This is a map of historical ("presettlement") vegetation for the state of Oregon, created with Arcview 3.2 by merging digital data from different sources: H. J. Andrews, General Land Office (GLO), Soil Survey Geographic (SSURGO), BLM, Oregon Gap analysis. The H. J. Andrews map forms the background into which more detailed coverages were incorporated. The data consist of an ArcView shapefile. Scale varies throughout the coverage, depending on the source of the data; the overall scale is 1:100,000.

LANDSURVEY_COUNTY_POLY_IN is a 1:24,000-scale polygon shapefile, originally with a projection of Universal Transverse Mercator (UTM) North American Datum (NAD) 1983 zone 16. After republishing this shapefile by the IGIO, this data is with a projection of WGS84.This shapefile was derived from a predecessor coverage named "IN_LANDSURVEY." IN_LANDSURVEY is a digital representation of land survey features as represented on the USGS 1:24,000 digital raster graphic (DRG) series. ESRI ArcEdit 8.1 and ESRI ArcView 3.2 were used to extract the following shapefiles from IN_LANDSURVEY: LANDSURVEY_COUNTY_LINE_IN, LANDSURVEY_COUNTY_POLY_IN, LANDSURVEY_SECTIONS_LINE_IN, LANDSURVEY_SECTIONS_POLY_IN, LANDSURVEY_STATE_LINE_IN, LANDSURVEY_STATE_POLY_IN, LANDSURVEY_TOWNSHIPS_LINE_IN, and LANDSURVEY_TOWNSHIPS_POLY_IN.

This shapefile was derived from a predecessor coverage named "IN_LANDSURVEY." IN_LANDSURVEY is a digital representation of land survey features as represented on the USGS 1:24,000 digital raster graphic (DRG) series. ESRI ArcEdit 8.1 and ESRI ArcView 3.2 were used to extract the following shapefiles from IN_LANDSURVEY: LANDSURVEY_COUNTY_LINE_IN, LANDSURVEY_COUNTY_POLY_IN, LANDSURVEY_SECTIONS_LINE_IN, LANDSURVEY_SECTIONS_POLY_IN, LANDSURVEY_STATE_LINE_IN, LANDSURVEY_STATE_POLY_IN, LANDSURVEY_TOWNSHIPS_LINE_IN, and LANDSURVEY_TOWNSHIPS_POLY_IN.NOTE -- This shapefile is identical to a version named "INDIANA_STATEBDY_24K_IGS_L". This metadata file is a copy of the metadata for "INDIANA_STATEBDY_24K_IGS_L" that has had minor edits. The shapefile and metadata were renamed to conform to a file-naming convention for a project funded outside the IGS.

Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the vegetation data analysis, the formation-level vegetation map was further edited and refined to develop an association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data and additional field observations. Each polygon was assigned one of eight vegetation association types based on plot data, field observations, aerial photography signatures, and topographic maps. An aerial photograph interpretation key for the vegetation associations was created. However, several associations could not be distinguished reliably by aerial photography signatures alone. Plot data, field observations, and topographic maps were relied upon in these circumstances to inform the polygon delineation and association name assignments. After the vegetation association map was completed, the thematic accuracy of this map was assessed.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the vegetation data analysis, the formation-level vegetation map was further edited and refined to develop an association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data and additional field observations. Each polygon was attributed with the name of a vegetation association based on plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Several polygons were labeled as mosaics of two associations because both types were present in the polygons and clear boundaries between the two associations could not be delineated. The category of Cleared Land was added as an Anderson level II category (modified) for polygons that had recently undergone woodlot removal as part of the battlefield rehabilitation. After the vegetation association map was completed, the thematic accuracy of this map was assessed.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles.

Following the vegetation data analysis, the formation-level vegetation map was further edited and refined to develop an association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data and additional field observations. Each polygon was assigned one of seven vegetation associations based on plot data, field observations, aerial photography signatures, and topographic maps. An aerial photograph interpretation key for the vegetation associations and Anderson level II categories (modified) is located in Appendix A. After the vegetation association map was completed, the thematic accuracy of this map was assessed.

