Skip to main content

Geographic and Projected Coordinate Systems

Geographic Coordinate System (GCS)

A Geographic Coordinate System (GCS) uses a three-dimensional spherical surface to define locations on Earth. It is based on a datum, an ellipsoid, and angular units (latitude and longitude).

Key Components of GCS:

  • Latitude (Ï•): Measures the north-south position relative to the Equator (0°). It ranges from 90°N to 90°S.
  • Longitude (λ): Measures the east-west position relative to the Prime Meridian (0°). It ranges from 180°E to 180°W.
  • Datum: Defines the reference ellipsoid and origin point.
  • Ellipsoid: An approximation of the Earth's shape.
  • Geoid: A model of Earth's gravitational surface.

Example of a Geographic Coordinate System:

  • WGS 84 (World Geodetic System 1984) – Used in GPS and global mapping applications.

Advantages of GCS:

  • Accurately represents global locations.
  • Commonly used for spatial data storage and sharing.

Disadvantages of GCS:

  • Distances and areas are distorted because the Earth is not a perfect sphere.
  • Not ideal for detailed, local mapping due to distortions in scale.

Projected Coordinate System (PCS)

A Projected Coordinate System (PCS) is a two-dimensional representation of Earth's surface created by mathematically transforming the curved surface of the Earth onto a flat plane.

Key Components of PCS:

  • Projection Type: Defines how the Earth's surface is transformed.
  • X, Y Coordinates: Express positions in meters or feet instead of latitude and longitude.
  • Origin and Datum: Ensures projection accuracy.

Types of Projections in PCS:

  1. Conformal Projection: Preserves shape but distorts area (e.g., Mercator projection).
  2. Equal-Area Projection: Maintains area but distorts shape (e.g., Albers Equal-Area).
  3. Equidistant Projection: Preserves distances along specific lines (e.g., Plate Carrée).
  4. Azimuthal Projection: Maintains direction but distorts distance (e.g., Lambert Azimuthal Equal Area).

Example of a Projected Coordinate System:

  • UTM (Universal Transverse Mercator): Divides the world into 60 zones, each 6° wide.
  • State Plane Coordinate System (SPCS): Used for high-accuracy local mapping in the U.S.

Advantages of PCS:

  • Preserves distances and areas, making it ideal for local and regional mapping.
  • Allows for easier measurements and calculations in GIS.

Disadvantages of PCS:

  • Distortion increases when used for large-scale or global mapping.
  • Different projections may be required for different regions.

Datums in GIS

A datum is a mathematical model that defines the size, shape, and orientation of the Earth for mapping and surveying purposes.

Types of Datums:

A. Geodetic Datums (Horizontal Datums)

Used for positioning locations on the Earth's surface.

  • Global Datums:

    • WGS 84: Used in GPS and most global applications.
    • ITRF (International Terrestrial Reference Frame): Used for scientific measurements.
  • Local Datums:

    • NAD 27 (North American Datum 1927): Based on Clarke 1866 Ellipsoid, used in North America.
    • NAD 83 (North American Datum 1983): Updated to align with modern satellite data.

B. Vertical Datums

Used for measuring elevations and depths.

  • Geoid-Based:

    • EGM96 (Earth Gravitational Model 1996): Used for global height measurements.
    • NAVD88 (North American Vertical Datum 1988): Used in North America.
  • Ellipsoid-Based:

    • WGS 84 Ellipsoid Height: Used in GPS applications.

Example:

  • A point in New York City might have different coordinates in WGS 84 versus NAD 83 due to differences in datum definitions.

Ellipsoid and Geoid in GIS

These are models of Earth's shape used in geodesy and GIS.

Ellipsoid

  • A mathematically defined smooth surface that approximates the shape of the Earth.
  • Used in map projections and coordinate systems.
  • Example: GRS 80 (Geodetic Reference System 1980), WGS 84.

Geoid

  • Represents the actual shape of the Earth based on gravity measurements.
  • More accurate for elevation measurements than ellipsoids.
  • Example: EGM2008 (Earth Gravitational Model 2008).

