Utah FORGE has been established to develop, test, and improve the technologies and techniques required to develop EGS-type geothermal resources. Drilling of the first of two deep deviated wells, 16A(78)-32, will begin in the second half of 2020. This well will serve as the injection well for the injection-production well pair that will form the heart of the laboratory. This submission contains an archive of well location data within the Roosevelt Hot Springs geothermal area. An Excel spreadsheet is included containing updated GPS data for Utah FORGE wells drilled during Phase 2C (56-32, 68-32, 78-32). This data was collected over time by the Utah Geological Survey and contains all coordinates collected and the final averaged XY coordinates in both Longitude and Latitude and UTM Zone 12, NAD83. Elevation is also included. GIS shapefiles with well points are provided in the archive.

This Application Programming Interface (API) provides instant conversion between HK 1980 Grid Coordinates (Northing and Easting) and WGS84 (ITRF96) Geodetic Coordinates (Latitude and Longitude). The conversion methods, parameters and formulas used in the coordinate conversion tool provided in this API are maintained by the Survey and Mapping Office, Lands Department. It is only applicable for coordinates within Hong Kong. Users SHOULD NOT use the results for applications requiring precise point positions. Transformation between datums does not improve the accuracy. In most cases, the transformation coordinates would be less accurate, because of the errors in the transformation and projection computation would be added to the results. Please seek advice from professional land surveyors. For enquiry, please contact the Geodetic Survey Section, Survey and Mapping Office, Lands Department. For details, please refer to User Manual (English Only): http://www.geodetic.gov.hk/transform/tformAPI_manual.pdf

New Parking Citations dataset here: https://data.lacity.org/Transportation/Parking-Citations/4f5p-udkv/about_data ---Archived as of September 2023--- Parking citations with latitude / longitude (XY) in US Feet coordinates according to the California State Plane Coordinate System - Zone 5 (https://www.conservation.ca.gov/cgs/rgm/state-plane-coordinate-system). For more information on Geographic vs Projected coordinate systems, read here: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://learn.arcgis.com/en/projects/make-a-web-map-without-web-mercator/

Parking citations with latitude / longitude (XY) in US Feet coordinates according to the NAD_1983_StatePlane_California_V_FIPS_0405_Feet projection.

Loudoun County Parcel X,Y coordinates table. Available in Latitude and Longitude decimal degrees and Virginia State Plane North.

Content

Parking citations with latitude / longitude (XY) in US Feet coordinates according to the NAD_1983_StatePlane_California_V_FIPS_0405_Feet projection.

Context

This is a dataset hosted by the city of Los Angeles. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore Los Angeles's Data using Kaggle and all of the data sources available through the city of Los Angeles organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

Cover photo by Scott Webb on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

This dataset contains the location of all active fire stations and fire related facilities within the City of Toronto. The locations are identified by XY (latitude and longitude) coordinates.

Parking citations with latitude / longitude (XY) in US Feet coordinates according to the NAD_1983_StatePlane_California_V_FIPS_0405_Feet projection.

Abstract This data and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are represented here as originally supplied: This data represents all the locations of NSW river gauges the Bureau of Meteorology has ingested into internal systems from NSW Department of Primary Industries at this point in time. There are plans to onboard more NSW agency data in the future. ## Purpose Data obtained under the Water Act 2008 for national water monitoring purposes ## Dataset History This data and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are represented here as originally supplied: Data is in excel format and contains the following fields: Station number Station name Long name Name of the spatial reference Easting Northing Latitude Longitude Please note location fields (x,y, lat, long) contain different number of digits which may impact transformation to geospatial object. Please ensure all records are represented spatialy during transformation. ## Dataset Citation Bureau of Meteorology (2016) River Gauge Locations NSW BOM 20160203. Bioregional Assessment Source Dataset. Viewed 14 June 2018, http://data.bioregionalassessments.gov.au/dataset/d2292117-f3b6-4c50-8756-2d9eba1a81a1.