"Pre-European Vegetation Map of Boorowa Shire and surrounds.; Vegetation map based on classified vegetation survey data, and modelling layers, derived from a 25 metre Digital Elevation Model, and a composite geology map derived from Department of Minerals geology data. Data derived from the following sources: Digital elevation model in integer format, 25 m grid cells, produced 1997, Land Information Centre; Catchment variables derived from DEM, using Arcview 3.2; Geology data from 1:250 K Geology Map, Department of Mineral Resources of NSW; Derived Elevation, Slope Steepness, Drainage from DEM; Combined Geology and sub-catchments within Boorowa Shire; Derivation of individual grid layers for each map unit; Compilation of individual map units, using merge request function in Arcview 3.2; Derivation of vegetation mask, using Landsat ETM band 5 to create a native forest/woodland cover map; Intersection of pre-european vegetation map with M305 native woody vegetation map to produce extant layer.; ; Method used was based on expert modelling of vegetation types, based on consultant EcoGIS's (Nic Gellie) knowledge of distribution of similar vegetation types in relation to lithology and broad landscape variables. To reduce possible error in expert models, modelling zones based on a combination of lithology classes and sub-catchments were produced from expert examination of the spread and patterns of each vegetation group. The modelling zones helped to reduce the number of vegetation groups to be modelled down to 2-3 groups; Careful inspection of sites within each vegetation group helped to determine the broad environmental niche of each vegetation group. A table of possible relationships between vegetation groups and environmental variables was drawn up to help with the modelling process. It was clear that the patterns of vegetation in the study area were more influenced by geochemistry of the lithology classes and topographic position in the landscape, rather than the conventional aspect and moisture relationships found in coastal higher rainfall environments. This conclusion helped to determine the development of terrain variables that could separate vegetation groups that occurred predominantly on ridges and hillslopes from those vegetation groups that occurred in valley bottoms. A neighbourhood variable, using stream pattern derived from the watershed models within Arcview, helped to distinguish hillslopes from valley bottoms.; ; The modelling process enabled a complete audit of all vegetation types mapped in the study area and allowed a transparent and flexible process of mapping to be documented. In the event that detailed inspection of the results of the model or field validation resulted in possible changes to the map, individual modelling zones could be remodelled with the new knowledge, or new site data. This approach also prevented grid layers from spreading to areas where the vegetation groups would logically not occur in. When all modelling zones had been modelled, the resultant grid layers were then compiled into a single Arcview view. The data layers were then sorted into an agreed order of precedence that enabled each grid layer to be displayed on the final vegetation map. Reclassification and merge request functions within Arcview Spatial Analyst then produced a pre-European vegetation map. The final pre-European vegetation map was then masked with an extant vegetation cover to produce an extant vegetation map."; ; VIS_ID 1626; ; ANZLIC: ANZNS0208000216

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Following the vegetation data analysis, the vegetation cover-type map was edited and refined to develop a preliminary association-level vegetation map. Using ArcView 3.2, polygon boundaries were revised onscreen based on the plot data, field observations, classification analyses, aerial photography signatures, and topographic maps. Each polygon was assigned the name of a preliminary vegetation association based on the five information sources listed above. A mirror stereoscope type F-71 and a Bausch and Lomb zoom stereoscope were used to interpret the aerial photography signatures. The field-collected “true” or “reference” GPS coordinates for the remaining 41 points were compared to the coordinates obtained from the mosaic viewed in ArcMap.

