39 results returned
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Title: Lowell
Contributors:- Cadastral maps
- 1909
Summary: Blueprint. Cadastral map showing landowners. Imprint: Crown Point, Ind. : F. L. Knight & Sons, 1909. Scale: Approximately 1:1,200. 1 inch = 100 feet; Dimensions: 118 x 203 cm Coordinates: W0872641 W0872302 N0411857 N0411638
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Title: Map of Lake County Indiana compiled for the official records
Contributors:- Cadastral maps
- 1908
Summary: Cadastral map showing landowners. Blackline. Imprint: Crown Point, Ind.: F. L. Knight & Sons, 1908. Scale: Approximately 1:40,000; Dimensions: 153 x 67 cm Coordinates: W0873200 W0871300 N0414200 N0411000
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Title: Map of Lake Co., Ind.
Contributors:- Not specified
- 1906
Summary: Blueprint. Shows additions and subdivisions of cities and towns. Imprint: Crown Point, Ind. : The Crown Point Register, [1906] Dimensions: 164 x 75 cm; Scale: 1:40,000 Coordinates: W0873052 W0871451 N0414130 N0410938
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Title: Calumet Region of Lake Co., Ind.
Contributors:- Cadastral maps
- 1906
Summary: Cadastral map showing landowners. Imprint: Crown Point, Ind. : F. L. Knight & Sons, 1906. Scale: 1:19,800; Dimensions: 91 x 136 cm Coordinates: W0873014 W0871640 N0414147 N0413236
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Title: Road Map of Lake County, Indiana
Contributors:- Not specified
- 1906
Summary: "Small figures represent rural routes." Imprint: Crown Point, Ind. : F.L. Knight & Sons, [1906] Scale: 1:130,000; Dimensions: 49 x 21 cm, on sheet 56 x 34 cm Coordinates: W0873200 W0871300 N0414200 N0411000
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Title: Road Map--Lake Co., Ind.
Contributors:- Road maps
- 1904
Summary: Blueprint. Imprint: Crown Point, Ind. : F. Knight & Sons, 1904. Scale: 1:130,000; Dimensions: on sheet 52 x 26 cm Coordinates: W0873136 W0871307 N0414539 N0410943
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Title: Map of East St. Cloud Survey, St. Cloud, Minnesota
Contributors:- Cadastral maps
- 1880
Summary: Map of East St. Cloud Survey, St. Cloud, Minnesota.
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Title: Map of Scandinavia park, Camrose, Alberta
Contributors:- Not specified
- 1912
Summary: "Prices of lots in Scandinavia Park" and plan of Camrose on verso. 31 x 26 centimeters, on sheet 36 x 31 centimeters
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Title: An accurate map of Hindostan or India, from the best authorities
Contributors:- Not specified
- 1817
Summary: Cartographic Details: Scale approximately 1:9,180,000 (E 64°--E 102°/N 36°--N 4°).Relief shown pictorially. Appears in the author's Carey's general atlas, improved and enlarged. 1817. Name burnished out below title, probably J.T. Scott, sculp. In top right margin: 53. 38 x 40 centimeters
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Title: City of Boston-Park Department, Marine Park grading plan
Contributors:- Not specified
- 1891
Summary: "Jan. 1891." Relief shown by contours. Includes key map. 61 x 85 centimeters
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Title: Twin Cities Metropolitan Area Urban Tree Canopy Assessment (2015)
Contributors:- Raster data ; LiDAR
- 2017
Summary: A high-resolution (1-meter) tree canopy assessment was completed for the Twin Cities Metropolitan Area. Mapping of existing and potential tree canopy is critical for urban tree management at the landscape level. This classification was created from combined 2015 aerial imagery, LIDAR data, and ancillary thematic layers. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach through multi-resolution image segmentation and an iterative set of classification commands in the form of customized rulesets. eCognition Developer was used to develop the rulesets and produce raster classification products for TCMA. The results were evaluated using randomly placed and independent verified assessment points. The classification product was analyzed at regional scales to compare distributions of tree canopy spatially and at different resolutions. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of tree canopy with highly accurate results.
