Model (Scanned Map Raster)

🔹 Concept

The MAP model represents scanned paper maps converted into digital raster form.

Usually:

  • Binary (0 or 1)

  • Black & White

🔹 Structure

  • High resolution scan (300–400 dpi)

  • Pixel values represent:

    • 1 = Feature present

    • 0 = Background

🔹 Key Terminologies

  • Binary Raster

  • Digitization

  • Vectorization

  • Cartographic Raster

  • Georeferencing

🔹 Example

A scanned topographic map:

  • Black lines = roads (1)

  • White background = empty (0)

Used for:

  • Digitizing boundaries

  • Extracting roads

  • Creating vector layers

🔹 Advantages

✔ Useful as background reference
✔ Helps in vectorization

🔹 Disadvantages

✖ Not suitable for analysis
✖ May contain scanning errors


FeatureGRID ModelIMAGE ModelMAP Model
Data TypeNumeric (continuous/discrete)Spectral valuesBinary / Categorical
PurposeSpatial analysisVisualization & Remote sensingBackground / Digitizing
Cell ValueElevation, rainfallRGB / spectral bands1 or 0
ExampleDEMSatellite imageScanned topo sheet

Raster Storage & Compression Methods

Because raster files can be large, special storage techniques are used.

1️⃣ Cell-by-Cell Storage

  • Stores every pixel value separately

  • Simple but large size

Example:
1 1 1 1 0 0 0 1 1

2️⃣ Run-Length Encoding (RLE)

Compresses repeated values.

Instead of:
1 1 1 1 0 0 0 1 1

Store as:
(4,1) (3,0) (2,1)

Saves space when neighboring pixels are similar.

3️⃣ Quadtree Model

Hierarchical division method.

  • Large uniform areas stored as one block

  • Divides only when values change

Example:
A forest area stored as one big block
Urban area divided into smaller blocks

Used in:

  • Large spatial datasets

  • Efficient storage systems


All three models are raster-based (cell structure), but:

  • GRID → Numerical analysis (DEM, rainfall, slope)

  • IMAGE → Remote sensing & spectral analysis

  • MAP → Scanned cartographic reference


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