This Python script (Shape2DJI_Pilot_KML.py) will scan a directory, find all the ESRI shapefiles (.shp), reproject to EPSG 4326 (geographic coordinate system WGS84 ellipsoid), create an output directory and make a new Keyhole Markup Language (.kml) file for every line or polygon found in the files. These new *.kml files are compatible with DJI Pilot 2 on the Smart Controller (e.g., for M300 RTK). The *.kml files created directly by ArcGIS or QGIS are not currently compatible with DJI Pilot.

Introduction

Geographical scale, in terms of spatial extent, provide a basis for other branches of science. This dataset contains newly proposed geographical and geological GIS boundaries for the Pan-Tibetan Highlands (new proposed name for the High Mountain Asia), based on geological and geomorphological features. This region comprises the Tibetan Plateau and three adjacent mountain regions: the Himalaya, Hengduan Mountains and Mountains of Central Asia, and boundaries are also given for each subregion individually. The dataset will benefit quantitative spatial analysis by providing a well-defined geographical scale for other branches of research, aiding cross-disciplinary comparisons and synthesis, as well as reproducibility of research results.

The dataset comprises three subsets, and we provide three data formats (.shp, .geojson and .kmz) for each of them. Shapefile format (.shp) was generated in ArcGIS Pro, and the other two were converted from shapefile, the conversion steps refer to 'Data processing' section below. The following is a description of the three subsets:

(1) The GIS boundaries we newly defined of the Pan-Tibetan Highlands and its four constituent sub-regions, i.e. the Tibetan Plateau, Himalaya, Hengduan Mountains and the Mountains of Central Asia. All files are placed in the "Pan-Tibetan Highlands (Liu et al._2022)" folder.

(2) We also provide GIS boundaries that were applied by other studies (cited in Fig. 3 of our work) in the folder "Tibetan Plateau and adjacent mountains (Others’ definitions)". If these data is used, please cite the relevent paper accrodingly. In addition, it is worthy to note that the GIS boundaries of Hengduan Mountains (Li et al. 1987a) and Mountains of Central Asia (Foggin et al. 2021) were newly generated in our study using Georeferencing toolbox in ArcGIS Pro.

(3) Geological assemblages and characters of the Pan-Tibetan Highlands, including Cratons and micro-continental blocks (Fig. S1), plus sutures, faults and thrusts (Fig. 4), are placed in the "Pan-Tibetan Highlands (geological files)" folder.

Note: High Mountain Asia: The name ‘High Mountain Asia’ is the only direct synonym of Pan-Tibetan Highlands, but this term is both grammatically awkward and somewhat misleading, and hence the term ‘Pan-Tibetan Highlands’ is here proposed to replace it. Third Pole: The first use of the term ‘Third Pole’ was in reference to the Himalaya by Kurz & Montandon (1933), but the usage was subsequently broadened to the Tibetan Plateau or the whole of the Pan-Tibetan Highlands. The mainstream scientific literature refer the ‘Third Pole’ to the region encompassing the Tibetan Plateau, Himalaya, Hengduan Mountains, Karakoram, Hindu Kush and Pamir. This definition was surpported by geological strcture (Main Pamir Thrust) in the western part, and generally overlaps with the ‘Tibetan Plateau’ sensu lato defined by some previous studies, but is more specific.

More discussion and reference about names please refer to the paper. The figures (Figs. 3, 4, S1) mentioned above were attached in the end of this document.

Data processing

We provide three data formats. Conversion of shapefile data to kmz format was done in ArcGIS Pro. We used the Layer to KML tool in Conversion Toolbox to convert the shapefile to kmz format. Conversion of shapefile data to geojson format was done in R. We read the data using the shapefile function of the raster package, and wrote it as a geojson file using the geojson_write function in the geojsonio package.

Version

Version 2022.1.

Acknowledgements

This study was supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB31010000), the National Natural Science Foundation of China (41971071), the Key Research Program of Frontier Sciences, CAS (ZDBS-LY-7001). We are grateful to our coauthors insightful discussion and comments. We also want to thank professors Jed Kaplan, Yin An, Dai Erfu, Zhang Guoqing, Peter Cawood, Tobias Bolch and Marc Foggin for suggestions and providing GIS files.

