Lesson 1: Introduction to Remote Sensing
Remote Sensing (RS) is the science and art of acquiring information about the Earth's surface, oceans, and atmosphere from a distance, typically using sensors mounted on satellites, aircraft, or drones (UAVs). Instead of physically touching the target, these sensors record reflected or emitted electromagnetic radiation.
Active vs. Passive Sensors
Sensors are broadly classified based on their energy source:
- Passive Sensors: Record natural radiation reflected or emitted by the Earth. The Sun is the primary source of illumination. Examples include Landsat Operational Land Imager (OLI) and Sentinel-2 Multi-Spectral Instrument (MSI). If it is night, passive optical sensors cannot capture reflected sunlight.
- Active Sensors: Provide their own energy source to illuminate the target. They emit electromagnetic pulses and measure the backscattered energy. Examples include RADAR (Synthetic Aperture Radar / SAR) and LiDAR. These sensors can capture data during both day and night, and can even penetrate cloud covers.
Lesson 2: The Electromagnetic Spectrum
All remote sensing systems rely on the Electromagnetic Spectrum (EMS). The spectrum ranges from high-energy gamma rays to long radio waves. Remote sensing primarily operates in the visible, infrared, and microwave wavelengths.
Key Wavelength Bands in RS:
- Visible Range (0.4 to 0.7 μm): Blue (0.4-0.5 μm), Green (0.5-0.6 μm), and Red (0.6-0.7 μm). These are the only wavelengths visible to the human eye.
- Infrared Range (0.7 to 100 μm):
• Near-Infrared (NIR, 0.7-1.3 μm): Extremely useful for monitoring vegetation health, as healthy plant cells highly reflect NIR radiation.
• Short-wave Infrared (SWIR, 1.3-3.0 μm): Sensitive to vegetation moisture levels and soil mineral composition.
• Thermal Infrared (TIR, 3.0-14 μm): Measures emitted heat (thermal radiation) from the Earth's surface. Used for surface temperature mapping. - Microwave Range (1 mm to 1 m): Primarily utilized by active RADAR systems to measure land textures, soil moisture, and ocean wave heights.
Atmospheric Windows
The atmosphere contains gases (water vapor, CO2, ozone) that absorb or scatter specific wavelengths. Wavelengths that pass through the atmosphere with minimal absorption are called atmospheric windows. Satellites are designed to record data specifically within these windows.
Lesson 3: Satellite Orbits
The path a satellite follows around the Earth is its orbit. Orbits are selected based on the sensor's capabilities and the purpose of the mission.
1. Sun-Synchronous (Polar) Orbits
These satellites orbit at altitudes of 600–800 km, passing near both poles. The orbit is synchronized with the Sun, meaning the satellite crosses the equator at the exact same local solar time on every pass. This ensures consistent sun illumination angles, making it much easier to detect land cover changes over time. Examples: Landsat, Sentinel-2, SPOT.
2. Geostationary Orbits
These satellites orbit at an altitude of approximately 35,786 km directly above the Earth's equator. They travel at the exact same rotational speed as the Earth. As a result, they remain stationary over a single point on the Earth's surface. These orbits are ideal for real-time weather monitoring and telecommunications. Examples: INSAT, METEOSAT.
Lesson 4: Coordinates & Coordinate Reference Systems
A Coordinate Reference System (CRS) defines how a two-dimensional, flat map represents the three-dimensional, curved surface of the Earth. Without a CRS, satellite pixels cannot align with real-world physical locations.
Geographic vs. Projected Coordinate Systems
- Geographic Coordinate System (GCS): Represents locations on a spherical three-dimensional model of the Earth using angular units (Degrees, Minutes, Seconds). Coordinates are measured in Latitude (Y, North/South) and Longitude (X, East/West) from the prime meridian and equator. The most common global datum is WGS 84 (EPSG:4326).
- Projected Coordinate System (PCS): Projects the curved GCS coordinates onto a flat two-dimensional plane using linear units (Meters, Feet). This allows accurate measurements of distance, area, and angles. The most widely used system is the Universal Transverse Mercator (UTM), which divides the Earth into 60 zones.
Lesson 5: Visual Image Interpretation
Before applying computer-based classification algorithms, geologists and geographers analyze remote sensing imagery using visual interpretation elements:
| Element | Description | Example Application |
|---|---|---|
| Tone / Color | Relative brightness or color band combinations in the image. | Healthy vegetation appears bright red in false-color infrared. |
| Size | The physical scale of the object relative to surrounding targets. | Distinguishing a single-family house from a large commercial warehouse. |
| Shape | The geometric outline or configuration of the object. | Straight-edged shapes indicate agricultural fields or man-made structures. |
| Texture | The visual roughness or smoothness of a region. | Lush forest canopy appears rough; calm open water appears smooth. |
| Pattern | The spatial arrangement of recurring objects. | Orchards show evenly spaced grids; rivers show branching dendritic patterns. |
| Shadow | The dark silhouette cast by an object. | Used to estimate building heights or identify mountain ridge terrain. |
| Association | Relating an object to its nearby features. | A large school building is often associated with adjacent playgrounds. |