Radiometric correction

Radiometric correction in remote sensing is a crucial process that aims to remove or reduce variations in the recorded radiance values of an image, ensuring that the data accurately represents the reflectance properties of the Earth's surface. This correction is essential for extracting meaningful information from remotely sensed imagery.

1. Source of Radiometric Error:

Radiometric errors in remote sensing can originate from various sources, including:

a. Atmospheric Effects: The Earth's atmosphere can scatter and absorb incoming sunlight and reflected light from the surface. These atmospheric effects can introduce errors in radiance values, particularly in the blue and ultraviolet spectral regions.

b. Sensor Characteristics: Different sensors have varying spectral and radiometric characteristics, leading to inconsistencies in radiance measurements.

c. Satellite Orbits: Variations in the satellite's position, speed, and angle relative to the Earth's surface can affect the radiance recorded by the sensor.

d. Ground Reflectance Variations: Changes in ground cover, terrain, and surface properties can result in varying reflectance values across an image.

e. Calibration Issues: Sensor calibration drift over time or inaccuracies in the calibration process can introduce radiometric errors.

2. Types of Radiometric Correction:

There are several methods for radiometric correction in remote sensing, depending on the specific sources of error and the data characteristics. Here are some common types:

a. Dark Object Subtraction (DOS): This method involves identifying the darkest objects in the image, which are assumed to be black, non-reflective surfaces. The radiance values of all pixels are adjusted based on the radiance of these dark objects to correct for sensor-specific errors.

b. Atmospheric Correction: Atmospheric correction algorithms attempt to estimate and remove the influence of the atmosphere on radiance values. They use atmospheric models and sensor data to adjust the recorded values to approximate surface reflectance.

c. Calibration Correction: This correction addresses sensor-specific errors by using calibration data to rescale and adjust the recorded radiance values.

d. Relative Radiometric Correction: In this approach, image-to-image variations are corrected by comparing and normalizing radiance values across different scenes or time periods.

e. Absolute Radiometric Correction: This method aims to provide accurate radiometric values by considering sensor-specific parameters and calibration data, making the data directly comparable across different sensors and time periods.

f. Top-of-Atmosphere (TOA) Reflectance: TOA reflectance correction calculates the reflectance values at the top of the atmosphere by removing atmospheric effects. This correction is valuable for comparing images acquired under varying atmospheric conditions.

Effective radiometric correction enhances the utility of remote sensing data for applications such as land cover classification, change detection, and environmental monitoring, by ensuring that the imagery accurately reflects the Earth's surface properties while minimizing errors caused by various sources.

Comments

geostationary and sun-synchronous

Orbital characteristics of Remote sensing satellite geostationary and sun-synchronous Orbits in Remote Sensing Orbit = the path a satellite follows around the Earth. The orbit determines what part of Earth the satellite can see , how often it revisits , and what applications it is good for . Remote sensing satellites mainly use two standard orbits : Geostationary Orbit (GEO) Sun-Synchronous Orbit (SSO) Geostationary Satellites (GEO) Characteristics Altitude : ~35,786 km above the equator. Period : 24 hours → same as Earth's rotation. Orbit type : Circular, directly above the equator . Appears "stationary" over one fixed point on Earth. Concepts & Terminologies Geosynchronous = orbit period matches Earth's rotation (24h). Geostationary = special type of geosynchronous orbit directly above equator → looks fixed. Continuous coverage : Can monitor the same area all the time. Applications Weather...

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. 🛰️ 1. Active Remote Sensing 📘 Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. 📊 Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...

Man-Made Disasters

A man-made disaster (also called a technological disaster or anthropogenic disaster ) is a catastrophic event caused directly or indirectly by human actions , rather than natural processes. These disasters arise due to negligence, error, industrial activity, conflict, or misuse of technology , and often result in loss of life, property damage, and environmental degradation . Terminology: Anthropogenic = originating from human activity. Technological hazard = hazard caused by failure or misuse of technology or industry. 🔹 Conceptual Understanding Man-made disasters are part of the Disaster Management Cycle , which includes: Prevention – avoiding unsafe practices. Mitigation – reducing disaster impact (e.g., safety regulations). Preparedness – training and planning. Response – emergency actions after the disaster. Recovery – long-term rebuilding and policy correction. These disasters are predictable and preventable through strong...

Contrast Enhancement

Image enhancement is the process of improving the visual quality and interpretability of an image. The goal is not to change the physical meaning of the image data , but to make important features easier to identify for visual interpretation or automatic analysis (e.g., classification, feature extraction). In simple terms, image enhancement helps make an image clearer, sharper, and more informative for human eyes or computer algorithms. Purpose of Image Enhancement To improve visual appearance of images. To highlight specific features such as roads, rivers, vegetation, or built-up areas. To enhance contrast or brightness for better differentiation. To reduce noise or remove distortions. To prepare images for further processing like classification or edge detection. Common Image Enhancement Operations Image Reduction: Decreases the size or resolution of an image. Useful for faster processing or overview visualization. Image Mag...

Natural Disasters

A natural disaster is a catastrophic event caused by natural processes of the Earth that results in significant loss of life, property, and environmental resources. It occurs when a hazard (potentially damaging physical event) interacts with a vulnerable population and leads to disruption of normal life . Key terms: Hazard → A potential natural event (e.g., cyclone, earthquake). Disaster → When the hazard causes widespread damage due to vulnerability. Risk → Probability of harmful consequences from interaction of hazard and vulnerability. Vulnerability → Degree to which a community or system is exposed and unable to cope with the hazard. Resilience → Ability of a system or society to recover from the disaster impact. 👉 Example: An earthquake in an uninhabited desert is a hazard , but not a disaster unless people or infrastructure are affected. Types Natural disasters can be classified into geophysical, hydrological, meteorological, clim...

Vineesh V, Geography

Search This Blog