Historic land uses on lots that were vacant, privately owned, and zoned for manufacturing in 2009. Information came from a review of several years of historical Sanborn maps over the past 100 years. When the SPEED 1.0 mapping application was created in 2009, OER had its vendor examine historic land use maps on vacant, privately-owned, industrially-zoned tax lots. Up to seven years of maps for each lot were examined, and information was recorded that indicated industrial uses or potential environmental contamination such as historic fill. Data for an additional 139 lots requested by community-based organizations was added in 2014. Each record represents the information from a map from a particular year on a particular tax lot at that time. Limitations of funding determined the number of lots included and entailed that not all years were examined for each lot.

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.

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

This data set depicts land use and land cover from the 1970s and 1980s and has been previously published by the U.S. Geological Survey (USGS) in other file formats. This version has been reformatted to other file formats and includes minor edits applied by the U.S. Environmental Protection Agency (USEPA) and USGS scientists. This data set was developed to meet the needs of the USGS National Water-Quality Assessment (NAWQA) Program.

The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.

About this layerThe Land Use Database held by the Northern Ireland Environment Agency (NIEA) provides a record of approximately 14,000 sites that have had previous industrial land use(s).What can you do with the layer?Visualisation: This layer can be used for visualisation online in web maps and in ArcGIS Pro.Analysis: This layer can be used in dashboards.Download: The data is downloadable.This layer is part of the Living Atlas of the World that provides access to thousands of beautiful and authoritative layers, web maps and apps.

The LUCAS LUC historical dataset consists of annual land use and land cover maps from 1950 to 2015. It is based on land cover data from the LANDMATE PFT dataset that was generated from ESA-CCI LC data. The ESA-CCI LC land cover classes are converted into 16 plant functional types and non-vegetated classes employing the method of Reinhart et al. (2021). The land use change information from the Land-Use Harmonization Data Set version 2 (LUH2 v2h, Hurtt et al. 2020) were imposed using the land use translator developed by Hoffmann et al. (2021). For each year, a map is provided that contains 16 fields. Each field holds the fraction the respective plant functional types and non-vegetated classes in the total grid cell (0-1). The LUCAS LUC dataset was constructed within the HICSS project LANDMATE and the WCRP flagship pilot study LUCAS to meet the requirements of downscaling experiments within EURO-CORDEX. Plant functional types and non-vegetated classes: 1 - Tropical broadleaf evergreen trees 2 - Tropical deciduous trees 3 - Temperate broadleaf evergreen trees 4 - Temperate deciduous trees 5 - Evergreen coniferous trees 6 - Deciduous coniferous trees 7 - Coniferous shrubs 8 - Deciduous shrubs 9 - C3 grass 10 - C4 grass 11 - Tundra 12 - Swamp 13 - Non-irrigated crops 14 - Irrigated crops 15 - Urban 16 - Bare

MethodThis dataset includes a detailed example for using our method (described in paper linked to below) to digitize historical land-use maps in R.MapsWe also release all of the Swedish land-use maps that we digitized for this project. This includes the Economic Map of Sweden (Ekonomiska kartan) over Sweden's 15 southernmost counties (7069 25 km2 sheets), plus 11 sheets of the District Economic Map (Häradsekonomiska kartan - but see http://bolin.su.se/data/Cousins-2015 for more accurate manual digitization).SvenskaHär kan du ladda ner 7069 Ekonomiska kartblad som vi digitaliserade över södra Sverige. En kort beskrivning av metoden publicerades i tidningen Kart & Bildteknik (se länk nedan).--UpdatesVersion 2: The digitized Economic Maps have been resampled so that they are all at a 1m resolution. In the original version they were all very close to 1m but not exactly the same, which made mosaicking difficult. This should be easier now. We now also link to the published paper in Methods in Ecology and Evolution.For more information, please see the readme file. For help or collaboration, please contact alistair.auffret@natgeo.su.se. If you use the data here in your work or research, please cite the publication appropriately.

The dataset was generated to describe historical land-use and land-cover (LULC)for the northern Colorado urban Front Range (which includes the cities of Boulder, Fort Collins, Greeley, and Denver) for an area covering approximately 1,023,660 hectares. The Front Range urban landscape is diverse and interspersed with highly productive agriculture as well as natural land cover types including evergreen forest in the Rocky Mountain foothills and Great Plains grassland. To understand the dynamics of urban growth, raster maps were created at a 1-meter resolution for each of four time steps, nominally 1937, 1957, 1977, and 1997. In total, 8 to 38 LULC classes were identified using manual interpretation techniques, aerial photographs, historical maps, and other available information. The maps provide high resolution spatial data for understanding the historical progression of urbanization and will allow further analysis of the effects of urban growth on social and ecological systems.

