Since 1908, the Harvard Forest has conducted forest surveys approximately every 10-20 years on its three largest tracts (total 1033 ha). These maps have been digitized along with maps of environmental factors (topography, soils), disturbance (1938 hurricane, historical land-use), and silvicultural treatments. These datalayers will allow researchers to understand the influence of environment factors, disturbances, and silviculture on the structure and composition of modern forest stands as well as assisting in locating and describing research sites. The dataset also includes an elevation grid (NED 30 meter cells), and a shapefile of linear features (trails, stonewalls, etc). Original maps were transcribed to standardized basemaps by various researchers. These basemaps were then scanned and digitized as shapefiles in ArcView GIS 3.2. The shapefiles were then transformed to Massachusetts State Plane Meters NAD83 projection in ArcGIS and rubbersheeted to align better with aerial photographs downloaded from MassGIS. Locations of control points will be permanently archived at the Harvard Forest to facilitate transformation of future datalayers.

This dataset contains elevation, 1986 forest type, land-use history, and soils maps for the Prospect Hill Tract, digitized from paper maps in the Harvard Forest Archives. File format = Idrisi 4.1 binary. Resolution = 10m x 10m. Coordinates = UTM zone 18. Datum = 1927 North American. This dataset has been replaced with a new vector series for the entire Harvard Forest (see HF110).

Toronto’s Don River Valley is arguably the city’s most distinctive physical feature. As a provider of water, power, sustenance, building materials, and transportation, it has played an important role in the city’s settlement and development. The river valley has changed dramatically in the years since European settlement, particularly during the late nineteenth and early twentieth century, when the Lower Don River was straightened and channelized and the huge marsh at its mouth drained and filled. Today, the Lower Valley forms the foundation for one of the most densely populated areas in Canada, outlining as it does the eastern portion of Toronto’s downtown core and radiating residential areas. This project documents historical changes in the landscape of the Don River Valley. Drawing from the wide range of geographical information available for the Don River watershed (and the Lower Don in particular), including historical maps, geological maps, fire insurance plans, planning documents, and city directories, the project uses Geographic Information Systems software to place, compile, synthesize and interpret this information and make it more accessible as geospatial data and maps. The project is a work in progress. To date, we have scanned several dozen historical maps of Toronto and the Don River watershed, and compiled the following geospatial datasets: 1) changes to the river channel and shoreline of Toronto harbour, 1858-1918; 2) industrial development in the Lower Don River Watershed, 1857-1951 (as points, and in some cases polygons); 3) historical mill sites in the Don River Watershed, 1825; 18524) land ownership in the watershed, 1860 and 1878; and 4) points of interest in the watershed. In the future, we hope to expand the project to include data from other Toronto area watersheds and other parts of the city. The project was conducted through a collaboration between Jennifer Bonnell, a doctoral student in the History of Education program at the University of Toronto's Ontario Institute for Studies in Education (OISE/UT) - now at York University in the History Department and Marcel Fortin, the Geographic Information Systems (GIS) and Map Librarian at the University of Toronto's Map and Data Library. Financial and in-kind support was provided by the Network in Canadian History and Environment (NiCHE) and the University of Toronto Libraries. Valuable research support for the Points of Interest pages came from Lost Rivers, a community-based urban ecology organization focused on building public awareness of the City's river systems. Jordan Hale, a University of Toronto Geography student conducted much of the digitization and database work.This project could not have been completed without their skilled assistance and dedication.

Inventory of Historic Properties for Anne Arundel County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the contiguous United States are ensemble mean values across 20 global climate models from the CMIP5 experiment (https://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-11-00094.1), downscaled to a 4 km grid. For more information on the downscaling method and to access the data, please see Abatzoglou and Brown, 2012 (https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/joc.2312) and the Northwest Knowledge Network (https://climate.northwestknowledge.net/MACA/). We used the MACAv2- Metdata monthly dataset; average temperature values were calculated as the mean of monthly minimum and maximum air temperature values (degrees C), averaged over the season of interest (annual, winter, or summer). Absolute change was then calculated between the historical and future time periods.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

