All organisations hold information about the core of their business. Forestry England holds information on trees and forests. We use this information to help us run our business and make decisions.

The role of the Forest Inventory (the Sub-compartment Database (SCDB) and the stock maps) is to be our authoritative data source, giving us information for recording, monitoring, analysis and reporting. Through this it supports decision-making on the whole of the FE estate. Information from the Inventory is used by FE, wider government, industry and the public for economic, environmental and social forest-related decision-making.

Furthermore, it supports forest-related national policy development and government initiatives, and helps us meet our national and international forest-related reporting responsibilities. Information on our current forest resource, and the future expansion and availability of wood products from our forests, is vital for planners both in and outside FE. It is used when looking at the development of processing industries, regional infrastructure, the effect upon communities of our actions, and to prepare and monitor government policies. The Inventory (SCDB and stock maps), with ‘Future Forest Structure’ and the ‘rollback’ functionality of Forester, will help provide a definitive measure of trends in extent, structure, composition, health, status, use, and management of all FE land holdings.

We require this to meet national and international commitments, to report on the sustainable management of forests as well as to help us through the process of business and Forest Design Planning. As well as helping with the above, the SCDB helps us address detailed requests from industry, government, non-government organisations and the public for information on our estate. FE's growing national and international responsibilities and the requirements for monitoring and reporting on a range of forest statistics have highlighted the technical challenges we face in providing consistent, national level data. A well kept and managed SCDB and GIS (Geographical Information System - Forester) will provide the best solution for this and assist countries in evidence-based policy making. Looking ahead at international reporting commitments; one example of an area where requirements look set to increase will be reporting on our work to combat climate change and how our estate contributes to carbon sequestration. We have put in place processes to ensure that at least the basics of our inventory are covered:

1. The inventory of forests;
2. The land-uses;
3. The land we own ( Deeds);
4. The roads we manage.

We depend on others to allow us to manage the forests and to provide us with funds and in doing so we need to be seen to be responsible and accountable for our actions. A foundation of achieving this is good record keeping. A subcompartment should be recognisable on the ground. It will be similar enough in land use, species or habitat composition, yield class, age, condition, thinning history etc. to be treated as a single unit. They will generally be contiguous in nature and will not be split by roads, rivers, open space etc. Distinct boundaries are required, and these will often change as crops are felled, thinned, replanted and resurveyed. In some parts of the country foresters used historical and topographical features to delineate subcompartment boundaries, such as hedges, walls and escarpments. In other areas no account of the history and topography of the site was taken, with field boundaries, hedges, walls, streams etc. being subsumed into the sub-compartment. Also, these features may or may not appear on the OS backdrop, again this was dependent on the staff involved and what they felt was relevant to the map. The main point is that, as managers we may find such obvious features in the middle of a subcompartment when nothing is indicated on the stock map, while the same thing would be indicated elsewhere.

Attributes;

FOREST Cost centre Nos. COMPTMENT Compartment Nos. SUBCOMPT Sub-compartment letter BLOCK Block nos. CULTCODE Cultivation Code CULTIVATN Cultivation PRIHABCODE Primary Habitat Code PRIHABITAT Primary Habitat PRILANDUSE Land Use of primary component PRISPECIES Primary component tree species PRI_PLYEAR prim. component year planted PRIPCTAREA Prim. component %Area of sub-compartment SECHABCODE Secondary Habitat Code SECHABITAT Secondary Habitat SECLANDUSE Land Use of secondary component SECSPECIES Secondary component tree species SEC_PLYEAR Secondary component year planted SECPCTAREA Secondary component %Area of sub-compartment TERLANDUSE Land Use of tertiary component TERSPECIES Tertiary component tree species TER_PLYEAR Tertiary component year planted TERPCTAREA Tertiary component %Area of sub-compartment TERHABITAT Tertiary Habitat TERHABCODE Tertiary Habitat Code.

Any maps produced using this data should contain the following Forestry Commission acknowledgement: “Contains, or is based on, information supplied by the Forestry Commission. © Crown copyright and database right 2025 Ordnance Survey AC0000814847”.

