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Case study · LandGenius

Client project · AugmentProject period2022

Spatial-data backend

Developed the Django and GDAL backend that connected spatial-data processing and environmental land analysis with the application and reporting workflows.

01

Why

A user wants to know about the land in a specific area: land cover, wetlands, streams, ponds, flood zones, endangered species and soil. The information exists in US sources for whole regions, but the user cares about only their own area.

02

Decision

The user defines the area in one of two ways: draw a polygon on the map, or upload a shapefile. The backend gets the extracted information for the necessary regions from a US API, then cuts out only the portion that falls inside the user's polygon or shapefile (Django with GDAL for the spatial processing). From that it builds the analysis, shows it, and the user can download the whole document as a PDF report. Payment is handled with Stripe.

How it fits

Hover or focus a box for the story behind it.

A person draws a polygon or uploads a shapefile. The backend gets the data for the necessary regions from a US API, cuts out only the area the person defined, and builds the analysis they can download as a PDF.Define the areaBuild the analysisDraw the project boundary on an interactive Mapbox map. Turf.js calculates the area of the polygon.Draw a polygon Mapbox map, Turf.jsUpload an existing shapefile. The polygon is extracted and shown on the map, so nobody has to redraw it.Upload a shapefile Polygon extractedBoth ways give the same thing: the area the person wants analyzed.Project area The boundaryThe boundary the person defined.Project area Drawn or fileThe backend gets the extracted information for the necessary regions from a US API: land cover, wetlands, streams, ponds, flood zones, endangered species and soil.US data API Needed regionsDjango with GDAL cuts out only the portion that falls inside the person's polygon or shapefile.Cut to area Django, GDALFrom that the application builds the land analysis and shows it.Analysis On screenThe whole analysis can be downloaded as a structured PDF report, built with fpdf. Payment is handled with Stripe.PDF report Download

A person defines the area in one of two ways: draw a polygon on the map, or upload a shapefile.

03

Alternatives considered

None.

04

What I built

Developed the application's Django backend and integrated GDAL to support spatial-data processing and retrieval.

The backend handled geographic information required by the land-analysis workflow and connected geospatial processing with the application's frontend and reporting functionality.

05

Outcome

A user gets a land analysis for any area they define, as a report they can download.

Technologies