GPS, GIS & Remote Sensing

Global navigation satellite systems (GNSS)

GNSS is the general term for satellite systems that provide positioning, navigation and timing worldwide.

Satellite-based augmentation systems (SBAS) improve accuracy and integrity using geostationary satellites and ground reference stations — e.g. GAGAN (GPS Aided GEO Augmented Navigation, developed by ISRO and AAI for India), WAAS (USA), EGNOS (Europe).

Segments of GPS

1. Space segment — the constellation of satellites broadcasting signals, with precise atomic clocks.
2. Control segment — a master control station (in Colorado, USA), monitor stations and ground antennas that track satellites, compute orbits (ephemerides) and clock corrections, and upload navigation messages.
3. User segment — receivers (navigation, mapping and geodetic/survey-grade) and antennas that compute position, velocity and time.

Signals

• Carrier frequencies (GPS): L1 = 1575.42 MHz, L2 = 1227.60 MHz, L5 = 1176.45 MHz.
• Codes: C/A (coarse/acquisition) code — civilian code on L1; P(Y) code — precise (encrypted military) code on L1 and L2; modernised civil codes L2C and L5.
• Navigation message — satellite ephemeris (precise orbit), almanac (approximate orbits of all satellites), clock corrections, ionospheric model parameters, health status.

Principle of positioning

Pseudorange (code) positioning

The receiver measures the travel time $\Delta t$ of the signal from satellite to receiver:

($c$ ≈ 299 792 458 m/s.) This measured range is called a pseudorange because the receiver clock is not synchronised with satellite clocks.

• Each pseudorange defines a sphere centred on the satellite; the position lies at the intersection (trilateration).
• Four unknowns — X, Y, Z coordinates and receiver clock bias — so at least four satellites must be observed simultaneously.
• A receiver clock error of just 1 microsecond corresponds to a range error of about 300 m — hence the clock bias must be solved.

Carrier-phase positioning

The receiver measures the phase of the carrier wave (wavelength about 19 cm for L1). The integer number of cycles between satellite and receiver (integer ambiguity) is unknown and must be resolved; once fixed, carrier phase gives millimetre to centimetre relative accuracy — the basis of survey-grade GNSS. Cycle slips (loss of lock) must be detected and repaired.

Sources of error

Dilution of precision

DOP measures how satellite geometry amplifies measurement errors:

• GDOP (geometric), PDOP (3D position), HDOP (horizontal), VDOP (vertical), TDOP (time).
• Low DOP = good geometry (satellites well spread across the sky); high DOP (satellites clustered) = poor accuracy.
• Position error ≈ DOP × range measurement error.
• Vertical accuracy is usually poorer than horizontal accuracy because satellites are above the horizon only.

Positioning methods

The Survey of India operates a CORS network providing real-time corrections for high-accuracy positioning across the country.

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).