An Introduction to Geographic Information Systems (GIS) and Current GIS Technologies

Introduction

Geographic Information Systems (GIS) are sophisticated computer-based frameworks designed to collect, store, analyze, manage, and visualize spatial data. These systems enhance our understanding of complex geographic phenomena by identifying patterns and relationships through spatial representation. GIS supports decision-making across various professional fields, including environmental science, urban planning, disaster management, agriculture, and commercial logistics. By combining spatial data with descriptive attributes, GIS facilitates detailed spatial analyses and effective communication of geographic insights.

Spatial Analysis in GIS

Spatial analysis is central to GIS, involving methods such as layering thematic datasets to examine and interpret geographic information. Common examples include overlays of land-use classifications, demographic distributions, transportation networks, and natural resources. This layered approach helps identify spatial patterns and trends that traditional statistical methods might miss. For example, urban planners use GIS to determine optimal locations for infrastructure development, while environmental researchers leverage GIS to predict the impacts of climate change on ecosystems.

Geographic Information Science (GIScience)

GIS technology is grounded in Geographic Information Science (GIScience), an interdisciplinary field providing foundational theories, methodologies, and analytical techniques essential for GIS functionality. GIScience incorporates various sub-disciplines, including cartography, geodesy, photogrammetry, remote sensing, and spatial statistics. These fields contribute critical expertise and tools, enhancing the effectiveness of GIS. Continuous advancements in data acquisition, computational capabilities, and analytical methods continually refine the relationship between GIS and GIScience.

GIS Data Layers

GIS incorporates multiple types of data layers, each representing specific geographic features or information. Common GIS data layers include:

Parcels: Individual property boundaries used for land management and taxation.
Zoning: Land-use regulations indicating permitted uses within specific areas.
Topography: Elevation contours and terrain features that influence planning and development.
Demographics: Population statistics and socio-economic data used for planning and resource allocation.
Land Cover: Information on vegetation, urban areas, water bodies, and natural resources.
Imagery: Satellite and aerial imagery providing visual context and analysis capabilities.
Map Data: Basemaps including roads, buildings, boundaries, and other reference information for context.
Geology: Information about the geological characteristics of the area being scanned.
Advanced Models: by using Building Information Modeling (BIM) technologies, our data stack can also have 3D models of the structure in the area.

Nonetheless, modern GIS techniques also include closer to the ground information such as:

Street/Ground level photographs: Photographs and imagery of the area taken at a street/ground level.
Ground level scans: Scans of buildings or areas/objects of interest in the area being scanned.

Data Layer Integration Methods

The true power of GIS comes from integrating the multiple collected data layers into a cohesive, holistic system of cross-correlated information. Effective GIS analysis often involves integrating multiple data layers. Common methods and approaches for data layer integration include:

Overlay Analysis: Combining different spatial layers to identify relationships and intersections, such as zoning areas with demographic information.
Spatial Join: Attaching attributes from one spatial layer to another based on their spatial relationship.
Raster and Vector Integration: Combining raster-based imagery (e.g., satellite images) with vector-based data (e.g., road networks) for comprehensive analysis.
Georeferencing: Aligning spatial data layers accurately within a coordinate system to ensure consistency and accuracy across layers.
Interpolation Techniques: Estimating values across a surface from known data points, such as elevation or temperature data.
Network Analysis: Integrating road or utility networks with spatial data to analyze connectivity, accessibility, and logistics.
Temporal Integration: Analyzing and visualizing changes in spatial data over time to understand historical trends and predict future developments.

For a more in-depth article about Data Layer integration in GIS go to the following article: Data Layering in GIS: Combining Multiple Data Layers in Maps.

Applications of GIS

The versatility of GIS technologies allows numerous applications across diverse sectors. In urban planning, GIS supports sustainable land-use optimization and management of urban growth. Emergency services rely on GIS for real-time disaster mapping, improving response times and resource allocation. In agriculture, GIS-driven precision agriculture techniques help monitor soil conditions, crop health, and irrigation systems, enhancing productivity and environmental sustainability. Businesses utilize GIS for market analysis, optimizing delivery routes, and enhancing customer interactions through spatial insights.

Deep Mapping

For an actual implementation of GIS using cross-correlated databases see: Deep Mapping, a system whose purpose is to gather enough information in order to map and ‘understand’ and contextualize the history and evolution of a city and its buildings, infrastructure, areas and structures.

Click here to go to the Deep Mapping article.

Current GIS Technologies

ArcGIS Pro (Esri): Comprehensive desktop software for GIS analysis and mapping.
QGIS (Open-source): Free, intuitive desktop application for GIS analysis.
GRASS GIS (Open-source): Advanced software for spatial data management and complex analyses.
Google Earth Engine: Cloud-based platform offering planetary-scale geospatial analyses.
Autodesk InfraWorks: 3D GIS software for infrastructure planning and visualization.
MapInfo Pro (Precisely): Specializes in spatial analytics and thematic mapping.
CARTO: Cloud-based platform for spatial data visualization and analytics.
GeoServer (Open-source): Web-based server software for publishing geospatial data.
PostGIS: Spatial database extension for PostgreSQL.
Mapbox: Cloud-based mapping and analytics platform.
ENVI: Integrates remote sensing imagery analysis with GIS capabilities.
Hexagon Geospatial’s M.App Enterprise: Platform for creating interactive GIS applications and dashboards.
TerraGo: Mobile solutions for geospatial data sharing and collaboration.
DroneDeploy: Platform integrating drone-captured aerial imagery with GIS analysis.

Common GIS Surveying Hardware

GNSS/GPS Receivers: Devices offering high-precision location data.
Total Stations: Instruments measuring angles and distances accurately.
Drones/UAVs: Aerial platforms capturing imagery for mapping and analysis.
LiDAR Scanners: Equipment capturing detailed elevation and topographic data.
Handheld GIS Devices: Portable units for field data collection and mapping.
Rugged Tablets and Field Computers: Durable devices tailored for harsh field conditions.
Laser Rangefinders: Instruments for precise distance measurements.
Digital Cameras and Photogrammetry Tools: Devices for capturing imagery used to generate detailed spatial models and maps.
- For a comprehensive guide on phogrammetry: A Comprehensive Guide to Photogrammetry: Principles, Technologies and Workflows

Emerging GIS Technologies

Emerging technologies continually expand GIS capabilities. Innovations such as real-time data analytics, cloud computing, artificial intelligence integration, and augmented reality visualization significantly improve GIS functionality and user accessibility. These advancements enable more interactive, intuitive, and powerful GIS applications, increasing the potential for widespread adoption across various user groups and organizations.