HomeLearnTopic Index

The Knowledge Network

The complete index of the GLOBEIR GIS & Remote Sensing Encyclopedia: 61 topics in 10 categories, each one an in-depth article.

01

GIS Fundamentals

The core concepts every geospatial professional builds on — data models, projections, topology, databases and standards.

  1. What is GIS? Geographic Information Systems ExplainedA clear definition of GIS, how a geographic information system works, its core components, and why organisations worldwide depend on it.
  2. Vector Data Model in GIS: Points, Lines and PolygonsHow the vector data model represents the world as points, lines and polygons with attributes, and when vector beats raster.
  3. Raster Data Model: Grids, Cells and Imagery in GISThe raster model explained — pixels, resolution, bands and when grid data is the right representation for spatial phenomena.
  4. Map Projections and Coordinate Systems ExplainedWhy the Earth cannot be flattened without distortion, how projections and datums work, and how to avoid the classic coordinate mistakes.
  5. Topology in GIS: Rules That Keep Spatial Data CleanWhat GIS topology means, common topology rules and errors, and why topology-clean data is the mark of production quality.
  6. Geodatabases and Spatial Databases: Storing GIS Data ProperlyFrom file geodatabases to PostGIS: how spatial databases store geometry, index it, and serve multi-user enterprise GIS.
  7. Spatial Metadata and Standards: ISO 19115, OGC and INSPIREWhy metadata makes spatial data findable and trustworthy, and the standards — ISO 19115, OGC, INSPIRE — that govern it.
02

Remote Sensing Fundamentals

How sensors observe the Earth from satellites and aircraft — the physics, the resolutions, the corrections and the core analysis methods.

  1. What is Remote Sensing? Earth Observation ExplainedA plain-language definition of remote sensing, how satellites and aircraft measure the Earth, and what the data is used for.
  2. The Electromagnetic Spectrum in Remote SensingHow different wavelengths — visible, infrared, thermal, microwave — reveal different properties of the Earth’s surface.
  3. Resolution in Remote Sensing: Spatial, Spectral, Temporal, RadiometricThe four resolutions that define any Earth-observation sensor, their trade-offs, and how to match resolution to application.
  4. Passive vs Active Remote Sensing SensorsThe fundamental split in Earth observation: sensors that record natural energy versus sensors that transmit their own signal.
  5. Satellite Orbits: Sun-Synchronous, Geostationary and ConstellationsHow orbit choice shapes what a satellite can observe — polar sun-synchronous mappers, geostationary sentinels and modern smallsat fleets.
  6. Satellite Image Preprocessing: Corrections That Make Data UsableRadiometric, atmospheric and geometric correction explained — the unglamorous steps that turn raw scenes into analysis-ready data.
  7. Image Classification in Remote Sensing: Methods That Map Land CoverSupervised, unsupervised, object-based and deep-learning classification — how pixels become land-cover maps, and how accuracy is proven.
  8. Change Detection in Remote Sensing: Methods and Best PracticeHow multi-date imagery reveals what changed on the ground — techniques from image differencing to time-series algorithms, and their pitfalls.
03

Sensors & Satellite Programs

The missions and sensor technologies that supply the world’s Earth-observation data — from Landsat and Sentinel to SAR, hyperspectral and thermal systems.

  1. The Landsat Program: Fifty Years of Earth ObservationWhy Landsat’s continuous archive since 1972 remains the backbone of land-change science, and what its sensors deliver today.
  2. Copernicus Sentinel Missions: Europe’s Free Eyes on EarthSentinel-1 radar, Sentinel-2 optical and their siblings — what each mission measures and why Copernicus changed operational monitoring.
  3. Commercial High-Resolution Satellites: The Sub-Metre MarketMaxar, Airbus, Planet and the new radar constellations — what commercial imagery offers, what it costs, and how tasking works.
  4. Synthetic Aperture Radar (SAR): Imaging Through Cloud and DarknessHow SAR builds images from microwave echoes, what backscatter means, and why InSAR can measure millimetres of ground movement.
  5. Hyperspectral Imaging: Reading the Chemistry of the SurfaceWhat hundreds of narrow spectral bands reveal — mineral identification, species mapping, water quality — and what makes hyperspectral hard.
  6. Thermal Remote Sensing: Mapping Temperature from AboveHow thermal infrared sensors measure surface temperature, and what heat maps reveal — urban heat islands, irrigation, leaks and fires.
04

LiDAR & Photogrammetry

Measuring the world in three dimensions — laser scanning, image-based reconstruction, elevation models and true orthophotos.

