Skip to main content

Mapping Process


The mapping process involves several systematic steps to transform real-world spatial information into a readable, accurate, and useful representation. Below is a structured explanation of each step in the mapping process, with key concepts, terminologies, and examples.


1. Defining the Purpose of the Map

Before creating a map, it is essential to determine its purpose and audience. Different maps serve different objectives, such as navigation, analysis, or communication.

Types of Maps Based on Purpose:

  • Thematic Maps: Focus on specific subjects (e.g., climate maps, population density maps).
  • Topographic Maps: Show natural and human-made features (e.g., contour maps, landform maps).
  • Tourist Maps: Highlight attractions, roads, and landmarks for travelers.
  • Cadastral Maps: Used in land ownership and property boundaries.
  • Navigational Maps: Used in GPS systems for wayfinding.

Example: A disaster risk map for floods will highlight flood-prone areas, emergency shelters, and evacuation routes.


2. Determining the Scale

Scale defines the relationship between distances on a map and real-world distances. It affects the level of detail that can be shown.

Types of Scale Representation:

  • Verbal Scale: Expressed in words (e.g., "1 cm represents 1 km").
  • Graphic Scale (Scale Bar): A visual bar that helps measure distances directly on the map.
  • Fractional/Ratio Scale: Expressed as a ratio (e.g., 1:50,000, meaning 1 unit on the map equals 50,000 units on the ground).

Scale Categories:

  • Large-scale maps (e.g., 1:10,000) – Show more detail, used for city maps.
  • Small-scale maps (e.g., 1:1,000,000) – Cover large areas with less detail, used for world maps.

Example: A city zoning map uses a large scale (1:5,000) to show detailed streets and land use, while a world political map uses a small scale (1:10,000,000) to show only country borders.


3. Selecting the Spatial Entities (Features to Include)

Maps do not include everything; only relevant features are selected based on the map's purpose.

Types of Spatial Entities:

  • Points: Used for features with no area (e.g., cities, landmarks, schools).
  • Lines: Represent linear features (e.g., roads, rivers, pipelines).
  • Polygons: Show areas (e.g., lakes, forests, administrative boundaries).

Example: A road map includes roads (lines), cities (points), and national parks (polygons), but excludes unnecessary details like individual houses.


4. Choosing Methods of Representation (Symbols and Colors)

Maps use different visual elements to represent spatial features clearly and effectively.

Common Map Representation Methods:

  • Symbols: Used to represent objects (e.g., an airplane symbol for an airport).
  • Colors: Differentiate features (e.g., blue for water, green for forests, brown for elevation).
  • Shading & Patterns: Used to show density or intensity (e.g., population density maps).
  • Labels & Annotations: Provide names and descriptions.

Example: A land use map might use yellow for urban areas, green for forests, and blue for water bodies.


5. Generalization (Simplifying the Map)

Generalization involves removing unnecessary details while keeping the most important information.

Generalization Techniques:

  • Selection: Choosing essential features to include.
  • Simplification: Reducing complexity (e.g., simplifying river curves).
  • Aggregation: Grouping similar features (e.g., showing small islands as one).
  • Exaggeration: Enlarging important small features (e.g., making roads wider for visibility).
  • Displacement: Moving features slightly to avoid overlap.

Example: On a world map, small towns may not be shown, and minor rivers might be omitted to avoid clutter.


6. Applying a Map Projection

Since the Earth is a 3D sphere, it must be transformed onto a 2D plane using map projections. Different projections are used depending on the purpose of the map.

Common Map Projections:

  • Mercator Projection: Preserves shape but distorts area (used for navigation).
  • Robinson Projection: Balances distortions for a realistic world map.
  • Lambert Conformal Conic Projection: Used for regional maps where shape accuracy is important.
  • UTM (Universal Transverse Mercator): Used in detailed topographic maps and GIS.