Polygons depict properties in Maryland listed on the National Register of Historic Places, a listing maintained by the U.S. Department of Interior. The number of National Register listings in Maryland as of March 21, 2000 is 1230. Of the 1,230 listings, the following were not digitized: Queen City Hotel in Allegany County, demolished; and Steamship Nobska, which was moved to Massachusetts; Timonium Mansion in Baltimore county,demolished; the Messina Archeological Site in Cecil County, delisted; 100 Hopkins Place in Baltimore City, delisted; and the William Costen House in Somerset County, delisted. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

These website files and Topic Modelling raw data result tables were used to build a supporting appendix website for the thesis: Debating the US Constitution - A computational approach to the structure and geography of the ratification debateThesis AbstractThis thesis uses computational research methods to investigate and analyse the themes and topics under debate during the US Constitutional ratification campaign (1787-1788).The ratification of the Constitution, and the American founding period in general, has been of near constant interest and debate among historians of the United States. There have been many interpretations and re-interpretations of the Constitution’s nature, causes and consequences. The ratification debate has always been a major source for these interpretations. Many aspects of the framing and adoption of the Constitution continue to yield lively debate. However, so far, the ratification debate has not yet been extensively analysed using the relatively new methods labelled as ‘Digital History’.The most comprehensive collection of primary source documents relating to the ratification debate is found in the multi-volume Documentary History of the Ratification of the Constitution, which is now available in digital form at the University of Wisconsin Libraries’ Digital Collections. By subjecting this corpus to computational analysis, this thesis offers quantitative empirical data in a presuppositionless categorisation of the debate’s topics. The resultant research data output is then interpreted, analysed, and contextualised using more traditional qualitative assessment. This combined quantitative and qualitative approach prioritises the importance of using digital techniques to actively engage with creating argument-driven history.The thesis begins with both an outline of the developments in digital historical studies and an overview of the historiography of the American founding, outlining the major interpretative frameworks (broadly categorised as: Progressive; Multiple Traditions; and Federalist, Unionist, and Internationalist). The second chapter provides a detailed description of the methodological tools and approaches used in the research, covering: corpus preparation; topic modelling; network maps; data charts; and GIS mapping. This is then followed by a brief assessment of best-practice in presenting digital research outputs in an historical monograph.Chapter three offers a high-level overview interpretation of the resultant data for the 40 modelled topics and a case-study assessment of the 85 document sub-set that makes up The Federalist, the most important work to come out of the founding period and a classic of American political thought. Chapter four focuses on a group of topics concerned with debates over the Form of Government that will be created under the Constitution, with the fifth chapter providing a detailed assessment of a single topic – the discussions regarding a Bill of Rights.The final chapter makes an assessment of the digital research approach as used for this project, highlighting the advantages and limitations of the methods employed. The chapter then discusses the main historiographical observations and conclusions that can be drawn from the research and revisits the American founding’s interpretative frameworks in light of these findings. Finally, a number of suggestions are made for future studies that could be made to advance the research further.In support of the thesis, an appendix website has been created to host the research data outputs including: dynamic data tables; topic-network maps; time-based graphs; and interactive maps showing the printing and reprinting locations of contemporary newspaper and pamphlet articles. A live version of the website may be available at: www.ratificationdebates.com. A back-up version of this website is available here.Copyright informationThe map image used throughout the website is courtesy of the “David Rumsey Map Collection, David Rumsey Map Center, Stanford Libraries” (list no. 33231) licensed under the Creative Commons License CC BY-SA. This license applies to the images only, with the data licensed as CC0.