This dataset contains all basic primary school details including address, longitude/latitude, geo (XY) coordinates and eircode information

Tags

   survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES




   Summary


   BES Research, Applications, and Education


   Description


   XY Positions for BES telephone survey. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 



   The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. 


   The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. 


   Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey.


   This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used

Summary Rail Crossings is a spatial file maintained by the Federal Railroad Administration (FRA) for use by States and railroads. Description FRA Grade Crossings is a spatial file that originates from the National Highway-Rail Crossing, Inventory Program. The program is to provide information to Federal, State, and local governments, as well as the railroad industry for the improvements of safety at highway-rail crossing. Credits Federal Railroad Administration (FRA) Use limitations There are no access and use limitations for this item. Extent West -79.491008 East -75.178954 North 39.733500 South 38.051719 Scale Range Maximum (zoomed in) 1:5,000 Minimum (zoomed out) 1:150,000,000 ArcGIS Metadata ▼►Topics and Keywords ▼►Themes or categories of the resource  transportation * Content type  Downloadable Data Export to FGDC CSDGM XML format as Resource Description No Temporal keywords  2013 Theme keywords  Rail Theme keywords  Grade Crossing Theme keywords  Rail Crossings Citation ▼►Title rr_crossings Creation date 2013-03-15 00:00:00 Presentation formats  * digital map Citation Contacts ▼►Responsible party  Individual's name Raquel Hunt Organization's name Federal Railroad Administration (FRA) Contact's position GIS Program Manager Contact's role  custodian Responsible party  Organization's name Research and Innovative Technology Administration/Bureau of Transportation Statistics Individual's name National Transportation Atlas Database (NTAD) 2013 Contact's position Geospatial Information Systems Contact's role  distributor Contact information  ▼►Phone  Voice 202-366-DATA Address  Type  Delivery point 1200 New Jersey Ave. SE City Washington Administrative area DC Postal code 20590 e-mail address answers@BTS.gov Resource Details ▼►Dataset languages  * English (UNITED STATES) Dataset character set  utf8 - 8 bit UCS Transfer Format Spatial representation type  * vector * Processing environment Microsoft Windows 7 Version 6.1 (Build 7600) ; Esri ArcGIS 10.2.0.3348 Credits Federal Railroad Administration (FRA) ArcGIS item properties  * Name USDOT_RRCROSSINGS_MD * Size 0.047 Location withheld * Access protocol Local Area Network Extents ▼►Extent  Geographic extent  Bounding rectangle  Extent type  Extent used for searching * West longitude -79.491008 * East longitude -75.178954 * North latitude 39.733500 * South latitude 38.051719 * Extent contains the resource Yes Extent in the item's coordinate system  * West longitude 611522.170675 * East longitude 1824600.445629 * South latitude 149575.449134 * North latitude 752756.624659 * Extent contains the resource Yes Resource Points of Contact ▼►Point of contact  Individual's name Raquel Hunt Organization's name Federal Railroad Administration (FRA) Contact's position GIS Program Manager Contact's role  custodian Resource Maintenance ▼►Resource maintenance  Update frequency  annually Resource Constraints ▼►Constraints  Limitations of use There are no access and use limitations for this item. Spatial Reference ▼►ArcGIS coordinate system  * Type Projected * Geographic coordinate reference GCS_North_American_1983_HARN * Projection NAD_1983_HARN_StatePlane_Maryland_FIPS_1900_Feet * Coordinate reference details  Projected coordinate system  Well-known identifier 2893 X origin -120561100 Y origin -95444400 XY scale 36953082.294548117 Z origin -100000 Z scale 10000 M origin -100000 M scale 10000 XY tolerance 0.0032808333333333331 Z tolerance 0.001 M tolerance 0.001 High precision true Latest well-known identifier 2893 Well-known text PROJCS["NAD_1983_HARN_StatePlane_Maryland_FIPS_1900_Feet",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree"

