GNSS and GIS Fundamentals: Systems, Analysis, and Applications

Posted on May 28, 2026 in Geography

GNSS Constellation Comparison

GPS Surveying Methods

GNSS in Disaster Management

1. Early Warning – GNSS monitors tectonic plate movement, land subsidence, and tsunamis in real time for early warning systems.
2. Damage Assessment – Post-disaster GNSS combined with satellite imagery quickly maps affected areas for relief planning.
3. Rescue Coordination – Tracks rescue teams, vehicles, and helicopters, guiding them to exact victim locations.
4. Flood Mapping – GNSS provides ground truth points for validating SAR-based flood extent maps.
5. Supply Tracking – Tracks relief material trucks, ensuring delivery to correct disaster-affected locations.

GNSS for Precision Farming

1. Accurate Field Mapping – GNSS provides exact boundary and area of agricultural fields for precise planning.
2. Variable Rate Application – Optimizes fertilizer, pesticide, and water application based on GPS-mapped soil zones.
3. Automated Machinery – GPS-guided tractors and sprayers follow exact paths, reducing overlaps and wastage.
4. Crop Monitoring – GNSS combined with sensors monitors crop health and growth at specific field locations.
5. Yield Mapping – GPS-tagged yield data collected during harvest identifies high and low productivity zones in the field.

GNSS Security: Jamming and Spoofing

1. Jamming – Intentional or accidental radio frequency interference blocks GNSS signals, causing complete loss of position fix.
2. Spoofing – Fake GNSS signals transmitted to mislead receivers, providing wrong position, speed, and timing data.
3. Effects – Wrong navigation data, vehicle tracking failure, aviation risks, and military positioning errors.
4. Signal Authentication – Encrypted GNSS signals and multi-constellation receivers reduce vulnerability to jamming and spoofing.
5. INS Integration – Integrating GNSS with Inertial Navigation Systems (INS) provides backup positioning when GNSS is compromised.

Pseudorange and Trilateration

1. Pseudorange Measurement – Receiver measures time delay between signal transmission from satellite and reception at the receiver.
2. Distance Calculation – Distance = time delay × speed of light (Pseudorange = Δt × c ≈ 3×10⁸ m/s).
3. Satellite Position – Ephemeris data provides exact satellite coordinates at the time of signal transmission.
4. Trilateration – Each satellite defines a sphere; the intersection of three spheres provides two possible position points on Earth.
5. Fourth Satellite – Solves receiver clock bias, selecting the correct point and providing accurate 3D position and time.

Multi-Constellation and Dual-Frequency Benefits

1. More Satellites – Multi-constellation provides more visible satellites, reducing DOP and improving accuracy, especially in urban canyons.
2. Redundancy – If one GNSS system fails or is jammed, other constellations continue providing positioning services.
3. Ionosphere Removal – Dual-frequency compares L1 and L2/L5 signals to remove frequency-dependent ionospheric delay.
4. Improved Accuracy – Dual-frequency improves accuracy from ~5 meters to less than 1 meter without external corrections.
5. Faster RTK – Dual-frequency allows faster carrier phase ambiguity resolution in RTK surveying, reducing initialization time.

GNSS Vulnerabilities and Mitigation

1. Jamming – Intentional RF interference drowns GNSS signals, causing loss of position fix in the affected area.
2. Spoofing – Fake GNSS signals cause receivers to compute incorrect position, speed, and timing information.
3. RAIM – Receiver Autonomous Integrity Monitoring detects faulty or spoofed satellite signals automatically.
4. Beamforming Antennas – Focus signal reception toward the satellite direction, ignoring ground-level interference.
5. Clock Monitoring – Oscillator drift detection in the receiver reveals spoofing attempts by identifying abnormal clock behavior.

Mini-Project: Campus Navigation App

1. Objective – Build a GNSS-based app to help students navigate campus buildings and track college buses in real time.
2. Components – Smartphone (GNSS + accelerometer), Flutter mobile app, Firebase cloud database, OpenStreetMap + QGIS campus map.
3. Methodology – Collect GNSS waypoints for buildings and bus stops; digitize campus map; develop routing app; add live bus tracking.
4. Expected Outcomes – Real-time user location on map, turn-by-turn navigation to buildings, and live bus arrival times.
5. Significance – Reduces time finding classrooms, improves campus mobility, and provides practical GNSS learning.

