4 resultados para Boston Common

em Harvard University


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This layer is a georeferenced raster image of the historic paper map entitled: Plan of portion of park system from Common to Franklin Park : including Charles River Basin, Charlesbank, Commonwealth Avenue, Back Bay Fens, Muddy River Improvement, Leverett Park, Jamaica Park, Arborway and Arnold Arboretum, [by] William Jackson, city engineer ; Olmsted, Olmsted & Eliot, landscape architects. It was published in Jan. 1894. Scale [ca. 1:9,000]. Covers Boston parks collectively known as the "Emerald Necklace." The image inside the map neatline is georeferenced to the surface of the earth and fit to the Massachusetts State Plane Coordinate System, Mainland Zone (in Feet) (Fipszone 2001). All map collar and inset information is also available as part of the raster image, including any inset maps, profiles, statistical tables, directories, text, illustrations, or other information associated with the principal map. This map shows park features such as roads, paths, recreational buildings and facilities, ground cover, and drainage. Also includes features surrounding parks: city roads, railroads, drainage, some public buildings, and more. This layer is part of a selection of digitally scanned and georeferenced historic maps of Massachusetts from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of regions, originators, ground condition dates (1755-1922), scales, and purposes. The digitized selection includes maps of: the state, Massachusetts counties, town surveys, coastal features, real property, parks, cemeteries, railroads, roads, public works projects, etc.

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This group of records contains deeds and related documents for a selection of properties owned by Harvard University in Boston and possibly Cambridge and other nearby communities through the mid 1940s. Documents include deeds, assignments of mortgages, receipts, correspondence, and other legal documents. Many of the documents record property transfers prior to Harvard's acquisition of the property, and often the documents do not fully identify Harvard's involvement with the property. The bulk of the documents date from the late 19th and early 20th centuries.

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LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

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This dataset consists of 2D footprints of the buildings in the metropolitan Boston area, based on tiles in the orthoimage index (orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 237890, 237894, 237898, 237902, 241890, 241894, 241898, 241902, 245898, 245902). This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). Roof height and footprint elevation attributes (derived from 1-meter resolution LIDAR (LIght Detection And Ranging) data) are included as part of each building feature. This data can be combined with other datasets to create 3D representations of buildings and the surrounding environment.