Geometric Mean Baseline of chlora from Sentinel-3B OLCI, data courtesy of Copernicus Program, mapping matches NOAA CoastWatch VIIRS Sectors cdm_data_type=Grid Conventions=CF-1.6, COARDS, ACDD-1.3 cw_orbit_type=descending cw_pass_type=day cw_processing_version=NRT S3B_OL_2_WFR cw_projection=Geographic cw_satellite=Sentinel-3B cw_sensor=OLCI cw_station_code=MAR cw_station_name=European Organization for the Exploitation of Meteorological Satellites cw_swath_sync_lines=1 Easternmost_Easting=60.033750000000026 geospatial_lat_max=44.88375 geospatial_lat_min=-0.1087500000000044 geospatial_lat_resolution=0.0075000000000000015 geospatial_lat_units=degrees_north geospatial_lon_max=60.033750000000026 geospatial_lon_min=-0.03374999999997864 geospatial_lon_resolution=0.007500000000000001 geospatial_lon_units=degrees_east geospatial_vertical_max=0.0 geospatial_vertical_min=0.0 geospatial_vertical_positive=up geospatial_vertical_units=m history=[cwutils 4.1.0.53 20250211_095418] cwcomposite --pedantic --coherent chlor_a/latitude --optimal sat_zenith/minabs --method optimal --inputs - --match ^(wqsf0|wqsf1|sat_zenith|latitude|longitude|chlor_a)$ /home/pub/svc_cwatch/aps/aps_z/browse/lvl4/modis/coastwatch/hdf/OLCVCW_J2025335_C4_072944_073244_090744_091044_KH00_closest_chlora.hdf [cwutils 4.1.0.53 20250211_095418] cwgraphics /home/pub/svc_cwatch/aps/aps_z/browse/lvl4/modis/coastwatch/hdf/OLCVCW_J2025335_C4_072944_073244_090744_091044_KH00_closest_chlora.hdf [cwutils 4.1.0.53 20250211_095418] cwimport --match=^graphics$ --copy /home/pub/svc_cwatch/aps/aps/aps/share/coastwatch/icons/North750XY0045Geographic.hdf /home/pub/svc_cwatch/aps/aps_o/browse/lvl4/modis/coastwatch/maskhdf/OLCVCW_J2025335_J2025335_F1_XY00_closest_chlora.hdf id=noaacwS3BOLCIchlaSectorXYDaily infoUrl=https://coastwatch.noaa.gov/cw/satellite-data-products/ocean-color/near-real-time/olci-sentinel3-global.html institution=Copernicus Program instrument=OLCI keywords_vocabulary=GCMD Science Keywords naming_authority=gov.noaa.coastwatch Northernmost_Northing=44.88375 OBSERVED_PROPERTY=chlor_a platform=Sentinel-3B source=Sentinel-3B_OLCI_chlora sourceUrl=(local files) Southernmost_Northing=-0.1087500000000044 standard_name_vocabulary=CF Standard Name Table v29 testOutOfDate=now-2days time_coverage_end=2025-12-01T12:00:00Z time_coverage_start=2024-11-27T12:00:00Z Westernmost_Easting=-0.03374999999997864

These TowCam navigation files were generated during 2002 R/V Melville cruise VANC01MV along a minor rift originating at the East Pacific Rise (EPR) at 2°40'N continuing southeastward for ~65 km. Photographs were assigned the position of the ship, assuming minimal layback of the camera sled. The files are in ASCII text format and present with the latitude and longitude in decimal degrees. There is one navigation file per TowCam deployment. The files were generated as part of a project called Geochemical and Geological Investigations of the Incipient Rift at 2° 40'N, East of the East Pacific Rise. Funding was provided by NSF awards OCE00-96360 and OCE00-99154.

Dataset provides an overview of the benthic macroinvertebrate communities in lotic systems in TRCA’s jurisdiction for the purposes of biomonitoring and bioassessment.

The data contained in the dataset were collected from 2013 - 2021 following The Ontario Benthos Biomonitoring Network (OBBN) standard sampling protocols. The dataset contains the necessary information for the calculations of biological metrics to assess stream health (not included; to be calculated at the discretion of dataset user).