HILDA+ version 2.0 is an updated version of the HILDA+ (HIstoric Land Dynamics Assessment+) doi:10.1594/PANGAEA.921846. It is a global dataset on annual land use/cover change between 1960-2020 at 1 km spatial resolution. It is based on a data-driven reconstruction approach and integrates multiple open data streams (from high-resolution remote sensing, long-term land use reconstructions and statistics). Compared to the previous version, this new HILDA+ version 2.0 uses a base map from the year 2020 (based on ESA World Cover), integrates new remote sensing-based land cover datasets (see documentation sheet in the uploaded data), is calibrated on updated national land use statistics from FAO and includes additional cropland-related land use categories: tree crops, agroforestry and annual crops. See the documentation and the paper reference for the method of cropland mapping. Forests are subdivided into different forest types based ESA CCI Land Cover (1992-2020). HILDA+ version 2.0 covers the following land use/cover categories (given with their respective code numbers in the dataset): 11: Urban areas, 22: Annual crops, 23: Tree crops, 24: Agroforestry, 33: Pasture/rangeland, 40: Forest (unknown/other), 41: Forest (evergreen, needle leaf), 42: Forest (evergreen, broad leaf), 43: Forest (deciduous, needle leaf), 44: Forest (deciduous, broad leaf), 45: Forest (mixed), 55: Unmanaged grass/shrubland, 66: Sparse/no vegetation.

This polygon data set documents the spatial extent of polygon files included in a release of enhanced U.S. Geological Survey historical land-use and land-cover data.

This data set depicts land use and land cover from the 1970s and 1980s and has been previously published by the U.S. Geological Survey (USGS) in other file formats. This version has been reformatted to other file formats and includes minor edits applied by the U.S. Environmental Protection Agency (USEPA) and USGS scientists. This data set was developed to meet the needs of the USGS National Water-Quality Assessment (NAWQA) Program.

This is collection of DWR County Land Use Surveys. You may scroll the list below to download any individual survey of interest. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer. For Statewide Crop Mapping follow the link below : https://data.cnra.ca.gov/dataset/statewide-crop-mapping For Region Land Use Surveys follow link below: https://data.cnra.ca.gov/dataset/region-land-use-surveys Questions about the survey data may be directed to Landuse@water.ca.gov.

This polygon data set provides ancillary information to supplement a release of enhanced U.S. Geological Survey (USGS) historical land-use and land-cover data. The data set presents some of the original file-header documentation, as well as some details describing how the data files were used in the data release, in a geographic context.

This dataset provides annual raster maps of historical and projected future land use and land cover (LULC) for California, USA. Changes in LULC over time were simulated using the Land Use and Carbon Scenario Simulator (LUCAS) model. The model was run at 1-km resolution on an annual timestep for historical (1985-2020) and projected future time periods (2021-2100). Simulations for the projected future time period were run under all combinations of four climate scenarios, two urbanization scenarios, and two vegetation management scenarios with 40 Monte Carlo realizations for each simulation.

This tabular data set contains information on historic and projected land-use/land-cover, compiled for two spatial components of the NHDPlus version 2.1 data suite (NHDPlusv2) for select regions of the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2.1 data suite by the unique identifier COMID. The source data is from the Modeled historic and projected land use and land cover for the conterminous United States produced by Terry Sohl and others (2014, 2018). The data provided here contains information for the years, 1980 through 2100, compiled as described above. The units are in percentages. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values were computed using the xstrm python software package (Wieferich and others, 2021).

This is collection of DWR Region Land Use Surveys. These include several county land use surveys, In addition, you may scroll the list below to download any individual survey of interest. Historic County Land Use Surveys spanning 1986 - 2015 may also be accessed using the CADWR Land Use Data Viewer. For Statewide Crop Mapping follow the link below : https://data.cnra.ca.gov/dataset/statewide-crop-mapping For County Land Use Surveys follow link below: https://data.cnra.ca.gov/dataset/resources/county-land-use-surveys Questions about the survey data may be directed to Landuse@water.ca.gov.

The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.This is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.There are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.The data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.

The Land Use Database held by the Northern Ireland Environment Agency (NIEA) provides a record of approximately 14,000 sites that have had previous industrial land use(s).

This data set represents U.S. Geological Survey (USGS) historical Land Use and Land Cover (LULC) from the 1970's that has been refined with 2000 population density at the block group level to indicate new residential development representative of the early 2000's. Any area having a population density of at least 1,000 people per square mile had been re-classified as "urban" land in this data set.