  1. What is LiDAR? Laser Scanning ExplainedHow LiDAR measures millions of precise 3D points with laser pulses, its platforms and returns, and what point clouds enable.
  2. Point Clouds and LiDAR ClassificationWhat lives inside a point cloud, how classification assigns every point a class, and why the ASPRS scheme and QC dashboards matter.
  3. Photogrammetry Explained: Measurement from PhotographsHow overlapping images become precise 3D measurements — aerial triangulation, stereo mapping and modern dense matching.
  4. DEM, DTM and DSM: Digital Elevation Models ExplainedThe difference between surface and terrain models, how elevation data is made, and what hydro-enforcement means.
  5. Orthophotos and True Ortho: Maps Made of ImageryWhy raw aerial images cannot be used as maps, how orthorectification fixes them, and what makes an ortho “true”.
  6. Structure from Motion (SfM): 3D Reconstruction for EveryoneHow SfM turns ordinary overlapping photos into 3D models and orthomosaics, and where it matches — or misses — survey-grade methods.
05

Drones & Surveying

Field data capture — UAV mapping, GNSS positioning, ground control and mobile mapping — where accuracy is made or lost.

  1. Drone Mapping Basics: From Flight Plan to DeliverableHow UAV surveys work end to end — flight design, overlap, GSD, processing — and what separates a survey from a flight.
  2. GNSS and GPS Surveying: RTK, PPK and Centimetre PositioningHow satellite positioning really works, why raw GPS is metre-grade, and how RTK/PPK corrections deliver centimetres.
  3. Ground Control Points and Survey AccuracyWhat GCPs and checkpoints are, how many you need and where, and how accuracy is honestly reported.
  4. UAV Regulations and Flight Planning for Commercial MappingThe regulatory landscape of commercial drone survey — categories, permissions, no-fly zones — and how professional operations plan around it.
  5. Mobile Mapping Systems: Surveying at Traffic SpeedVehicle-mounted LiDAR and cameras that capture corridors in a drive-through — how MMS works and where it beats other methods.
06

Spatial Analysis & Modelling

The analytical core of GIS — overlay, interpolation, networks, terrain, hydrology and spatial statistics that turn data into answers.

  1. Spatial Analysis: An Overview of the GIS Analyst’s ToolkitThe families of spatial analysis — queries, overlay, distance, networks, surfaces, statistics — and how real problems combine them.
  2. Buffer and Overlay Analysis: The Workhorses of GISHow buffering and overlay answer “what is near” and “what coincides” — the two questions behind most practical GIS analysis.
  3. Spatial Interpolation: IDW, Kriging and Estimating Between SamplesHow continuous surfaces are estimated from point samples — the main methods, their assumptions, and how to validate them.
  4. Network Analysis and Routing in GISShortest paths, service areas, fleet routing and location-allocation — how GIS models movement along real networks.
  5. Terrain Analysis: Slope, Aspect, Viewshed and BeyondWhat elevation models reveal when you differentiate them — slope, aspect, curvature, visibility and terrain-driven siting.
  6. Hydrological Analysis in GIS: Watersheds, Flow and FloodHow terrain becomes hydrology — flow direction, accumulation, watershed delineation and the path to flood modelling.
  7. Spatial Statistics and Hotspot AnalysisTesting whether spatial patterns are real — autocorrelation, Getis-Ord hotspots, clustering and regression that respects geography.
07

GeoAI & Machine Learning

Where artificial intelligence meets geography — deep learning on imagery, training data, spectral indices and cloud-scale analysis platforms.

