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Datasets:
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road-damage

Modalities:
Geospatial
Tabular
Size:
10K<n<100K
Tags:
geospatial
open-data
tabular
parquet
geojson
csv
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metadata 
tags:
  - geospatial
  - open-data
  - tabular
  - parquet
  - geojson
  - csv
  - road-damage
  - query
  - semantic-search
  - image-geolocation
  - year-2023
  - year-2024
  - year-2025
  - mapillary
  - inaturalist
libraries:
  - datasets
size_categories:
  - 10K<n<100K
pretty_name: Road Damage Dataset - Global Road Condition Observations - EmbedEarth

Road Damage Dataset - Global Road Condition Observations - EmbedEarth

This dataset contains geolocated observations selected for the semantic query “Road Damage.” The records were retrieved because their source text, visual context, or metadata matched the query; this is a discovery-oriented collection rather than a complete administrative inventory. It is useful for exploratory mapping, visual search evaluation, geospatial research, and building retrieval or monitoring workflows around road damage. The release contains 25,473 records from 2023, 2024, 2025; matched-observation details are preserved in properties, with associated media available through media_url when supplied. Prepared and distributed by EmbedEarth from Mapillary and iNaturalist.

Dataset contents

Columns

The downloadable Parquet and CSV files use a normalized schema. Source-specific fields are not separate top-level columns; they are JSON-encoded in properties. GeoJSON exposes the same record attributes alongside its geometry.

Column Type Description
id string Stable identifier for the exported record.
image_id string Identifier of the record included in the optional image archive; null when no image was sampled.
sample boolean Whether this record was selected for the optional image archive sample.
latitude float64 Latitude in decimal degrees (WGS 84) when a valid location is available.
longitude float64 Longitude in decimal degrees (WGS 84) when a valid location is available.
geometry_wkb binary The record geometry encoded as Well-Known Binary for spatial workflows.
media_url string URL for an associated image or other visual media when available.
attribution string Attribution text carried into the exported record.
source string Source or provider label carried into the exported record.
properties string A JSON-encoded object containing source-specific attributes; parse this field to access the original subject fields.

Source-specific properties

The properties column is a JSON-encoded object containing semantic retrieval attributes. The exact keys vary by contributing source; common examples are:

Property group What it means
address Address text when supplied by the matched observation.
captured_at Timestamp of the visual or geospatial observation.
source_url URL associated with the source observation when supplied.
owner / publisher Source owner or publisher when supplied.
year / month / season / time_of_day Temporal context derived from the observation when supplied.

Downloads

Data source and attribution

Prepared and distributed by EmbedEarth.

Original or contributing sources:

Build with EmbedEarth

  • Geographic Feature List — browse geographic features available through EmbedEarth
  • EmbedEarth — programmable infrastructure for Earth
  • Developer Documentation — APIs, tools, guides, and examples
  • GitHub — EmbedEarth/e2 — open-source code, issues, and contributions
  • Geographic Search SDK — search geographic features and regions programmatically
  • API — integrate geographic search and spatial data into applications
  • SDK — build geographic capabilities directly into applications
  • CLI — work with geographic search and spatial data from the terminal
  • MCP — connect geographic search and spatial tools to AI agents

Install from npm:

npm i @embedearth/cli
npm i @embedearth/sdk
npm i @embedearth/mcp

Use and limitations

Use it for exploratory mapping, visual search evaluation, geospatial research, and building retrieval or monitoring workflows around the query theme. It is a ranked semantic selection, not a complete administrative inventory of every occurrence.

No machine-readable license was supplied in the source metadata. Confirm the applicable terms from each contributing source before redistribution or commercial use.