"Extant Native Vegetation of Boorowa Shire and surrounds.; Vegetation map based on classified vegetation survey data, and modelling layers, derived from a 25 metre Digital Elevation Model, and a composite geology map derived from Department of Minerals geology data. Data derived from the following sources: Digital elevation model in integer format, 25 m grid cells, produced 1997, Land Information Centre; Catchment variables derived from DEM, using Arcview 3.2; Geology data from 1:250 K Geology Map, Department of Mineral Resources of NSW; Derived Elevation, Slope Steepness, Drainage from DEM; Combined Geology and sub-catchments within Boorowa Shire; Derivation of individual grid layers for each map unit; Compilation of individual map units, using merge request function in Arcview 3.2; Derivation of vegetation mask, using Landsat ETM band 5 to create a native forest/woodland cover map; Intersection of pre-european vegetation map with M305 native woody vegetation map to produce extant layer.; ; Method used was based on expert modelling of vegetation types, based on consultant EcoGIS's (Nic Gellie) knowledge of distribution of similar vegetation types in relation to lithology and broad landscape variables. To reduce possible error in expert models, modelling zones based on a combination of lithology classes and sub-catchments were produced from expert examination of the spread and patterns of each vegetation group. The modelling zones helped to reduce the number of vegetation groups to be modelled down to 2-3 groups; Careful inspection of sites within each vegetation group helped to determine the broad environmental niche of each vegetation group. A table of possible relationships between vegetation groups and environmental variables was drawn up to help with the modelling process. It was clear that the patterns of vegetation in the study area were more influenced by geochemistry of the lithology classes and topographic position in the landscape, rather than the conventional aspect and moisture relationships found in coastal higher rainfall environments. This conclusion helped to determine the development of terrain variables that could separate vegetation groups that occurred predominantly on ridges and hillslopes from those vegetation groups that occurred in valley bottoms. A neighbourhood variable, using stream pattern derived from the watershed models within Arcview, helped to distinguish hillslopes from valley bottoms.; ; The modelling process enabled a complete audit of all vegetation types mapped in the study area and allowed a transparent and flexible process of mapping to be documented. In the event that detailed inspection of the results of the model or field validation resulted in possible changes to the map, individual modelling zones could be remodelled with the new knowledge, or new site data. This approach also prevented grid layers from spreading to areas where the vegetation groups would logically not occur in. When all modelling zones had been modelled, the resultant grid layers were then compiled into a single Arcview view. The data layers were then sorted into an agreed order of precedence that enabled each grid layer to be displayed on the final vegetation map. Reclassification and merge request functions within Arcview Spatial Analyst then produced a pre-European vegetation map. The final pre-European vegetation map was then masked with an extant vegetation cover to produce an extant vegetation map."; ; VIS_ID 1624; ; ANZLIC: ANZNS0208000217