Hyperspectral vs. Multispectral Data

Narrow Bands – Hyperspectral has 200+ bands (5–10 nm width) vs. multispectral (3–10 bands, 100–200 nm width), capturing diagnostic absorption features missed by multispectral.

Unique Spectral Signature – Every material absorbs light at specific wavelengths; hyperspectral detects exact absorption positions, while multispectral averages across features.

Spectral Library Matching – Hyperspectral pixel spectra are matched against USGS/JPL libraries using the SAM algorithm for exact identification.

Sub-pixel Detection – Hyperspectral detects materials covering less than 10% of a pixel using linear spectral unmixing.

Case Study – AVIRIS hyperspectral identified 20+ minerals at Cuprite, Nevada; Landsat MSS identified only 2 classes, reducing exploration costs by 50%.

EMR Interaction with Earth’s Surface

1. Reflection – Energy bounces off the surface, providing color and texture information used in optical remote sensing.
2. Absorption – Energy is taken in and converted to heat; water absorbs most NIR and SWIR radiation, appearing dark.
3. Transmission – Energy passes through material; water is transparent in blue wavelengths, allowing depth mapping.
4. Emission – Surface emits thermal radiation based on temperature (Planck’s Law); used in thermal remote sensing.
5. Spectral Signature – Unique combination of reflection, absorption, and emission used to identify land cover types.

Blackbody Radiation in Thermal Sensing

1. Definition – A blackbody is an ideal object that absorbs all incoming radiation and emits maximum energy at every wavelength.
2. Planck’s Law – Blackbody emission depends only on temperature; hotter objects emit more energy at shorter wavelengths.
3. Stefan-Boltzmann Law – Total energy emitted is proportional to the fourth power of absolute temperature (E = σT⁴).
4. Thermal Sensing Relevance – Earth’s surface emits thermal infrared radiation like a near-blackbody; sensors detect this to measure temperature.
5. Applications – Urban heat island mapping, forest fire detection, volcanic monitoring, and sea surface temperature measurement.

Thermal Infrared Window

1. Definition – Wavelength range of 8–14 µm where Earth’s emitted thermal energy passes through the atmosphere with minimal absorption.
2. Atmospheric Transmission – Allows thermal sensors on satellites to measure surface temperature without significant interference.
3. Peak Emission – Earth’s peak thermal emission occurs at approximately 10 µm, falling within this window.
4. Day and Night Imaging – Thermal sensors detect emitted radiation, working day and night unlike optical sensors.
5. Applications – Urban heat island mapping, fire detection, volcanic monitoring, and industrial heat pollution detection.

Multispectral Scanning Applications

1. Urban vs. Rural – NIR and red bands distinguish built-up areas from vegetation; concrete appears bright in SWIR.
2. Agriculture Mapping – Identifies crop types, fallow land, and irrigation boundaries using spectral differences.
3. Forestry Mapping – Distinguishes dense vs. degraded forest and plantation vs. natural forest using NIR and red edge bands.
4. Water Body Delineation – Water absorbs strongly in NIR, making it appear dark; lakes and rivers are easily delineated.
5. Change Detection – Multi-date imagery shows urban expansion, deforestation, and agricultural conversion over time.

Atmospheric Correction for Temperature

1. Water Vapor Absorption – Water vapor causes temperature underestimation of 5–10°C without correction.
2. Aerosol and Haze Effect – Aerosols scatter and absorb thermal radiation, causing false brightness variations.
3. Correction Methods – Dark Object Subtraction and radiative transfer models (FLAASH/6S) improve accuracy.
4. Output Improvement – Corrected imagery matches ground measurements within 1–2°C.
5. Validation – Corrected satellite temperatures are compared with ground station data to confirm accuracy.

Whiskbroom vs. Pushbroom Scanners

1. Whiskbroom Mechanism – Scanning mirror moves mechanically (across-track); single detector builds image line by line.
2. Whiskbroom Disadvantage – Mechanical parts wear out; geometric distortion increases at image edges.
3. Whiskbroom Example – Used in older Landsat 1–7 sensors.
4. Pushbroom Mechanism – Fixed linear CCD array samples entire ground line simultaneously without moving parts.
5. Pushbroom Advantage – No moving parts increases reliability; longer dwell time improves Signal-to-Noise Ratio (SNR).

