Remote Sensing & GIS

Remote sensing

Remote sensing is the science of obtaining information about objects or areas on the earth's surface without physical contact, by detecting and analysing electromagnetic radiation reflected or emitted by them — usually from aircraft or satellites.

The remote sensing process

1. Energy source (sun or the sensor itself).
2. Radiation and the atmosphere — scattering and absorption on the way down and up.
3. Interaction with the target — absorption, transmission, reflection, emission.
4. Recording by the sensor.
5. Transmission, reception and processing at ground stations.
6. Interpretation and analysis.
7. Application — maps, decisions.

Electromagnetic spectrum

Atmospheric windows — wavelength ranges where the atmosphere is relatively transparent (visible, parts of IR, thermal window, microwaves); sensors operate in these windows.

Spectral signatures

Different materials reflect differently across wavelengths:

• Healthy vegetation — low reflectance in blue and red (absorbed by chlorophyll), a peak in green, and very high reflectance in NIR (leaf structure).
• Water — low reflectance, especially absorbs NIR strongly (appears dark in NIR images); turbid water reflects more in visible.
• Soil — reflectance generally increases with wavelength; decreases with moisture and organic matter.

False colour composite (FCC) — standard FCC displays NIR as red, red as green and green as blue, so vegetation appears red.

Passive and active sensors

• Passive sensors — record natural energy (reflected sunlight or emitted thermal radiation): multispectral scanners, cameras, thermal sensors. Depend on sunlight (for reflected bands) and clear skies.
• Active sensors — emit their own energy and record the return:
  • RADAR / SAR (synthetic aperture radar) — microwave; penetrates clouds; works day and night; used for flood mapping, soil moisture, deformation (InSAR).
  • LiDAR (light detection and ranging) — laser pulses; very accurate elevation data, vegetation structure, DTMs.

Platforms and orbits

• Ground-based, airborne (aircraft, drones) and spaceborne (satellites) platforms.
• Geostationary orbit — about 35 786 km above the equator; satellite appears fixed relative to earth; continuous coverage of a large area — weather and communication satellites.
• Sun-synchronous polar orbit — low altitude (typically about 600–900 km), near-polar; passes over a place at the same local solar time — earth resources satellites.

Resolutions

Indian remote sensing programme

• IRS-1A (1988) was India's first operational remote sensing satellite; the Indian Remote Sensing (IRS) series has grown into one of the largest civilian constellations.
• Missions include Resourcesat (natural resources), Cartosat series (high-resolution stereo imagery for cartography), Oceansat (ocean studies), RISAT (radar imaging), and others.
• The National Remote Sensing Centre (NRSC), Hyderabad, acquires, processes and distributes data; the Bhuvan geoportal provides Indian satellite imagery and thematic maps.

Image interpretation and processing

Elements of visual interpretation

Tone/colour, size, shape, texture, pattern, shadow, and site/association (location relative to other features).

Digital image processing

1. Pre-processing:
   • Radiometric correction — sensor errors, atmospheric effects, illumination.
   • Geometric correction (georeferencing) — removing distortions and registering to map coordinates using ground control points; resampling (nearest neighbour, bilinear, cubic convolution).
2. Image enhancement — contrast stretching, filtering (smoothing, edge enhancement), band ratios, principal components, colour composites.
3. Image classification:
   • Supervised — analyst defines training sites; algorithms such as maximum likelihood, minimum distance, parallelepiped, and machine-learning classifiers.
   • Unsupervised — computer groups pixels into clusters (e.g. ISODATA, k-means), which the analyst labels.
   • Object-based classification — segments images into objects.
4. Accuracy assessment — error (confusion) matrix, overall accuracy, producer's and user's accuracy, kappa coefficient.
5. Change detection — comparing images of different dates.

Geographic Information System (GIS)

A GIS is a computer-based system to capture, store, query, analyse and display geographically referenced (spatial) data together with their attributes.

Components

Hardware, software, data (spatial and attribute), people and methods/procedures.

Data models

• Attribute data — stored in tables linked to features (database management systems); queried with SQL-like commands.
• TIN (triangulated irregular network) — vector representation of surfaces.

Data input

Digitising paper maps, scanning and vectorisation, GNSS/total station field data, remote sensing imagery, existing digital data (CAD, census tables), LiDAR point clouds. Metadata describes source, accuracy, projection and date.

Coordinate systems and projections

All data must share a coordinate reference system: geographic (latitude/longitude on a datum such as WGS 84) or projected (e.g. UTM zones — eastings and northings in metres). Georeferencing registers scanned maps and images to real-world coordinates.

Spatial analysis

Digital elevation models

DEM (bare-earth elevations, also DTM) and DSM (surface including buildings and trees). Sources: contours, stereo photogrammetry, LiDAR, radar interferometry — e.g. SRTM (about 30 m global), CartoDEM (from Cartosat stereo data).