Key Differences:

FeatureEllipsoidGeoid
DefinitionSmooth mathematical model of EarthRealistic Earth shape based on gravity
PurposeUsed for mapping and coordinate systemsUsed for measuring precise elevations
ExampleWGS 84, GRS 80EGM96, NAVD88

Example in GIS:

  • GPS uses an ellipsoid model (WGS 84) for positioning.
  • Elevation data often references the geoid (EGM96) for height measurements.


  • GCS (Latitude-Longitude) is best for global positioning but introduces distortions.
  • PCS (Projected X-Y coordinates) is ideal for precise local measurements.
  • Datums define how coordinates align with Earth's shape.
  • Ellipsoids approximate Earth's smooth shape, while geoids account for gravitational variations.

Practical Applications in GIS:

  • GPS Navigation: Uses WGS 84 for positioning.
  • Land Surveys: Use local datums like NAD 83 for high-accuracy mapping.
  • Elevation Mapping: Uses geoid-based vertical datums for terrain analysis.
  • Urban Planning: Uses UTM projections for detailed city mapping.

Comments

Popular posts from this blog

RADIOMETRIC CORRECTION

  Radiometric correction is the process of removing sensor and environmental errors from satellite images so that the measured brightness values (Digital Numbers or DNs) truly represent the Earth's surface reflectance or radiance. In other words, it corrects for sensor defects, illumination differences, and atmospheric effects. 1. Detector Response Calibration Satellite sensors use multiple detectors to scan the Earth's surface. Sometimes, each detector responds slightly differently, causing distortions in the image. Calibration adjusts all detectors to respond uniformly. This includes: (a) De-Striping Problem: Sometimes images show light and dark vertical or horizontal stripes (banding). Caused by one or more detectors drifting away from their normal calibration — they record higher or lower values than others. Common in early Landsat MSS data. Effect: Every few lines (e.g., every 6th line) appear consistently brighter or darker. Soluti...

Atmospheric Correction

It is the process of removing the influence of the atmosphere from remotely sensed images so that the data accurately represent the true reflectance of Earth's surface . When a satellite sensor captures an image, the radiation reaching the sensor is affected by gases, water vapor, aerosols, and dust in the atmosphere. These factors scatter and absorb light, changing the brightness and color of the features seen in the image. Although these atmospheric effects are part of the recorded signal, they can distort surface reflectance values , especially when images are compared across different dates or sensors . Therefore, corrections are necessary to make data consistent and physically meaningful. 🔹 Why Do We Need Atmospheric Correction? To retrieve true surface reflectance – It separates the surface signal from atmospheric influence. To ensure comparability – Enables comparing images from different times, seasons, or sensors. To improve visual quality – Remo...

Geometric Correction

When satellite or aerial images are captured, they often contain distortions (errors in shape, scale, or position) caused by many factors — like Earth's curvature, satellite motion, terrain height (relief), or the Earth's rotation . These distortions make the image not properly aligned with real-world coordinates (latitude and longitude). 👉 Geometric correction is the process of removing these distortions so that every pixel in the image correctly represents its location on the Earth's surface. After geometric correction, the image becomes geographically referenced and can be used with maps and GIS data. Types  1. Systematic Correction Systematic errors are predictable and can be modeled mathematically. They occur due to the geometry and movement of the satellite sensor or the Earth. Common systematic distortions: Scan skew – due to the motion of the sensor as it scans the Earth. Mirror velocity variation – scanning mirror moves at a va...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification:   - You have prior knowledge about the c...

Hazard Mapping Spatial Planning Evacuation Planning GIS

Geographic Information Systems (GIS) play a pivotal role in disaster management by providing the tools and frameworks necessary for effective hazard mapping, spatial planning, and evacuation planning. These concepts are integral for understanding disaster risks, preparing for potential hazards, and ensuring that resources are efficiently allocated during and after a disaster. 1. Hazard Mapping: Concept: Hazard mapping involves the process of identifying, assessing, and visually representing the geographical areas that are at risk of certain natural or human-made hazards. Hazard maps display the probability, intensity, and potential impact of specific hazards (e.g., floods, earthquakes, hurricanes, landslides) within a given area. Terminologies: Hazard Zone: An area identified as being vulnerable to a particular hazard (e.g., flood zones, seismic zones). Hazard Risk: The likelihood of a disaster occurring in a specific location, influenced by factors like geography, climate, an...