Forest resources in Washington and Oregon were surveyed in the 1930s by employees of the USDA Forest Service, Pacific Northwest Forest Experiment Station. As part of this process, forest cover maps were created on paper at an original scale of 1:253,440. Forest and land cover types recorded include classifications such as: agricultural, balsam fir mountain hemlock, cedar-redwood, deforested burns, Douglas-fir, hardwood, juniper, lodgepole pine, non-forest pine mix, ponderosa pine, recent cutover, spruce-hemlock, subalpine and non-commercial, water, etc. An additional subcategory classification is also provided which gives additional insight into tree size classes for conifers or species group for hardwoods. These forest and land cover types are provided as both a shapefile and geopackage for Washington and Oregon combined.The 1928 McSweeney-McNary Forestry Research Act (P.L. 70-466, 45 Stat. 699-702) directed the Secretary of Agriculture to make and keep current a comprehensive inventory and analysis of the nation's forest resources. The decision was made to begin the nationwide survey with the Douglas-fir region and shortly thereafter to expand to the other forested lands of Washington and Oregon. Surveys were conducted between 1930 and 1936. Results of these surveys were reported in many formats including quarter state maps (4 maps per state) as well as many printed reports.The history of this project and copies of some of the early results as well, were published in Harrington (2003) which included a CD with a digital map (an ArcView GIS shapefile) for all of Washington and Oregon.

This is the GIS data and imagery used for analyses in the article
Sixty-seven years of land-use change in southern Costa Rica by Zahawi
et al. currently in revision at PLOS One.

This study required the orthorectification of historic aerial photographs, as well as forest cover mapping and landscape analysis of 320 km² around the Las Cruces Biological Station in San Vito de Coto Brus, Costa Rica. The imagery and GIS data generated were used to account for forest cover change over five different time periods from 1947 to 2014.

The datasets supplied include GIS files for:

• Extent of the study area (shapefile).
• Forest cover mapped for each time period (geotiff).
• Imagery of the mosaics generated with the orthorectified historic aerial photographs (geotiff).
• Age in studied time periods of the current forest patches (shapefile).
• Connectivity lines inside the studied area (shapefiles).

All files are in Costa Rica Transverse Mercator 2005 (CRTM05) projected coordinate reference system. For transformation between coordinate systems please refer to http://epsg.io/5367

Aerial photographs for the years 1947, 1960, 1980 and 1997 were acquired from the Organization for Tropical Studies GIS Lab and the Instituto Geográfico Nacional of Costa Rica. The orthorectification process was done first on the 1997 set of images and used the current 1:50,000 and 1:25,000 Costa Rican cartography to identify geographical reference points. The set of 1997 orthophotos was used as a reference set to orthorectify remaining years with the exception of 1947 images. The orthorectification process and all other geospatial analyses were done on the CRTM05 spatial reference system and the resulting orthophotos had a 2m cell size. The largest Root Mean Square error (RMSE) of the orthorectification of these three time slices of aerial photographs was 15 m.

Given the lack of information on flight parameters, and the expansive forest coverage in 1947 photographs, images were georeferenced and built into a mosaic using river basins and the few forest clearings that had a similar shape in the 1960 flyover. The 1947 set of images did not cover the whole study area, having empty areas without photographs that represented ˜12.1% of the analysis extent. Nonetheless, these areas were classified as forested given that forest was present in these same areas in the 1960 imagery.

Forest mapping was done by visual interpretation of orthophotos and Google imagery. The areas were considered forested if tree crowns were easily identified when viewing the images at a scale of 1:10,000. In areas where it was difficult to discern the type of land cover, a scale of 1:5,000 was used. This was done to eliminate agroforestry systems such as shaded coffee areas (with trees planted in rows) or very early stages of forest regeneration from the forest land-cover class. The analysis was done only in areas that were cloud free in the five time slices. This resulted in the elimination of 134 ha (~0.4%) from of the original area outlined above. Polygons were drawn over the different areas using QGIS and were transformed into raster files of 10 m cell size.