Citation

Liu, J., Milne, R. I., Zhu, G. F., Spicer, R. A., Wambulwa, M. C., Wu, Z. Y., Li, D. Z. (2022). Name and scale matters: Clarifying the geography of Tibetan Plateau and adjacent mountain regions. Global and Planetary Change, In revision

Jie Liu & Guangfu Zhu. (2022). Geographical and geological GIS boundaries of the Tibetan Plateau and adjacent mountain regions (Version 2022.1). https://doi.org/10.5281/zenodo.6432940

Contacts

Dr. Jie LIU: E-mail: liujie@mail.kib.ac.cn;

Mr. Guangfu ZHU: zhuguangfu@mail.kib.ac.cn

Institution: Kunming Institute of Botany, Chinese Academy of Sciences

Address: 132# Lanhei Road, Heilongtan, Kunming 650201, Yunnan, China

Copyright

This dataset is available under the Attribution-ShareAlike 4.0 International (CC BY-SA 4.0).

The South Florida Water Management District (SFWMD) and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 174 NOAA Atlas 14 stations in central and south Florida. The change factors were computed as the ratio of projected future to historical extreme precipitation depths fitted to extreme precipitation data from various downscaled climate datasets using a constrained maximum likelihood (CML) approach. The change factors correspond to the period 2050-2089 (centered in the year 2070) as compared to the 1966-2005 historical period. An areal reduction factor (ARF) is computed to convert rainfall statistics of a point, such as at a weather station, to an area, such as a watershed or model grid cell. Regions considered for the development of change factors as part of this study study are taken from NOAA National Center for Environmental Information (NCEI) U.S. Climate Divisions for the state of Florida with some modifications in south Florida. Geospatial data provided in an ArcGIS shapefile are described herein. Areal reduction factors (ARF) and their standard deviation have been calculated for each region. For each model grid cell closest to each NOAA Atlas 14 station, return levels for extreme precipitation depth are adjusted from the area-scale to the station-scale by dividing by the areal reduction factor (ARF) for the ARF region where the station is located. See Areal_reduction_factors.xlsx and Table 1 of Datasets_station_information.xlsx for the ARF data by ARF region, event duration, and model grid-cell area.

Stream network data originated from USGS National Hydrologic Database (NHD). While the NHD is a very useful and spatially accurate dataset, it is missing one attribute that is commonly referenced as a method to classify and stratify streams, the Strahler Stream Order. Stream order information was available on the Surface Waters Information Management System (SWIMS), digitized from 1:100,000 scale maps. ArcGIS was used to convert the SWIMS vectors to points, spaced at 100 meter intervals, and then to calculate the distance to nearest point (NHD stream to SWIMS points). For each arc segment, the attributes of the nearest point were then appended to the attribute table. While this process successfully added the stream order to the NHD arcs, there were some errors. There were instances of the nearest point to a segment actually belonging to a tributary, and being incorrectly assigned to the wrong stream segment. Also, since the NHD data is much more detailed in its inclusion of smaller streams, the origin for the calculation of 1st order and 2nd order streams is different. Efforts were made to address and correct both of these issues, but users should recognize that not all errors were corrected.The stream network was manually scanned for inconsistencies in stream order flow (jumping from a 3rd order to 1st order, and then back to a 3rd order) and corrected. Emphasis was placed on correcting the larger (3rd order and greater) steams first, and many (but not all) of the 1st and 2nd order. Instances of stream beginnings being mislabeled as an order greater than 1st order were corrected by searching for all dangling arcs (stream beginnings) and then recoding them to a order of 1. This process corrected 1,199 arcs that had been incorrectly coded. One last issue users should be aware of is that since the NHD includes streams not used in calculating the Strahler order in the SWIMS dataset, there are inconsistencies in the labeling of 1st and 2nd order streams. Some corrections were made where obvious lager gaps were in the SWIMS database, but for the most part the original SWIMS stream order was transferred directly. Where adjustments were made, they were only made to lower (less then 4th order) streams.Last Updated October 2013.