Los Angeles County Department of Public Works’ Vertical Control Network is composed of more than 1,700 miles (2,720 kilometers) of level runs and comprise nearly 9,000 benchmarks. The basic accuracy of the net is reflected by an indicated field probable error of ± 0.017 feet per mile (4 mm per kilometer) of leveling as determined from conditions of closure. However, because of varying degrees of subsidence and heaving, the true datum is recovered only by obtaining substantial agreement of a number of benchmarks.For each active benchmark, a point representation was created in GIS by locating them based on their description. Parcel data, mile markers, the County Address Management System (CAMS), LARIAC aerials, oblique photos, 2-foot contour lines and/or Google Street View were used in assisting with the location.The creation of the benchmarks in GIS greatly enhances the Vertical Control Network by adding visual context with respect to their representative geospatial locations. With a glance, geospatial patterns can be observed and out-of-place benchmarks can be quickly identified and remapped to the correct location after verification.To facilitate the adjustment, indexing and distribution of adjusted values in the network, the county territory was divided into 33 quads or areas. For identification purposes, each quad was given a name (for example, “Rosemead”, “La Mirada”, “Santa Fe”, and etc.). Index maps, county maps, and other information can be accessed and downloaded on the basis of each of the quads by going to Survey Division’s Benchmark Retrieval System (https://pw.lacounty.gov/sur/benchmark). General adjustments are carried out every 5 to 10 years and the provided elevation data is expected to remain sound during this period. When a quad is adjusted, new elevations will be published and the date of the readjustment will be noted. No historical data is provided, but it can be acquired from Survey Division’s Public Records Counter or via the fee based Optional Technical Research (OTR) program. For general questions, contact:Hector Chang626-458-7038hchang@dpw.lacounty.govFor survey-related questions, contact:Charles Springstun626-320-9896cspring@dpw.lacounty.govThe following resources can be used to obtain historical benchmark data:PUBLIC RECORDS COUNTER900 S. Fremont Ave, 4th FloorAlhambra, CA 918037:00 AM to 5:00 PM Mon – ThursPhone: (626) 458-5137OPTIONAL TECHNICAL RESEARCH (OTR)7:00 AM to 5:00 PM Mon – ThursPhone: (626) 458-5131

Inventory of Historic Properties for Baltimore County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

Inventory of Historic Properties for Harford County. The Maryland Inventory of Historic Properties vector layers are depictions of the approximate locations of historic structures, monuments, districts, and other properties that are listed on the Maryland Inventory of Historic Properties. No attribute information is available for this dataset. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful. This is part of a collection of 221 Baltimore Ecosystem Study metadata records that point to a geodatabase. The geodatabase is available online and is considerably large. Upon request, and under certain arrangements, it can be shipped on media, such as a usb hard drive. The geodatabase is roughly 51.4 Gb in size, consisting of 4,914 files in 160 folders. Although this metadata record and the others like it are not rich with attributes, it is nonetheless made available because the data that it represents could be indeed useful.

The National Forest Climate Change Maps project was developed by the Rocky Mountain Research Station (RMRS) and the Office of Sustainability and Climate to meet the needs of national forest managers for information on projected climate changes at a scale relevant to decision making processes, including forest plans. The maps use state-of-the-art science and are available for every national forest in the contiguous United States with relevant data coverage. Currently, the map sets include variables related to precipitation, air temperature, snow (including snow residence time and April 1 snow water equivalent), and stream flow.Historical (1975-2005) and future (2071-2090) precipitation and temperature data for the state of Alaska were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP) (https://snap.uaf.edu). Monthly precipitation values (mm) were summed over the season of interest (annual, winter, or summer). These datasets have several important differences from the MACAv2-Metdata (https://climate.northwestknowledge.net/MACA/) products, used in the contiguous U.S. They were developed using different global circulation models and different downscaling methods, and were downscaled to a different scale (771 m instead of 4 km). While these cover the same time periods and use broadly similar approaches, caution should be used when directly comparing values between Alaska and the contiguous United States.Raster data are also available for download from RMRS site (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/categories/us-raster-layers.html), along with pdf maps and detailed metadata (https://www.fs.usda.gov/rm/boise/AWAE/projects/NFS-regional-climate-change-maps/downloads/NationalForestClimateChangeMapsMetadata.pdf).This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: ISO-19139 metadata ArcGIS Hub Dataset ArcGIS GeoService For complete information, please visit https://data.gov.

This data package contains 3 GIS layers showing generalized forest types across New England as delineated in older forestry publications. These were digitized so that they can be used to illustrate broad vegetation patterns across the region in modern publications. These GIS layers include maps drawn by Hawley and Hawes (1912), RT Fisher (1933), and Westveld and the Committee on Silviculture, New England Section, Society of American Foresters (1956).