The link: * Access the data directory* is available in the section*Dataset description sheets; Additional information*. Ecoforest maps in PDF format are available at a scale of 1/20,000 and cover Quebec territory approximately up to the 52nd parallel. Each map covers an average area of approximately 250 km2 and presents forest information for the territory concerned. Its accuracy is approximately 10 meters. These maps are an image of the current ecoforest map for the corresponding year. Maps 2021, 2022, 2023 and 2024 The maps 2021, 2022, 2023, as well as those of 2024 are produced from the up-to-date ecoforest map of the corresponding year. It represents the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the picture was taken. According to the maps, data using the forest stand inventory approach (AIPF) is included when available for a complete sheet. Main components: type of vegetation (forest species group, density class, class of density, class of height, age class, etc.) or type of AIPF vegetation (detailed forest species, density (%), height (m), age class, etc.); slope class; class of slope; nature of the terrain (peatlands, height class, age class, etc.); topography (level curves); fragmentation. 2019 and 2020 maps The 2019 maps, as well as those of 2020, are produced from up-to-date ecoforest maps of the corresponding year. They represent the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the photo-interpretation of aerial photographs from the 4th and 5th ecoforestry inventories of southern Quebec were taken. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in public forests. The information presented corresponds to the current ecoforest map of 2019 or 2020 as the case may be. On each of the maps, the name of the stands is expressed by the group of species. Main components: type of vegetation (forest species, density, height, height, age class, etc.); slope class; nature of the terrain (peatlands, gravel, etc.); hydrography (lakes, rivers, streams, streams, swamps, etc.); transport network and swamps, etc.); transport network and bridges; topography (level curves); fragmentation. Maps 2015 The 2015 maps are produced from the photo-interpretation of aerial photographs from the 3rd and 4th ecoforest inventories of southern Quebec. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (cutting and planting) carried out in public forests. The information presented corresponds to the 2015 updated ecoforest map. MAP FOR PRINTING (GEOREFERENCED)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The locations of wells that have been drilled for oil production, gas or salt resources or for underground storage of hydrocarbons.This data can be used for land use and resource management, emergency management, as well as compliance and enforcement in the petroleum industry. The Data is collected on an on-going basis and maintained in the Ontario Petroleum Data System (OPDS). Additional Documentation Petroleum Well - Data DescriptionPetroleum Well - DocumentationPetroleum Well- User Guide Status
On going: data is being continually updated

Maintenance and Update Frequency

Semi-monthly: data is updated twice a month

Contact Petroleum Operations Section, Ministry of Natural Resources and Forestry, POSrecords@ontario.ca

The forest fire map shows forest fires that occurred mainly in the territory of southern Quebec, i.e. the area located south of the territorial limit of attributable forests. This map data makes it possible to improve knowledge about fire regimes and to meet the specific needs of special management plans following forest fires. They can also be used to meet a variety of study and research needs, such as analyzing the impact of climate change, modeling post-fire regeneration, and studying ecosystem dynamics. This information is obtained from and produced from a variety of sources, including satellite images, aerial photographs, field or aerial surveys, fire scar dating, and archival documents. This data contains four types of mapping as well as fire regime mapping: • Detailed fire mapping, from 1976 to the present. This mapping includes burn types, total burn and partial burn, when information is available. In addition, for fires that have been characterized, information on the classes of burning patterns is added. The minimum mapping area can be up to 0.1 ha, depending on the source products used. This map is partially available for areas located in the north of southern Quebec. • Mapping the simplified contours of fires, from 1972 to today. This map shows the external contours of fires (without fragmentation), in order to represent them globally in a product that is easily usable and can be integrated into current information systems, GPS or others. Resulting from the fusion of detailed fire mapping, this product was designed to meet various customer needs. This map is partially available for the sectors located in the north of southern Quebec. • The mapping of the origin of fires having been listed by the protection organizations (e.g.: SOPFEU) for the period from 1972 to today. This mapping includes the date, the source of ignition (human or lightning) and the protection zone. It is available for all of Quebec. • The mapping of ancient fires concerns fires that occurred between the very end of the 19th century and 1975. This mapping comes from the information present on the forest maps of the first and second inventories, as well as from the information contained on the ecoforest maps of the third and fourth inventories. The dating of these fires is done using various methods, including the analysis of study trees bearing fire scars and the consultation of archival documents. This data is available for the following regions: Saguenay-Lac-Saint-Jean (02), Bas-Saint-Laurent (02), Bas-Saint-Laurent (01), Gaspésie-Îles-de-la-Madeleine (11), Abitibi-Témiscamingue (08), Mauricie-Centre-du-Québec (04-17), and Lanaudière-du-Québec (04-17), and Lanaudière-Laurentides (14-15). • Mapping fire regimes in southern Quebec. This map shows 13 zones with distinct fire regimes. These areas were delineated based on available information on the areas burned during the period 1890-2020 and other potentially decisive environmental variables, such as physiography, the abundance of different tree species known to be dependent on fire as well as the location of natural and anthropogenic ignitions. Fire regime mapping covers all forest areas under management as well as a more northern portion that is not managed. The detailed methodology is presented in Forest Research Paper no. 189 “Zoning fire regimes in southern Quebec” (coming soon). This zoning may be useful to ensure better consideration of the risk of fire in a forest management context. It can also serve as a territorial basis for projecting future fire activity taking into account various factors, such as climate change, fire suppression as well as changes in the types of fuels and their distribution on the territory.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The Geographic Names Information System (GNIS) is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types. See http://geonames.usgs.gov for additional information.

