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Found 10 records similar to Weekly Best-Quality Maximum - NDVI Anomalies

Federal

Each pixel value corresponds to the mean historical “Best-quality” Max-NDVI value for a given week, as calculated from the previous 20 years in the MODIS historical record (i.e. does not include data from the current year). These data are also often referred to as “weekly baselines” or “weekly normals”.

Last Updated: Jul. 19, 2021
Date Published: Nov. 1, 2012
Organization: Agriculture and Agri-Food Canada
Formats: PDF GeoTIF
Keywords:  Crops, Climate, Agriculture, Remote sensing
Federal

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

Last Updated: Jul. 19, 2021
Date Published: Nov. 1, 2012
Organization: Agriculture and Agri-Food Canada
Formats: PDF GeoTIF
Keywords:  Climate, Crops, Agriculture, Remote sensing
Federal

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.

Last Updated: Jul. 19, 2021
Date Published: Nov. 1, 2012
Organization: Agriculture and Agri-Food Canada
Formats: PDF GeoTIF
Keywords:  Agriculture, Crops, Climate, Remote sensing
Federal

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.

Last Updated: Jul. 19, 2021
Date Published: Nov. 1, 2012
Organization: Agriculture and Agri-Food Canada
Formats: PDF GeoTIF
Keywords:  Climate, Crops, Agriculture, Remote sensing
Federal

The Crop Condition Assessment Program (CCAP) is developed and maintained by the Remote Sensing and Geospatial Analysis Section (RSGA) within the Agriculture Division. The CCAP combines remote sensing, GIS, and the Internet to provide reliable, objective, and timely information on crop and pasture/rangeland conditions using a mapping application for the whole Canadian agricultural area and the northern portion of the United States. Since the 2010 growing season, the CCAP has been enhanced with the integration of MODerate-resolution Imaging Spectoradiometer (MODIS) data (250-meter resolution). This detector captures two spectral bands (red and infrared) that have proven to be extremely useful for vegetation monitoring to produce the Normalized Difference Vegetation Index (NDVI).

Last Updated: Jan. 11, 2023
Date Published: Feb. 1, 2019
Organization: Statistics Canada
Formats: HTML XLS ZIP
Keywords:  Agriculture, Satellite images, MODIS, NDVI, growing season, Resolution, CCAP, Plants, Agricultural assistance
Federal

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).

Last Updated: Jul. 19, 2021
Date Published: Nov. 1, 2012
Organization: Agriculture and Agri-Food Canada
Formats: PDF GeoTIF
Keywords:  Agriculture, Crops, Climate, Remote sensing
Federal

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.

Last Updated: Nov. 24, 2022
Date Published: Mar. 6, 2015
Organization: Agriculture and Agri-Food Canada
Formats: WMS PDF HTML GeoTIF ESRI REST
Keywords:  Drainage, Satellites, Water, Soil quality, Soil, Hydrology, Remote sensing
Federal

The dataset includes two data products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) imager operated by the US National Oceanic and Atmospheric Administration (NOAA) onboard Suomi National Polar-Orbiting Partnership (SNPP) satellite:

1) Normalized Difference Vegetation Index (NDVI)

2) Snow Mask (Snow) with supplementary information about data quality and scene identification

Each product, NDVI and Snow, has been derived at two spatial resolutions:

1) I-band resolution for 250-m spatial grid (VIIRS image bands I1 and I2)

2) M-band resolution for 500-m spatial grid (VIIRS moderate resolution bands M5 and M7)

Datasets are produced with a daily temporal frequency, i.e. one file per day. The study area with the size of 5,700 km × 4,800 km covers Canada and neighboring regions (Trishchenko, 2019). The VIIRS time series are produced from VIIRS /SNPP imagery at CCRS from January 1, 2017.

Last Updated: Nov. 1, 2022
Date Published: Jul. 19, 2022
Organization: Natural Resources Canada
Formats: DOCX GeoTIF
Keywords:  Vegetation, Snow, Normalized Difference Vegetation Index; NDVI, Satellite images, Remote sensing
Federal

The Congenital Anomalies data tool was developed by the Canadian Congenital Anomalies Surveillance System (CCASS) to present prevalence rates, temporal trends and certain factors associated with congenital anomalies in Canada. This resource is a collaborative effort between the Public Health Agency of Canada, the Canadian Perinatal Surveillance System’s External Advisory Committee and the Canadian Congenital Anomalies Surveillance Provincial and Territorial Network.

Last Updated: Jul. 26, 2019
Date Published: Nov. 30, 2017
Organization: Public Health Agency of Canada
Formats: CSV
Keywords:  Congenital Anomalies
Federal

A cross-country summary of the averages and extremes for the month, including precipitation totals, max-min temperatures, and degree days. This data is available from stations that produce daily data.

Last Updated: Sep. 27, 2022
Date Published: Jul. 26, 2022
Organization: Environment and Climate Change Canada
Formats: CSV HTML GEOJSON
Keywords:  Atmosphere, National (CA), Provide Weather Information Products and Services, Deliver Weather Products and Services to Clients, Meteorological Service of Canada, Weather and Environmental Operations, Unclassified, Climate change, Climate
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