To support a wide range of efforts to understand the geographic context and historical conditions of the Indian residential schools sites for a wide range of stakeholders, Indigenous Services Canada has created a Web service to access and visualize historical aerial photography for those sites. The Historical aerial photography of Indian residential schools dataset contains digital scans of aerial photographs that were acquired from 1924 to 1998 over Indian Residential school sites and surrounding areas across Canada, as well as basic information about each photography and depicted site. The digital images were georeferenced, to match ground coordinates, saved in a resampled uncompressed raster format and compiled in a single mosaic layer. The dataset does not include the complete range of aerial photographs of each site. Instead, an attempt has been made to select a single optimal photograph for each site based on good photographic quality and the site's years of operation. In some cases no photograph is available, and in others a photograph was only available after the years of operation. The source scanned prints was obtained from the archives of the National Air Photo Library (NAPL) of Natural Resources Canada (NRCAN). This dataset should be considered evergreen as new information and photography sources are identified. It should be noted that this dataset can only be downloaded using ArcGIS and ArcPro software as well as other GIS software.

Information on the nature, duration and obstacles caused by ongoing work on major projects on the City of Montreal's road network.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The data sets analyzed come from bicycle counting detectors installed on various sites by SUM-DIGD. These sensors record the number of cyclists crossing each minute, allowing detailed observation of the number of cyclists passing by. In some locations, detectors also provide speed data, enriching behavioral analysis. In order to facilitate interpretation and identify trends, raw data is aggregated in several ways: ### * -15 min * -1hr * -daily * -monthly * -annual This methodology makes it possible to monitor the evolution of bicycle traffic, to identify seasonal variations and to assess the impact of specific developments or events. Aggregation is carried out using automated processes, guaranteeing the consistency of the time series and the quality of the analyses.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

This data set contains public events in the City of Montreal as broadcast on [the City calendar] (https://montreal.ca/calendrier). The data provides information on the main characteristics of the event, including date, type of event (e.g. show, public session, exhibition), target audience, cost, and location.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The dataset contains projects that are currently, or have been, subject to environmental assessment review. Attributes include the project description, project phase, decision, and proponent name. This layer consists of points themed two ways: a. Project Phase- This theme consists of layers showing what phase each project is in - pre-EA, application review, post-decision, and withdrawn or terminated; and b. Project Type - This theme consists of nine layers that reflect the potential types of projects under review. This dataset is coming from the EAO Project Information Centre (EPIC) and is updated daily. For more information on any of the project points go to https://projects.eao.gov.bc.ca/.

Heat Wave Days are the number of days in the forecast period with a maximum temperature above the cardinal maximum temperature, the temperature at which crop growth ceases. This temperature is 35°C for warm season crops (dhw_warm). Week 1 and week 2 forecasted index is available daily from April 1 to October 31. Week 3 and week 4 forecasted index is available weekly (Thursday) from April 1 to October 31. Warm season crops require a relatively warm temperature condition. Typical examples include bean, soybean, corn and sweet potato. They normally grow during the summer season and early fall, then ripen in late fall in southern Canada only. Other agricultural regions in Canada do not always experience sufficiently long growing seasons for these plants to achieve maturity. The optimum temperature for such crops is 30°C. Agriculture and Agri-Food Canada (AAFC) and Environment and Climate Change Canada (ECCC) have together developed a suite of extreme agrometeorological indices based on four main categories of weather factors: temperature, precipitation, heat, and wind. The extreme weather indices are intended as short-term prediction tools and generated using ECCC’s medium range forecasts to create a weekly index product on a daily and weekly basis.

Applications for the surface location of a well associated with oil and gas activity. This dataset contains point features for proposed applications collected through the BC Energy Regulator's Application Management System (AMS). This dataset is updated nightly

Probability of total precipitation above 100mm over the forecast period (pweek100_prob) Week 1 and week 2 forecasted probability is available daily from September 1 to August 31. Week 3 and week 4 forecasted probability is available weekly (Thursday) from September 1 to August 31. Precipitation (moisture availability) establishes the economic yield potential and product quality of field crops. Both dry and wet precipitation extremes have the ability to inhibit proper crop growth. The greatest daily precipitation index covers the risk of excessive precipitation in the short term, while the other indices pertain to longer term moisture availability. Agriculture and Agri-Food Canada (AAFC) and Environment and Climate Change Canada (ECCC) have together developed a suite of extreme agrometeorological indices based on four main categories of weather factors: temperature, precipitation, heat, and wind. The extreme weather indices are intended as short-term prediction tools and generated using ECCC’s medium range forecasts to create a weekly index product on a daily and weekly basis.

Cool Wave Days are the number of days in the forecast period with a minimum temperature below the cardinal minimum temperature, the lowest temperature at which crop growth will begin (dcw-warm). This temperature is 10°C for warm season crops. Week 1 and week 2 forecasted index is available daily from April 1 to October 31. Week 3 and week 4 forecasted index is available weekly (Thursday) from April 1 to October 31. Warm season crops require a relatively warm temperature condition. Typical examples include bean, soybean, corn and sweet potato. They normally grow during the summer season and early fall, then ripen in late fall in southern Canada only. Other agricultural regions in Canada do not always experience sufficiently long growing seasons for these plants to achieve maturity. The optimum temperature for such crops is 30°C. Agriculture and Agri-Food Canada (AAFC) and Environment and Climate Change Canada (ECCC) have together developed a suite of extreme agrometeorological indices based on four main categories of weather factors: temperature, precipitation, heat, and wind. The extreme weather indices are intended as short-term prediction tools and generated using ECCC’s medium range forecasts to create a weekly index product on a daily and weekly basis.

Province wide spatial view showing aquifers designated as a Water Reservation. These Reserves set aside water in an aquifer specifically for future treaty obligations, and are formally established through Orders in Council issued by the Lieutenant Governor in Council, as authorized under Sections 39–41 of the Water Sustainability Act.