In order to better protect unique commercial, environmental, and cultural resources from oil spills, the Oil Pollution Act of 1990 mandated a coordinated effort by federal, state, and local regulatory agencies and the regulated community to enhance oil spill preparedness and response. This coverage provides the location and attached data for the mapping area. The development of spatial databases and geographic information systems is done pursuant to implementing the preparedness and response mandates of the Oil Pollution Act of 1990.These data were prepared at map scales of 1:24,000 and 1:100,000 and are best used in applications of comparable resolution. In addition, these data were developed to meet specific project objectives and therefore may not represent exhaustive feature inventories.Locational information and the attached database information for the tribal interest coverage were primarily obtained from the members of tribal administrations and local government agencies after an initial identification period that included the use of generic maps and information from U.S. federal, state, regional, and local agencies with holdings in the Michigan Mapping Area were also contacted for site-specific information. The 7.5 minute quadrangle maps, as digital raster graphics, were also used as a base layer for locational and boundary information. The Delorme Atlas and Gazetteer series for Michigan also provided additional supporting information for location and in some instances basic contact information. Phone and mail correspondence was also used to fill in applicable data gaps in preparation of the draft atlas. The data was plotted in a GIS using ESRI's ArcView 3.2 and displayed against the digital raster imagery at a scale of 1:24,000. Data links were incoporated into these GIS files to match the mapped sites to the appropriate data record as outlined in Section 5.2.1, Entity and Attribute Overview. Draft hard copy atlases were prepared from this data, supplied by the Great Lakes Commission, and the USGS's Upper Midwest Environmental Sciences Center (UMESC) in Onalaska, Wisconsin. The UMESC produced hard copy maps in portable document files (.pdf) format at scales of 1:25,000 and 1:100,000. These maps were then reproduced and distributed by the Great Lakes Commission for external review by primary source data holders. All updated, corrected and amended information was then added to the project files and returned to the UMESC for distribution in .pdf hardcopy format; and electronic distribution via CD-ROM and the Internet. Final electronic formats include ArcView 3.2 shapefiles, .e00 ArcExport files, .pdfs, and converted CAMEO/Landview files.Regional data was merged using Geoprocessing Wizard to create a statewide coverage and was then clipped to the Huron Basin, which included a 25 kilometer buffer. The Huron basin coverage was reprojected, changing the datum from NAD 27 to NAD 83, using the MI DNR Projection Extension.Great Lakes Commission staff working on the Area Contingency Planning project verified all descriptive and spatial attributes and collected confirmation from owners and/or managers of attributes and boundaries via surveys or direct external review. Spatial data were cross-checked with multiple sources.Data were developed for this layer utilizing multiple primary sources, from federal, state, and local governmental agencies and owner/operators of the tribal interests. These primary sources include USGS 7.5 minute quadrangle maps; federal state, local and private land manager/owner hard copy and electronic sources; and an exhaustive holders of data. Initial data were supplied by state agencies maintining tribal lands records state-wide in hard copy and electronic format. Data was reviewed for location and accuracy at the scale of 1:24,000 on appropriate base maps. Location and attribute information is only as accurate and complete as the informaiton specifically applies to each individual record at the time of data development. Data for these facilities are primarily atrributed polygons, plotted in ArcView 3.2 GIS. These polygons were generated in 1999 and updated in 2000 based on current information from primary sources but do not necessarily always exactly overlay the base map 7.5 minute quadrangle maps with previous publication dates.This coverage does not necessarily include all tribal interest areas within the Huron Basin. Exhaustive efforts were made to compile as thorough an atlas as possible, with particular in depth detail paid to those areas in proximity to surface waters. However, under-reporting may occur.Horizontal positional accuracy is tested by visual comparison of hard copy check plots to the source materials and verifying the location of the data on screen relative to other data layers in the same geographic area.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The vegetation classification and mapping processes were conducted essentially in tandem. Mappers and ecologists conferred to review the list of potential associations, as well as the appropriate scale for mapping. Photos were viewed in stereo and preliminary polygon boundaries were delineated with a .30-mm rapidograph pen on polypropylene sleeves placed over the aerial photos. Preliminary polygons were classified and labeled with their appropriate USNVC association using the aerial photograph interpretation key and USNVC descriptions, and by conferring with NatureServe ecologists. The initial line work was also used to determine a sampling scheme for plot and observation data collection, and the USNVC association list resulting from the field work was used to aid polygon classification. Once delineations were groundtruthed and rectified, USNVC association-level polygon line work was transferred to GIS shapefiles via onscreen digitizing in ArcView v.3.2a (ESRI 1992–2000). USNVC association and Anderson Level II (modified) land use names and codes were added to the attribute table of the vegetation shapefile. A separate wetland map for the park was created from the vegetation map polygons belonging to the Saturated Cold-deciduous Forest and Saturated Temperate Perennial Forb Vegetation formations.

Edited: This dataset contains a 500 foot buffered subset of features for "Hard Banks" in the Northwest Gulf of Mexico. Features in this dataset were used to satisfy Texas Resource Management Codes Sensitive Areas definitions requirements. Original: This layer depicts shelf sediment textures, hard banks, and gravel deposits on the continental shelf of the U. S. Gulf of Mexico as a map and is summarized from 16 different sources (U. S. Department of the Interior 1983, Visual No. 3). The visual was prepared from existing sources to accompany an Environmental Impact Statement. The visual displays general classification of bottom sediments (using the Shepard pyramid) throughout the Gulf of Mexico. The U. S. Department of the Interior does not guarantee the accuracy of the map to the extent of responsibility of liability for reliance thereon. This visual is not to be used for navigation purposes, nor is it a legal document for federal leasing purposes. Polygons delineating sediment types in the Gulf of Mexico were digitized with ArcView 3.2a software and a CalComp Drawing Board III. The layer was modified from the map and stored in a non-projected format with coordinates in decimal degrees.Field Definition:For field definitions contact the National Oceanic and Atmospheric Administration

Description

Functional archaeological sites (sites properly dated and interpreted), indications of occupation (sites poorly dated and/or misinterpreted) and isolated discoveries known from the documentation of the Heritage Office of the Seine-Saint-Denis department, and validated by the Regional Archaeology Service. Several sites can be grouped into a global site. The contours were produced under ArcView 3.2 on the Perdif. Since initial location documents relate to variable scales, the contour may have variable meanings specified in the location accuracy field of the winning table.