Hydrographic sheets (H-sheets) and nautical charts produced by the National Ocean Service (NOS) during the 1800s provide historic sounding (water depth) measurements of coastal areas. The data can be vectorized into a geographic information system (GIS), adjusted to a modern vertical datum, and converted into a digital elevation model to provide an interpretation of the historic seafloor elevation. These data were produced to provide an estimate of historical bathymetry for the Mississippi-Alabama coastal region to aid geologic and coastal hazards studies. This data release includes georeferenced H-sheets, depth soundings, and a bathymetric grid derived from the 1847 and 1895 soundings. The original NOS H-sheets and nautical charts were scanned by the National Oceanic and Atmospheric Administration (NOAA) and are available through the National Geophysical Data Center (NGDC) website (NOAA, 2021) as non-georeferenced digital raster files. U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) staff performed the following procedures: H-sheets were georeferenced, georeferenced raster images were projected to a modern datum, and historical bathymetric sounding measurements were digitized to create a vector point shapefile. Sounding data were converted from feet (ft) and fathoms (fm) to meters (m), projected to modern mean low water (MLW), and converted to the North American Vertical Datum of 1988 (NAVD88) GEOID12A using NOAA's datum transformation software, VDatum. Please read the full metadata for details on data collection, digitized data, dataset variables, and data quality.

Dataset Card for Dataset Name

Reformatted from stanfordnlp/SHP dataset. To make it consistent with other preference dsets, we:

convert upvotes to scores in a [1, 10] scale. This is achieved by 1) convert the better response's upvotes to score of [5.0, 10.0] by:def shp_map_score(score, threshold=78): # 78 is chosen because about the best 10% data has score > 78 if score > threshold: return 10.0 # linearly map the rest # start with 5.0 because we assume that any… See the full description on the dataset page: https://huggingface.co/datasets/when2rl/SHP_reformatted.

Seattle Parks and Recreation GIS Map Layer Shapefile - Public Art Outside Park

Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata.

OR

Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/34

The Florida Flood Hub for Applied Research and Innovation and the U.S. Geological Survey have developed projected future change factors for precipitation depth-duration-frequency (DDF) curves at 242 National Oceanic and Atmospheric Administration (NOAA) Atlas 14 stations in Florida. The change factors were computed as the ratio of projected future to historical extreme-precipitation depths fitted to extreme-precipitation data from downscaled climate datasets using a constrained maximum likelihood (CML) approach as described in https://doi.org/10.3133/sir20225093. The change factors correspond to the periods 2020-59 (centered in the year 2040) and 2050-89 (centered in the year 2070) as compared to the 1966-2005 historical period. An areal reduction factor (ARF) is computed to convert rainfall statistics of a point, such as at a weather station, to an area, such as a watershed or model grid cell. Regions considered for the development of change factors as part of this study study are taken from NOAA National Center for Environmental Information (NCEI) U.S. Climate Divisions for the state of Florida with some modifications in south Florida. Geospatial data provided in an ArcGIS shapefile are described herein. Areal reduction factors (ARF) and their standard deviation have been calculated for each region. For each model grid cell closest to each NOAA Atlas 14 station, return levels for extreme precipitation depth are adjusted from the area-scale to the station-scale by dividing by the areal reduction factor (ARF) for the ARF region where the station is located. See Areal_reduction_factors.xlsx and Table 1 of Datasets_station_information.xlsx for the ARF data by ARF region, event duration, and model grid-cell area.

