Home /Search
Search datasets
We have found 976 datasets for the keyword " radar". You can continue exploring the search results in the list below.
Datasets: 106,031
Contributors: 42
Results
976 Datasets, Page 1 of 98
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.)
Photo radar
Location of photo radars: - Red light monitoring device- Still photo radar- Fixed photo radar and red light surveillance- Mobile photo radar**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
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.
Acquisition plans of the RADARSAT Constellation Mission
The RADARSAT Constellation is the evolution of the RADARSAT Program with the objective of ensuring data continuity, improved operational use of Synthetic Aperture Radar (SAR) and improved system reliability. The three-satellite configuration provides daily revisits of Canada's vast territory and maritime approaches, as well as daily access to 90% of the world's surface.RCM is tasked solely by the Government of Canada, to acquire data, first and foremost in support of Government of Canada services and needs. RCM data and services contributes to ensuring the safety and security of Canadians; monitoring and protecting the environment; monitoring of climate change; managing Canada’s natural resources; and stimulating innovation, research and economic development. In addition to these core user areas, there are expected to be a wide range of ad hoc uses of RADARSAT Constellation data in many different applications within the public and private sectors, both in Canada and internationally. The current data set reflects the acquisition plans that are designed to meet the RCM SAR imaging demands of the Government of Canada. These are being made available publicly in advance of the acquisitions. To meet the data needs of the Government of Canada, acquisitions may be changed without notice. After their acquisition and processing, the RCM image products listed in the current data set, will be delivered to the Earth Observation Data Management System - EODMS (https://www.eodms-sgdot.nrcan-rncan.gc.ca/index-en.html) portal of Natural Resources Canada. Users can register to the EODMS portal as public users to retrieve the RCM image products. For those requiring a greater access to RCM imagery consisting of product types or spatial resolutions not available to public users: you may apply to upgrade your public account to an ‘RCM external vetted entity’ EODMS user type account. For more information on this process, please contact the Canadian Space Agency using the information available at the following link : https://www.asc-csa.gc.ca/eng/satellites/radarsat/access-to-data/how-to-become-a-user.aspPublication frequency :I. Future acquisition plans are published every two weeks for a two-week window that starts two weeks from the publication date. As an example, acquisition plan published on April 1st covers acquisitions from April 14 to 27. The next plan is published on April 14th and covers from April 28 to May 11.II. Past acquisitions plans are published monthly and covers a period of one month from the first to the last day As an example, acquisition plan published on April 1st covers acquisition made between the March 1 and March 31. The next plan covers the month of April.
Canada’s PALSAR-2 L-band dual-polarized radar backscatter summer composite, circa 2020
This data publication contains an optimized mosaic of PALSAR-2 L-band dual-polarized radar backscatter summer composite for the year 2020 across Canada (excluding the Arctic Archipelago). Its primary purpose is to offer the best possible L-band radar summer-like composite mosaic mostly tailored for i) classifying natural treed or shrubby vegetation covers, and ii) estimating their structural attributes, such as height and biomass. ## Methodology:This product is based on the freely available and open dataset of yearly JAXA Global PALSAR-2/PALSAR Mosaics ver. 1 (hereafter JAXA GPM v1). They were generated by the Japanese space agency (JAXA) using PALSAR L-band synthetic aperture radar sensors aboard the Advanced Land Observing Satellites (ALOS): ALOS-2 PALSAR-2 (2015 to 2020) and ALOS PALSAR (2007 to 2010). JAXA GPM v1 provide yearly mosaics orthorectified and slope-corrected L-band HH- and HV-polarized gamma naught (γ°) backscatter amplitude with 25-m pixel size and scaled as 16-bit data (Shimada et al. 2014). JAXA GPM v1 are accessible as a Google Earth Engine image collection at https://developers.google.com/earth-engine/datasets/catalog/JAXA_ALOS_PALSAR_YEARLY_SAR.The yearly 2007 to 2020 JAXA GPM v1 dataset across Canada underwent a post-processing and compositing methodology implemented in Google Earth Engine, as detailed in Pontone et al. 2024 and summarized in a pdf “Readme” file provided with the dataset. In summary, the method involves these three steps: 1. Post-processing of yearly γ° HH and HV datasets: handling data gaps, filtering speckle noise, and generating two radar vegetation indices, the HV/HH ratio (HVHH) and the radar forest degradation index (RFDI).2. Temporal compositing from 2015 to 2020 of post-processed yearly γ° PALSAR-2 HH, HV, HVHH, and RFDI backscatter data aimed to i) address data gaps and ii) mitigate detrimental backscatter fluctuations across ALOS-2 orbits resulting from numerous out-of-summer acquisitions.3. Generating the final PALSAR-2 L-band γ° radar backscatter summer composite circa 2020 raster files. ## Performance et limitations:The resulting Canada-wide, excluding the Arctic Archipelago, gap-free and radiometrically optimized mosaic of circa 2020 PALSAR-2 L-band backscatter summer composite was found significantly improved compared to the single-year 2020 JAXA GPM v1 mosaic, particularly in northern boreal Canada (Pontone et al. 2024). However, this product should be considered as a summer-like composite and users should be mindful of the following known limitations: • In northwestern Canada, there were often minimal to no summer PALSAR-2 acquisitions, resulting in residual backscatter fluctuations across ALOS-2 orbits.