Skip to main content

Discrete Detectors and Scanning mirrors Across the track scanner Whisk broom scanner.

Multispectral Imaging Using Discrete Detectors and Scanning Mirrors (Across-Track Scanner or Whisk Broom Scanner)

Multispectral Imaging: This technique involves capturing images of the Earth's surface using multiple sensors that are sensitive to different wavelengths of electromagnetic radiation. This allows for the identification of various features and materials based on their spectral signatures.

Discrete Detectors: These are individual sensors that are arranged in a linear or array configuration. Each detector is responsible for measuring the radiation within a specific wavelength band.

Scanning Mirrors: These are optical components that are used to deflect the incoming radiation onto the discrete detectors. By moving the mirrors, the sensor can scan across the scene, capturing data from different points.

Across-Track Scanner or Whisk Broom Scanner: This refers to the scanning mechanism where the mirror moves perpendicular to the direction of flight. This allows for the collection of data along a swath, covering a wide area on the ground.

Remote Sensing Terminologies

A. Rotating Mirror

  • Definition: A mechanical component in some satellite-based remote sensing systems that rotates to scan the Earth's surface. It directs sunlight onto a sensor, enabling the collection of data over a wide area.
  • Purpose: To increase the coverage area of the sensor, allowing for rapid data acquisition.

B. Internal Detectors

  • Definition: Sensors within a remote sensing instrument that convert electromagnetic radiation into electrical signals. These signals are then processed to produce images or data.
  • Purpose: To capture and measure the intensity of radiation reflected or emitted from the Earth's surface.

C. Instantaneous Field of View (IFOV)

  • Definition: The smallest area on the ground that can be resolved by a remote sensing sensor at a given time.
  • Purpose: To determine the spatial resolution of the sensor, indicating the level of detail it can capture.

D. Ground Resolution Cell Viewed (GRCV)

  • Definition: The area on the ground corresponding to the IFOV of a sensor at a specific altitude.
  • Purpose: To measure the size of the smallest distinguishable feature on the Earth's surface.

E. Angular Field of View (AFOV)

  • Definition: The angle between the extreme rays of the field of view of a sensor.
  • Purpose: To determine the extent of the area that can be observed by the sensor at a given distance.

F. Swath

  • Definition: The width of the area on the ground that a sensor can cover in a single pass.
  • Purpose: To measure the lateral coverage of the sensor, indicating the efficiency of data collection.

How it works:

  1. Radiation Collection: The scanning mirror deflects incoming radiation from the Earth's surface onto the array of discrete detectors.
  2. Spectral Separation: Each detector measures the radiation within its specific wavelength band, capturing information about different materials and features.
  3. Scanning: The scanning mirror moves across the scene, allowing the sensor to collect data from multiple points.
  4. Data Processing: The collected data is processed to create multispectral images that can be analyzed to identify and classify features based on their spectral signatures.

Key advantages of this approach:

  • High spatial resolution: Can capture detailed images of the Earth's surface.
  • Wide swath coverage: Can cover a large area in a single pass.
  • Versatility: Can be used for various remote sensing applications, such as land use mapping, vegetation monitoring, and mineral exploration.
Warm regards.
..
Vineesh V
AISHE and UGC Nodal Officer
Assistant Professor of Geography,
Government College Chittur, Palakkad
https://g.page/vineeshvc

Comments

Popular posts from this blog

Remote Sensing Technology

Remote sensing is a rapidly evolving geospatial technology used to collect information about the Earth's surface and atmosphere without direct physical contact . It involves detecting and measuring electromagnetic radiation (EMR) reflected or emitted from objects using sensors mounted on satellites, aircraft, or drones. Remote sensing systems are fundamentally classified based on (1) the energy source used for illumination and (2) the region of the electromagnetic spectrum utilized for sensing . 1. Types of Remote Sensing Based on Energy Source Remote sensing systems are commonly categorized according to whether the sensor generates its own energy or relies on naturally available radiation . Passive Remote Sensing Principle: Passive remote sensing relies on natural sources of electromagnetic energy , primarily solar radiation reflected from the Earth's surface or thermal radiation emitted by objects. Operation: Most passive sensors operate during daylight when sunlight is av...

