GIS

A GIS (Geographic Information System) is a software framework that connects any data to maps of the Earth. In practice, GIS enables city planners and climate professionals to store, visualize, and analyze spatial data (locations, shapes, and attributes) of features such as streets, parcels, buildings, parks and infrastructure. GIS data include both vector formats (points, lines, polygons) and raster formats (gridded images like satellite maps).

What is GIS and GIS data

GIS stores spatial data (where things are) along with their attributes (descriptive information). Spatial data can come in layers, each representing a theme or feature type. Typical urban GIS layers include:

• Parcels and land use: city parcel maps, cadastral boundaries, zoning districts.
• Buildings and infrastructure: footprints, heights, utilities, roads, transit lines, bike paths.
• Green spaces: parks, street trees, urban forests, green roofs, wetlands, and water bodies.
• Environmental layers: elevation/DEM, flood zones, soil types, climate zones.
• Social and demographic layers: population density, age distribution, income, health data, etc.

GIS supports both vector layers (e.g. a point for each tree, a polygon for each park) and raster layers (e.g. satellite imagery, digital elevation models, or gridded indices). For instance, a city might have a raster layer of satellite-derived NDVI (vegetation index) or land surface temperature, and vector layers of roads or census tracts.

Data are integrated into GIS from many sources: municipal surveys, field GPS measurements, mobile apps, open-data portals, and remote sensing. For example, a tree census might be collected via GPS-enabled smartphones or LiDAR (laser scans), then joined with city registry data in a GIS. Citizen science apps and drones can feed GIS with up-to-date tree or park inventories. Public open data (e.g. building footprints from OpenStreetMap, or Copernicus satellite products) provide free layers for cities to import. By combining multiple sources, a GIS database can become the single repository for all spatial information about a city’s climate risks and resources.

GIS in urban planning and climate adaptation

GIS is widely used to map climate hazards and overlay them with city assets and vulnerabilities. For example, GIS can highlight urban heat islands by mapping land surface temperature and impervious surfaces. It can also map flood zones, sea-level rise projections, air pollution hot-spots, and landslide risk. By layering these with social data (population age, health, income) or infrastructure (hospitals, roads), cities can pinpoint where to focus resilience measures.

GIS also supports urban planning more broadly. City planners use GIS for zoning, infrastructure siting, and public space design, all of which are now incorporating climate criteria. For example, planners might use GIS to identify priority corridors for green corridors or to analyze where increasing tree canopy would most reduce heat or improve air quality (see rule 3-30-300). Many planning departments maintain GIS-based “digital twins” of the city , comprehensive map databases, that serve as the foundation for climate action plans (SECAPs) and nature-based solutions.

Why cities need to predict the future of their trees

• 3-30-300
• Adaptation
• Greenery
• UpGreen

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GIS for monitoring urban greenery and trees

GIS plays a central role in tracking and managing urban green assets. A foundational step is often a tree inventory, a GIS database of street trees and park trees. Some cities conduct a full citywide tree census, using GPS or LiDAR to map every street tree. Such data allow forestry managers to plan maintenance and replacements by need. A digital inventory turns reactive care (fixing hazards as they occur) into proactive planning, e.g. prioritizing watering or pruning in neighborhoods with many mature trees.

Other techniques for mapping greenery include:

• High-resolution satellite or aerial imagery: Can be used to classify land cover and compute an urban tree canopy layer.
• LiDAR (Light Detection and Ranging): Airborne LiDAR sensors can derive 3D tree canopy height and density, enabling precise canopy cover and even species estimates.
• Smartphone and GPS surveys: Field workers or citizen scientists can use mobile GIS apps to tag trees, parcels, or habitats in situ.

Urban tree canopy map

These data feed into GIS to produce practical outputs. For instance, GIS can generate an urban tree canopy map showing percent canopy cover for each city block or park. It can also measure compliance with canopy goals. Many cities now reference the 3-30-300 rule for urban greening: each resident should see 3 trees from home, neighborhoods should have ≥30% tree canopy, and everyone should live within 300m of a park. A GIS can calculate all of these metrics: it can buffer each building by 300m to check park access, compute canopy percentage by neighborhood, and count visible trees per block. By quantifying these targets, cities use GIS to assess equity of greenery and plan new planting where the rules are unmet.

GIS is also used to monitor change over time. By comparing canopy layers year-to-year (from LiDAR or imagery), a city can track trends in tree loss or growth. This enables evaluating the impact of planting programs or identifying emerging problems. For example, GIS might highlight where canopy is declining (due to construction or pests) so crews can respond. In essence, GIS turns raw data on urban forests into clear maps for setting priorities and measuring outcomes.

Combining satellite data, remote sensing, and GIS

Modern GIS often ingests products from satellite and aerial remote sensing. Widely used indices include NDVI (Normalized Difference Vegetation Index) which highlights green vegetation from multispectral images (e.g. ESA’s Sentinel-2 satellites), and LST (Land Surface Temperature) from thermal sensors (e.g. Sentinel-3, Landsat). By importing these layers into a GIS, cities can overlay satellite-based GIS maps on their local data. For example, an NDVI raster can be masked to the city boundary to identify green hotspots versus bare asphalt areas, guiding where trees are needed. Similarly, a GIS layer of LST shows the hottest city zones by day, correlating with low vegetation or high imperviousness.

European programs like Copernicus provide ready-to-use spatial datasets that fit into urban GIS workflows. For instance, the Copernicus Land Monitoring Service offers:

• High-Resolution Layer – Imperviousness: maps of sealed surfaces in cities, which directly indicate urban expansion and heat-island potential.
• Urban Atlas: harmonized land use/cover maps for Europe’s urban areas (including street tree layers and building heights), useful for heatwave modelling and green space access analysis.
• Tree Cover Density and Forests layers: detailed tree canopy maps that cities use to measure and plan green infrastructure.
• High-Resolution Vegetation Phenology (HR-VPP): time-series data on vegetation cycles; this was used, for example, to assess urban green quality over time in Turin (Torino), Italy.

These satellite-derived products become GIS layers that planners can query and style. For example, an imperviousness layer might be shaded red for highly paved zones; a street-tree layer might be used to calculate canopy percentage per neighborhood. The Copernicus Urban Atlas even includes street-tree counts for European cities. All these data, together with in-situ measurements, give cities a rich view of their green infrastructure without needing on-site surveys everywhere.

Beyond Copernicus, other remote sensing tools integrate with GIS. For example, NDVI maps from Planet Labs or NASA MODIS can be clipped to city parks to quantify vegetation health, and thermal imagery can identify UHI spots. In practice, GIS serves as the integrator: it brings together sensor data (satellite, drone, LiDAR) with ground data in one spatial framework. Advanced analysis, such as detecting tree stress, calculating ecosystem service (like carbon sequestration), or modeling cooling from shade, is performed within the GIS environment using these fused layers.

Dowload our hanbooks: The 3-30-300 rule and Greenery Audit Copenhagen