Remote Sensing Part 3: Image and Resolution

Nature of the Image

• Pixel: Basic unit in imaging with spatial and spectral properties.
• Spatial Property: Represents the height and width of ground features.
• Spectral Property: Indicates intensity of spectral response in a specific band.
• Sample Components:
  • Buildings: 15% coverage, 90% reflectance.
  • Sand: 15% coverage, 100% reflectance.
  • Trees: 50% coverage, 50% reflectance.
  • Water: 20% coverage, 10% reflectance.

Image Resolution Types

• Spatial Resolution: Defines the smallest detail visible in an image; high resolution allows for discernible small features.
• Spectral Resolution: Refers to the wavelength range detected by the sensor; narrower bands enhance resolution.
• Radiometric Resolution: Measures the sensor's detail observation capability; more levels allow for finer detail.
• Temporal Resolution: Indicates observation frequency depending on satellite orbit, target latitude, and sensor swath width.

Spatial Resolution

• Coarser resolutions obscure small features, while finer resolutions reveal them.
• Influencing Factors: Atmosphere, haze, smoke, sensor clarity, pixel size, and Instantaneous Field of View (IFOV).
• IFOV: Angle of visibility for sensor detection, affecting spatial resolution.
• Shorter focal lengths yield wider fields of view; longer lengths provide smaller footprints.

Image Scale

• Scale represents the distance on an image versus the corresponding ground distance.
• Large scale (e.g., 1:50,000) shows objects clearly; small scale (e.g., 1:250,000) renders objects less discernible.
• Ground Sample Distance (GSD): Distance between pixel centers, greater height results in larger GSD and lower resolution.

Interpretability in Spatial Resolution

• Detectability: Ability to record an object’s presence even if it's below the operational capacity.
• Recognizability: Identifying objects correctly; can be detected but not recognized.
• Identification: Distinguishing features such as vehicle types or tree species.

Spectral Resolution

• Spectral resolution is determined by bandwidths of detected bands; narrow bands provide greater resolution.
• Multispectral sensors record data across multiple bands, combining them to form color images.

Types of Composite Images

• True Color Composite: Combines primary color bands (red, green, blue) captured by sensors.
• False Color Composite: Uses arbitrary color assignments to identify distinct ground features, especially when primary bands are not available.
• Natural Composite Image: Resembles a visual photograph created from available spectral bands.

Hyperspectral Sensors

• Capture numerous narrow spectral bands, enabling detailed reflectance spectrum construction.
• Typically more than 100 bands recorded, facilitating advanced spectral analyses via imaging spectrometers.

Remote Sensing Applications

• Geological: Includes mapping surface deposits, mineral exploration, environmental geology, and hazard mapping.
• Hydrological: Encompasses wetland mapping, flood monitoring, and groundwater exploration.
• Land-Use: Addresses wildlife habitat protection, urban development, and damage assessment from disasters.
• Oceanographic: Involves ocean monitoring, storm forecasting, and oil spill response.

Signal to Noise Ratio

• Defined as the ratio of signal power to background noise; high SNR simplifies differentiation between the two.

Balancing Resolutions

• Fine spatial resolution typically correlates with small IFOV but may lead to lower energy detection capabilities.
• Successful imaging requires a balance between spatial, spectral, and radiometric resolutions tailored to specific objectives.