The Digital Geologic-GIS Map of a portion of Petrified Forest National Park, Arizona is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (pefo_geology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (pefo_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (pefo_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) this file (pefo_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (pefo_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (pefo_geology_metadata_faq.pdf). Please read the pefo_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: Arizona Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (pefo_geology_metadata.txt or pefo_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:50,000 and United States National Map Accuracy Standards features are within (horizontally) 25.4 meters or 83.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

The dataset covers all non-forestry areas in the Free State of Saxony. Non-forestry land is the land that does not serve the purposes of the forestry operation, but which has its own economic significance. For each area, ownership type, forestry farm number, forest section, department, subdivision, sub-area and stock as well as forest district and territory are indicated. The data are part of the forest basic data/forest map and are at the same time the basis for the collection/running of all basic forest data as well as the other types of maps derived from it in the state enterprise Sachsenforst.

This dataset includes the extent of the boreal forest as well as the extent of managed boreal forest worldwide. The extent of boreal forest was produced from Brandt et al. (2013) and a modified version of Goudilin (1987). Managed forest was defined as suggested by IPCC (2003) using data from FAFS (2009), Gauthier et al. (2014), See et al. (2015) and AICC maps. The extent of managed forest mostly includes areas managed for wood production, areas protected from large-scale disturbances as well as formal protected areas. Both boreal forest extent and managed boreal forest extent are available in raster and vector data. Please cite this data product as: Boucher, D., D.G. Schepaschenko, S. Gauthier, P. Bernier, T. Kuuluvainen, A. Z. Shvidenko. 2024. World boreal forest and managed boreal forest extent. DOI: 10.23687/88d70716-2600-4995-8d5f-86f96e383abf These data were presented in the following article: Gauthier, S., P. Bernier, T. Kuuluvainen, A. Z. Shvidenko, D. G. Schepaschenko. 2015. Boreal forest health and global change. Science 349:819-822. DOI: 10.1126/science.aaa9092 References: J. P. Brandt, M. D. Flannigan, D. G. Maynard, I. D. Thompson, W. J. A. Volney, Environ. Rev. 21, 207–226 (2013) I. S. Goudilin, Landscape map of the USSR. Legend to the landscape map of the USSR. Scale 1:2 500 000. Moscow, Ministry of Geology of the USSR (1987) [in Russian]. Inter-governmental panel on climate change (IPCC). J. Penman, M. Gytarsky, T. Hiraishi, T. Krug, D. Kruger, et al., Eds., Good practice guidance for land use, land-use change and forestry (IPCC/NGGIP/IGES, Kanawaga, 2003) Federal Agency of Forest Service (FAFS), Forest Fund of the Russian Federation (state by 1 January 2009) (Federal Agency of Forest Service, Moscow, 2009) [in Russian] S. Gauthier et al., Environ. Rev. 22, 256–285 (2014). See et al., Harnessing the power of volunteers, the internet and Google Earth to collect and validate global spatial information using Geo-Wiki. Technological Forecasting and Social Change. (2015). doi:10.1016/j.techfore.2015.03.002 Alaska Interagency Coordination Center (AICC). Fire Information. https://fire.ak.blm.gov/content/maps/aicc/Large%20Maps/Alaska_Fire_Management_Options.pdf (the version of 2014 was used)

