Satellites Remote Sensing

Earth Resources Satellites

These satellites are designed mainly for natural resource monitoring – land, water, vegetation, and environment.

1. LANDSAT (USA, since 1972)

World's first dedicated Earth observation satellite series.
Provides long-term continuous data for >50 years.
Sensors: MSS (Multispectral Scanner), TM (Thematic Mapper), ETM+ (Enhanced TM), OLI (Operational Land Imager).
Resolution: 15–30 m (optical).
Applications: Land cover change, agriculture, forests, water resources.
Fact: Landsat archive is the longest continuous Earth observation record.

2. SPOT (France, 1986 onwards)

Name: Satellite Pour l'Observation de la Terre.
Sensors: HRV (High Resolution Visible), HRVIR (with Infrared).
Resolution: 1.5–20 m.
Applications: Urban studies, vegetation monitoring, mapping.
Fact: First civilian satellite to offer stereo imaging (3D views).

3. IRS (India, 1988 onwards)

Name: Indian Remote Sensing Satellite Series.
Sensors: LISS (Linear Imaging Self Scanner), PAN (Panchromatic), WiFS (Wide Field Sensor).
Resolution: 5–180 m depending on sensor.
Applications: Agriculture, water resources, forestry, disaster management.
Fact: India's IRS program is one of the largest civilian remote sensing programs in the world.

4. IKONOS (USA, launched 1999)

One of the first commercial high-resolution satellites.
Resolution: 1 m (panchromatic), 4 m (multispectral).
Applications: Urban planning, infrastructure mapping, defense, precision agriculture.
Fact: Made high-resolution satellite imagery available for civilian use.

Meteorological Satellites

These satellites are designed for weather and climate monitoring.

1. INSAT (India)

Name: Indian National Satellite System.
Operates in Geostationary Orbit (GEO, ~36,000 km).
Functions: Weather forecasting, cyclone tracking, rainfall estimation, communication.
Fact: INSAT combines meteorology + telecommunications + broadcasting.

2. NOAA (USA)

Name: National Oceanic and Atmospheric Administration Satellites.
Operates in Polar Orbit (LEO ~850 km).
Sensor: AVHRR (Advanced Very High Resolution Radiometer).
Applications: Sea surface temperature, vegetation, snow cover, weather monitoring.
Fact: Continuous data since 1970s, key for climate change studies.

3. GOES (USA)

Name: Geostationary Operational Environmental Satellites.
Orbit: Geostationary (36,000 km).
Applications: Real-time weather monitoring, storm tracking, atmosphere studies.
Fact: Provides continuous images of the same region every few minutes → crucial for cyclone and hurricane monitoring.

Optical Mechanical Scanners

These are instruments (sensors) that scan the Earth's surface in different wavelengths of the electromagnetic spectrum.

1. MSS (Multispectral Scanner) – Landsat

Records data in 4 spectral bands (visible + near IR).
Spatial resolution: ~80 m.
Use: Early land cover studies.

2. TM (Thematic Mapper) – Landsat

Improved sensor with 7 bands (visible, NIR, SWIR, thermal).
Spatial resolution: 30 m (optical), 120 m (thermal).
Use: Agriculture, geology, vegetation, water.

3. LISS (Linear Imaging Self Scanner) – IRS

Variants: LISS-I, II, III, IV.
Resolutions: 72 m (LISS-I) → 5.8 m (LISS-IV).
Use: Agriculture, forestry, resources.

4. WiFS (Wide Field Sensor) – IRS

Wide coverage, ~180 m resolution.
Use: Vegetation and crop monitoring at regional scale.

5. PAN (Panchromatic) – IRS

Records in single broad band (black & white).
Very high spatial resolution: ~5–6 m.
Use: Urban mapping, cartography, image fusion.

In short:

Earth Resource Satellites (LANDSAT, SPOT, IRS, IKONOS) → monitor land, vegetation, water.
Meteorological Satellites (INSAT, NOAA, GOES) → monitor atmosphere, weather, climate.
Optical Scanners (MSS, TM, LISS, WiFS, PAN) → instruments onboard satellites that capture data in different resolutions and spectral ranges.

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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...

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...

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...

Resolution of Sensors in Remote Sensing

Spatial Resolution 🗺️ Definition : The smallest size of an object on the ground that a sensor can detect. Measured as : The size of a pixel on the ground (in meters). Example : Landsat → 30 m (each pixel = 30 × 30 m on Earth). WorldView-3 → 0.31 m (very detailed, you can see cars). Fact : Higher spatial resolution = finer details, but smaller coverage. Spectral Resolution 🌈 Definition : The ability of a sensor to capture information in different parts (bands) of the electromagnetic spectrum . Measured as : The number and width of spectral bands. Types : Panchromatic (1 broad band, e.g., black & white image). Multispectral (several broad bands, e.g., Landsat with 7–13 bands). Hyperspectral (hundreds of very narrow bands, e.g., AVIRIS). Fact : Higher spectral resolution = better identification of materials (e.g., minerals, vegetation types). Radiometric Resolution 📊 Definition : The ability of a sensor to ...

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...

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