The widespread influence of land use and natural disturbance on population, community, and landscape dynamics and the long-term legacy of disturbance on modern ecosystems requires that a historical, broad-scale perspective become an integral part of modern ecological studies and conservation assessment and planning. In previous studies, the Harvard Forest Long Term Ecological Research (LTER) program has developed an integrated approach of paleoecological and historical reconstruction, meteorological modeling, air photo interpretation, GIS analyses, and field studies of vegetation and soils, to address fundamental ecological questions concerning the rates, direction, and causes of vegetation change, to evaluate controls over modern species and community distributions and landscape patterns, and to provide critical background for conservation and restoration planning. In the current study, we extend this approach to investigate the link between landscape history and the abundance, distribution, and dynamics of species, communities and landscapes of the Cape Cod to Long Island coastal region, including the islands of Martha's Vineyard, Nantucket, and Block Island. The study region includes many areas of high conservation priority that are linked geographically, historically, and ecologically. This data package includes GIS layers digitized by Harvard Forest researchers from copies of the US Coastal Survey “T-Sheet” maps available from the National Archives in College Park, Maryland. The US Coastal Survey, and then the US Coast and Geodetic Survey mapped the region, or specific parts of it, several times between 1832 and the 1960s. In this project we digitized the earliest T-Sheet available for each location. The original maps were surveyed between 1832 and 1886, with most of them made between 1835 to 1855. The original maps showed features such as roads, farm walls, railroads, buildings, some industrial buildings, saltworks, wharfs, and land cover including woodlands, sandplains, grasslands, open agricultural fields, cultivated areas, fruit tree orchards, wetlands, etc. Many sheets had symbols which differentiated conifer trees from hardwoods. There were some inconsistencies in what features were mapped or how they were drawn between the original T-Sheets. Since we digitized the maps over the course of several different research projects, we did not always digitize all of the same features in each geographic area, therefore users of this data are encouraged to look at scans of the original T-Sheets for their specific areas of interest (links below). We always digitized land cover and roads and occasionally buildings and fences as mentioned in the datasets below.

The widespread influence of land use and natural disturbance on population, community, and landscape dynamics and the long-term legacy of disturbance on modern ecosystems requires that a historical, broad-scale perspective become an integral part of modern ecological studies and conservation assessment and planning. In previous studies, the Harvard Forest Long Term Ecological Research (LTER) program has developed an integrated approach of paleoecological and historical reconstruction, meteorological modeling, air photo interpretation, GIS analyses, and field studies of vegetation and soils, to address fundamental ecological questions concerning the rates, direction, and causes of vegetation change, to evaluate controls over modern species and community distributions and landscape patterns, and to provide critical background for conservation and restoration planning. In the current study, we extend this approach to investigate the link between landscape history and the abundance, distribution, and dynamics of species, communities and landscapes of the Cape Cod to Long Island coastal region, including the islands of Martha's Vineyard, Nantucket, and Block Island. The study region includes many areas of high conservation priority that are linked geographically, historically, and ecologically. This dataset includes a land cover GIS layer created from aerial photographs from 1938. Janice Stone interpreted the photos onto acetates which were then redrawn onto USGS topographic maps using a zoom transfer scope to reduce edge distortion from the photographs. The landcover polygons were then digitized into a GIS. As 1938 is near the midpoint between the peak of 19th century agricultural land clearance and the modern plant communities of the region, this data provides valuable information on changing landscape characteristics and vegetation successional patterns which shape the modern landscape.

This is the digitized version of a map of the Hohokam canal system in what is now the Phoenix metropolitan area. It is based on the thesis research by J. B. Howard "Paleohydraulics: Techniques for modeling the operation and growth of prehistoric canal systems"

