v0.2.0 · Open source · Paper on arXiv

Publication-ready research maps, without the GIS pain.

No ArcGIS, no QGIS, no shapefiles. AcadGIS is a free, open-source study-area & research map generator — it turns a place name and a data table into journal-ready figures (choropleths, terrain, satellite layers and more) in a few lines of Python.

Read the docs Star on GitHub
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LIVE NOW

Try the AcadGIS web app
— it's live.

The no-code map builder is out. Pick a country, style every layer — water, region fills, basemaps, grids, legends — and export a publication-ready figure at 300 DPI. Right in your browser, free, no install.

Free for research, academic & personal use · unlimited exports

app.acadgis.com A study-area figure of Bangladesh and Dhaka exported from the AcadGIS web app Exported straight from the app — Bangladesh → Dhaka, 2-map template
New in v0.2.0

One import. See what AcadGIS can generate.

Live Sentinel-2 NDVI, ESA WorldCover land cover, satellite basemaps, DEM topography, heat maps, cartograms and multi-panel study areas — every figure below is import acadgis as agis and a few lines.

Browse the tutorials →  Get it on PyPI

How it works

Every research map is built from layers

AcadGIS stacks boundaries, choropleths, terrain and your sampling points into one publication-ready figure. Move your mouse over it.

boundaries · choropleth · terrain · sampling points — composited into one figure
What it makes

Every map a research paper needs

From the study-area figure to choropleths, terrain and sampling-site maps — all publication-ready by default.

Boundaries on demand

Country → state → district → sub-district, by name. No shapefile hunting.

The full thematic catalogue

Choropleths, heat maps, dot-density, bivariate maps, cartograms, isopleths & isolines.

Real satellite data, one call

add_ndvi() pulls live Sentinel-2; add_landcover() pulls ESA WorldCover 10 m. No accounts.

Study-area layouts

Country → region → site multi-panel figures with custom connectors, arrows and highlights.

Terrain, basemaps & rasters

DEM shaded relief, satellite/OSM tile basemaps, and any GeoTIFF — continuous, classed or RGB.

Rivers, sea & drainage

Dense OpenStreetMap rivers, clean ne10m oceans, DEM-derived streams.

Two ways to use it

Code it, or click it

import acadgis as agis

sa = agis.StudyArea("India").zoom_into("West Bengal")
sa.figure(suptitle="Study Area: West Bengal")
sa.save("study_area.png", dpi=300)

Python package available now

Open source on PyPI. pip install acadgis — or just tell your AI agent to use it: one import gives boundaries, thematic maps, satellite layers and study-area figures.

Get the package →   Docs →

Web app live now

For everyone else. Pick a region, style every layer, export — entirely in the browser, no install.

Launch app.acadgis.com →

FAQ

Frequently asked questions

Is AcadGIS free?

Yes. AcadGIS is free and open-source (Apache-2.0). Run pip install acadgis and every map generator — study-area, choropleth, terrain and more — is included.

Do I need GIS experience to make a study-area map?

No. AcadGIS takes a few lines of Python — and you can even ask an AI coding agent to write them for you. No QGIS, ArcGIS or shapefiles required.

Can it make a choropleth map from a spreadsheet?

Yes. Pass a CSV or DataFrame and AcadGIS joins it to administrative boundaries by name — with fuzzy matching for spelling variants (Chittagong → Chattogram) — and shades each region by value.

What kinds of maps can I generate?

Study-area and locator maps, choropleths, heat maps, dot-density, bivariate maps and cartograms, interpolated isopleths and isolines, terrain relief, river networks, plus satellite NDVI and land-cover maps — all publication-ready.

Where do the boundaries and data come from?

Administrative boundaries from GADM (country to sub-district), terrain from Copernicus GLO-30, and rivers/context from Natural Earth and OpenStreetMap. Everything downloads on demand by name and caches locally.

Open source · Apache-2.0

Start making maps today

AcadGIS 0.2.0 is on PyPI right now. Install it, or point your AI agent at the docs and describe the map you want.

Read the docs Star on GitHub

📄 Read the paper: AcadGIS on arXiv (2607.10017) — please cite it if AcadGIS helps your research.