Datasets:

cmg777
/

project2026e

license: cc-by-4.0
language:
  - en
  - es
pretty_name: >-
  ds4bolivia — Bolivian municipalities: SDGs, satellite embeddings & nighttime
  lights
tags:
  - bolivia
  - sdg
  - sustainable-development
  - satellite-embeddings
  - nighttime-lights
  - remote-sensing
  - geospatial
size_categories:
  - n<1K

Bolivian Municipalities — SDGs, Satellite Embeddings & Nighttime Lights

Socioeconomic, satellite, and geographic measures for Bolivia's 339 municipalities across its 9 departments — the analysis data for the project "Predicting the Sustainable Development of Bolivian Municipalities with Satellite Embeddings and Machine Learning" (Carlos Mendez, Nagoya University).

This dataset is a public mirror of the data/ folder in cmg777/project2026e. Every file is keyed on asdf_id (integer, 0–338), the universal join key across all datasets. To attach municipality/department labels, merge any file to regionNames/regionNames.csv on asdf_id.

Path	Description
`ds4bolivia_v20250523.csv`	Analysis-ready merged master (339 × 351) — all subfolders joined on `asdf_id`.
`definitions_ds4bolivia_v20250523.csv`	Data dictionary for the master file (`varname` → `varlabel`).
`regionNames/`	Administrative IDs & names — the join foundation.
`sdg/`	IMDS + 14 composite SDG indices (0–100 scale).
`sdgVariables/`	64 individual SDG indicators across all 17 goals.
`satelliteEmbeddings/`	64-dim Google Satellite Embeddings — simple-mean (2017) and population-weighted (2017–2025 panel).
`nighttimeLights/`	VIIRS nighttime lights (simple-average & population-weighted, 2017–2021), plus `rasters/` GeoTIFF.
`predictions/`	Out-of-sample predictions for SDG 1, 7 and 13 (four-view: actual, lights, embeddings, combined) plus space-time forward projections.
`maps/`	Municipality boundary polygons (GeoJSON), keyed by `asdf_id`.
`sdg/`, `regionNames/`, …	Each subfolder ships its own `README.md` with a full variable dictionary.

Provenance & coverage

Spatial unit: 339 Bolivian municipalities (9 departments); version v20250523.
Source: quarcs-lab/ds4bolivia; the 64-dim satellite embeddings are Google Satellite Embeddings (Google Earth Engine); SDG indices and the IMDS index follow Andersen et al. (2020).
Time coverage: population 2001–2020; nighttime lights 2012–2021; most SDG variables 2012–2019; satellite embeddings 2017 (simple-mean) and 2017–2025 (population-weighted panel).

Load from Python

Load any file straight from the Hub (no full clone needed):

import pandas as pd
from huggingface_hub import hf_hub_download

path = hf_hub_download(
    repo_id="cmg777/project2026e",
    repo_type="dataset",
    filename="satelliteEmbeddings/bolivia_pop_weighted_2017.csv",
)
df = pd.read_csv(path)

The companion repo ships a code/hf_data.py helper with a data_path() function that prefers a local copy and otherwise streams the file from this dataset.

Bolivian Municipalities — SDGs, Satellite Embeddings & Nighttime Lights

Contents

Provenance & coverage

Load from Python