The United States Public Land Survey (PLS) divided land into one square mile units, termed sections. Surveyors used trees to locate section corners and other locations of interest (witness trees). As a result, a systematic ecological dataset was produced with regular sampling over a large region of the United States, beginning in Ohio in 1786 and continuing westward.
We digitized and georeferenced archival hand drawn maps of these witness trees for 27 counties in Ohio. This dataset consists of a GIS point shapefile with 11,925 points located at section corners, recording 26,028 trees (up to four trees could be recorded at each corner). We retain species names given on each archival map key, resulting in 70 unique species common names. PLS records were obtained from hand-drawn archival maps of original witness trees produced by researchers at The Ohio State University in the 1960’s. Scans of these maps are archived as “The Edgar Nelson Transeau Ohio Vegetation Survey” at The Ohio State University: http://hdl.handle.net/1811/64106.
The 27 counties are: Adams, Allen, Auglaize, Belmont, Brown, Darke, Defiance, Gallia, Guernsey, Hancock, Lawrence, Lucas, Mercer, Miami, Monroe, Montgomery, Morgan, Noble, Ottawa, Paulding, Pike, Putnam, Scioto, Seneca, Shelby, Williams, Wyandot. Coordinate Reference System: North American Datum 1983 (NAD83). This material is based upon work supported by the National Science Foundation under grants #DEB-1241874, 1241868, 1241870, 1241851, 1241891, 1241846, 1241856, 1241930.

Sand-plain ecosystems are a priority for conservation because they are uncommon, support numerous rare or uncommon plant and animal species, serve as groundwater recharge areas, and are threatened by land development. The 5,200-acre Manuel F. Correllus State Forest, in the central part of Martha’s Vineyard, is part of one of the larger sand-plain ecosystems in New England. This GIS data package was created as part of a study on the history and ecology of Martha’s Vineyard and the state forest as part of an effort to understand sandplain landscapes and make management recommendations for their maintenance.

Land use/land cover was interpreted from historical aerial photographs for riparian buffer zones surrounding 50 lakes in Vilas County, Wisconsin. Photography from the 1930s, 1960s, and 1990s were interpreted, resulting in land use/land cover data for three time periods.

This dataset is part of a time series of maps that encompasses the development of the entire 20th century. Landuse categories include Urban, Agriculture, Desert, and Recreation. The development of these maps is to describe the nature of the change of each category between years. Based upon available data, the years used for this dataset are 1912, 1934, 1955, 1975, and 1995. Data sources used include U.S. Soil Conservation Service air photos, USGS topographic maps, Glendale Historical Society, Salt River Project historical agricultural data, and Arizona Department of Water Resoures historical agricutlural data.

The primary purpose of this dataset is to provide VCRLTER researchers and students with a convenient and comprehensive set of historical NOS t-sheet shorelines spanning the full Virginia Eastern Shore in a single GIS data layer. From NOAA-NOS-NGS source metadata: "These shoreline data represent a vector conversion of a set of NOS raster shoreline manuscripts identified by t-sheet or tp-sheet numbers. These vector data were created by contractors for NOS who vectorized georeferenced raster shoreline manuscripts using Environmental Systems Research Institute, Inc. (ESRI)(r), ArcInfo's(r) ArcScan(r) software to create individual ArcInfo coverages. The individual coverages were ultimately edgematched within a surveyed project area and appended together. The NOAA NESDIS Environmental Data Rescue Program (EDRP) funded this project. The NOAA National Ocean Service, Coastal Services Center, developed the procedures used in this project and was responsible for project oversight. The project intent was to rescue valuable historical data and make it accessible and useful to the coastal mapping community. This process involved the conversion of original analog products to digital mapping products. This file is a further conversion of that product from a raster to a vector product that may be useful for Electronic Charting and Display Information Systems (ECDIS) and geographic information systems (GIS)." Original NOAA-NOS-NGS data were organized by project, with each project containing a single shapefile containing the historical shoreline features from multiple T-sheets based on surveys from roughly the same time period. There were 43 projects containing information from 208 T-sheets and TP-sheets that were found to cover the Eastern Shore of VA and southern MD and ranging in time from 1847 to 1978 (plus one set of shorelines from 2009 for the new Chincoteague bridge and the immediate surrounding area). VCRLTER staff combined these 43 shapefiles into a single shapefile with an added "PROJID" attribute to identify the source project. This shoreline dataset compliments and overlaps other VCRLTER shoreline datasets for the Virginia barrier islands that contain historical shorelines derived from a combination of sources, including: a subset of the included NOS t-sheets (digitized by VCRLTER researchers prior to availability in digital format from NOAA-NOS-NGS); NOAA coastal change maps; photointerpretation of aerial photos (from USGS, USACE, VITA-VGIN-VBMP, and others), and satellite imagery (from ETM+ Landsat 7 and IKONOS); and GPS surveys.