cl_maintenanceAndUpdateFrequency

RI_534

82 record(s)
 
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    Each pixel value corresponds to the day-of-week (1-7) from which the Weekly Best-Quality NDVI retrieval is obtained (1 = Monday, 7 = Sunday).

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    This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer (<5 cm). The data is created daily and is averaged for the ISO standard week and month. The data is produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 6.20 of the SMOS soil moisture processor. The data are produced by the European Space Agency and obtained under a Category 1 proposal for Level 2 soil moisture data. The data are gridded to a resolution of 0.25 degrees. Data quality flags have been applied to remove areas where rainfall is present during the acquisition, where snow cover is detected and when Radio Frequency Interference (RFI) is above an acceptable threshold.

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    The Indigenous Geographical Names dataset presents an extract from the Canadian Geographical Names Data Base (CGNDB) of geographical names with roots in Indigenous cultures. These geographical names reflect heritage, language, personal names, and cultural practices. Terrain and water features, populated places and culturally relevant places are geographical feature types present in the dataset. The Geographical Names Board of Canada (GNBC) is working to increase awareness of existing Indigenous place names and help promote the revitalization of Indigenous cultures and languages. Many more Indigenous place names exist in Canada, and this dataset will be constantly evolving as additional Indigenous place names are officially recognized and identified. The Geographical Names Board of Canada does not warrant or guarantee that the information is accurate, complete or current at all times. For more information, to report data errors, or to suggest improvements, please contact the GNBC Secretariat at Natural Resources Canada with questions or for more information. The CGNDB is the authoritative national database of Canada's geographical names. The purpose of the CGNDB is to store geographical names and their attributes that have been approved by the GNBC, the national coordinating body responsible for standards and policies on place names. This dataset is extracted from the CGNDB on a weekly basis, and consists of current officially approved names, feature type, coordinates of the feature, decision date, source, Indigenous language of origin where known, and other attributes.

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    Location and characterization of all the civic addresses of the City of Repentigny.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    City of Trois-Rivières sewer pipe network**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    Punctual location of bus shelters on the territory of the City of Repentigny.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    Location of municipal sports fields on the territory of the City of Repentigny.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    Civic addresses of air-conditioned public places.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

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    This data represents the dryness of the land surface based on vegetation conditions. The data is created weekly and uses weekly information on precipitation anomalies (namely the Standardized Precipitation Index or SPI) and satellite vegetation condition derived from Normalized Difference Vegetation Index (NDVI) from the MODIS Satellite. These dynamic data sets along with static data sets on land cover, soil water holding capacity, irrigation, ecozones and land surface elevation are used to model the drought severity, based on the Palmer Drought Severity Index (PDSI). The mapcubist model was trained on historical data and applied in real time to the dynamic inputs to produce drought severity ratings. The model is run at a 1km resolution and was developed by the AAFC, the United States Geological Survey and the United States Drought Monitor at the University of Nebraska Lincoln.

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    Information on permits issued to Quebec City**This third party metadata element was translated using an automated translation tool (Amazon Translate).**