Radar image. Polarization in Remote Sensing

L band radars operate on a wavelength of 15-30 cm and a frequency of 1-2 GHz. L band radars are mostly used for clear air turbulence studies. S band radars operate on a wavelength of 8-15 cm and a frequency of 2-4 GHz. Because of the wavelength and frequency, S band radars are not easily attenuated.

Polarization refers to the direction of travel of an electromagnetic wave vector's tip:

vertical (up and down),

horizontal (left to right), or

circular (rotating in a constant plane left or right).

a synthetic aperture radar (SAR) for high-resolution imaging.

a radar altimeter, to measure the ocean topography.

echo amplitude

a wind scatterometer to measure wind speed and direction.

Other types of radars have been flown for Earth observation missions: precipitation radars such as the

Tropical Rainfall Measuring Mission,

cloud radars like the one used on Cloudsat.

RISAT-1 (SAR, ISRO India, 2012)

RORSAT (SAR, Soviet Union, 1967-1988)

Seasat (SAR, altimeter, scatterometer, US, 1978)

ERS-1 & ERS-2 (European Remote-Sensing Satellite) (altimeter, combined SAR/scatterometer)

TOPEX/Poseidon (altimeter)

Tropical Rainfall Measuring Mission (Precipitation Radar)

Cloudsat (cloud radar)

Metop (scatterometer)

QuickScat (scatterometer)

Polarization in radar imaging refers to the orientation of the electric field of the radar waves that are used to illuminate the target. There are two main types of polarization: linear and circular. Linear polarization has the electric field oscillating in one plane, while circular polarization has the electric field oscillating in a circular pattern. The type of polarization used can affect the radar image, as different types of targets will reflect the radar waves differently based on the polarization. For example, linear polarization is better for detecting targets with smooth surfaces, while circular polarization is better for detecting targets with rougher surfaces. Additionally, using different types of polarization can help to reduce the effects of interference from other sources.

HH, HV, and VV are types of polarization that are used in radar imaging.

HH stands for horizontally polarized transmitted signal and horizontally polarized received signal. This type of polarization is useful for detecting targets with smooth surfaces, as the horizontally polarized radar waves will be reflected more efficiently by these types of targets.

HV stands for horizontally polarized transmitted signal and vertically polarized received signal. This type of polarization is useful for detecting targets with rougher surfaces, as the horizontally polarized radar waves will be scattered in many directions by these types of targets, resulting in a stronger return signal.

VV stands for vertically polarized transmitted signal and vertically polarized received signal. This type of polarization is useful for detecting targets with rougher surfaces, as the vertically polarized radar waves will be scattered in many directions by these types of targets, resulting in a stronger return signal.

Using these different types of polarization can help to enhance the contrast and details in radar images, and also it can be used to extract information about the targets, such as their shape, size, and surface roughness.

Comments

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...

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...

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 choléra dans Paris et le département 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...

Vineesh V, Geography

Search This Blog