Parcels and property data maintained and provided by Lee County Property Appraiser are converted to points. Property attribute data joined to parcel GIS layer by Lee County Government GIS. This dataset is generally used in spatial analysis.Process description: Parcel polygons, condominium points and property data provided by the Lee County Property Appraiser are processed by Lee County's GIS Department using the following steps:Join property data to parcel polygons Join property data to condo pointsConvert parcel polygons to points using ESRI's ArcGIS tool "Feature to Point" and designate the "Source" field "P".Load Condominium points into this layer and designate the "Source" field "C". Add X/Y coordinates in Florida State Plane West, NAD 83, feet using the "Add X/Y" tool.Projected coordinate system name: NAD_1983_StatePlane_Florida_West_FIPS_0902_FeetGeographic coordinate system name: GCS_North_American_1983

 Name
 Type
 Length
 Description


 STRAP
 String
 25
 17-digit Property ID (Section, Township, Range, Area, Block, Lot)


 BLOCK
 String
 10
 5-digit portion of STRAP (positions 9-13)


 LOT
 String
 8
 Last 4-digits of STRAP


 FOLIOID
 Double
 8
 Unique Property ID


 MAINTDATE
 Date
 8
 Date LeePA staff updated record


 MAINTWHO
 String
 20
 LeePA staff who updated record


 UPDATED
 Date
 8
 Data compilation date


 HIDE_STRAP
 String
 1
 Confidential parcel ownership


 TRSPARCEL
 String
 17
 Parcel ID sorted by Township, Range & Section


 DORCODE
 String
 2
 Department of Revenue. See https://leepa.org/Docs/Codes/DOR_Code_List.pdf


 CONDOTYPE
 String
 1
 Type of condominium: C (commercial) or R (residential)


 UNITOFMEAS
 String
 2
 Type of Unit of Measure (ex: AC=acre, LT=lot, FF=frontage in feet)


 NUMUNITS
 Double
 8
 Number of Land Units (units defined in UNITOFMEAS)


 FRONTAGE
 Integer
 4
 Road Frontage in Feet


 DEPTH
 Integer
 4
 Property Depth in Feet


 GISACRES
 Double
 8
 Total Computed Acres from GIS


 TAXINGDIST
 String
 3
 Taxing District of Property


 TAXDISTDES
 String
 60
 Taxing District Description


 FIREDIST
 String
 3
 Fire District of Property


 FIREDISTDE
 String
 60
 Fire District Description


 ZONING
 String
 10
 Zoning of Property


 ZONINGAREA
 String
 3
 Governing Area for Zoning


 LANDUSECOD
 SmallInteger
 2
 Land Use Code


 LANDUSEDES
 String
 60
 Land Use Description


 LANDISON
 String
 5
 BAY,CANAL,CREEK,GULF,LAKE,RIVER & GOLF


 SITEADDR
 String
 55
 Lee County Addressing/E911


 SITENUMBER
 String
 10
 Property Location - Street Number


 SITESTREET
 String
 40
 Street Name


 SITEUNIT
 String
 5
 Unit Number


 SITECITY
 String
 20
 City


 SITEZIP
 String
 5
 Zip Code


 JUST
 Double
 8
 Market Value


 ASSESSED
 Double
 8
 Building Value + Land Value


 TAXABLE
 Double
 8
 Taxable Value


 LAND
 Double
 8
 Land Value


 BUILDING
 Double
 8
 Building Value


 LXFV
 Double
 8
 Land Extra Feature Value


 BXFV
 Double
 8
 Building Extra Feature value


 NEWBUILT
 Double
 8
 New Construction Value


 AGAMOUNT
 Double
 8
 Agriculture Exemption Value


 DISAMOUNT
 Double
 8
 Disability Exemption Value


 HISTAMOUNT
 Double
 8
 Historical Exemption Value


 HSTDAMOUNT
 Double
 8
 Homestead Exemption Value


 SNRAMOUNT
 Double
 8
 Senior Exemption Value


 WHLYAMOUNT
 Double
 8
 Wholly Exemption Value


 WIDAMOUNT
 Double
 8
 Widow Exemption Value


 WIDRAMOUNT
 Double
 8
 Widower Exemption Value


 BLDGCOUNT
 SmallInteger
 2
 Total Number of Buildings on Parcel


 MINBUILTY
 SmallInteger
 2
 Oldest Building Built


 MAXBUILTY
 SmallInteger
 2
 Newest Building Built


 TOTALAREA
 Double
 8
 Total Building Area


 HEATEDAREA
 Double
 8
 Total Heated Area


 MAXSTORIES
 Double
 8
 Tallest Building on Parcel


 BEDROOMS
 Integer
 4
 Total Number of Bedrooms


 BATHROOMS
 Double
 8
 Total Number of Bathrooms / Not For Comm


 GARAGE
 String
 1
 Garage on Property 'Y'


