Náttúrulegt birkilendi á Íslandi er kortlagning yfir alla náttúrulega birkiskóga og birkikjarr á Íslandi. Helstu upplýsingar eru hæð, þekja og aldur. Skilið er á milli núverandi hæðar og aldur fullvaxta birkis. Það er gert samkvæmt alþjóðlegum skilgreiningum um hæð trjágróðurs þar sem miðað er við hæð fullvaxta skógar. Birki var fyrst kortlagt á árunum 1972-1975 og var unnin leiðrétting á gögnunum og gerðar frekari greiningar á árunum 1987-1991. Gögnin voru því komin nokkuð til ára sinna þegar ákveðið var að hefja endurkortlagningu á öllu náttúrulegu birki á Íslandi. Fór sú vinna fram á árunum 2010-2014 og er núverandi þekja því afrakstur þeirrar vinnu. Flatarmál náttúrulegs birkis á Íslandi er 150.600 ha. Frá árinu 1987 hefur flatarmál birkis með sjálfsáningu aukist um 9% og nemur 13.000 ha. Gögnin voru upphaflega hugsuð fyrir mælikvarða 1:15.000, hins vegar var talsvert stór hluti landsins kortlagður í mælikvarða 1:5000 – 1:10.000.

The National Ecological Framework for Canada's "Surficial Geology by Ecodistrict” dataset contains tables that provide surficial geology information with the ecodistrict framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

**NOTE** This dataset is going to be replaced by the Data Catalogue layer: [Forest Inventory Ground Plots - Public Access](https://catalogue.data.gov.bc.ca/dataset/6d6d115f-4cc2-4141-909e-3344b3a72bcf) This new layer links to the updated database for all Forest Analysis and Inventory Branch ground sample plots. Growth and Yield dataset is a provincial data set that comprised of Permanent Sample Plots (PSP). Researchers such as GY modellers and those wanting to know the position of all samples will use the all status view to better understand the spatial distribution of historic measurement data including samples that are currently destroyed or inactive

Fish holding areas (i.e. areas of concentration of salmon and herring, both adult and juvenile) in coastal British Columbia. Attribute information includes overall relative importance, species of salmon and other fish observed at various times throughout the year as well as information on spawning activity and larvae. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

The National Ecological Framework for Canada's "Surficial Geology by Ecozone” dataset contains tables that provide surficial geology information with the ecozone framework polygons. It provides codes that characterize surficial geology (unconsolidated geologic materials) and their English and French-language descriptions as well as information about the area and percentage of the polygon that the material occupies.

The National Ecological Framework for Canada's "Total Land and Water Area by Ecozone” dataset provides land and water area values for ecozone framework polygons, in hectares. It includes attributes for a polygon’s total area, land-only area and large water body area.

A list of the various 'regional' (zone/subzone/variant/phase) ecological units of the current biogeoclimatic ecosystem classification. At this 'regional' level, vegetation, soils and topography are used to infer the climate and to identify geographic areas that have relatively uniform climate. These geographic areas are termed biogeoclimatic units. The basic biogeoclimatic unit is the Subzone. These units are grouped into Zones and may be further subdivided into variants based on further refinements of climate (e.g., wetter, drier, snowier). The map units of the Biogeoclimatic map are mapped to the highest possible thematic resolution - subzone or variant. In some cases, where further sampling is required to define the unit climatically, polygons are labelled as an undifferentiated unit (e.g. CWH un)

