cl_maintenanceAndUpdateFrequency

RI_534

78 record(s)
 
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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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    Each pixel value corresponds to the quality control, cloud cover and snow fraction value for each pixel in the Best-Quality Max-NDVI product.

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    The Oil and Gas Rights dataset contains the digital boundaries for existing exploration licences, significant discovery licences, production licences, former permits, former leases and the Norman Wells Proven Area. These boundaries are available for download on the Northern petroleum pesources Website at https://www.rcaanc-cirnac.gc.ca/eng/1100100036087/1538585604719. The Oil and Gas Rights dataset is Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) and Indigenous Services Canada (ISC) primary source for northern petroleum titles geographic location on maps.

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    The Freshwater Fish Habitat Accessibility MODEL- Pacific Salmon and Steelhead predicts the potential extent of accessible freshwater habitat for Pacific Salmon species and Steelhead in BC. Using the BC Freshwater Atlas as the mapping base, the model presumes that in watershed groups where a given species is known to occur, the species can potentially access any stream that is either: - downstream of a known, validated fish observations for the given species OR - has no known barrier to fish passage downstream AND - has no segment steeper (for at least 100m) than the known swimming ability of the given species anywhere downstream This product is an ACCESSIBILITY MODEL only – it represents only the streams that Pacific Salmon and Steelhead could potentially use for migration, based on known/modelled barriers and the given species swimming ability. The model accounts only for natural barriers and connectivity – other essential characteristics for defining fish habitat are not included. For example, streams modelled as accessible may not have flow sufficient for supporting fish. As such, this model is not appropriate for use in operational applications. It is more appropriate for landscape level assessments and planning exercises. Site specific projects such as riparian buffer delineation require field assessment, stream measurements and fish sampling.

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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 service provides routeing measures. These include established (mandatory) direction of traffic flow, recommended direction of traffic flow, separation lines, separation zones, limits of restricted routeing measure, limits of routeing measures, precautionary areas, archipelagic sea lanes (axis line and limit beyond which vessels shall not navigate) and fairways designated by regulatory authority.

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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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    Each pixel value corresponds to the best quality maximum NDVI recorded within that pixel over the week specified. Poor quality pixel observations are removed from this product. Observations whose quality is degraded by snow cover, shadow, cloud, aerosols, and/or low sensor zenith angles are removed (and are assigned a value of “missing data”). In addition, negative Max-NDVI values, occurring where R reflectance > NIR reflectance, are considered non-vegetated and assigned a value of 0. This results in a Max-NDVI product that should (mostly) contain vegetation-covered pixels. Max-NDVI values are considered high quality and span a biomass gradient ranging from 0 (no/low biomass) to 1 (high biomass).

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    Each pixel value corresponds to the difference (anomaly) between the mean “Best-Quality” Max-NDVI of the week specified (e.g. Week 18, 2000-2014) and the “Best-Quality” Max-NDVI of the same week in a specific year (e.g. Week 18, 2015). Max-NDVI anomalies < 0 indicate where weekly Max-NDVI is lower than normal. Anomalies > 0 indicate where weekly Max-NDVI is higher than normal. Anomalies close to 0 indicate where weekly Max-NDVI is similar to normal.

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    Each pixel value corresponds to the actual number (count) of valid Best-quality Max-NDVI values used to calculate the mean weekly values for that pixel. Since 2020, the maximum number of possible observations used to create the Mean Best-Quality Max-NDVI for the 2000-2014 period is n=20. However, because data quality varies both temporally and geographically (e.g. cloud cover and snow cover in spring; cloud near large water bodies all year), the actual number (count) of observations used to create baselines can vary significantly for any given week and year.