Skip to main content

Microwave Remote Sensing

Active and passive microwave remote sensing are two distinct methods used in the field of remote sensing to collect information about the Earth's surface and atmosphere using microwave radiation. Let's explore the principles of each:


1. Active Microwave Remote Sensing:

   - Principle: Active microwave remote sensing involves the transmission of microwave pulses from a sensor or satellite to the Earth's surface. These pulses are then reflected or scattered back to the sensor, where they are received and analyzed to gather information about the target area.

   - Key Features:

     - Microwave Source: An active microwave sensor emits microwave radiation (usually in the form of radar pulses) towards the Earth.

     - Reflection and Scattering: When the microwave pulses encounter objects on the Earth's surface, they interact with them. Some of the energy is reflected back to the sensor, while the rest is scattered.

     - Distance Measurement: By measuring the time it takes for the microwave pulses to travel to the target and return (time-of-flight), active microwave remote sensing can calculate the distance to the target.

     - Applications: Active microwave remote sensing is used for applications such as topographic mapping, vegetation monitoring, and soil moisture estimation. Synthetic Aperture Radar (SAR) is a common example of an active microwave sensor.


2. Passive Microwave Remote Sensing:

   - Principle: Passive microwave remote sensing, on the other hand, relies on the detection of naturally occurring microwave radiation emitted or scattered by the Earth's surface and atmosphere. Instead of actively transmitting microwave signals, passive sensors measure the microwave radiation already present.

   - Key Features:

     - Microwave Receiver: Passive microwave sensors have specialized receivers that can detect microwave emissions from the Earth.

     - Spectral Bands: These sensors are sensitive to specific microwave frequencies or spectral bands, which correspond to different properties of the Earth's surface or atmosphere.

     - Applications: Passive microwave remote sensing is often used for monitoring atmospheric conditions (e.g., weather forecasting), sea surface temperature, sea ice concentration, and soil moisture. It is particularly valuable for studying the Earth's energy balance.


In summary, active microwave remote sensing involves sending out microwave pulses and measuring their reflections or scattering, while passive microwave remote sensing relies on naturally emitted or scattered microwave radiation. Each method has its unique applications and advantages, making them valuable tools for Earth observation and scientific research.





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...

Pre During and Post Disaster

Disaster management is a structured approach aimed at reducing risks, responding effectively, and ensuring a swift recovery from disasters. It consists of three main phases: Pre-Disaster (Mitigation & Preparedness), During Disaster (Response), and Post-Disaster (Recovery). These phases involve various strategies, policies, and actions to protect lives, property, and the environment. Below is a breakdown of each phase with key concepts, terminologies, and examples. 1. Pre-Disaster Phase (Mitigation and Preparedness) Mitigation: This phase focuses on reducing the severity of a disaster by minimizing risks and vulnerabilities. It involves structural and non-structural measures. Hazard Identification: Recognizing potential natural and human-made hazards (e.g., earthquakes, floods, industrial accidents). Risk Assessment: Evaluating the probability and consequences of disasters using GIS, remote sensing, and historical data. Vulnerability Analysis: Identifying areas and p...

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....