GIS & Remote Sensing

Geospatial technologies for mapping, analysis, and Earth observation.

Author

Geography Team

Official Syllabus

NEP-2020 Syllabus

NoteCore I Paper VIII β€” Remote Sensing and GIS

**(4 Credit, Theory: 45hrs, Practical: 30hrs)*

**Unit I:* - Sources and characteristics of spatial data: Maps vs RS images - Concept of Remote Sensing, Meaning and significance of EMR Spectrum - Elements of a RS image: Pixel, Digital Number (DN), Band, Resolution - Visual Interpretation of Aerial Photograph and Satellite imagery

**Unit II:* - Abstraction and representation of Spatial Data - Data Models in GIS (Vector Data Model: Types/Components) - Attribute data Management - Query of Spatial and non-spatial Data - Processing and Analysis of Vector Data (Geoprocessing, Overlay Analysis)

**Unit III:* - Working with Continuous spatial Data (Raster Data processing) - Various Gridded Data Sources and application, DEM - Interpretation of Remote Sensing images: Visual and Digital interpretation - Supervised and Unsupervised classification, LULC classification, NDVI - Accuracy assessment - Facility Information System using spatial data, Land Use planning, disaster management

UGC NET Syllabus

TipUnit X β€” Remote Sensing and GIS
  • Remote sensing applications
  • Digital mapping
  • Geographic Information System (GIS)
  • Thematic maps

Welcome to the GIS & Remote Sensing module of Geography OpenCourseWare.

Part A: Common Topics (NEP-2020 & UGC NET)

These topics are covered in both the NEP-2020 undergraduate syllabus and the UGC NET syllabus.

Fundamentals of Remote Sensing and EMR

WarningπŸ“˜ Syllabus Coverage
Syllabus Topic Details
NEP-2020 Unit I β€” Concept of Remote Sensing, EMR Spectrum, Resolution
UGC NET Remote sensing applications

Get the Presentation β†—   |   Watch the Video β†—

NoteKey Concepts
  • Remote Sensing: Acquiring information about an object/phenomenon without making physical contact.
  • EMR (Electromagnetic Radiation): Energy waves interacting with targets. Key regions: Visible (0.4-0.7 Β΅m), Near Infrared (NIR, 0.7-1.3 Β΅m), Shortwave Infrared (SWIR), Thermal IR, Microwave. Vegetation stress is best detected using the SWIR region.
  • NDVI (Normalized Difference Vegetation Index): Calculated as (NIR - Red) / (NIR + Red).
  • GIS Components: It is important to note that GPS is NOT considered a core component of a Geographic Information System (GIS), which typically consists of hardware, software, data, people, and methods.
  • Interaction with Atmosphere: Scattering (Rayleigh, Mie, Non-selective) and Absorption (Ozone, Carbon dioxide, Water vapour). Atmospheric windows.
  • Spectral Signatures: Unique reflectance/emittance curve of a material (e.g., healthy vegetation reflects highly in NIR, absorbs in Red).
  • Sensor Resolutions:
    • Spatial: Size of the smallest detectable feature (pixel size).
    • Spectral: Number and width of spectral bands.
    • Temporal: Revisit time of the satellite.
    • Radiometric: Sensitivity to differences in signal strength (bit depth).
  • **Key Satellite Sensors and Platforms:*
    • Landsat-8 OLI, Sentinel-2 MSI, MODIS, ASTER are major multispectral sensors.
    • LISS-3: The sensor has a spatial resolution of 23.5 meters. The spectral range of the 10-bit SWIR band of the LISS-3 sensor on Resourcesat-2 is 1.55 – 1.70 Β΅m.
    • AWiFS (Advanced Wide Field Sensor): The spatial resolution of this sensor is 56 meters.
    • CartoDEM: This digital elevation model has its origin in India.
    • INSAT (Indian National Satellite): Series of multipurpose geostationary satellites used for Meteorology, telecommunications, and broadcasting.
    • EOS-01: An Indian SAR-based (Synthetic Aperture Radar) earth imaging satellite launched in 2020.
  • **Image Processing & ML:*
    • Random Forest: A widely used and effective machine learning algorithm based on the idea of bagging.
    • FCC Representation: In a standard FCC of the winter season, laterite duricrusts are typically represented in Brown.

