Geographic Information Systems (GIS) Lecture Notes

Introduction to Remote Sensing

• Overview of Week's Focus:
  • Types of spatial analysis in GIS
  • Introduction to remote sensing
  • Basics of spatial analysis
  • Advanced spatial analysis
  • Limitations of GIS

What is Remote Sensing?

• Definition:

  • Science and art of obtaining information about an object, area, or phenomenon from a distance without physical contact.
  • Examples: Buildings, soil types, water bodies, natural disasters (e.g., landslides, earthquakes).

• Example of Remote Sensing:

  • Watching a video lecture (sensing without physical contact).

Types of Remote Sensing

• Passive Remote Sensing:

  • Uses natural energy (e.g., sunlight). Sensors detect reflected solar radiation.

• Active Remote Sensing:

  • Sensors emit their own energy (e.g., radar).

Remote Sensing Process

1. Data Acquisition:

   • Sensors (active or passive) collect data.
   • Data can be raster images, numerical data, or reference data.

2. Data Interpretation:

   • Visual or digital interpretation using algorithms.

3. Output Generation:

   • Outputs may include maps, numerical reports, or technical reports.

Types of Sensors

• Satellite Remote Sensing:

  • Typically 800-900 km above the Earth's surface.

• High Altitude Remote Sensing:

  • 20-30 km above the surface.

• Low Altitude Remote Sensing:

  • 1-2 km above the ground.

• Ground Level Remote Sensing:

  • On the Earth's surface (e.g., UAVs).

Data and Resolutions

• Data Transformation:
  • Transform data from analog to digital forms.
• Resolutions in Remote Sensing:
  • Spatial Resolution: The size of the area represented by a pixel.
  • Spectral Resolution: The number and width of spectral bands.
  • Radiometric Resolution: The sensitivity of the sensor to detect variations in energy levels (measured in bits).
  • Temporal Resolution: How often data is collected for the same area.

Electromagnetic Spectrum

• Definition:

  • The range of all types of electromagnetic radiation.

• Key Concepts:

  • Wavelength, frequency, energy relationships.
  • Energy of a quantum: E = Hν, where H is Planck's constant and ν is frequency.
  • Wien's Displacement Law: Wavelength is inversely proportional to temperature.
  • Stefan-Boltzmann Law: Total radiant emittance is proportional to the fourth power of temperature.

Reflectance Curves

• Importance:
  • Reflectance curves show how different materials (e.g., vegetation, water, soil) reflect light differently across the electromagnetic spectrum.
  • NDVI (Normalized Difference Vegetation Index): Used to assess vegetation health and density.

Conclusion

• Summary of Key Points:
  • Remote sensing is essential for various applications in GIS. Understanding resolutions and the electromagnetic spectrum is critical for effective analysis.
  • In upcoming classes, we will delve deeper into GIS spatial analysis and advanced topics.