Vineesh V, Geography

In remote sensing, a mixed pixel (also called a mixed cell or mixel ) is a pixel that contains more than one land-cover type inside its area. This is very common when: spatial resolution is coarse (e.g., 30 m, 250 m) land cover is patchy or complex boundaries between features exist (forest–agriculture, land–water edges) Traditional hard classification assigns each pixel to one single class only → either forest or soil or water. But mixed pixels contain fractions of several classes simultaneously, so hard classification produces errors. Two major solutions are: Spectral Mixture Analysis (SMA) Fuzzy Classification 1. Spectral Mixture Analysis (SMA) (Also called Linear Spectral Unmixing ) ✔ Concept SMA assumes that the reflectance recorded by a pixel is a linear combination of the reflectance of pure materials within that pixel. These pure materials are called endmembers . ✔ Endmembers Endmembers are spectrally pure classes found...

Assembling the Training Data Training data (also called training samples or signature sets ) are the foundation of supervised image classification in remote sensing. This is where the analyst selects representative examples of each land-cover class—such as water, vegetation, urban, soil, etc.—from the satellite image. To prepare training data properly, several analytical and interactive steps are used. These help ensure that the classes are well separated and that the classifier receives the correct spectral information. 1. Graphical Representation of Spectral Response Patterns ✔ What it means For each class (e.g., water, forest, built-up), the training pixels have a spectral signature —a pattern of reflectance values across the image's spectral bands. This pattern is visualized using: Spectral reflectance curves Band-by-band scatter plots Histograms for each band ✔ Purpose To understand how different classes behave in different bands To che...

Resolution 

LiDAR (Light Detection and Ranging) is an active remote sensing technology that uses laser pulses to measure distances to the Earth's surface and create high-resolution 3D maps . LiDAR sensors emit short pulses of laser light (usually in the near-infrared range) and measure the time it takes for the pulse to return after hitting an object. Because LiDAR measures distance very precisely, it is excellent for mapping: terrain vegetation height buildings forests coastlines flood plains ✅ 1. Active Sensor LiDAR sends its own laser energy, unlike passive sensors that rely on sunlight. ✅ 2. Laser Pulse LiDAR emits thousands of pulses per second (even millions). Wavelengths commonly used: Near-Infrared (NIR) → land and vegetation mapping Green (532 nm) → water/ bathymetry (penetrates shallow water) ✅ 3. Time of Flight (TOF) The sensor measures the time taken for the laser to travel: from the sensor → to the sur...

Jet stream  Warm regards. .. Vineesh V UGC Nodal Officer Assistant Professor of Geography, PG and Research Department of Geography, Government College Chittur, Palakkad.

Unmanned Earth resources satellites are satellites equipped with remote sensing instruments used to collect images and environmental data from the Earth's surface without a crew onboard. They help monitor: land use vegetation soil and water resources climate oceans atmosphere natural hazards These satellites are grouped based on the type of radiation they measure and the sensors they carry. Five Groups of Unmanned Earth Resources Satellites Remote sensing satellites can be categorized into five main groups , based on the wavelengths they record and the type of environmental information they collect. First-Generation Earth Resources Satellites Wavelength region: Visible and Near-Visible (VNIR) ✔ Characteristics Use multispectral scanners Record reflected sunlight Mainly for land use, vegetation, and surface mapping ✔ Example Landsat series (Landsat 1, 2, 3) These were the first generation of Earth resource sate...

Radar sensors are active remote sensing instruments that use microwave radiation to detect and measure Earth's surface features. They transmit their own energy (radio waves) toward the Earth and record the backscattered signal that returns to the sensor. Since they do not depend on sunlight, radar systems can collect data: day or night through clouds, fog, smoke, and rain in all weather conditions This makes radar extremely useful for Earth observation. 1. Active Sensor A radar sensor produces and transmits its own microwaves. This is different from optical and thermal sensors, which depend on sunlight or emitted heat. 2. Microwave Region Radar operates in the microwave region of the electromagnetic spectrum , typically from 1 mm to 1 m wavelength. Common radar frequency bands: P-band (70 cm) L-band (23 cm) S-band (9 cm) C-band (5.6 cm) X-band (3 cm) Each band penetrates and interacts with surfaces differently: Lo...

Thermal sensors are remote sensing instruments that detect naturally emitted thermal infrared (TIR) radiation from the Earth's surface. Unlike optical sensors (which detect reflected sunlight), thermal sensors measure heat energy emitted by objects because of their temperature. They work mainly in the Thermal Infrared region (8–14 µm) of the electromagnetic spectrum. 1. Thermal Infrared Radiation All objects above 0 Kelvin (absolute zero) emit electromagnetic radiation. This is explained by Planck's Radiation Law . For Earth's surface temperature range (about 250–330 K), the peak emitted radiation occurs in the 8–14 µm thermal window . Thus, thermal sensors detect emitted energy , not reflected sunlight. 2. Emissivity Emissivity is the efficiency with which a material emits thermal radiation. Values range from 0 to 1 : Water, vegetation → high emissivity (0.95–0.99) Bare soil → medium (0.85–0.95) Metals → low (0.1–0.3) E...

Decorrelation stretching is an image enhancement technique used to improve color contrast in multispectral remote sensing images. It reduces the correlation between image bands and spreads out (stretches) their color values so that features become easier to see. It is mainly used to enhance true-color or false-color composite images . Why Is It Needed?  Remote sensing bands often have strong correlations . For example: Red and NIR bands both reflect strongly from vegetation Visible bands (R, G, B) reflect similarly from many surfaces Because of this correlation: Images look dull , low-contrast , or washed-out Important features become hard to distinguish Decorrelation stretching solves this by reducing band-to-band correlation and enhancing color differences. How Decorrelation Stretching Works  1. Identify the Correlation Between Bands Multispectral bands often show similar brightness patterns. This makes the composite image look flat. 2...