  1. GeoAI: Where Machine Learning Meets GISWhat GeoAI covers — from feature extraction to prediction — and what it takes to make machine learning work on spatial problems.
  2. Deep Learning on Satellite ImageryHow convolutional networks and segmentation models extract buildings, roads and land cover from imagery at scale.
  3. Training Data and Annotation for Geospatial AIWhy labelled data decides model quality, how geospatial annotation is done well, and what quality control looks like.
  4. NDVI and Spectral Indices: The Arithmetic of Earth ObservationHow simple band ratios like NDVI quantify vegetation, water, soil and burn severity — and how to use them without fooling yourself.
  5. Cloud Geospatial Platforms: Google Earth Engine and BeyondHow planetary-scale cloud platforms changed Earth-observation analysis — data next to compute, and what that enables.
08

Web GIS & Technology

Maps as software — web GIS architecture, OGC services, vector tiles, open-source stacks, digital twins and developer tooling.

  1. What is Web GIS? Maps as Living SoftwareHow web GIS turns spatial data into browser applications — architecture, components and what separates portals that thrive from those that die.
  2. OGC Web Services: WMS, WFS, WMTS and the New OGC APIsThe interoperability standards that let any client consume any server’s maps and features — and how the API generation modernises them.
  3. Vector Tiles and Modern BasemapsWhy modern web maps ship geometry instead of pictures — how vector tiles work, and what they change about styling and performance.
  4. Open Source GIS: QGIS, PostGIS, GeoServer and the Modern StackThe open-source geospatial ecosystem — what each major component does, and how full production stacks are assembled without licence fees.
  5. Digital Twins in the Built EnvironmentWhat separates a digital twin from a 3D model — live data, simulation and decision loops — and how city and asset twins are actually built.
  6. GIS APIs and Developer Tools: Building Location into SoftwareThe developer’s view of geospatial — mapping SDKs, geocoding and routing APIs, spatial SQL and the libraries that glue it together.
09

Cartography & Data

Making maps that communicate — design principles, thematic techniques, scale, and where trustworthy geospatial data comes from.

  1. Cartographic Design Principles: Maps That CommunicateVisual hierarchy, colour, typography and honesty — the design discipline that separates readable maps from decorated data.
  2. Thematic Map Types: Choropleth, Heat, Flow and FriendsThe main thematic mapping techniques, what data each suits, and the classic ways each one misleads when misused.
  3. Map Scale and Generalization: Detail That Fits the ZoomWhat scale really means, why maps must generalise, and how multi-scale databases keep every zoom honest and legible.
  4. GIS vs GPS vs Remote Sensing: Untangling the TrioThe three most confused acronyms in geospatial — what each does, how they differ, and how they work together.
  5. Open Geospatial Data Sources: The Free FoundationsWhere trustworthy free spatial data lives — imagery, elevation, OpenStreetMap, boundaries and climate — and how to use it responsibly.
10

GIS Applications by Domain

How geospatial technology delivers in practice — agriculture, cities, disasters, environment, utilities and defence.

  1. GIS and Remote Sensing in AgricultureFrom satellite crop monitoring to variable-rate prescriptions — how geospatial technology runs modern and smallholder agriculture alike.
  2. GIS in Urban Planning and Smart CitiesThe spatial backbone of city-making — base maps, land use, 3D models, growth analytics and the operations layer of smart cities.
  3. GIS in Disaster Management: Before, During and AfterHow geospatial technology runs the disaster cycle — risk mapping, early warning, response coordination and damage assessment.
  4. GIS in Environmental Management and ClimateMonitoring ecosystems, assessing impacts and planning adaptation — the geospatial toolkit of environmental science and policy.
  5. GIS in Utilities and Telecom: Networks as DataWhy network industries run on GIS — connectivity models, outage response, vegetation compliance and fiber rollout.
  6. GIS in Defence and National SecurityTerrain analysis, geospatial intelligence and mission planning — how location technology serves defence, lawfully and effectively.