 CARPORT
 String
 1
 Carport on Property 'Y'


 POOL
 String
 1
 Pool on Property 'Y'


 BOATDOCK
 String
 1
 Boat Dock on Property 'Y'


 SEAWALL
 String
 1
 Sea Wall on Property 'Y'


 NBLDGCOUNT
 SmallInteger
 2
 Total Number of New Buildings on ParcelTotal Number of New Buildings on Parcel


 NMINBUILTY
 SmallInteger
 2
 Oldest New Building Built


 NMAXBUILTY
 SmallInteger
 2
 Newest New Building Built


 NTOTALAREA
 Double
 8
 Total New Building Area


 NHEATEDARE
 Double
 8
 Total New Heated Area


 NMAXSTORIE
 Double
 8
 Tallest New Building on Parcel


 NBEDROOMS
 Integer
 4
 Total Number of New Bedrooms


 NBATHROOMS
 Double
 8
 Total Number of New Bathrooms/Not For Comm


 NGARAGE
 String
 1
 New Garage on Property 'Y'


 NCARPORT
 String
 1
 New Carport on Property 'Y'


 NPOOL
 String
 1
 New Pool on Property 'Y'


 NBOATDOCK
 String
 1
 New Boat Dock on Property 'Y'


 NSEAWALL
 String
 1
 New Sea Wall on Property 'Y'


 O_NAME
 String
 30
 Owner Name


 O_OTHERS
 String
 120
 Other Owners


 O_CAREOF
 String
 30
 In Care Of Line


 O_ADDR1
 String
 30
 Owner Mailing Address Line 1


 O_ADDR2
 String
 30
 Owner Mailing Address Line 2


 O_CITY
 String
 30
 Owner Mailing City


 O_STATE
 String
 2
 Owner Mailing State


 O_ZIP
 String
 9
 Owner Mailing Zip


 O_COUNTRY
 String
 30
 Owner Mailing Country


 S_1DATE
 Date
 8
 Most Current Sale Date > $100.00


 S_1AMOUNT
 Double
 8
 Sale Amount


 S_1VI
 String
 1
 Sale Vacant or Improved


 S_1TC
 String
 2
 Sale Transaction Code


 S_1TOC
 String
 2
 Sale Transaction Override Code


 S_1OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_2DATE
 Date
 8
 Previous Sale Date > $100.00


 S_2AMOUNT
 Double
 8
 Sale Amount


 S_2VI
 String
 1
 Sale Vacant or Improved


 S_2TC
 String
 2
 Sale Transaction Code


 S_2TOC
 String
 2
 Sale Transaction Override Code


 S_2OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_3DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_3AMOUNT
 Double
 8
 Sale Amount


 S_3VI
 String
 1
 Sale Vacant or Improved


 S_3TC
 String
 2
 Sale Transaction Code


 S_3TOC
 String
 2
 Sale Transaction Override Code


 S_3OR_NUM
 String
 13
 Original Record (Lee County Clerk)


 S_4DATE
 Date
 8
 Next Previous Sale Date > $100.00


 S_4AMOUNT
 Double
 8
 Sale Amount


 S_4VI
 String
 1
 Sale Vacant or Improved


 S_4TC
 String
 2
 Sale Transaction Code


 S_4TOC
 String
 2
 Sale Transaction Override Code


 S_4OR_NUM
 String
 13

Seattle Parks and Recreation GIS Map Layer Shapefile - Ash Cans

Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata.