Spectral Signature  A spectral signature is the unique pattern in which an object: absorbs energy reflects energy emits energy across different wavelengths of the electromagnetic spectrum. ✔ Key Points Every natural and man-made object on Earth interacts with sunlight differently. These interactions produce a distinct pattern , just like a "fingerprint". Sensors on satellites record these patterns as digital numbers (DN values) . These patterns help to identify and differentiate objects such as vegetation, soil, water, snow, buildings, minerals, etc. ✔ Examples of Spectral Signatures Healthy vegetation → High reflectance in NIR , strong absorption in red Water → Strong absorption in NIR and SWIR , low reflectance Dry soil → Gradual increase in reflectance from visible to NIR Snow → High reflectance in visible , low in SWIR ✔ Why Spectral Signature Matters It allows: Land cover classification Chan...

The Fourier Transform (FT) is a mathematical method used in remote sensing to break an image into its spatial frequency components . Think of it as changing the view of an image—from shapes and objects (spatial domain) to patterns and textures (frequency domain). Why Fourier Transform Remote sensing images contain patterns such as: smooth water bodies rough mountains sharp boundaries regular textures (agriculture fields) The Fourier transform helps us: Identify landscape changes Study surface texture (smooth, rough, periodic) Remove noise Sharpen or smooth images Detect repeated patterns (crop rows, sand ripples) 1. Spatial Domain This is the original image in terms of rows and columns (x, y). Here, pixel values represent brightness (DN values). 2. Frequency Domain After applying Fourier Transform, the image is represented in terms of spatial frequencies : Low frequencies → slow changes (smooth areas, water, sky) ...

1. What Are Optical Sensors? Optical sensors are remote sensing instruments that detect solar radiation reflected or emitted from the Earth's surface in specific portions of the electromagnetic spectrum (EMS) . They mainly work in: Visible region (0.4–0.7 µm) Near-Infrared – NIR (0.7–1.3 µm) Shortwave Infrared – SWIR (1.3–3.0 µm) Thermal Infrared – TIR (8–14 µm) — emitted energy, not reflected Optical sensors capture spectral signatures of surface features. Each object reflects/absorbs energy differently, creating a unique spectral response pattern . a) Electromagnetic Spectrum (EMS) The continuous range of wavelengths. Optical sensing uses solar reflective bands and sometimes thermal bands . b) Spectral Signature The unique pattern of reflectance or absorbance of an object across wavelengths. Example: Vegetation reflects strongly in NIR Water absorbs strongly in NIR and SWIR (appears dark) c) Radiance and Reflectance Radi...

How to Read & Draw Contour Lines? These 5 rules will help you, Rule 1 - Every point of a contour line has the same elevation.  Rule 2 - contour lines separate uphill from downhill. Rule 3 - contour lines do not touch or cross each other except at a cliff. Rule 4 - Every 5th contour line is darker in colour.

Remote sensing indices are band ratios designed to highlight specific surface features (vegetation, soil, water, urban areas, snow, burned areas, etc.) using the spectral reflectance properties of the Earth's surface. They improve classification accuracy and environmental monitoring. 1. Vegetation Indices NDVI – Normalized Difference Vegetation Index Formula: (NIR – RED) / (NIR + RED) Concept: Vegetation reflects strongly in NIR and absorbs in RED due to chlorophyll. Measures: Vegetation greenness & health Uses: Agriculture, drought monitoring, biomass estimation EVI – Enhanced Vegetation Index Formula: G × (NIR – RED) / (NIR + C1×RED – C2×BLUE + L) Concept: Corrects for soil and atmospheric noise. Measures: Vegetation vigor in dense canopies Uses: Tropical rainforest mapping, high biomass regions GNDVI – Green Normalized Difference Vegetation Index Formula: (NIR – GREEN) / (NIR + GREEN) Concept: Uses Green instead of Red ...

India's rock record spans a vast geological time scale from >3.5 billion years to the present . Geologists classify India's rocks into four major rock systems : Archaean (oldest) Purana Dravidian Aryan (youngest) This classification is based on: Age of rock formation Mode of origin (igneous, sedimentary, metamorphic) Tectonic setting Presence of fossils Mineral resources 1. Craton An ancient, stable part of the continental crust (e.g., Indian Peninsular Craton). 2. Basement Complex The oldest crystalline rocks forming the foundation over which younger layers are deposited (Archaean rocks). 3. Orogeny Mountain-building phases affecting rock formation (e.g., Himalayan orogeny for Tertiary rocks). 4. Sedimentation Deposition of sediments by water, wind, or ice, forming sedimentary rocks. 5. Fossils Preserved remains of ancient life; indicate geological age and depositional environment. (Purana = unfossilifer...

Territorial conflicts are disputes where two or more countries claim sovereignty over a geographic region. These disputes typically arise due to: Historical claims Colonial-era boundary definitions Ethnic or cultural overlap Strategic and resource significance River dynamics and shifting landforms Key Concepts: 1. Boundary A legally established line separating the territories of two states. 2. Border / Frontier A broader zone of interaction and control around a boundary. 3. LOC (Line of Control) A de facto military control line (India–Pakistan in Jammu & Kashmir). 4. LAC (Line of Actual Control) A de facto border separating Indian and Chinese-administered territories. 5. Radcliffe Line The 1947 boundary line dividing India and Pakistan (later India and Bangladesh). 6. Enclave / Exclave Territorial pockets of one country surrounded by another (e.g., India–Bangladesh enclaves before 2015). 7. Riverine Boundary A border defined by...