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We have found 4,181 datasets for the keyword " service de co-emballage". You can continue exploring the search results in the list below.
Datasets: 106,102
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4,181 Datasets, Page 1 of 419
Manitoba Co-Packer Services App
Web app showing locations of co-packer services in Manitoba.This web application shows the locations of co-packer services in Manitoba. A contract manufacturer or co-packer is a company that manufactures and/or packages food for other companies to sell. This list is not inclusive nor an endorsement for services. For more information, visit Manitoba Agriculture. This app uses the Manitoba Co-Packer Services feature layer and the Manitoba Co-Packer Services Map.
Manitoba Co Packer Services
Feature point layer showing locations of co-packer services in Manitoba.null
Manitoba Co-Packer Services Map
Map showing locations of co-packer services in Manitoba.This map shows the locations of co-packer services in Manitoba. A contract manufacturer or co-packer is a company that manufactures and/or packages food for other companies to sell. This list is not inclusive nor an endorsement for services. For more information, visit Manitoba Agriculture. This map uses the feature layer Manitoba Co-Packer Services and forms part of the Manitoba Co-Packer Services App.
Planning Map for Public EV Charging Infrastructure
The Zero Emission Vehicle Infrastructure Program (ZEVIP) aims at addressing the lack of charging infrastructure in Canada, one of the key barriers to zero emission vehicle adoption by increasing the availability of localized charging where Canadians live, work, travel and play. This Planning Map for Public EV Charging Infrastructure identifies priority areas and accounts for available charging infrastructure and expected charging needs with a focus on public corridor charging. To optimize web performance when using the map, it is recommended you zoom into the areas you are exploring. Priority areas are identified on a scale ranging from lowest to highest priority. Public Corridor Charging includes the EV charging needs of those travelling longer distances on highways and major roads. The objective is to ensure that EV drivers can travel over the majority of Canada’s road network connecting most communities in an EV without being limited on vehicle range. The map identifies priority locations within 1.6 kilometres of major roads based on criteria such as, traffic, expected EV adoption and distance between chargers
Vessel Density Mapping of 2016 AIS Data in the Northwest Atlantic
The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.
Natural Gas Processing Plants - North American Cooperation on Energy Information
Facilities designed to recover natural gas liquids from a stream of natural gas. These facilities control the quality of the natural gas to be marketed.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.Parent Collection:[North American Cooperation on Energy Information, Mapping Data](https://open.canada.ca/data/en/dataset/aae6619f-f9f3-435d-bc32-42decd58b674)
American shad breeding areas in the fluvial section and Estuary of St. Lawrence
Layer that includes the known information on the american shad breeding areas in the St. Lawrence River and Estuary according to a literature review of documents produced between 1976 and 1997.Additional InformationAmerican shad's breeding areas were produced according to a literature review of the following documents:Blais, J.-P. et V. Legendre. 1976. La ouananiche, Salmo salar, du lac Tremblant, Québec. Québec, Ministère du Loisir, de la Chasse et de la Pêche, Direction régionale de Montréal, Rapp. tech. 06-11, 116 p.Boulet, M., J. Leclerc et P. Dumont. 1995. Programme triennal d'étude sur le suceur cuivré. Québec, Ministère de l'Environnement et de la Faune, Service de l'aménagement et de l'exploitation de la faune, Montréal, Rapp. d'étape, 61 p.Boulet, M., Y. Chagnon et J. Leclerc. 1996. Recherche et caractérisation des aires de fraye des suceurs cuivré et ballot au bief d'aval du barrage de Saint-Ours (rivière Richelieu) en 1992. Québec, Ministère de l'Environnement et de la Faune, Service de l'aménagement et de l'exploitation de la faune, Longueuil, Rapp. trav. 06-38, xi + 37 p.Dumont, P. et R. Fortin. 