Sources

Department of Seine-Saint-Denis — Departmental Geographic Information System (GIS)

** Origin of the data — Producer**

Directorate for Culture, Heritage, Sport and Recreation

Column list

— codeite: Site code — ID: Geometry (Lambert93) — source: Digitisation source — country code: Patriarch Code — codemerimee: Mérimé code — municipality: main municipality — commune2: secondary municipality — address: address — inventinforenq: Referrer — anneedecouvenq: Year of discovery — etatdecouverte: State of discovery — levelinterpretation: Level of interpretation — precision grip: Accuracy of the right-of-way — denomination: Name — precisiondeno: Accuracy of the right-of-way — destsuccactu: destsuccactu — name: name — description: description

Distribution format

These files are offered in the form of:

Geojson files (UTF-8 encoding and WGS84 projection) Csv files (ANSI encoding)

Contact

If you have any questions, or report an improvement, you can contact us at data93@cg93.fr

Links

— See the sheet on the Seine-Saint-Denis Open Data Portal — See on the map portal of Seine-Saint-Denis

The Wildlife Conservation Society (WCS) has digitally captured the Townsend Whaling Charts that were published as a series of 4 charts with the article titled "The distribution of certain whales as shown by logbook records of American whale ships" by Charles Haskins Townsend in the journal Zoologica in 1935.The 4 charts show the locations of over 50,000 captures of 4 whale species; sperm whales (36,908), right whales (8,415), humpback whales (2,883) and bowhead whales (5,114). Capture locations were transcribed from North American (“Yankee”) pelagic whale vessel log books dating from 1761 to 1920 and plotted onto nautical charts in a Mercator projection by a cartographer. Each point plotted on the charts represents the location of a whaling ship on a day when one or more whales were taken and is symbolized by month of the year using a combination of color and open and closed circles.Townsend and his cartographer plotted vessel locations as accurately as possible according to log book records. When plotting locations on an earlier sperm whale chart published in 1931 the cartographer spaced points where locations were very dense, "extending areas slightly" for a number of whaling grounds. However, for charts in preparation at this time, Townsend states that "this difficulty is avoided by omitting some of the data, rather than extend the ground beyond actual whaling limits." We assumed that this statement refers to the 1935 charts but there is still some question as to whether the cartographer did in fact space locations and thus expand whaling grounds.The charts were then georeferenced in the native projection of the charts, the Mercator projection, using GIS software (ESRI ArcView 3.2). Each vessel capture location plotted on the charts was then digitized as a point feature and attributed with the month of capture. One GIS file (ESRI shapefile) was then created for each whale species represented by the charts; sperm whale, right whale, humpback whale and bowhead whale.Digitizing errors include missed points, particularly from areas of dense chart locations, and incorrect assignment of month of capture because of difficulty distinguishing between chart colors. However to limit these errors multiple checks of digitized and chart locations were made and color enhancements of chart scans were used to ensure correct month assignments. Overall we are confident that at least 95% of catch locations have been digitized and that at least 95% of month attributes are correct.For full resolution digital copies of the Townsend charts please contact Gillian Woolmer (gwoolmer@wcs.org).

SW_COAL_ENTRY, the predecessor of COAL_MINE_ENTRIES_IN, is a point- based ESRI ArcView shapefile that shows the locations of underground coal mine entrances in the coal region of Indiana. SW_COAL_ENTRY includes entrance locations of underground mines that operated in Indiana since the mid-1800s. COAL_MINE_ENTRIES_IN is attributed to allow the mine entrances to be differentiated based on entrance type (hoist shaft, other shafts, slope, unknown), depth, mine number, source information (map number), and azimuth (a numeric value between 0 and 360 used in ArcView GIS version 3.2, with the symbol used by COAL_MINE_ENTRIES_IN.avl, to rotate the slope entrance symbols to the approximate orientation of the actual mine entrances).

