Skip to main content

Atmospheric Window in Remote Sensing


The atmospheric window is like a "clear path" in the sky. It means certain parts of sunlight or energy (called electromagnetic radiation) can pass through the Earth's atmosphere without getting blocked. These "clear paths" are very helpful in remote sensing—when we study the Earth using satellites and sensors.

Why are Atmospheric Windows Important?

Just like how we can see clearly through a clean glass window, satellites can "see" the Earth clearly through these atmospheric windows. These windows help in:

  • Taking clear pictures of land, water, and forests

  • Measuring temperature of the Earth's surface

  • Even looking through clouds using special types of energy!

Types of Atmospheric Windows and What They Show

  1. Visible and Near-Infrared (VNIR) Window (0.4 to 1.0 micrometers)

    • This is the light we can mostly see with our eyes

    • Used to observe green plants, water bodies, and land cover

  2. Shortwave Infrared (SWIR) Window (1.0 to 3.0 micrometers)

    • Helps in finding minerals, moisture in soil, and plant health

  3. Mid-Infrared (MIR) Window (3.0 to 8.0 micrometers)

    • Used for studying rocks, soil, and clouds

  4. Thermal Infrared (TIR) Window (8.0 to 14.0 micrometers)

    • Helps measure temperature of the ground

    • Useful to find hot spots like fires or volcanoes

  5. Microwave Window (1 millimeter to 1 meter)

    • Can see through clouds and trees

    • Great for radar images, used in weather tracking and disaster studies

Important Terms – Made Simple

  • Atmospheric Window: A part of light or energy that can pass through the air without much blockage.

  • Electromagnetic Spectrum: The full range of energy waves – from very long radio waves to very short gamma rays.

  • Absorption Band: A part where gases in the atmosphere block the energy.

  • Transmission Window: A part where gases let the energy pass through easily.

TypeWavelength RangeUsed For
VNIR0.4 – 1.0 µmSeeing plants, water, and land from space
SWIR1.0 – 3.0 µmChecking minerals, plant moisture
MIR3.0 – 8.0 µmStudying rocks, soil, clouds
TIR8.0 – 14.0 µmMeasuring heat, surface temperature
Microwave1 mm – 1 mRadar imaging, even through clouds and forests



Comments

Popular posts from this blog

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology:    - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants.    - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis:    - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis.    - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping:    - Photozincography development allows maps to be split into layers for vegetation, water, etc.    - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography:    - Waldo Tobler's 1959 publication details using computers for cartography.    - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification:   - You have prior knowledge about the c...

History of GIS

The history of Geographic Information Systems (GIS) is rooted in early efforts to understand spatial relationships and patterns, long before the advent of digital computers. While modern GIS emerged in the mid-20th century with advances in computing, its conceptual foundations lie in cartography, spatial analysis, and thematic mapping. Early Roots of Spatial Analysis (Pre-1960s) One of the earliest documented applications of spatial analysis dates back to  1832 , when  Charles Picquet , a French geographer and cartographer, produced a cholera mortality map of Paris. In his report  Rapport sur la marche et les effets du cholĂ©ra dans Paris et le dĂ©partement de la Seine , Picquet used graduated color shading to represent cholera deaths per 1,000 inhabitants across 48 districts. This work is widely regarded as an early example of choropleth mapping and thematic cartography applied to epidemiology. A landmark moment in the history of spatial analysis occurred in  1854 , when  John Snow  inv...

Representation of Spatial and Temporal Relationships

In GIS, spatial and temporal relationships allow the integration of location (the "where") and time (the "when") to analyze phenomena across space and time. This combination is fundamental to studying dynamic processes such as urban growth, land-use changes, or natural disasters. Key Concepts and Terminologies Geographic Coordinates : Define the position of features on Earth using latitude, longitude, or other coordinate systems. Example: A building's location can be represented as (11.6994° N, 76.0773° E). Timestamp : Represents the temporal aspect of data, such as the date or time a phenomenon was observed. Example: A landslide occurrence recorded on 30/07/2024 . Spatial and Temporal Relationships : Describes how features relate in space and time. These relationships can be: Spatial : Topological (e.g., "intersects"), directional (e.g., "north of"), or proximity-based (e.g., "near"). Temporal : Sequential (e....

GIS: Real World and Representations - Modeling and Maps

Geographic Information Systems (GIS) serve as a bridge between the real world and digital representations of geographic phenomena. These representations allow users to store, analyze, and visualize spatial data for informed decision-making. Two key aspects of GIS in this context are modeling and maps , both of which are used to represent real-world geographic features and phenomena in a structured, analyzable format. Let's delve into these concepts, terminologies, and examples in detail. 1. Real World and Representations in GIS Concept: The real world comprises physical, tangible phenomena, such as landforms, rivers, cities, and infrastructure, as well as more abstract elements like weather patterns, population densities, and traffic flow. GIS allows us to represent these real-world phenomena digitally, enabling spatial analysis, decision-making, and visualization. The representation of the real world in GIS is achieved through various models and maps , which simplify...