1977. Relations entre les niveaux d'eau printaniers et la reproduction du Grand Brochet du Haut-Richelieu et de la baie Missisquoi. Université du Québec à Montréal, Département des sciences biologiques, pour le Bureau international Champlain Richelieu, Comité d'impact sur l'environnement, x + 108 p.Dumont, P. et S. Desjardins. 1989. Lettre adressée à M. André Poulin du Département de géographie, Université de Sherbrooke, au sujet de la faune et les habitats de la portion aval de la rivière aux Brochets. Québec, Ministère du Loisir, de la Chasse et de la Pêche, Direction régionale de Montréal. Dumont, P., J. Leclerc et L. Bouthillier. 1989a. Données d'inventaire, baie Brazeau, rivière des Outaouais, été 1989. Québec, Ministère du Loisir, de la Chasse et de la Pêche, Service de l'aménagement et de l'exploitation de la faune, Montréal. [Données non publiées].Environnement Illimité inc. 1994. Centrale Les Cèdres - Nouvel aménagement. Avant-projet phase 2, études environnementales. Description du milieu biologique. Volumes 1 et 2. Rapport préparé pour la Vice-Présidence Environnement Hydro-Québec, Service production, réfection et localisation, 241 p. + annexes.Fournier, P. et L.-M. Soyez. 1988. Étude de l'utilisation faunique printanière du marais de Rosemère. Québec, Ministre du Loisir, de la Chasse et de la Pêche, Service de l'aménagement et de l'exploitation de la faune, Montréal, 13 p.Gagnon, M., Y. Ménard et J.-F. La Rue. 1993. Caractérisation et évaluation des habitats du poisson dans la zone de transition saline du Saint-Laurent. Rapp. tech. can. sci. halieut. aquat. 1920: viii + 104 p.Gendron, M. 1986. Rivière-des-Prairies. Aménagement d'un haut-fond, printemps 1986. Groupe de recherche SEEEQ ltée pour la Direction Environnement d'Hydro-Québec, 103 p.Gendron, M. 1987. Rivière-des-Prairies. Suivi de l'aménagement d'un haut-fond, printemps 1987. Le Groupe de recherche SEEEQ ltée pour la Direction Environnement d'Hydro-Québec, 60 p.Gendron, M. 1988. Rivière-des-Prairies. Suivi de l'aménagement du haut-fond, synthèse 1982-1988. Le Groupe de recherche SEEEQ ltée pour le Service de recherche en environnement et santé publique, Vice-Présidence Environnement, Hydro-Québec, 95 p.Guay, G. et M. Couillard. 1985. Étude de l'utilisation printannière et autonmale des rapides de Lachine par les poissons. Environnement Illimité inc. pour le Secrétariat Archipel, 167 pages + annexes.Laramée, P. 1983. La vie printanière dans les rapides de Lachine : Reproduction des poissons. Éco-Recherches inc. pour Vice-Présidence Environnement Hydro-Québec et le Secrétariat Archipel, 30 p. + 7 annexes. Leclerc, J. 1983. La montaison de l'Alose savoureuse dans la rivière des Mille Iles en 1983. Rapport réalisé par Bio-Conseil inc. pour le compte du Service des études hydrauliques et écologiques, Ministère de l'Environnement du Québec, 45 p.Letendre, M., B. Dumas et M. Beaudoin. 1990. Inventaire de la rivière des Prairies, au niveau de l'île de Pierre. Québec, Ministère du Loisir de la Chasse et de la Pêche, Service de l'aménagement et de l'exploitation de la faune, Montréal. [Travaux en cours].Provost, J., L. Verret et P. Dumont. 1984. L'Alose savoureuse au Québec : synthèse des connaissances biologiques et perspectives d'aménagement d'habitats. Canada, Ministère des Pêches et Océans, Direction de la recherche sur les pêches, Laboratoire de Québec, Rapport manuscrit canadien des sciences halieutiques et aquatiques no 1793, xi + 114 p.Thérrien, J., H. Marquis, G Shooner et P. Bérubé.1991. Caractérisation des habitats recherchés pour la fraie des principales espèces de poisson du fleuve Saint-Laurent (Cornwall à Montmagny). Étude réalisée pas le Groupe Environnement Shooner inc. Pour le compte du Ministère des Pêches et des Océans du Canada. 16 p.
Recreational Vessel Traffic Model for British Columbia
Description:Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC.The files included here are:--A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC).--Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code.Methods:Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record.References:Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765Data Sources:Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12)Uncertainties:Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.
Vessel Density Mapping of 2024 Automatic Identification System (AIS) Data in the Northwest Atlantic
The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.
Vessel Density Mapping of 2022 AIS Data in the Northwest Atlantic
The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.
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