Example: A flight route map uses Mercator projection because it preserves direction, while a climate zone map uses Robinson projection to give a realistic representation.


7. Applying Spatial Reference System (Coordinate System)

Every map needs a spatial reference system to position features correctly. This involves choosing the right coordinate system.

Types of Coordinate Systems:

  • Geographic Coordinate System (GCS): Uses latitude and longitude (e.g., WGS84).
  • Projected Coordinate System (PCS): Uses Cartesian (X, Y) coordinates (e.g., UTM Zones).
  • Local Coordinate Systems: Customized for a region (e.g., Indian Grid System).

Why Spatial Reference Matters?

  • Ensures maps align correctly with other datasets.
  • Allows for accurate measurements of distance and area.

Example:

  • Google Maps uses the Web Mercator projection (EPSG:3857).
  • GIS applications in India commonly use WGS 84 UTM Zone 44N for better accuracy.

Comments

Popular posts from this blog

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. ๐Ÿ›ฐ️ 1. Active Remote Sensing ๐Ÿ“˜ Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. ๐Ÿ“Š Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...

Resolution of Sensors in Remote Sensing

Spatial Resolution ๐Ÿ—บ️ Definition : The smallest size of an object on the ground that a sensor can detect. Measured as : The size of a pixel on the ground (in meters). Example : Landsat → 30 m (each pixel = 30 × 30 m on Earth). WorldView-3 → 0.31 m (very detailed, you can see cars). Fact : Higher spatial resolution = finer details, but smaller coverage. Spectral Resolution ๐ŸŒˆ Definition : The ability of a sensor to capture information in different parts (bands) of the electromagnetic spectrum . Measured as : The number and width of spectral bands. Types : Panchromatic (1 broad band, e.g., black & white image). Multispectral (several broad bands, e.g., Landsat with 7–13 bands). Hyperspectral (hundreds of very narrow bands, e.g., AVIRIS). Fact : Higher spectral resolution = better identification of materials (e.g., minerals, vegetation types). Radiometric Resolution ๐Ÿ“Š Definition : The ability of a sensor to ...

Optical Sensors in Remote Sensing

1. What Are Optical Sensors? Optical sensors are remote sensing instruments that detect solar radiation reflected or emitted from the Earth's surface in specific portions of the electromagnetic spectrum (EMS) . They mainly work in: Visible region (0.4–0.7 ยตm) Near-Infrared – NIR (0.7–1.3 ยตm) Shortwave Infrared – SWIR (1.3–3.0 ยตm) Thermal Infrared – TIR (8–14 ยตm) — emitted energy, not reflected Optical sensors capture spectral signatures of surface features. Each object reflects/absorbs energy differently, creating a unique spectral response pattern . a) Electromagnetic Spectrum (EMS) The continuous range of wavelengths. Optical sensing uses solar reflective bands and sometimes thermal bands . b) Spectral Signature The unique pattern of reflectance or absorbance of an object across wavelengths. Example: Vegetation reflects strongly in NIR Water absorbs strongly in NIR and SWIR (appears dark) c) Radiance and Reflectance Radi...

geostationary and sun-synchronous

Orbital characteristics of Remote sensing satellite geostationary and sun-synchronous  Orbits in Remote Sensing Orbit = the path a satellite follows around the Earth. The orbit determines what part of Earth the satellite can see , how often it revisits , and what applications it is good for . Remote sensing satellites mainly use two standard orbits : Geostationary Orbit (GEO) Sun-Synchronous Orbit (SSO)  Geostationary Satellites (GEO) Characteristics Altitude : ~35,786 km above the equator. Period : 24 hours → same as Earth's rotation. Orbit type : Circular, directly above the equator . Appears "stationary" over one fixed point on Earth. Concepts & Terminologies Geosynchronous = orbit period matches Earth's rotation (24h). Geostationary = special type of geosynchronous orbit directly above equator → looks fixed. Continuous coverage : Can monitor the same area all the time. Applications Weather...