This archive consists of marine seismic reflection profile data collected in four survey areas from southeast of Charleston Harbor to the mouth of the North Edisto River of South Carolina. These data were acquired June 26 - July 1, 1996, aboard the R/V G.K. Gilbert. Included here are data in a variety of formats including binary, American Standard Code for Information Interchange (ASCII), Hyper Text Markup Language (HTML), Portable Document Format (PDF), Rich Text Format (RTF), Graphics Interchange Format (GIF) and Joint Photographic Experts Group (JPEG) images, and shapefiles. Binary data are in Society of Exploration Geophysicists (SEG) SEG-Y format and may be downloaded for further processing or display. Reference maps and GIF images of the profiles may be viewed with a web browser. The Geographic Information Systems (GIS) map documents provided were created with Environmental Systems Research Institute (ESRI) GIS software ArcView 3.2 and 8.1. For more information on the seismic surveys see http://walrus.wr.usgs.gov/infobank/g/g196sr/html/g-1-96-sr.meta.html These data are also available via GeoMapApp (http://www.geomapapp.org/) and Virtual Ocean ( http://www.virtualocean.org/) earth science exploration and visualization applications.

During 1992, 1:20,000 scale aerial photography for Bogue Sound, North Carolina was collected as part of an effort to map submerged aquatic vegetation (SAV) in Coastal North Carolina. The imagery was collected following a strict set of guidelines as detailed in NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (NOAA Technical Report NMFS 123 1995; see Chapter 4 online at www.coast.noaa.gov/crs/lca/methods.html). Photographs were taken at low tide and during times that the growth stage of the SAV allowed for clear identification. Care was taken to minimize the effects of turbidity, sun glint, wind, and haze on the photos. The imagery was scanned using a photogrammetric quality scanner (AGFA Horizon Plus) at a resolution of 600 dots per inch (dpi) resulting in a pixel resolution of 0.85 meters. Signature development took place during the summer of 2001. The images were orthorectified using ground control points selected from the state digital orthoquads and the National Imagery and Mapping Agency (NIMA) Digital Terrain Elevation Data (DTED(r)). The benthic data is classified according to the System for Classification of Habitats in Estuarine and Marine Environments (SCHEME). This system is fully described in "Development of a System for Classification of Habitats in Estuarine and Marine Environments (SCHEME) for Florida, Report to U.S. EPA - Gulf of Mexico Program, Florida Fish and Wildlife Conservation Commission, Florida Marine Research Institute. Review Draft 12/04/02." The images were interpreted and digitized on screen using ArcGIS 8.2 and labeled using ArcView 3.2 and the Benthic Habitat Digitizer extension (developed by the NOS Biogeography Program). The data have not been assessed for thematic accuracy due to the large disparity between dates of image acquisition in 1992 and interpretation in 2002. The data was assessed for horizontal spatial accuracy and thematic agreement during the fall of 2002. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

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 represents parcels not mapped or sourced in Vector Property Map. Please refer to the common ownership lots layer in https://opendata.dc.gov for the most current data on ownership. Property Owner Points. This dataset contains points that represent the approximate location of real property lots within the District of Columbia. Each property point is generated based on a corresponding record maintained within the Office of Tax and Revenue (OTR) Real Property Tax Administration's (RPTA) real property database. Each point contains the full attribution of database fields derived from ITS public release extract. The initial data conversion effort was begun in 1997 as a means to provide RPTA with a digital mapping system which could be maintained to reflect ongoing changes to property lots and ownership. The initial step was to scan RPTA tax square maps from aperture cards at an effective paper resolution of 400 DPI. The resulting images were then georeferenced to DC's 0.2-meter resolution 1995 digital orthophotos. During the georeferencing process, the images were not warped; they were simply scaled and rotated to best fit the orthophotos. The DC tax assessor provided a database of active tax accounts which were placed interactively by an operator using the georeferenced square image and the orthophoto. Centroids were placed on the primary structure visible in the orthophoto within the raster property polygon. The placement was performed within ArcView 3.2 using a customized data production application. Accounts which could not be placed in the first pass were then reviewed by another operator to attempt to find their correct location. The placed points were QC'd through a spatial overlay with the square index to assure a match between the square field value within the property database and the actual square polygon into which the point was placed. Spot checking was then performed to confirm that the centroids fell within the correct raster lot. The centroids were delivered to OTR as a single citywide AutoCAD DWG file. Attribute features with square, suffix, and lot numbers (SSLs) were included as an AutoCAD block.