OR

Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/1

Please read all of the information below before downloading and using this file. Overview: The purpose of this file is to allow NCDOT employees to track and locate areas that need to be preserved and/or maintained for mitigation credit as part of various permits. They include projects built both off- and onsite throughout the state, as well as projects done as full delivery from consultants and projects partially built or managed by other agencies (e.g. NC Ecosystem Enhancement Program or EEP). The sites in this service are only a portion of the known sites in the state, as the database they were pulled from is a work in progress. These files should not be used or cited in official documents. Feel free to contact us regarding specific sites as we may have more particular information available. We also ask that any information you may have on any sites that are missing data or are omitted be shared with us so we can improve our database. You can access monitoring reports and permits for some sites and projects by clicking the link in the “NCDOT Permits and Monitoring Reports” field (“hypWeblink” from the query results view) and navigating the appropriate page. Full metadata should be included with a download of this file. If not, please contact ddjohnson[at]ncdot.gov and a copy will be provided. You may also download a pdf of the metadata here. We ask that this file not be distributed without metadata. You can find a map containing these data here here. Known Issues: Site Boundaries – The majority of these sites do have a corresponding boundary, and its source would be denoted in the “Boundary Source” field (“BoundSrc” in the query results view). Due to data collection and conversion limitations, we cannot guarantee the accuracy of site boundaries. To assist with gauging the degree of accuracy, the "Boundary Source" field can tell you where the boundary originated. However, it should be noted that even boundaries taken from surveys can misrepresent the site if the boundary shifted during the conversion from CAD formats. We are in the process of reviewing the information we have and making further documentation of available parcel and conservation easement data to cut down on uncertainty where possible. Some locations have been taken from files provided by the Ecosystem Enhancement Program (as noted in the "Boundary Source" field). EEP quality control/quality assurance is on-going. Please contact EEP for the most recent information about specific project areas. Sites whose property documents have been collected and published by EEP will have a link in the “EEP Property Documents” field (“EEP_Folio” from the query results). Status attribute - This refers to the last-known status of a project, which may be only current as of the date the project was entered in the database. A project having a boundary does not mean that it has been completed or that it will be, so be sure to find the current status of any project before making any decisions regarding the area. River Basin - The river basin names and 8-digit hydrologic unit codes (HUCs; called CU or catalog units in the attributes) in these files may differ from what some organizations are using. These are from a boundary file released by CGIA in 2008. Contact Dave Johnson with any questions related to the contents of this service: ddjohnson[at]ncdot.gov 919-707-6130

Seattle Parks and Recreation GIS Map Layer Shapefile - Football Field Point

Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata.

OR

Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/17

Seattle Parks and Recreation GIS Map Layer Shapefile - Soccer Field Point

Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata.

OR

Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/39

Dataset for provision of cadastral map in digital form in SHP format. Data comes from ISKN (Information System of Cadastre of Real Estates). Cadastral map includes planimetric and descriptive component. Planimetry contains boundaries of parcels, cadastral and administrative units, perimeters of buildings and geodetic control points. Descriptive elements contain lettering (parcel numbers, geographical names etc.), map symbols (symbols of nature of land use etc.) and lines (boundaries of protected zones etc.). Some information of digital map is omitted during the data conversion into SHP format (information on point number, quality code linked to planimetry points, line symbols etc.). Dataset is provided as Open Data (licence CC-BY 4.0). Data is based on ISKN (Information System of the Cadastre of Real Estates). Cadastral map is provided via cadastral units using JTSK coordinate system (EPSG:5514). Data is available for cadastral units with digital form of cadastral map only - (to the 2025-07-21 it is 99.34% of the territory of the Czech Republic, i.e. 78 346.82km2). Data is provided in SHP format (Windows-1250 character encoding). Dataset is compressed (ZIP) for downloading. More in the Cadastral Act No. 256/2013 Coll., Cadastral Decree No. 357/2013 Coll., Cadastral Decree on Data Provision No. 357/2013 Coll., as amended.

description: Seattle Parks and Recreation GIS Map Layer Shapefile - Misc Court Outline Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/19; abstract: Seattle Parks and Recreation GIS Map Layer Shapefile - Misc Court Outline Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/19

