City-owned industrial lands, also known as employment lands, play a vital role in local economic development and job creation. The City of Kingston ensures the availability of shovel-ready industrial land for immediate development and secures land for future growth. City-owned industrial lands are located in four well-planned and fully-serviced business parks that have state-of-the-art infrastructure. These lands are zoned to allow a variety of businesses ranging from general and prestige industrial uses to limited commercial and service-related uses. A wide selection of parcels of various sizes is available.This story map guides users through the City's four business and industrial parks, highlighting available lots and providing details and sketches for each. For contact information, see the Kingston Economic Development Corporation's Business Parks page.

This map shows how commercial activity is distributed within urban areas and the impact of commercial services on the urban landscape, by mapping what proportion of stores (hence jobs) in an urban area that are found in industrial zones. Industrial zones are extensive areas zoned for industrial use that nowadays are home to wholesalers, big-box retailers and a variety of services and small office buildings. These are specialized destinations, often oriented to other businesses; not the kinds of places you stumble upon by accident. As the most recent form of commercial concentration, they are most often found in rapidly growing cities, especially the largest cities. Since industrial zones support a wide range of specialized activities they usually benefit from commercial specialization as indicated by the index of centrality. The distribution indicates that cities in Ontario and the Prairies have higher values than cities in Quebec, the Atlantic region and British Columbia.

This map shows the 53 generating stations that were operated by companies of the mining or energy industries. The stations are often relatively large - the largest has a capacity of 912 000 kilowatts.

The 54 plants are operated by a wide variety of industries. Plants run by these industries tend to be fairly small (the largest is 38 000 kilowatts). They also tend to be found in cities. By type, these plants are a mix of hydro and thermal stations. The hydro plants tend to be older installations located in Eastern Canada.

A set of three estimates of land-cover types and annual transformations of land use are provided on a global 0.5 x0.5 degree lat/lon grid at annual time steps. The longest of the three estimates spans 1770-2010. The dataset presented here takes into account land-cover change due to four major land-use/management activities: (1) cropland expansion and abandonment, (2) pastureland expansion and abandonment, (3) urbanization, and (4) secondary forest regrowth due to wood harvest. Due to uncertainties associated with estimating historical agricultural (crops and pastures) land use, the study uses three widely accepted global reconstruction of cropland and pastureland in combination with common wood harvest and urban land data set to provide three distinct estimates of historical land-cover change and underlying land-use conversions. Hence, these distinct historical reconstructions offer a wide range of plausible regional estimates of uncertainty and extent to which different ecosystem have undergone changes. The three estimates use a consistent methodology, and start with a common land-cover map during pre-industrial conditions (year 1765), taking different courses as determined by the land-use/management datasets (cropland, pastureland, urbanization and wood harvest) to attain forest area distributions close to satellite estimates of forests for contemporary period. The satellite based estimates of forest area are based on MODIS sensor. All data uses the WGS84 spatial coordinate system for mapping.

This detail map supports the City-Owned Industrial Lands story map, and shows features such as available lots. City-owned industrial lands are located in four well-planned and fully-serviced business parks that have state-of-the-art infrastructure. These lands are zoned to allow a variety of businesses ranging from general and prestige industrial uses to limited commercial and service-related uses. A wide selection of parcels of various sizes is available. For contact information, see the Kingston Economic Development Corporation's Business Parks page.

Solar Footprints in California

This GIS dataset consists of polygons that represent the footprints of solar powered electric generation facilities and related infrastructure in California called Solar Footprints. The location of solar footprints was identified using other existing solar footprint datasets from various sources along with imagery interpretation. CEC staff reviewed footprints identified with imagery and digitized polygons to match the visual extent of each facility. Previous datasets of existing solar footprints used to locate solar facilities include:

GIS Layers: (1) California Solar Footprints, (2) UC Berkeley Solar Points, (3) Kruitwagen et al. 2021, (4) BLM Renewable Project Facilities, (5) Quarterly Fuel and Energy Report (QFER)

Imagery Datasets: Esri World Imagery, USGS National Agriculture Imagery Program (NAIP), 2020 SENTINEL 2 Satellite Imagery, 2023

Solar facilities with large footprints such as parking lot solar, large rooftop solar, and ground solar were included in the solar footprint dataset. Small scale solar (approximately less than 0.5 acre) and residential footprints were not included. No other data was used in the production of these shapes. Definitions for the solar facilities identified via imagery are subjective and described as follows:

Rooftop Solar: Solar arrays located on rooftops of large buildings.

Parking lot Solar: Solar panels on parking lots roughly larger than 1 acre, or clusters of solar panels in adjacent parking lots.

Ground Solar: Solar panels located on ground roughly larger than 1 acre, or large clusters of smaller scale footprints.

Once all footprints identified by the above criteria were digitized for all California counties, the features were visually classified into ground, parking and rooftop categories. The features were also classified into rural and urban types using the 42 U.S. Code § 1490 definition for rural. In addition, the distance to the closest substation and the percentile category of this distance (e.g. 0-25th percentile, 25th-50th percentile) was also calculated. The coverage provided by this data set should not be assumed to be a complete accounting of solar footprints in California. Rather, this dataset represents an attempt to improve upon existing solar feature datasets and to update the inventory of "large" solar footprints via imagery, especially in recent years since previous datasets were published.