Components of a GIS

1. Hardware – Computers, servers, GPS devices, scanners, and plotters for data processing and storage.
2. Software – GIS applications (ArcGIS, QGIS, ERDAS) for analysis, visualization, and map production.
3. Data – Spatial data (maps, images) and attribute data (tables) linked together.
4. People – GIS professionals and analysts who interpret results and make decisions.
5. Methods/Procedures – Defined workflows for data collection and analysis ensuring consistent results.

Vector vs. Raster Data Models

Geodatabase Creation Process

1. Requirements Analysis – Define purpose, data types, coordinate system, and scale.
2. Schema Design – Design feature classes, tables, relationships, domains, and subtypes.
3. Data Collection – Collect spatial data from GPS, imagery, and existing maps.
4. Data Entry and Import – Import data into GIS software; assign coordinate systems.
5. Validation and Quality Check – Check for topology errors, missing attributes, and geometry standards.

Types of Spatial Analysis in GIS

1. Query and Selection – Retrieving features based on attribute conditions or spatial location.
2. Buffer Analysis – Creating zones of specified distance around features to identify proximity.
3. Overlay Analysis – Combining layers (union, intersect, clip) to show spatial relationships.
4. Network Analysis – Finding shortest paths and service areas using connected line features.
5. Spatial Statistics – Measuring patterns, clustering, and distribution using hot spot analysis.

Network Analysis in GIS

1. Definition – Uses connected line features (roads, pipes) to solve problems involving movement and flow.
2. Shortest Path – Finds optimal route minimizing distance, time, or cost.
3. Service Area Analysis – Identifies areas reachable from a facility within a specified time.
4. Closest Facility – Finds the nearest facility (hospital, fire station) from an incident location.
5. Applications – Transportation planning, utility management, and emergency response.

SQL in GIS

1. Definition – Standard programming language used to query and manage data in relational databases.
2. Attribute Query – SELECT statements filter features based on attribute values (e.g., road_type = ‘highway’).
3. Spatial Query – GIS extends SQL with spatial functions (e.g., ST_Distance to find features near floods).
4. Joins and Relations – SQL JOIN combines spatial and non-spatial tables using common IDs.
5. GIS Software Integration – ArcGIS, QGIS, and PostGIS use SQL for automation and analysis.

GIS Project Design Steps

1. Problem Definition – Define objectives, study area, deliverables, and timeline.
2. Data Requirements – Identify spatial/attribute data, sources, and coordinate systems.
3. Database Design – Design schema, feature classes, and quality standards.
4. Analysis Design – Plan sequence of GIS operations to answer project questions.
5. Output and Presentation – Define final maps, reports, and dashboards for communication.

GIS in Urban Planning

1. Land Use Planning – Maps existing land use and models future growth scenarios.
2. Infrastructure Planning – Plans road networks and utilities using network analysis.
3. Population Analysis – Integrates census data to map density and housing demand.
4. Environmental Management – Identifies green zones, flood plains, and pollution hotspots.
5. Disaster Risk Mapping – Maps flood and earthquake risks to guide emergency planning.

GPS in GIS Data Collection

1. Field Data Collection – Collects precise coordinates of features for direct import into GIS.
2. Accuracy Levels – Handheld (3–5 m), DGPS (sub-meter), RTK (centimeter).
3. Attribute Recording – Records location and attribute data simultaneously using mobile apps.
4. Real-time Tracking – Enables live monitoring of vehicles and assets.
5. Ground Truth Verification – Validates satellite image classification and GIS analysis results.

Advantages of 3D GIS

1. Realistic Visualization – Creates 3D city models for better understanding of proposals.
2. Volumetric Analysis – Calculates earthwork volumes, stockpiles, and building structures.
3. Line of Sight Analysis – Determines visibility for telecommunications and military operations.
4. Shadow and Solar Analysis – Models shadows for solar panel placement and urban comfort.
5. Underground Mapping – Maps subsurface infrastructure in 3D to reduce excavation conflicts.