"[Site Name] A unique tracking id that identifies a distinct site as distinguished by coordinates [Watershed] Name of the watershed each site is located within [Subwatershed] Name of the subwatershed each site is located within [UTM Zone], [UTM Easting], [UTM Northing] The Universal Transverse Mercator (UTM) of site location to the nearest metre [Latitude], [Longitude] The XY coordinates of site location in decimal degree units [Year], [Collection Date] The calendar year and date on which the sample was collected [Phylum] Consistent Phylum name of the taxa [Class] Consistent Class name of the taxa [Order] Consistent Order name of the taxa [Family] Consistent Family name of the taxa [BMI Taxa] Consistent unique name of the taxa at the level the taxa was identified to [Common Name] Consistent common name of the taxa at the Order or Family level [Total Count] Number of Individuals in each BMI taxa [Habitat Sampled] The micro-habitat unit targeted for sampling. Based on The Ontario Benthos Biomonitoring Network (OBBN) standard sampling protocols, targeted habits include riffles and pools: Riffle areas of fast, turbulent water, often characterized by gravel/cobble substrates, and Pool areas of slow, deeper than average water associated with deposition or the impoundment of water from a flow obstruction. [Subsample Number] The sequence of transect subsamples were collected, ranged from 1-3. This number is used to differentiate the two riffles transect subsamples. [Collection Method] The sampling device with which the sample was collected. [Lab Method] The processing method with which the sample was sorted in the laboratory. "

Tags survey, environmental behaviors, lifestyle, status, PRIZM, Baltimore Ecosystem Study, LTER, BES Summary BES Research, Applications, and Education Description XY Positions for BES telephone survey. The BES Household Survey 2003 is a telephone survey of metropolitan Baltimore residents consisting of 29 questions. The survey research firm, Hollander, Cohen, and McBride conducted the survey, asking respondents questions about their outdoor recreation activities, watershed knowledge, environmental behavior, neighborhood characteristics and quality of life, lawn maintenance, satisfaction with life, neighborhood, and the environment, and demographic information. The data from each respondent is also associated with a PRIZM� classification, census block group, and latitude-longitude. PRIZM� classifications categorize the American population using Census data, market research surveys, public opinion polls, and point-of-purchase receipts. The PRIZM� classification is spatially explicit allowing the survey data to be viewed and analyzed spatially and allowing specific neighborhood types to be identified and compared based on the survey data. The census block group and latitude-longitude data also allow us additional methods of presenting and analyzing the data spatially. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. The BES 2003 telephone survey was conducted by Hollander, Cohen, and McBride from September 1-30, 2003. The sample was obtained from the professional sampling firm Claritas, in order that their "PRIZM" encoding would be appended to each piece of sample (telephone number) supplied. Mailing addresses were also obtained so that a postcard could be sent in advance of interviewers calling. The postcard briefly informed potential respondents about the survey, who was conducting it, and that they might receive a phone call in the next few weeks. A stratified sampling method was used to obtain between 50 - 150 respondents in each of the 15 main PRIZM classifications. This allows direct comparison of PRIZM classifications. Analysis of the data for the general metropolitan Baltimore area must be weighted to match the population proportions normally found in the region. They obtained a total of 9000 telephone numbers in the sample. All 9,000 numbers were dialed but contact was only made on 4,880. 1508 completed an interview, 2524 refused immediately, 147 broke off/incomplete, 84 respondents had moved and were no longer in the correct location, and a qualified respondent was not available on 617 calls. This resulted in a response rate of 36.1% compared with a response rate of 28.2% in 2000. The CATI software (Computer Assisted Terminal Interviewing) randomized the random sample supplied, and was programmed for at least 3 attempted callbacks per number, with emphasis on pulling available callback sample prior to accessing uncalled numbers. Calling was conducted only during evening and weekend hours, when most head of households are home. The use of CATI facilitated stratified sampling on PRIZM classifications, centralized data collection, standardized interviewer training, and reduced the overall cost of primary data collection. Additionally, to reduce respondent burden, the questionnaire was revised to be concise, easy to understand, minimize the use of open-ended responses, and require an average of 15 minutes to complete. The household survey is part of the core data collection of the Baltimore Ecosystem Study to classify and characterize social and ecological dimensions of neighborhoods (patches) over time and across space. This survey is linked to other core data, including US Census data, remotely-sensed data, and field data collection, including the BES DemSoc Field Observation Survey. Additional documentation of this database is attached to this metadata and includes 4 documents, 1) the telephone survey, 2) documentation of the telephone survey, 3) metadata for the telephone survey, and 4) a description of the attribute data in the BES survey 2003 survey. This database was created by joining the GDT geographic database of US Census Block Group geographies for the Baltimore Metropolitan Statisticsal Area (MSA), with the Claritas PRIZM database, 2003, of unique classifications of each Census Block Group, and the unique PRIZM code for each respondent from the BES Household Telephone Survey, 2003. The GDT database is preferred and used because of its higher spatial accuracy than other databases describin... Visit https://dataone.org/datasets/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-bes%2F337%2F610 for complete metadata about this dataset.