This procedure produced a total solar project footprint of 150,250 acres. Attempts to classify these footprints and isolate the large utility-scale projects from the smaller rooftop solar projects identified in the data set is difficult. The data was gathered based on imagery, and project information that could link multiple adjacent solar footprints under one larger project is not known. However, partitioning all solar footprints that are at least partly outside of the techno-economic exclusions and greater than 7 acres yields a total footprint size of 133,493 acres. These can be approximated as utility-scale footprints.

Metadata: (1) CBI Solar Footprints

Abstract: Conservation Biology Institute (CBI) created this dataset of solar footprints in California after it was found that no such dataset was publicly available at the time (Dec 2015-Jan 2016). This dataset is used to help identify where current ground based, mostly utility scale, solar facilities are being constructed and will be used in a larger landscape intactness model to help guide future development of renewable energy projects. The process of digitizing these footprints first began by utilizing an excel file from the California Energy Commission with lat/long coordinates of some of the older and bigger locations. After projecting those points and locating the facilities utilizing NAIP 2014 imagery, the developed area around each facility was digitized. While interpreting imagery, there were some instances where a fenced perimeter was clearly seen and was slightly larger than the actual footprint. For those cases the footprint followed the fenced perimeter since it limits wildlife movement through the area. In other instances, it was clear that the top soil had been scraped of any vegetation, even outside of the primary facility footprint. These footprints included the areas that were scraped within the fencing since, especially in desert systems, it has been near permanently altered. Other sources that guided the search for solar facilities included the Energy Justice Map, developed by the Energy Justice Network which can be found here:

https://www.energyjustice.net/map/searchobject.php?gsMapsize=large&giCurrentpageiFacilityid;=1&gsTable;=facility&gsSearchtype;=advanced

The Solar Energy Industries Association’s “Project Location Map” which can be found here:

https://www.seia.org/map/majorprojectsmap.php

also assisted in locating newer facilities along with the "Power Plants" shapefile, updated in December 16th, 2015, downloaded from the U.S. Energy Information Administration located here:

https://www.eia.gov/maps/layer_info-m.cfm

There were some facilities that were stumbled upon while searching for others, most of these are smaller scale sites located near farm infrastructure. Other sites were located by contacting counties that had solar developments within the county. Still, others

Mapping of industrial areas on the territory of the City of Longueuil.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

The regional growth strategy (RGS) layer is maintained as the basis for defining land use boundaries. It is generalized into four land use designations within the City of Burnaby, and was created as a part of a larger GVRD RGS dataset.

This map depicts the 77 electrical generating plants operated by forest-based industries. These industries are defined using the North American Industrial Classification. These plants are scattered throughout Canada, and are about equally divided between being hydro or thermal plants.

Output by industry, in current dollars, evaluated at basic price for all provinces and territories. These estimates are derived from the provincial Supply and Use Tables.

This interactive web application shows the locations of commercial fisheries and commercial fish species production (kg) in Manitoba, by community. It names the communities involved in the industry, shows the number of fishers by community and also shows the location of packing sheds across Manitoba. For each location, pop ups provides additional information, including the round weight (kg) by species for the 2016 calendar year. This application is populated by the web map: Manitoba Commercial Fishing Industry Map.

The Ministry of Environment manages a dataset of mining and industrial facilities it regulates. This content will help increase awareness and transparency regarding these activities in the province. These include agricultural processing facilities, mining facilities, power generation facilities, oil and gas processing facilities, and industrial waste management facilities.For further information, please contact the Ministry of Environment Inquiry Centre (Toll Free) 1-800-567-4224, centre.inquiry@gov.sk.ca or visit the link on saskatchewan.ca.Locations are approximate and do not capture the entire facilities footprint.Information on this map is provided as a public service by the Government of Saskatchewan. We cannot guarantee that all information is current and accurate. Users should verify the information before acting on it. The Saskatchewan Government does not assume any responsibility for any damages caused by (mis)use of this map.

This multi-scale map (counties and tracts) shows the predominant industry in 2018. Remember: Industry is the main activity of the employer/business, not the nature of the occupation/job. For example, big construction firms have lawyers, project managers, IT people, etc. who all work in the construction industry. Data come from Esri's Demographics that can be accessed via the Enrich Layer tool.