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Title: Minnesota Land Cover Classification and Impervious Surface Area by Landsat and Lidar (2013 Update)
Contributors:- Vector data ; Raster data ; LiDAR
- 2016
Summary: This is a 15-meter raster dataset of a land cover and impervious surface classification for 2013, level two classification. The classification was created using a combination of multitemporal Landsat 8 data and LiDAR data with Object-based image analysis. By using objects instead of pixels we were able to utilize multispectral data along with spatial and contextual information of objects such as shape, size, texture and LiDAR-derived metrics to distinguish different land cover types. While OBIA has become the standard procedure for classification of high resolution imagery we found that it works equally well with Landsat imagery. For the objects classified as urban or developed, a regression model relating the Landsat greenness variable to percent impervious was developed to estimate and map the percent impervious surface area at the pixel level.
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Title: Duluth 1-Meter Land Cover Classification (Urban Focused)] (2016)
Contributors:- Raster data ; LiDAR
- 2016
Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.
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Title: Twin Cities Metropolitan Area 1-Meter Land Cover Classification (Urban Focused) (2016)
Contributors:- Raster data ; LiDAR
- 2016
Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.
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Title: Rochester 1-Meter Land Cover Classification (Urban Focused)] (2016)
Contributors:- Raster data ; LiDAR
- 2016
Summary: A high-resolution (1-meter) land cover classification raster dataset was completed for three different geographic areas in Minnesota: Duluth, Rochester, and the seven-county Twin Cities Metropolitan area. This classification was created using high-resolution multispectral National Agriculture Imagery Program (NAIP) leaf-on imagery (2015), spring leaf-off imagery (2011- 2014), Multispectral derived indices, LiDAR data, LiDAR derived products, and other thematic ancillary data including the updated National Wetlands Inventory, LiDAR building footprints, airport, OpenStreetMap roads and railroads centerlines. These data sets were integrated using an Object-Based Image Analysis (OBIA) approach to classify 12 land cover classes: Deciduous Tree Canopy, Coniferous Tree Canopy, Buildings, Bare Soil, other Paved surface, Extraction, Row Crop, Grass/Shrub, Lakes, Rivers, Emergent Wetland, Forest and Shrub Wetland. We mapped the 12 classes by using an OBIA approach through the creation of customized rule sets for each area. We used the Cognition Network Language (CNL) within the software eCognition Developer to develop the customized rule sets. The eCognition Server was used to execute a batch and parallel processing which greatly reduced the amount of time to produce the classification. The classification results were evaluated for each area using independent stratified randomly generated points. Accuracy assessment estimators included overall accuracies, producers accuracy, users accuracy, and kappa coefficient. The combination of spectral data and LiDAR through an OBIA method helped to improve the overall accuracy results providing more aesthetically pleasing maps of land cover classes with highly accurate results.
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Title: Charleston Harbor, South Carolina, 1856 (Raster Image)
Contributors:- Raster data
- 2013
- Harvard Map Collection, Harvard College Library
- United States Coast Survey, cartographer, publisher.
- Mc Coy, G., engraver.
- Yeager, E. (Edward), engraver.
- Knight, J., engraver.
- Danforth, F., engraver.
- Maffitt, John Newland, 1819-1886, surveyor.
- Gilbert, S. A., surveyor.
- Boutelle, C. O. (Charles Otis), surveyor.
- Bache, A. D. (Alexander Dallas), 1806-1867, surveyor.
Summary: This layer is a georeferenced raster image of the historic paper nautical chart entitled: Preliminary chart of Charleston harbor and its approaches. A trigonometrical survey under the direction of A.D. Bache, superintendent of the Survey of the Coast of the United States ; triangulation by C.O. Boutelle ; topography by S.A. Gilbert ; hydrography by the party under the command of J.N. Maffitt ; engd. by F. Danworth, J. Knight, E. Yeager & G. Mc Coy. It was published by U.S. Coast Survey Office in 1856. Scale 1:30,000. The image inside the map neatline is georeferenced to the surface of the earth and fit to the South Carolina State Plane NAD 1983 coordinate system (Fipszone 3900). 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, index maps, legends, or other information associated with the principal map. This map shows features such as drainage, cities and other human settlements, roads, built-up areas and selected buildings, docks, wharves, shoreline features (rocks, shoals, anchorage points, ports, inlets, etc.), and more. Relief shown by hachures; depths shown by contours and soundings. Includes 2 views, notes, sailing directions, tides' table, table of currents, list of buoys and of beacons. Images includes manuscript additions and newspaper clippings.This layer is part of a selection of digitally scanned and georeferenced historic maps from the Harvard Map Collection. These maps typically portray both natural and manmade features. The selection represents a range of originators, ground condition dates, scales, and map purposes.