Stream network data originated from USGS National Hydrologic Database (NHD). While the NHD is a very useful and spatially accurate dataset, it is missing one attribute that is commonly referenced as a method to classify and stratify streams, the Strahler Stream Order. Stream order information was available on the Surface Waters Information Management System (SWIMS), digitized from 1:100,000 scale maps. ArcGIS was used to convert the SWIMS vectors to points, spaced at 100 meter intervals, and then to calculate the distance to nearest point (NHD stream to SWIMS points). For each arc segment, the attributes of the nearest point were then appended to the attribute table. While this process successfully added the stream order to the NHD arcs, there were some errors. There were instances of the nearest point to a segment actually belonging to a tributary, and being incorrectly assigned to the wrong stream segment. Also, since the NHD data is much more detailed in its inclusion of smaller streams, the origin for the calculation of 1st order and 2nd order streams is different. Efforts were made to address and correct both of these issues, but users should recognize that not all errors were corrected.The stream network was manually scanned for inconsistencies in stream order flow (jumping from a 3rd order to 1st order, and then back to a 3rd order) and corrected. Emphasis was placed on correcting the larger (3rd order and greater) steams first, and many (but not all) of the 1st and 2nd order. Instances of stream beginnings being mislabeled as an order greater than 1st order were corrected by searching for all dangling arcs (stream beginnings) and then recoding them to a order of 1. This process corrected 1,199 arcs that had been incorrectly coded. One last issue users should be aware of is that since the NHD includes streams not used in calculating the Strahler order in the SWIMS dataset, there are inconsistencies in the labeling of 1st and 2nd order streams. Some corrections were made where obvious lager gaps were in the SWIMS database, but for the most part the original SWIMS stream order was transferred directly. Where adjustments were made, they were only made to lower (less then 4th order) streams.Last Updated October 2013.

During 1980, the U.S. Geological Survey (USGS) conducted a seismic-reflection survey utilizing Uniboom seismics in southern Rhode Island Sound aboard the Research Vessel Asterias. This cruise totalled 3 survey days. Data from this survey were recorded in analog form and archived at the USGS. Due to recent interest in the geology of Rhode Island Sound and in an effort to make the data more readily accessible while preserving the original paper records, the seismic data from this cruise were scanned and converted to TIFF images and SEG-Y data files. Navigation data were converted from LORAN-C time delays to latitudes and longitudes, which are available in ESRI shapefile format and as eastings and northings in space-delimited text format.

This dataset contains the location of 32,000 airports around the world. The data is shapefile format (.shp). The dataset contains the name of the airport, its lat/lon, elevation, country and timezone. The 3 letter codes are available in the alternative name field but are mixed in with other information. Data was extracted from the Geonames database and converted to shapefile using GDAL commands in Postgis. All data from GeoNames is distributed under the creative commons attribution 3.0 agreement. GIS vector data. This dataset was first accessioned in the EDINA ShareGeo Open repository on 2012-04-18 and migrated to Edinburgh DataShare on 2017-02-22.

description: Seattle Parks and Recreation GIS Map Layer Shapefile - Adult Fitness Equipment Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/0; abstract: Seattle Parks and Recreation GIS Map Layer Shapefile - Adult Fitness Equipment Shapefile - This Seattle Parks and Recreation ARCGIS park feature map layer was exported from SPU ARCGIS and converted to a shapefile then manually uploaded to data.seattle.gov via Socrata. OR Web Services - Live "read only" data connection ESRI web services URL: http://gisrevprxy.seattle.gov/arcgis/rest/services/DPR_EXT/ParksExternalWebsite/MapServer/0

During 1980, a seismic-reflection survey utilizing Uniboom seismics was conducted by the U.S. Geological Survey (USGS) in western Rhode Island Sound aboard the Research Vessel Neecho. This cruise consisted of 2 legs totalling 8 survey days. Data from this survey were recorded in analog form and archived at the USGS. As a result of recent interest in the geology of Rhode Island Sound and in an effort to make the data more readily accessible while preserving the original paper records, the seismic data from this cruise were scanned and converted to TIFF images and SEG-Y data files. Navigation data were converted from LORAN-C time delays to latitudes and longitudes, which are available in ESRI shapefile format and as eastings and northings in space-delimited text format.