GIS Fundamentals and Spatial Data Models

WarningπŸ“˜ Syllabus Coverage
Syllabus Topic Details
NEP-2020 Unit II β€” Data Models in GIS, Vector Data Model
UGC NET Geographic Information System (GIS)

Get the Presentation β†—   |   Watch the Video β†—

NoteKey Concepts
  • GIS (Geographic Information System): A computer system for capturing, storing, querying, analyzing, and displaying geospatial data.
  • Components of GIS: Hardware, Software, Data, People, Procedures.
  • Vector Data Model: Represents features as discrete points, lines, and polygons using coordinates. Best for boundaries, roads, land parcels.
    • Topology: Mathematical rules defining spatial relationships (adjacency, connectivity, containment).
  • Raster Data Model: Represents continuous space as a grid of cells (pixels). Better for elevation (DEM), temperature, imagery.
  • Attribute Data: Non-spatial tabular data linked to spatial features (Relational Database Management System - RDBMS).

Image Interpretation (Visual and Digital)

WarningπŸ“˜ Syllabus Coverage
Syllabus Topic Details
NEP-2020 Unit I & III β€” Visual Interpretation, Digital interpretation
UGC NET Remote sensing applications

Get the Presentation β†—   |   Watch the Video β†—

NoteKey Concepts
  • Visual Image Interpretation: Identifying features using human cognitive processes.
    • Elements: Tone/Color, Size, Shape, Texture, Pattern, Shadow, Site, Association.
  • Digital Image Processing (DIP): Computer-based manipulation of digital numbers (DNs).
    • Pre-processing: Radiometric correction (haze, sun angle), Geometric correction (rectification).
    • Enhancement: Contrast stretching, spatial filtering, band rationing (e.g., NDVI).
  • Image Classification: Assigning pixels to thematic classes (Land Use/Land Cover).
    • Supervised: Analyst defines training sites (spectral signatures), algorithm classifies rest of image (Maximum Likelihood, Random Forest).
    • Unsupervised: Algorithm automatically groups pixels into clusters based on statistical similarity (K-Means, ISODATA); analyst assigns labels later.

Spatial Analysis and Geoprocessing

WarningπŸ“˜ Syllabus Coverage
Syllabus Topic Details
NEP-2020 Unit II β€” Query, Geoprocessing, Overlay Analysis
UGC NET Geographic Information System (GIS)

Get the Presentation β†—   |   Watch the Video β†—

NoteKey Concepts
  • Attribute Query (SQL): Selecting features based on their attribute values (e.g., β€œPopulation > 1,000,000”).
  • Spatial Query: Selecting features based on spatial relationships (intersect, within, adjacent).
  • Vector Overlay Operations: Combining two or more layers to create a new layer (Union, Intersect, Identity).
  • Proximity Analysis: Buffering (creating zones of a specified distance around features).
  • Geoprocessing: Executing operations (Clip, Dissolve, Merge) to manipulate data and solve spatial problems.
  • Vector Data Model: Represents geographical features as points, lines, and polygons.
  • Raster Analysis: Map Algebra (local, focal, zonal, global operations), suitability modeling.
  • Bilinear Interpolation: A resampling technique that uses a weighted average of the four closest pixels to determine the new pixel value.
  • Overlay Analysis Applications: This technique is suitable for identifying changes in river bankline polygons across different years.

Applications of GIS and Remote Sensing

WarningπŸ“˜ Syllabus Coverage
Syllabus Topic Details
NEP-2020 Unit III β€” LULC, NDVI, Facility Information System, Land Use planning, disaster management
UGC NET Remote sensing applications, Digital mapping, Thematic maps

Get the Presentation β†—   |   Watch the Video β†—

NoteKey Concepts
  • Vegetation Indices: NDVI (Normalized Difference Vegetation Index) = (NIR - Red) / (NIR + Red). Evaluates vegetation health and biomass.
  • Land Use / Land Cover (LULC): Mapping and monitoring changes over time (urban sprawl, deforestation).
  • Disaster Management: Flood inundation mapping, forest fire burn scar analysis, earthquake damage assessment, landslide susceptibility zonation.
  • Urban and Regional Planning: Facility site selection (suitability analysis), transportation network routing (Network Analysis), land use zoning.
  • Digital Elevation Models (DEM): Extracting slope, aspect, stream networks, and watershed boundaries.

Quick Reference

GIS & Remote Sensing Quick Reference

Key Books and Authors

Book Author
Remote Sensing and Image Interpretation Lillesand, Kiefer, & Chipman
Geographic Information Systems and Science Longley, Goodchild, Maguire, Rhind

Key Concepts

Concept Description
Electromagnetic Spectrum Visible, NIR, SWIR, TIR, Microwave used in RS.
Resolution Spatial, Spectral, Radiometric, Temporal.
Vector vs Raster Points/lines/polygons vs Grids/pixels.
Active vs Passive RS Radar/LiDAR (Active) vs Optical (Passive).

Notes compiled by Geography Team