Hazard Exposure - Built Form Infrastructure - DCRRA
Dataset summarizing hazard exposure of built form infrastructure in British Columbia, broken down by region and the province. This is a subset of the datasource shown on the British Columbia Hazard Insights Tool.
The Disaster and Climate Risk and Resilience Assessments (DCRRA) evaluated the presence and characteristics of valued assets in areas potentially exposed to six types of hazards: coastal and riverine flooding, earthquakes, wildfires, extreme heat, drought. The findings from this project aim to support disaster risk assessments, management strategies, and communication planning.
A structured workflow was developed to map the spatial relationships between hazards and valued assets. This process identifies hazard exposure boundaries and quantifies exposure or non-exposure using metrics such as area, area-weighted sum, length, dollar value, and count. The assessment results are designed for provincial-scale analysis. All values have been rounded (see report Table 3-3 for details).
The results reflect provincial-level data analysis and is suitable for large-scale hazard exposure but not for local community level analysis.
For a detailed explanation of the methodology and its limitations, please refer to the this report.
Datasets available for download
-
Exposure_Infrastructure_AssetsTable
Layer 118 via ArcGIS REST API
-
Exposure_Infrastructure_Assets (Explore)HTML
Explore Exposure_Infrastructure_Assets on ArcGIS Hub
Additional Info
| Field | Value |
|---|---|
| Last Updated | March 25, 2026, 01:46 (UTC) |
| Created | March 25, 2026, 01:46 (UTC) |
|
Domain / Topic
Domain or topic of the dataset being cataloged.
|
|
|
Title
Title for the Dataset.
|
Hazard Exposure - Built Form Infrastructure - DCRRA |
|
Description
A description of the dataset.
|
Dataset summarizing hazard exposure of built form infrastructure in British Columbia, broken down by region and the province. This is a subset of the datasource shown on the British Columbia Hazard Insights Tool. The Disaster and Climate Risk and Resilience Assessments (DCRRA) evaluated the presence and characteristics of valued assets in areas potentially exposed to six types of hazards: coastal and riverine flooding, earthquakes, wildfires, extreme heat, drought. The findings from this project aim to support disaster risk assessments, management strategies, and communication planning. A structured workflow was developed to map the spatial relationships between hazards and valued assets. This process identifies hazard exposure boundaries and quantifies exposure or non-exposure using metrics such as area, area-weighted sum, length, dollar value, and count. The assessment results are designed for provincial-scale analysis. All values have been rounded (see report Table 3-3 for details). The results reflect provincial-level data analysis and is suitable for large-scale hazard exposure but not for local community level analysis. For a detailed explanation of the methodology and its limitations, please refer to the this report. |
|
Tags / Keywords
Keywords/tags categorizing the dataset.
|
|
|
Format (CSV, XLS, TXT, PDF, etc)
File format of the dataset.
|
|
|
Dataset Size
Dataset size in megabytes.
|
120.0 |
|
Metadata Identifier
Metadata identifier – can be used as the unique identifier for catalogue entry
|
|
|
Published Date
Published date of the dataset.
|
2025-09-11 |
|
Time Period Data Span (start date)
Start date of the data in the dataset.
|
|
|
Time Period Data Span (end date)
End date of time data in the dataset.
|
|
|
GeoSpatial Area Data Span
A spatial region or named place the dataset covers.
|
| Field | Value |
|---|---|
|
Identifier
Unique identifier for the dataset.
|
f90830da2b3744f78ffec66bad4bfdd1 |
|
Language
Language(s) of the dataset
|
English |
|
Link to dataset description
A URL to an external document describing the dataset.
|
https://bchazardinsightstool-bcgov03.hub.arcgis.com/datasets/bcgov03::hazard-exposure-built-form-infrastructure-dcrra |
|
Persistent Identifier
Data is identified by a persistent identifier.
|
|
|
Globally Unique Identifier
Data is identified by a persistent and globally unique identifier.
|
|
|
Contains data about individuals
Does the data hold data about individuals?
|
|
|
Contains data about identifiable individuals
Does the data hold identifiable data about individual?
|
|
|
Contains Indigenous Data
Does the data hold data about Indigenous communities?
|
|
|
Portal Type
Platform type of the source portal.
|
| Field | Value |
|---|---|
|
Version
Version of the datatset
|
None |
|
Source
Source of the dataset.
|
None |
|
Version notes
Version notes about the dataset.
|
|
|
Is version of another dataset
Link to dataset that it is a version of.
|
|
|
Other versions
Link to datasets that are versions of it.
|
|
|
Provenance Text
Provenance Text of the data.
|
EM GeoHub |
|
Provenance URL
Provenance URL of the data.
|
|
|
Temporal resolution
Describes how granular the date/time data in the dataset is.
|
|
|
GeoSpatial resolution in meters
Describes how granular (in meters) geospatial data is in the dataset.
|
|
|
GeoSpatial resolution (in regions)
Describes how granular (in regions) geospatial data is in the dataset.
|
| Field | Value |
|---|---|
|
Indigenous Community Permission
Who holds the Indigenous Community Permission. Who to contact regarding access to a dataset that has data about Indigenous communities.
|
|
|
Community Permission
Community permission (who gave permission).
|
|
|
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
|
| Field | Value |
|---|---|
|
Number of data rows
If tabular dataset, total number of rows.
|
240 |
|
Number of data columns
If tabular dataset, total number of unique columns.
|
108 |
|
Number of data cells
If tabular dataset, total number of cells with data.
|
25920 |
|
Number of data relations
If RDF dataset, total number of triples.
|
|
|
Number of entities
If RDF dataset, total number of entities.
|
|
|
Number of data properties
If RDF dataset, total number of unique properties used by the triples.
|
|
|
Data quality
Describes the quality of the data in the dataset.
|
|
|
Metric for data quality
A metric used to measure the quality of the data, such as missing values or invalid formats.
|
0 Comments