_The link: * Access the data directory is available in the sectionDataset description sheets; Additional information. Ecoforest maps in PDF format are available at a scale of 1/20,000 and cover Quebec territory approximately up to the 52nd parallel. Each map covers an average area of approximately 250 km2 and presents forest information for the territory concerned. Its accuracy is approximately 10 meters. These maps are an image of the current ecoforest map for the corresponding year. _Maps 2021, 2022, 2023 and 2024 The maps 2021, 2022, 2023, as well as those of 2024 are produced from the up-to-date ecoforest map of the corresponding year. It represents the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the picture was taken. According to the maps, data using the forest stand inventory approach (AIPF) is included when available for a complete sheet. Main components: type of vegetation (forest species group, density class, class of density, class of height, age class, etc.) or type of AIPF vegetation (detailed forest species, density (%), height (m), age class, etc.); slope class; class of slope; nature of the terrain (peatlands, height class, age class, etc.); topography (level curves); fragmentation. 2019 and 2020 maps The 2019 maps, as well as those of 2020, are produced from up-to-date ecoforest maps of the corresponding year. They represent the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the photo-interpretation of aerial photographs from the 4th and 5th ecoforestry inventories of southern Quebec were taken. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in public forests. The information presented corresponds to the current ecoforest map of 2019 or 2020 as the case may be. On each of the maps, the name of the stands is expressed by the group of species. Main components: type of vegetation (forest species, density, height, height, age class, etc.); slope class; nature of the terrain (peatlands, gravel, etc.); hydrography (lakes, rivers, streams, streams, swamps, etc.); transport network and swamps, etc.); transport network and bridges; topography (level curves); fragmentation. Maps 2015 The 2015 maps are produced from the photo-interpretation of aerial photographs from the 3rd and 4th ecoforest inventories of southern Quebec. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (cutting and planting) carried out in public forests. The information presented corresponds to the 2015 updated ecoforest map. MAP FOR PRINTING (GEOREFERENCED)This third party metadata element was translated using an automated translation tool (Amazon Translate).*

The link: * Access the data directory* is available in the section*Dataset description sheets; Additional information*. Ecoforest maps in PDF format are available at a scale of 1/20,000 and cover Quebec territory approximately up to the 52nd parallel. Each map covers an average area of approximately 250 km2 and presents forest information for the territory concerned. Its accuracy is approximately 10 meters. These maps are an image of the current ecoforest map for the corresponding year. Maps 2021, 2022, 2023 and 2024 The maps 2021, 2022, 2023, as well as those of 2024 are produced from the up-to-date ecoforest map of the corresponding year. It represents the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the picture was taken. According to the maps, data using the forest stand inventory approach (AIPF) is included when available for a complete sheet. Main components: type of vegetation (forest species group, density class, class of density, class of height, age class, etc.) or type of AIPF vegetation (detailed forest species, density (%), height (m), age class, etc.); slope class; class of slope; nature of the terrain (peatlands, height class, age class, etc.); topography (level curves); fragmentation. 2019 and 2020 maps The 2019 maps, as well as those of 2020, are produced from up-to-date ecoforest maps of the corresponding year. They represent the result of the photo-interpretation of aerial photographs taken during the 4th and 5th ecoforestry inventories of southern Quebec to which were added natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in the public forest following the year in which the photo-interpretation of aerial photographs from the 4th and 5th ecoforestry inventories of southern Quebec were taken. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (harvesting and reforestation) carried out in public forests. The information presented corresponds to the current ecoforest map of 2019 or 2020 as the case may be. On each of the maps, the name of the stands is expressed by the group of species. Main components: type of vegetation (forest species, density, height, height, age class, etc.); slope class; nature of the terrain (peatlands, gravel, etc.); hydrography (lakes, rivers, streams, streams, swamps, etc.); transport network and swamps, etc.); transport network and bridges; topography (level curves); fragmentation. Maps 2015 The 2015 maps are produced from the photo-interpretation of aerial photographs from the 3rd and 4th ecoforest inventories of southern Quebec. An update is then carried out taking into account natural disturbances (fires, epidemics, windfalls, etc.) and forest interventions (cutting and planting) carried out in public forests. The information presented corresponds to the 2015 updated ecoforest map. MAP FOR PRINTING (GEOREFERENCED)**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows three condensed maps and four graphs representing various forestry and woodworking processes as well as the correlating statistics for Canada. The first map on this plate shows the locations of sash, door and planing mills for 1951. This map includes establishments engaged wholly or principally in millwork or the production of sash, doors, frames, mouldings, planed lumber, matched lumber (other than hardwood flooring), prefabricated houses, wooden furniture, boxes and containers as well as plants specializing in milling in transit. The second map shows most of the plants devoted to furniture production in 1951, although some of them also manufacture commodities other than furniture as secondary products. The furniture industry is not exclusively concerned with woodworking as it produces such things as household furniture, office and store fixtures, metal and upholstered furniture and mattresses. In 1951, the furniture industry employed 27 274 persons and ranked 11th among manufacturing industries in terms of numbers employed and with a value of production of $190 907 420 ranked 24th in terms of value of production. The third and largest map on this plate shows the labour force engaged in forestry and logging and is based on 1951 census data. This labour force includes the craftsmen, labourers, technical and administrative personnel of logging companies, self employed loggers, foresters, fire rangers, and other forestry service personnel. Also included on this plate are three graphs showing lumber production for 1951. The first graph shows quantity of lumber production by province; the second shows value of woods operations by product; and the third shows quantity of lumber cut by kind.