• The composite may exhibit patchy radiometric noise in areas that experienced major disturbances (fires, harvesting) between 2015 and 2020 despite they were accounted for in our compositing methodology.• This product is deemed less performant, or possibly not suitable, for i) characterizing highly dynamic land cover types such as grasslands, croplands, and water bodies, or for ii) estimating soil and/or vegetation moisture content for the year 2020.As a final note, JAXA released an improved GPM ver. 2 that was not available at the time of this study. A preliminary analysis shows that the circa 2020 PALSAR-2 composite product still seems to outperform the 2020 JAXA GPM v2 in northern Canada. ## Additional Information on Dataset: This dataset comprises four raster geotiff files of circa 2020 L-band PALSAR-2 summer temporal composites as mosaics of orthorectified and radiometrically slope corrected dual-polarized HH and HV gamma naught (γ°) backscatter amplitude, along with two radar vegetation indices (HVHH, RFDI), all scaled as 16-bit Digital Number (DN) values with 30-m pixel size in Lambert conformal conic projection. An additional 8-bit RGB quick-view file is also provided. A companion pdf ”Readme” file provides further details about these geotiff files and equations to convert DN values to γ° absolute intensity values. ## Dataset Citation: Beaudoin, A., Villemaire, P., Gignac, C., Tolszczuk, S., Guindon, L., Pontone, N., Millard, C. (2024). Canada’s PALSAR-2 dual-polarized L-band radar summer backscatter composite, circa 2020. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/8ec4ee78-9240-4bd0-9c97-d3a27829e209In addition, please provide credits to the Japanese space agency JAXA with the mention “Original Global PALSAR-2/PALSAR Mosaics v1 provided by JAXA (©JAXA)” ## Publication Reference for Product Development and Use in Wetland Mapping: Pontone, N., Millard, K., Thompson, D., Guindon, L., Beaudoin, A. (2024). A hierarchical, Multi-Sensor Framework for Peatland Sub-Class and Vegetation Mapping Throughout the Canadian Boreal Forest. Remote Sensing for Ecology and Conservation (accepted for publication).## Cited reference: Shimada, M., Itoh, T., Motooka, T., Watanabe, M., Tomohiro, S., Thapa, T., Lucas, R. (2014). New Global Forest/Non-Forest Maps from ALOS PALSAR Data (2007-2010). Remote Sensing of Environment, 155, pp. 13-31. https://doi.org/ 10.1016/j.rse.2014.04.014
NWT Aster DEM
The ASTER instrument that was launched onboard NASA’s Terra spacecraft in December 1999 has an along-track stereoscopic capability using two telescopes in its near infrared spectral band to acquire data from nadir and backward views. Over 1.2 million scenes (level-1A products) acquired between March 2000 and August 2008 were used to generate the ASTER Global DEM (ASTGTM) collection. For more information on the ASTER Global DEM, please see the metadata link.
The Canadian Radiological Monitoring Network – Airborne Radioactivity
This dataset provides the results obtained by Health Canada’s Radiological Monitoring Network (CRMN) for airborne radioactivity content at monitoring stations across Canada. More information about the CRMN network can be found on the Health Canada website (see link below). The results provided are activity concentration, uncertainty and the minimum detectable concentration for the naturally occurring radionuclides, beryllium-7 (7Be) and lead-210 (210Pb), and the anthropogenic (originating from human activity) radionuclides, cesium-134 (134Cs), cesium-137 (137Cs), and iodine-131 (131I). The data comes from the analysis of particulates accumulated in filter media, drawn by high-volume air samplers fixed in the field. Such data is typically dominated by natural radionuclides, such as 7Be and 210Pb. 7Be is a natural cosmogenic radionuclide that is produced in the upper atmosphere when cosmic rays bombard oxygen and nitrogen. 210Pb is also a natural radioisotope that results from the decay of uranium (238U) to radium (226Ra). 238U comes from the soil and eventually decays to 210Pb. Radon-222, which is a natural radioactive gas, is also a part of this decay chain. Radon moves through the soil and becomes diluted in the atmosphere. If a home is built on soil or rocks that contain uranium, radon can seep into homes and may accumulate to high levels. More information about the Health Canada radon program can be found on the Health Canada website. For all our stations, the airborne radioactivity data shows a small increase in the activity concentration of 134Cs, 137Cs and 131I measured between March and May of 2011, attributable to the nuclear accident at the Fukushima-Daiichi Nuclear Power Station. It is important to note that, even at their respective peaks, the measured activity concentrations of 134Cs, 137Cs and 131I represent only a small fraction of typical background exposure from natural sources of radiation. Occasionally, other small increases in activity concentration of anthropogenic radionuclides are observed. Spikes in 137Cs activity are often associated with forest fires, which can lead to the re-suspension of 137Cs already present in the environment, most likely from atmospheric nuclear weapons testing in the 1960’s. Detection of small amounts of 131I is commonly associated with its medical use by hospitals.The map shows the approximate sampling location for each monitoring station. Stations are found within the associated location range.
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and topics that matter to you.
Please send us your feedback