Eelgrass (Zostera marina) is important to waterfowl such as Atlantic Brant (Branta bernicla hrota), Canada Goose (Branta canadensis), American Black Duck (Anas rubripes), Common Goldeneye (Bucephala clangula) and Barrow's Goldeneye (Bucephala islandica). In New Brunswick eelgrass can be found along the Gulf of St. Lawrence, in protected harbours. Within this dataset are the results of eelgrass land-cover classifications using either satellite or aerial photography for seven harbours: Bouctouche (46 30’N, 64 39’W); Miscou (47.90 N, -64.55 W); Neguac (47.25 N, -65.03 W); Richibucto (46.70 N, -64.80 W); Saint-Simon (47.77 N, -64.76 W); Tracadie (47.55 N, -64.88 W); and Cocagne (46.370 N, -64.600 W). Information on each dataset is provided: 1. Bouctouche This dataset contains results from an eelgrass classification for Bouctouche Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 688 sites. Two-thirds of these sites were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 83.7% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 187 sites that were within the classification area, 131 were correct, 51 were "one-off", and 5 were incorrect [(131 + (51/2))/ 187 = 0.837]. 2. Miscou True colour aerial photography at 57 centimetre resolution was collected on August 20th and 24th, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 103 sites. From these sites 70% were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 96.7% of the time (30/31 = 0.967). 3. Neguac This dataset contains results from an eelgrass classification for Neguac Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 126 sites. Two-thirds of these sites were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 81% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 39 sites that were within the classification area, 27 were correct, 9 were "one-off", and 3 were incorrect [(27 + (9/2))/ 39 = 0.81]. 4. Richibucto Eelgrass classification in Richibucto Harbour, New Brunswick. Derived from a Quickbird satellite image collected on August 28, 2007 at as close to low-tide as possible. Quickbird's ground resolution is 2.4 m. Classification was objected-oriented using Definiens software. Accuracy was 81.5%. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence. 5. Saint-Simon An eelgrass distribution map was classified from remotely sensed imagery in Shippagan Harbour, New Brunswick. Derived from a Quickbird satellite image collected on July 27, 2007 at as close to low-tide as possible. Classification was objected-oriented using Definiens software. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence. 6. Tracadie This dataset contains results from an eelgrass classification for Tracadie Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 101 sites. Approximately two-thirds of these sites were used to assist in image classification, while the remainder was used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 79.3% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 29 sites that were within the classification area, 18 were correct, 10 were "one-off", and 1 was incorrect [(18 + (10/2))/ 29 = 0.793]. 7. Cocagne Visible orthorectified aerial photography was used to classify polygons containing eelgrass in Cocagne Harbour. Field data for image training and validation were collected along transects in summer 2008 using a dGPS positioned towfish holding sidescan sonar and a video camera that was later transcribed as XY geographic points to describe eelgrass presence and a qualitative description of density. The area was flown for photography on September 24, 2008. eCognition Developer 8 software was used to segment the imagery, essentially polygons. Polygons were then classified manually for the presence of eelgrass. Using field data revealed eelgrass presence to be mapped correctly 87.2% of the time.

The documented occurrence data package contains 3 datasets that, in combination, help to provide generalized information about woodland caribou locations and survey areas in Saskatchewan. This information may assist users in their efforts to avoid or mitigate impacts to woodland caribou when operating in woodland caribou range. Generalized locations of caribou use have been provided to better reflect their large home ranges. Absence of a hexagon in an area should not be interpreted as absence of woodland caribou. Please read the Data Guide for important information about this product. Download survey boundaries, telemetry occurrence, and sightings/sign. Download the full package, including data guide here. The Woodland Caribou Documented Occurrence public data product is composed of three shapefiles/feature classes: 1. Woodland Caribou Occurrence - Sighting and Sign 2. Woodland Caribou Occurrence - Telemetry 3. Woodland Caribou Survey Boundaries The two occurrence datasets contain a grid of 18 sq km hexagons (tessellation). The inclusion of a hexagon in the dataset indicates that one or more animal sightings or sign, or telemetry points have been documented in that area. Importantly, lack of caribou occurrence (e.g. no hexagon) should not be interpreted as absence of woodland caribou. Rather, data may not have been collected in these areas or incidental or other observations have not been received.   The survey boundaries dataset displays the boundaries of woodland caribou surveys that were completed by or in collaboration with the Ministry of Environment from 2005 to 2024. Boundaries are from multiple sources, and include various types of surveys (fecal pellet collection or telemetry). These boundaries provide context when viewed alongside the woodland caribou occurrence datasets. We expect to see more occurrence locations in areas that have been surveyed. This information may provide context to areas with a seemingly higher number of occurrences.  For a full description of the data, please refer to the Data Guide document available for download on the Saskatchewan GeoHub.

Ecodivisions are areas of broad climatic and physiographic uniformity, defined at the continental level.