description: The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the Big Sycamore reserve area was mosaicked from data collected in 1998. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 1998 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was interrupted. In non-differential mode, the receiver provided a position with 30-50 m accuracy. A KVH Industries Inc. azimuth digital gyro-compass provided ship headings with 0.5 degree accuracy. Navigation data were recorded using Yo-Nav version 1.19 (Gann, 1992). The sidescan fish was towed approximately 30 m above the seafloor. The distance of the fish behind the ship was not known during this survey and must be estimated when the data are processed in order to produce the sidescan image mosaics. The resolution of the processed data mosaics is 0.2 m. The data are presented here at a resolution of 1 m. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Nearshore Benthic Habitat Mapping Project. See http://walrus.wr.usgs.gov/nearshorehab for more information.; abstract: The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the Big Sycamore reserve area was mosaicked from data collected in 1998. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 1998 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was interrupted. In non-differential mode, the receiver provided a position with 30-50 m accuracy. A KVH Industries Inc. azimuth digital gyro-compass provided ship headings with 0.5 degree accuracy. Navigation data were recorded using Yo-Nav version 1.19 (Gann, 1992). The sidescan fish was towed approximately 30 m above the seafloor. The distance of the fish behind the ship was not known during this survey and must be estimated when the data are processed in order to produce the sidescan image mosaics. The resolution of the processed data mosaics is 0.2 m. The data are presented here at a resolution of 1 m. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Nearshore Benthic Habitat Mapping Project. See http://walrus.wr.usgs.gov/nearshorehab for more information.

This feature service provides the current Priority Production Areas (PPAs) for the San Francisco Bay Region. PPAs identify clusters of industrial businesses and prioritize them for economic development investments and protection from competing land uses. These districts are already well-served by the region’s goods movement network.Typical businesses in PPAs include manufacturing, distribution, warehousing and supply chains.Jobs in PPAs enable the industrial sector to thrive and grow. They also improve the lives of workers by making the basic costs of living more affordable. Many middle-wage PPA jobs do not require four-year college degrees, and they are close to more-affordable housing.PPAs are nominated by local governments and adopted by the Association of Bay Area Governments. PPAs must be:Zoned for industrial use or have predominantly industrial usesOutside Priority Development Areas and other areas within walking distance of a major rail commute hub (such as BART, Caltrain, Amtrak or SMART)Located in jurisdictions with a certified housing element

description: The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the southern Anacapa Passage area was mosaicked from data collected in 1999 and 2000. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 2000 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was interrupted. In non-differential mode, the receiver provided a position with 30-50 m accuracy. A KVH Industries Inc. azimuth digital gyro-compass provided ship headings with 0.5 degree accuracy. Navigation data were recorded using Yo-Nav (Gann, 1992). The sidescan fish was towed approximately 30 m above the seafloor. The distance of the fish behind the ship was not known during this survey and must be estimated when the data are processed in order to produce the sidescan image mosaics. The resolution of the processed data mosaics is 0.2 m. The data are presented here at a resolution of 1 m. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Nearshore Benthic Habitat Mapping Project. The sidescan data were processed using USGS MIPS sonar processing software (Chavez, 1984). See http://walrus.wr.usgs.gov/nearshorehab for more information about this data set.; abstract: The sidescan sonar image of the nearshore seafloor (0 to 100 m water depths) of the southern Anacapa Passage area was mosaicked from data collected in 1999 and 2000. A Klein 2000 sidescan system was used for geophysical surveying. A Triton Elics Isis brand side-scan data recording system was used on the cruise. The 2000 survey was navigated with a Leica Differential Global Positioning System (DGPS) which provided a ship position with accuracy of 1-5 m in DGPS mode. At times during the cruise differential signal was interrupted. In non-differential mode, the receiver provided a position with 30-50 m accuracy. A KVH Industries Inc. azimuth digital gyro-compass provided ship headings with 0.5 degree accuracy. Navigation data were recorded using Yo-Nav (Gann, 1992). The sidescan fish was towed approximately 30 m above the seafloor. The distance of the fish behind the ship was not known during this survey and must be estimated when the data are processed in order to produce the sidescan image mosaics. The resolution of the processed data mosaics is 0.2 m. The data are presented here at a resolution of 1 m. This is one of a collection of digital files of a geographic information system of spatially referenced data related to the USGS Coastal and Marine Geology Program Nearshore Benthic Habitat Mapping Project. The sidescan data were processed using USGS MIPS sonar processing software (Chavez, 1984). See http://walrus.wr.usgs.gov/nearshorehab for more information about this data set.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows two condensed maps illustrating the distribution of the labour force engaged in manufacturing circa early 1950s. The map has a dot representing every 100 people in the manufacturing labour force, with places of 1000 or more people in manufacturing being shown as proportional circles, instead. There are additional data for the 18 census metropolitan areas. This consists of a pie graph for each of these places showing the breakdown of the manufacturing labour force into each of 16 manufacturing industry types. The total manufacturing labour force in each of the census metropolitan areas is also given.

Contained within the 4th Edition (1974) of the Atlas of Canada are two maps. The first map shows sites of extraction operations, sites of processing plants and mineral types for industrial mineral operations for Eastern Canada in 1970. The second map, whose scale is 1:30 000 000, shows the location and annual capacities for cement plants as a percentage of the total national capacity for cement operations in 1970. Several graphs also accompany and show the value of production of cement by province for 1970, the value of the production of industrial minerals (except structural materials) for 1970, the value of the production of structural materials for 1970 and the volume of selected industrial minerals for the period 1886 to 1970.