Spectral Signature vs. Spectral Reflectance Curve

Spectral Signature  A spectral signature is the unique pattern in which an object: absorbs energy reflects energy emits energy across different wavelengths of the electromagnetic spectrum. ✔ Key Points Every natural and man-made object on Earth interacts with sunlight differently. These interactions produce a distinct pattern , just like a "fingerprint". Sensors on satellites record these patterns as digital numbers (DN values) . These patterns help to identify and differentiate objects such as vegetation, soil, water, snow, buildings, minerals, etc. ✔ Examples of Spectral Signatures Healthy vegetation → High reflectance in NIR , strong absorption in red Water → Strong absorption in NIR and SWIR , low reflectance Dry soil → Gradual increase in reflectance from visible to NIR Snow → High reflectance in visible , low in SWIR ✔ Why Spectral Signature Matters It allows: Land cover classification Chan...

REMOTE SENSING INDICES

Remote sensing indices are band ratios designed to highlight specific surface features (vegetation, soil, water, urban areas, snow, burned areas, etc.) using the spectral reflectance properties of the Earth's surface. They improve classification accuracy and environmental monitoring. 1. Vegetation Indices NDVI – Normalized Difference Vegetation Index Formula: (NIR – RED) / (NIR + RED) Concept: Vegetation reflects strongly in NIR and absorbs in RED due to chlorophyll. Measures: Vegetation greenness & health Uses: Agriculture, drought monitoring, biomass estimation EVI – Enhanced Vegetation Index Formula: G × (NIR – RED) / (NIR + C1×RED – C2×BLUE + L) Concept: Corrects for soil and atmospheric noise. Measures: Vegetation vigor in dense canopies Uses: Tropical rainforest mapping, high biomass regions GNDVI – Green Normalized Difference Vegetation Index Formula: (NIR – GREEN) / (NIR + GREEN) Concept: Uses Green instead of Red ...

Atmospheric Window

The atmospheric window in remote sensing refers to specific wavelength ranges within the electromagnetic spectrum that can pass through the Earth's atmosphere relatively unimpeded. These windows are crucial for remote sensing applications because they allow us to observe the Earth's surface and atmosphere without significant interference from the atmosphere's constituents. Key facts and concepts about atmospheric windows: Visible and Near-Infrared (VNIR) window: This window encompasses wavelengths from approximately 0. 4 to 1. 0 micrometers. It is ideal for observing vegetation, water bodies, and land cover types. Shortwave Infrared (SWIR) window: This window covers wavelengths from approximately 1. 0 to 3. 0 micrometers. It is particularly useful for detecting minerals, water content, and vegetation health. Mid-Infrared (MIR) window: This window spans wavelengths from approximately 3. 0 to 8. 0 micrometers. It is valuable for identifying various materials, incl...

Spatial Entity and Spatial Object

Concepts Spatial Entity : Refers to any real-world feature or phenomenon that exists in a specific location and can be identified in space. This emphasizes the actual physical or conceptual presence of the feature. Spatial Object : Represents the digital or computational representation of a spatial entity within a Geographic Information System (GIS). This includes its geometry (e.g., points, lines, polygons) and associated attributes. Key Distinction : While the terms are often interchangeable, spatial entity tends to focus on the real-world phenomenon, whereas spatial object highlights its representation in GIS. Key Terminologies Geographic Coordinates : Define the location of spatial entities using a coordinate system (e.g., latitude and longitude). Example: A building at 40.748817° N, 73.985428° W . Geometry Types : Point : Represents a single location (e.g., a well or a bus stop). Line : Represents linear features (e.g., roads, rivers). Polyg...