Satellite remote sensing operates on the fundamental principles of capturing and analyzing electromagnetic radiation reflected or emitted from the Earth's surface. The core principles include energy source and interaction, spectral resolution, spatial resolution, radiometric resolution, and temporal resolution. While the provided reference focuses primarily on active sensors using microwave radiation, a comprehensive understanding requires considering both active and passive systems.
Key Principles Explained
-
Energy Source and Interaction: Remote sensing relies on an energy source, which is most commonly the sun for passive systems. Active systems, however, provide their own energy source (e.g., microwave radar). The energy interacts with the Earth's surface, and the nature of this interaction (reflection, absorption, transmission, scattering) is dependent on the properties of the surface material.
-
Spectral Resolution: This refers to the sensor's ability to define narrow wavelength intervals. High spectral resolution allows for fine distinctions between different surface features based on their unique spectral signatures (the pattern of reflectance and emittance across various wavelengths). For example, different types of vegetation reflect light differently in the near-infrared part of the spectrum.
-
Spatial Resolution: This defines the smallest discernible object or feature on the ground. It's typically expressed as the size of a pixel in the image (e.g., 30 meters, 1 meter). A higher spatial resolution means finer details can be observed.
-
Radiometric Resolution: This refers to the sensitivity of the sensor to differences in signal strength. It determines the number of distinct levels of brightness or reflectance that can be recorded. Higher radiometric resolution (e.g., 12-bit) provides more detailed information about subtle variations in surface characteristics than lower resolution (e.g., 8-bit).
-
Temporal Resolution: This describes how often a sensor revisits and acquires data for the same location. High temporal resolution is important for monitoring dynamic phenomena like deforestation, flooding, or agricultural changes. Satellites with different orbits provide varying temporal resolutions.
Passive vs. Active Remote Sensing
| Feature | Passive Remote Sensing | Active Remote Sensing |
|---|---|---|
| Energy Source | Sun (or Earth's own emitted radiation) | Sensor's own source (e.g., radar, lidar) |
| Signal Measured | Reflected or emitted radiation | Backscattered signal |
| Examples | Landsat, Sentinel, MODIS | Radar satellites (e.g., RADARSAT), lidar (e.g., ICESat) |
| Advantages | Relatively simple, requires less power, sensitive to spectral features | Can operate day or night, penetrates clouds, provides information about surface roughness and structure |
| Disadvantages | Dependent on sunlight, affected by atmospheric conditions | Requires more power, can be more complex to interpret, may have speckle noise (radar), potentially costly development |
Active Sensors: Illuminating with Microwaves
As the provided reference correctly states, active sensors, such as those using radar, emit their own microwave radiation to illuminate the target area. The sensor then measures the amount of microwave energy scattered back. This allows for data acquisition even at night or through cloud cover, a significant advantage over passive systems. By analyzing the backscattered signal, information about surface roughness, moisture content, and other physical properties can be derived.
In summary, the principles of satellite remote sensing encompass the capture and analysis of electromagnetic radiation from the Earth’s surface, utilizing both passive and active systems to gather data across different spectral, spatial, radiometric, and temporal resolutions. The choice of sensor and its configuration is highly dependent on the specific application.
