Tutorial 0: What is spatial data?
A gentle introduction to maps, rasters, and vectors in the context of land restoration.
0.1 Why “where” matters
- Restoration decisions are always tied to location (which farm, which watershed, which district).
- Spatial data simply means data that has a location attached (coordinates, boundaries, or pixels).
- Spatial data helps us see patterns that are invisible in other data structures: hotspots, gradients, clusters.
0.2 The two main types: vector and raster
- Vector data: points, lines, polygons (e.g., villages, roads, administrative boundaries).
- Raster data: grids of pixels (e.g., rainfall, SOC, tree cover, EVI, land surface temperature).
- When you see a heatmap or continuous surface on our dashboards, you are looking at raster data.
0.3 Spatial datasets you will see on K4GGWA
- Climate: rainfall, temperature, drought indicators, fire frequency.
- Land health: soil organic carbon (SOC), erosion risk, vegetation indices, land cover classes.
- Socio-ecological context: administrative boundaries, population, infrastructure where relevant.
0.4 Common formats and jargon
- GeoTIFF / COG: image-like files that store rasters (e.g., SOC, EVI) with geographic information.
- Shapefile / GeoPackage / GeoJSON: common formats for vector data such as boundaries or sample plots.
- CRS (Coordinate Reference System): the “language” maps use to describe locations on Earth.
0.5 How we manage spatial data for the GGW
- We combine field measurements, satellite data, and existing public datasets.
- Data is cleaned, harmonised, and stored in structured catalogues so that indicators can be mapped consistently.
- This foundation allows us to build the maps you see on the dashboards and in the State of the Land reports.