This repository holds data for following research article: Mina M, Marzini S, Crespi A & Albrich K (2025) Building virtual forest landscapes to support forest management: the challenge of parameterization. Forests Monitor 2(1), 49-96, https://doi.org/10.62320/fm.v2i1.19

The archived data consist in input files for the iLand model (version 2.0) for the Venosta study area. The dataset includes: biophysical parameters, historical climate database, digital elevation model, wind topomodifier map, forest cover area, forest landscape snapshot, and project file.

For further information on setting up the iLand model in a landscape visit https://iland-model.org/iland-book. iLand is freely available research tool for non-commercial use. The model is fully documented in the iLand webpage and released under the GNU General Public License. The source code is open access and available in this Github repository.

If interested in using iLand with this associated dataset for a research study or a project, please contact Marco Mina (marco.mina@eurac.edu)

Research article associated to this dataset

Mina M, Marzini S, Crespi A & Albrich K (2025) Building virtual forest landscapes to support forest management: the challenge of parameterization. Forests Monitor r 2(1), 49-96, https://doi.org/10.62320/fm.v2i1.19

ABSTRACT. Simulation models are important tools to study the impacts of climate change and natural disturb-ances on forest ecosystems. Being able to track tree demographic processes in a spatially explicit manner, process-based forest landscape models are considered the most suitable to provide robust projections that can aid decision making in forest management. However, landscape models are challenging to parameterize and setting up new study areas for application studies largely depends on data availability. The aim of this study is to demonstrate the parameterization process, including model testing and evaluation, for setting up a study area in the Italian Alps in a process-based forest landscape model using available data. We processed soil, climate, carbon pools, vegetation, disturb-ances and forest management data, and ran iterative spin-up simulations to generate a virtual landscape best resembling current conditions. Our results demonstrated the feasibility of initializing forest landscape models with data that are typically available from forest management plans and national forest inventories, as well as openly available mapping products. Evaluation tests proved the ability of the model to capture the environmental constraints driving regeneration dynamics and in-ter-specific competition in forests of the Italian Alps, as well as to simulate natural disturbances and carbon dynamics. The model can subsequently be applied to investigate forest landscape develop-ment under a suite of future scenarios and provide recommendations for adapting forest management decisions.

Thuringian forest biotope mapping is the comprehensive mapping of all biotopes in the forest. It is a joint project of the Forestry and Nature Conservation Administration the Free State of Thuringia. The aim of the mapping is the mapping and documentation of the current natural environment as well as the assessment of the forest and nature conservation value of all forest biotopes. Particular emphasis is placed on the recording of specially protected biotopes in accordance with § 18 ThürNatG. A mapping guide is available as a working material. As a result, various maps (digital and analog) as well as a factual data collection are available.

Additional file 1: Table S1. The species, amount and monetary value of plant parts collected in the study area. Table S2. Description of the skill levels required for occupations and the ratios of choosing wild food.

The Thuringian forest biotope mapping is the comprehensive mapping of all forest biotopes. It is a joint project of the forest and nature conservation administration of the Free State of Thuringia. The aim of the mapping is the natural area-related recording and documentation of the current natural features as well as the assessment of the forestry and nature conservation value of all forest biotopes. Particular value is placed on the recording of the specially protected biotopes according to § 18 ThürNatG. Mapping instructions are available as working material. As a result, various maps (digital and analogue) as well as a collection of factual data are available.

The Digital Geologic-GIS Map of the Giant Forest 15' Quadrangle, California is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (gifo_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (gifo_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (gifo_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (seki_manz_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (seki_manz_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (gifo_geology_metadata_faq.pdf). Please read the seki_manz_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (gifo_geology_metadata.txt or gifo_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:62,500 and United States National Map Accuracy Standards features are within (horizontally) 31.8 meters or 104.2 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

All organisations hold information about the core of their business. The Forestry Commission holds information on trees and forests. We use this information to help us run our business and make decisions.