If you use this dataset, please cite the IJRR data paper (bibtex is below). We present a dataset collected from a canoe along the Sangamon River in Illinois. The canoe was equipped with a stereo camera, an IMU, and a GPS device, which provide visual data suitable for stereo or monocular applications, inertial measurements, and position data for ground truth. We recorded a canoe trip up and down the river for 44 minutes covering 2.7 km round trip. The dataset adds to those previously recorded in unstructured environments and is unique in that it is recorded on a river, which provides its own set of challenges and constraints that are described in this paper. The data is divided into subsets, which can be downloaded individually. Video previews are available on Youtube: https://www.youtube.com/channel/UCOU9e7xxqmL_s4QX6jsGZSw The information below can also be found in the README files provided in the 527 dataset and each of its subsets. The purpose of this document is to assist researchers in using this dataset. Images ====== Raw --- The raw images are stored in the cam0 and cam1 directories in bmp format. They are bayered images that need to be debayered and undistorted before they are used. The camera parameters for these images can be found in camchain-imucam.yaml. Note that the camera intrinsics describe a 1600x1200 resolution image, so the focal length and center pixel coordinates must be scaled by 0.5 before they are used. The distortion coefficients remain the same even for the scaled images. The camera to imu tranformation matrix is also in this file. cam0/ refers to the left camera, and cam1/ refers to the right camera. Rectified --------- Stereo rectified, undistorted, row-aligned, debayered images are stored in the rectified/ directory in the same way as the raw images except that they are in png format. The params.yaml file contains the projection and rotation matrices necessary to use these images. The resolution of these parameters do not need to be scaled as is necessary for the raw images. params.yml ---------- The stereo rectification parameters. R0,R1,P0,P1, and Q correspond to the outputs of the OpenCV stereoRectify function except that 1s and 2s are replaced by 0s and 1s, respectively. R0: The rectifying rotation matrix of the left camera. R1: The rectifying rotation matrix of the right camera. P0: The projection matrix of the left camera. P1: The projection matrix of the right camera. Q: Disparity to depth mapping matrix T_cam_imu: Transformation matrix for a point in the IMU frame to the left camera frame. camchain-imucam.yaml -------------------- The camera intrinsic and extrinsic parameters and the camera to IMU transformation usable with the raw images. T_cam_imu: Transformation matrix for a point in the IMU frame to the camera frame. distortion_coeffs: lens distortion coefficients using the radial tangential model. intrinsics: focal length x, focal length y, principal point x, principal point y resolution: resolution of calibration. Scale the intrinsics for use with the raw 800x600 images. The distortion coefficients do not change when the image is scaled. T_cn_cnm1: Transformation matrix from the right camera to the left camera. Sensors ------- Here, each message in name.csv is described ###rawimus### time # GPS time in seconds message name # rawimus acceleration_z # m/s^2 IMU uses right-forward-up coordinates -acceleration_y # m/s^2 acceleration_x # m/s^2 angular_rate_z # rad/s IMU uses right-forward-up coordinates -angular_rate_y # rad/s angular_rate_x # rad/s ###IMG### time # GPS time in seconds message name # IMG left image filename right image filename ###inspvas### time # GPS time in seconds message name # inspvas latitude longitude altitude # ellipsoidal height WGS84 in meters north velocity # m/s east velocity # m/s up velocity # m/s roll # right hand rotation about y axis in degrees pitch # right hand rotation about x axis in degrees azimuth # left hand rotation about z axis in degrees clockwise from north ###inscovs### time # GPS time in seconds message name # inscovs position covariance # 9 values xx,xy,xz,yx,yy,yz,zx,zy,zz m^2 attitude covariance # 9 values xx,xy,xz,yx,yy,yz,zx,zy,zz deg^2 velocity covariance # 9 values xx,xy,xz,yx,yy,yz,zx,zy,zz (m/s)^2 ###bestutm### time # GPS time in seconds message name # bestutm utm zone # numerical zone utm character # alphabetical zone northing # m easting # m height # m above mean sea level Camera logs ----------- The files name.cam0 and name.cam1 are text files that correspond to cameras 0 and 1, respectively. The columns are defined by: unused: The first column is all 1s and can be ignored. software frame number: This number increments at the end of every iteration of the software loop. camera frame number: This number is generated by the camera and increments each time the shutter is triggered. The software and camera frame numbers do not have to start at the same value, but if the difference between the initial and final values is not the same, it suggests that frames may have been dropped. camera timestamp: This is the cameras internal timestamp of the frame capture in units of 100 milliseconds. PC timestamp: This is the PC time of arrival of the image. name.kml -------- The kml file is a mapping file that can be read by software such as Google Earth. It contains the recorded GPS trajectory. name.unicsv ----------- This is a csv file of the GPS trajectory in UTM coordinates that can be read by gpsbabel, software for manipulating GPS paths. @article{doi:10.1177/0278364917751842, author = {Martin Miller and Soon-Jo Chung and Seth Hutchinson}, title ={The Visual–Inertial Canoe Dataset}, journal = {The International Journal of Robotics Research}, volume = {37}, number = {1}, pages = {13-20}, year = {2018}, doi = {10.1177/0278364917751842}, URL = {https://doi.org/10.1177/0278364917751842}, eprint = {https://doi.org/10.1177/0278364917751842} }

