Settlement Characterization¶

To design efficient connectivity solutions, it is essential to distinguish between urban centers and remote rural outposts. GigaSpatial leverages the Global Human Settlement Layer (GHSL) to characterize any POI based on its built environment.

The "Why": Building vs. Population Scenarios¶

• GHSL provides a standardized, global view of the earth's surface, classified into different settlement types (SMOD - Settlement Model).
• PoiViewGenerator allows you to "drape" your POIs over this global layer to inherit their local settlement classification.

Integrating these two allows for automated stratification of your data (e.g., analyzing school connectivity costs specifically for Rural vs Semi-Dense Urban areas).

The Workflow¶

1. Initialize the GHSL Handler¶

The GHSLDataHandler manages the downloading and reading of global settlement rasters.

from gigaspatial import GHSLDataHandler

# Initialize handler for the Settlement Model (SMOD) product
ghsl_handler = GHSLDataHandler(product="GHS_SMOD", year=2020)

2. Identify Urban/Rural contexts¶

We use the PoiViewGenerator to map these global classifications to our specific points of interest.

from gigaspatial import PoiViewGenerator

# Assume gdf_schools is our GeoDataFrame of school locations
view = PoiViewGenerator(gdf_schools)

# Enrich the schools with GHSL SMOD categories
# This resolves to the SMOD (Settlement Model) for each point
enriched_schools = view.map_smod(stat="median")

Understanding SMOD Classifications¶

GHSL SMOD data provides values that correspond to standard settlement types:

Rationale for this Combination¶

Manual classification of thousands of sites is impossible. By combining a Global Handler (GHSL) with a Local View Generator, GigaSpatial allows you to perform "Site Stratification" at the click of a button.

This becomes especially powerful when combined with WorldPop data to calculate not just where a settlement is, but how many people live in the surrounding urban/rural cluster.