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We have found 1,005 datasets for the keyword "radar coverage". You can continue exploring the search results in the list below.
Datasets: 100,679
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1,005 Datasets, Page 1 of 101
Dynamic Radar Composite Coverage
Radar coverage is provided to dynamically display the zones covered by the radars every 6 minutes, and to provide information on the availability (or not) of the contributing radars as well as on the areas of overlap.
North American Radar Composite (1 km)
This mosaic is calculated over the North American domain with a horizontal spatial resolution of 1 km. This mosaic therefore includes all the Canadian and American radars available in the network and which can reach a maximum of 180 contributing radars. To better represent precipitation over the different seasons, this mosaic renders in mm/h to represent rain and in cm/h to represent snow. For the two precipitation types (rain and snow), we use two different mathematical relationships to convert the reflectivity by rainfall rates (mm/h rain cm/h for snow). This is a hybrid mosaic from DPQPE (Dual-Pol Quantitative Precipitation Estimation) for S-Band radars. For the US Nexrad radars, ECCC uses the most similar product from the US Meteorological Service (NOAA). This product displays radar reflectivity converted into precipitation rates, using the same formulas as the Canadian radars.
RADARSAT Constellation Mission National Land Mosaic
The Canada Centre for Mapping and Earth Observation (CCMEO) has created a 30m resolution radar mosaic of Canada's landmass from the RADARSAT Constellation Mission (RCM). This product highlights different types of radar interaction with the surface, which can assist the interpretation and study of land cover on a national scale. The national mosaic is made up of 3222 RCM images acquired between August 2023 and February 2024. (Credit: RADARSAT Constellation Mission imagery © Government of Canada [2024]. RADARSAT is an official mark of the CSA.)
Ontario radar digital surface model
The Ontario Radar Digital Surface Model (DSM) has the following features: * source data: 1 arc second spaceborne C-Band Interferometric Synthetic Aperture Radar (IFSAR) data * Ministry of Natural Resources (MNR) Lambert Conformal Conic Projection * vertical datum in both EGM96 and CGVD28, separately * elevation value: floating * local Polynomial Interpolation from vector elevation points * spatial resolution: 30 meter * asurface elevation model This product offers significant advancements in elevation data in the province. [Read the details about these advancements and other technical specifications,](https://geohub.lio.gov.on.ca/maps/mnrf::ontario-radar-digital-surface-model/) including data processing, major spatial characteristics of the Radar DSM, and the steps to generate the Northern Ontario Radar DSM.
Weather Radar - 24 Hour Accumulation
This product shows the rain accumulation, in mm, over the last 24 hour period based on DPQPE. This product is available every 6 minutes.
Surface precipitation type product (SPTP)
This product is a 1km resolution composite over the North American domain, which, for areas with radar coverage, can distinguish the occurrence, type and intensity of precipitation. This product uses two 1km radar composites as input: a North American composite cleaned using dual polarization technology, another particle classification radar composite (precipitation) and surface temperature from the High Resolution Deterministic Prediction System (HRDPS). The SPTP product is produced every 6 minutes.
Collection - Radarsat Constellation Mission Analysis Ready Data Canada Land Mosaic
The three-satellite RADARSAT Constellation Mission (RCM) acquires synthetic aperture radar data of the Earth's surface. Canadian lands and waters are tracked daily. The standardized RCM acquisition plan uses ScanSAR 30m beams with a compact polarimetric configuration and enables bimonthly monitoring of Canadian land cover. The Canada Centre for Remote Sensing (CCRS) has created a 30m resolution land cover map of Canada, representing the decomposition of information from the data collected according to the type of interaction of the radar wave with the earth's surface. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
MASC Risk Areas/MASC Risk Regions
This file outlines the boundaries of the 15 risk areas defined by Manitoba Agricultural Services Corporation./This file describes the boundaries of the 15 risk areas defined by the Manitoba Agricultural Services Corporation.This file outlines the boundaries of the 15 risk areas defined by Manitoba Agricultural Services Corporation. Manitoba Agricultural Services Corporation (MASC) divides Manitoba into 15 Risk Areas of similar crop production risks, which are used to determine the premiums a producer country and the coverage that crops receive. For more information, visit MASC's website: https://www.masc.mb.ca/masc.nsf/maps_risk_areas.html This file describes the boundaries of the 15 at-risk areas defined by the Manitoba Agricultural Services Corporation. The Manitoba Agricultural Services Corporation divides Manitoba into 15 high-risk regions where crop production risks are similar. They are used to determine the premium the producer pays and the coverage the crops receive. For more information, visit the Manitoba Agricultural Services Corporation website: https://www.masc.mb.ca/masc_fr.nsf/maps_risk_areas.html**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Chlorophyll-a concentration at the Atlantic Zone Monitoring Program (AZMP)-Quebec’s stations
Chlorophyll-a (mg/m2) time series at the 3 fixed stations and 46 stations, grouped into transects, of the Atlantic Zonal Monitoring Program (AZMP) under the Quebec region responsibility.The mean integrated chlorophyll-a data (0-100 m) of the last ten years are displayed as 2 layers, one for the June survey (2013-2022. 2020 not sampled), another for the autumn survey (2013-2022). A third layer shows the positions of the fixed stations of the program (Anticosti Gyre, Gaspé Current and Rimouski).Each station is linked with a .png file showing the chlorophyll-a time series and with a .csv file containing all the integrated chlorophyll-a data acquired at those stations since the beginning of the program sampling (columns : Station, Latitude, Longitude, Date(UTC), Sounding(m), Depth_min/Profondeur_min(m), Depth_max/Profondeur_max(m), Integrated_chlorophyll-a/Chlorophylle-a_intégrée(mg/m²)).PurposeThe Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment.The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties.In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period.Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp.Supplemental InformationWater sampling for chlorophyll-a analysis (Welschmeyer 1994 method) is done from Niskin bottles according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.
Monthly Fraction of Vegetation Cover of Canada from Medium Resolution Satellite Imagery
FCOVER corresponds to the amount of the ground surface that is covered by vegetation, including the understory, when viewed vertically (from nadir). FCOVER is an indicator of the spatial extent of vegetation independent of land cover class. It is a dimensionless quantity that varies from 0 to 1, and as an intrinsic property of the canopy, is not dependent on satellite observation conditions. This product consists of a national scale coverage (Canada) of monthly maps of FCOVER indicator during a growing season (May-June-July-August-September) at 20m resolution.References:L. Brown, R. Fernandes, N. Djamai, C. Meier, N. Gobron, H. Morris, C. Canisius, G. Bai, C. Lerebourg, C. Lanconelli, M. Clerici, J. Dash. Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States IISPRS J. Photogramm. Remote Sens., 175 (2021), pp. 71-87, https://doi.org/10.1016/j.isprsjprs.2021.02.020. https://www.sciencedirect.com/science/article/pii/S0924271621000617Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun, 2023.Validation of Simplified Level 2 Prototype Processor Sentinel-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over North American forests,Remote Sensing of Environment, Volume 293, https://doi.org/10.1016/j.rse.2023.113600.https://www.sciencedirect.com/science/article/pii/S0034425723001517
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