Home /Search
Search datasets
We have found 35 datasets for the keyword "83a". You can continue exploring the search results in the list below.
Datasets: 103,468
Contributors: 42
Results
35 Datasets, Page 1 of 4
Annual Maximum and Minimum Daily Water Level or Flow
The annual maximum and minimum daily data are the maximum and minimum daily mean values for a given year.
Maximum Temperature (°C)
Maximum Temperature represents the highest recorded temperature value (°C) at each location for a given time period. Time periods include the previous 24 hours and the previous 7 days from the available date where a climate day starts at 0600UTC.
Annual Maximum and Minimum Instantaneous Water Level or Flow
The annual maximum and minimum instantaneous data are the maximum and minimum instantaneous values for a given year.
CEEI Primary Indicators Total 2007 Communities
Community Energy and Emissions Inventory (CEEI) Primary Indicators Total 2007 Reporting Year by Community
Moisture Anomaly Index
The Moisture Anomaly Index (Palmer-Z) is an estimate of the moisture difference from normal (a 30-year mean). It attempts to express conditions for the current month regardless of what may have occurred before the month in question.
CEEI Primary Indicators Per Capita 2007 Communities
Community Energy and Emissions Inventory (CEEI) Primary Indicators Per Capita 2007 Reporting Year by Community
Ratio of children and seniors to working-age population (0 to 14 and 65 and over versus 15 to 64) by census division, 2016
This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census division. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.
MTA - Mineral Mining Divisions with Codes
Administrative boundaries called mining divisions were once used for recording claims. This information is now historic. This dataset contains the codes for each of the 24 mining division. For example, 1=ALBERNI, 2=ATLIN, 3=CARIBOO, 4=CLINTON, 5=FORT STEELE. These boundaries are no longer used for current administration. Mining division is needed when submitting the title page for your Technical Work Report. More information on ARIS Reports (https://www2.gov.bc.ca/gov/content/industry/mineral-exploration-mining/british-columbia-geological-survey/assessmentreports/submissionmineral). They can also be used to reference historical records.
Wildfire Year/dNBR/Mask 1985-2015
Wildfire Year/dNBR/Mask 1985-2015Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. The wildfire change magnitude included in this product is expressed via differenced Normalized Burn Ratio (dNBR), computed as the variation between the spectral values before and after the change event. This dataset is composed of three layers: (1) binary wildfire mask, (2) year of greatest wildfire disturbance, and (3) differenced Normalized Burn Ratio (dNBR) transformed for data storage efficiency to the range 0-200. The actual dNBR value is derived as follows: dNBR = value / 100. Higher dNBR values are related to higher burn severity. The information outcomes represent 30 years of wildfires in Canada's forests, derived from a single, consistent spatially-explicit data source in a fully automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2015 for Canada's 650 million hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., 2015. An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2015. Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. (Hermosilla et al. 2015b).Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011
VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1)
Geospatial forest inventory dataset updated for depletions, such as harvesting, and projected annually for growth. Sample attributes in this dataset include: age, species, volume, height. The Vegetation Resources Inventory (VRI) spatial datasets describe both where a vegetation resource (ie timber volume, tree species) is located and how much of a given resource is within an inventory unit. Suggested citation: Forest Analysis and Inventory Branch (2024). VRI - 2024 - Forest Vegetation Composite Rank 1 Layer (R1). British Columbia Data Catalogue. https://catalogue.data.gov.bc.ca/dataset/2ebb35d8-c82f-4a17-9c96-612ac3532d55
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and
topics that matter to you.
Please send us your feedback