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Title: Geneva, Switzerland, 1850 (Raster Image)
Contributors:- Raster data
- 2010
- Harvard Map Collection, Harvard College Library
- Davies, Benjamin Rees.
- Society for the Diffusion of Useful Knowledge (Great Britain).
- Charles Knight & Co.
Summary: This layer is a georeferenced raster image of the historic paper map entitled: Geneva = (Geneve), engraved by B.R. Davies. It was published by Charles Knight & Co. in 1850. Scale [ca. 1:3,600]. Covers Geneva, Switzerland. Map in English and French. The image inside the map neatline is georeferenced to the surface of the earth and fit to the 'CH1903_LV03' coordinate system. 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, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads, drainage, built-up areas and selected buildings, fortification, ground cover, and more. Includes inset: Environs of Geneva, and view: View of Geneva. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.
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Title: Moscow, Russia, 1836 (Raster Image)
Contributors:- Raster data
- 2009
- Harvard Map Collection, Harvard College Library
- Clarke, W. B.
- Davies, Benjamin Rees.
- Charles Knight & Co.
- Society for the Diffusion of Useful Knowledge (Great Britain)
Summary: This layer is a georeferenced raster image of the historic paper map entitled: [Moscow = Moskvi], drawn by W. B. Clarke, Archt., engraved by B. R. Davies. It was published under the superintendence of the Society for the Diffusion of Useful Knowledge [by] Charles Knight & Co. in 1836. Scale [ca. 1:33,000]. Covers Moscow, Russia. Map in English and Russian (including romanized Russian). The image inside the map neatline is georeferenced to the surface of the earth and fit to the European Datum 1950, Universal Transverse Mercator (UTM) Zone 37N projected coordinate system. 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, index maps, legends, or other information associated with the principal map.This map shows features such as roads, drainage, built-up areas and selected buildings, bridges, ground cover, fortification, and more. Includes illustrations.This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.
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Title: Dresden, Germany, 1851 (Raster Image)
Contributors:- Raster data
- 2008
- Harvard Map Collection, Harvard College Library
- Clarke, W. B.
- Charles Knight & Co.
- Society for the Diffusion of Useful Knowledge (Great Britain)
- Henshall, W.
Summary: This layer is a georeferenced raster image of the historic paper map entitled: Dresden, drawn by W.B. Clarke, archt.; engraved by W. Henshall. It was published under the superintendence of the Society for the Diffusion of Useful Knowledge [by] Charles Knight & Co. in [1851]. Scale [ca. 1:12,000]. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Deutsches Hauptdreiecksnetz (DHDN) 3-degree Gauss-Kruger Zone 5 coordinate system. 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, index maps, legends, or other information associated with the principal map. This map shows features such as roads, railroads and stations, drainage, built-up areas and selected buildings, parks, and more. Relief is shown by hachures. Includes views of buildings. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.
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Title: Amsterdam, Netherlands, 1850 (Raster Image)
Contributors:- Raster data
- 2008
- Harvard Map Collection, Harvard College Library
- Clarke, W. B.
- Davies, Benjamin Rees.
- Charles Knight & Co.
- Society for the Diffusion of Useful Knowledge (Great Britain)
Summary: This layer is a georeferenced raster image of the historic paper map entitled: Amsterdam, drawn by W. B. Clarke; engraved by B. R. Davies. It was published by for the Superintendance of the Society of Diffusion of Useful Knowledge [by] Charles Knight & Co. in [1850]. Scale [ca. 1:5,660]. Covers a portion of Amsterdam. The image inside the map neatline is georeferenced to the surface of the earth and fit to the Dutch National Grid: RD (Rijksdriehoekstelsel) GCS Amersfoort (Bessel 1841) coordinate system. 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, index maps, legends, or other information associated with the principal map. This map shows features such as roads, bridges, drainage, canals, dikes, wharves, docks, built-up areas and selected buildings, water mills, and more. Includes inset map: Plan of the Environs of Amsterdam, and illustrations of buildings. Map in English with place names in Dutch. This layer is part of a selection of digitally scanned and georeferenced historic maps from The Harvard Map Collection as part of the Imaging the Urban Environment project. Maps selected for this project represent major urban areas and cities of the world, at various time periods. These maps typically portray both natural and manmade features at a large scale. The selection represents a range of regions, originators, ground condition dates, scales, and purposes.