The role of the Forest Inventory (the Sub-compartment Database (SCDB) and the stock maps) is to be our authoritative data source, giving us information for recording, monitoring, analysis and reporting.

Through this it supports decision-making on the whole of the FC estate. Information from the Inventory is used by the FC, wider government, industry and the public for economic, environmental and social forest-related decision-making. Furthermore, it supports forestrelated national policy development and government initiatives, and helps us meet our national and international forest-related reporting responsibilities.

Information on our current forest resource, and the future expansion and availability of wood products from our forests, is vital for planners both in and outside the FC. It is used when looking at the development of processing industries, regional infrastructure, the effect upon communities of our actions, and to prepare and monitor government policies.

The Inventory (SCDB and stock maps), with ‘Future Forest Structure’ and the ‘rollback’ functionality of Forester, will help provide a definitive measure of trends in extent, structure, composition, health, status, use, and management of all FC land holdings. We require this to meet national and international commitments, to report on the sustainable management of forests as well as to help us through the process of business and Forest Design Planning. As well as helping with the above, the SCDB helps us address detailed requests from industry, government, non-government organisations and the public for information on our estate.

The FC’s growing national and international responsibilities and the requirements for monitoring and reporting on a range of forest statistics have highlighted the technical challenges we face in providing consistent, national level data. A well kept and managed SCDB and GIS (Geographical Information System - Forester) will provide the best solution for this and assist Countries in evidence-based policy making.

Looking ahead at international reporting commitments; one example of an area where requirements look set to increase will be reporting on our work to combat climate change and how our estate contributes to carbon sequestration. We have put in place processes to ensure that at least the basics of our inventory are covered:

1. The inventory of forests;
2. The land-uses;
3. The land we own ( Deeds);
4. The roads we manage.

We depend on others to allow us to manage the forests and to provide us with funds and in doing so we need to be seen to be responsible and accountable for our actions. A foundation of achieving this is good record keeping.

A sub compartment should be recognisable on the ground. It will be similar enough in land use, species or habitat composition, yield class, age, condition, thinning history etc. to be treated as a single unit. They will generally be contiguous in nature and will not be split by roads, rivers, open space etc. Distinct boundaries are required, and these will often change as crops are felled, thinned, replanted and resurveyed.

In some parts of the country foresters used historical and topographical features to delineate sub-compartment boundaries, such as hedges, walls and escarpments. In other areas no account of the history and topography of the site was taken, with field boundaries, hedges, walls, streams etc. being subsumed into the sub-compartment. Also, these features may or may not appear on the OS backdrop, again this was dependent on the staff involved and what they felt was relevant to the map. The main point is that, as managers we may find such obvious features in the middle of a sub-compartment when nothing is indicated on the stock map, while the same thing would be indicated elsewhere.

Attributes;

FOREST Cost centre Nos. COMPTMENT Compartemnt Nos. SUBCOMPT Sub-compartment letter SUBCOMPTID Unique identifier BLOCK Block nos. CULTCODE Cultivation Code CULTIVATN Cultivation PRIHABCODE Primary Habitat Code PRIHABITAT Primary Habitat PRILANDUSE Land Use of primary component PRISPECIES Primary component tree species PRI_PLYEAR prim. component year planted PRIPCTAREA Prim. component %Area of sub-compartment SECHABCODE Secondary Habitat Code SECHABITAT Secondary Habitat SECLANDUSE Land Use of secondary component SECSPECIES Secondary component tree species SEC_PLYEAR Secondary component year planted SECPCTAREA Secondary component %Area of sub-compartment TERLANDUSE Land Use of tertiary component TERSPECIES Tertiary component tree species TER_PLYEAR Tertiary component year planted TERPCTAREA Tertiary component %Area of sub-compartment TERHABITAT Tertiary Habitat TERHABCODE Tertiary Habitat Code

Any maps produced using this data should contain the following Forestry Commission acknowledgement: “Contains, or is based on, information supplied by the Forestry Commission. © Crown copyright and database right [Year] Ordnance Survey [100021242]”. Attribution statement: Contains OS data © Crown copyright [and database right] [year].

Additional file 2. Test studies and scoping results. List of test studies and results of search string scoping process.