This data is the distribution data of the prehistoric era sites on the Qinghai-Tibet Plateau and surrounding areas, which is derived from the Supplementary Maps of the paper: Chen, F.H., Dong, G.H., Zhang, D.J., Liu, X.Y., Jia, X., An, C.B., Ma, M.M., Xie, Y.W., Barton, L., Ren, X.Y., Zhao, Z.J., & Wu, X.H. (2015). Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 BP. SCIENCE, 347, 248-250. The Qinghai-Tibet Plateau, with an average altitude of more than 4000m, is the highestand largest plateau all around the world, and also is one of the most unsuitable areas for human life with long-term on the earth. The remains at the archaeological site are direct evidences left behind the ancient human activities. The original data of this data is digitized from the results of the Qinghai-Tibet Plateau high-textual census and archaeological survey (Qinghai Volume and Tibet Volume of the Chinese Cultural Relics Atlas). The map was digitized mainly based on the distribution maps of the sites, and the latitude and longitude coordinates and altitude were obtained. a total of 6,950 sites, most of which are distributed in the northern part of the plateau. The age range of the site is between 7000BP and 2300BP. This data set is of reference value for the research on the process and power of human diffusion to the Tibetan Plateau in the prehistoric era and other studies related to human activities in the Tibetan Plateau and the prehistoric era.

File List bivalve.txt

Description The ASCII text data frame bivalve.txt contains 200 rows of observations corresponding to the 0.25 square meter sample plots on a 250 m × 500 m area on the sandflat of Wiroa Island, Manukau Harbor, New Zealand (data from Legendre et al. 1997). The 21 column variables are: LN.MACG15, logarithm of counts of Macomona >15 mm; MACG15, counts of Macomona >15 mm; ELEV.M, bed elevation in meters above chart datum; ELEV2, ELEV.M squared; ELEV3, ELEV.M cubed; X.CTR, longitude coordinates centered to mean 0; Y.CTR, latitude coordinates centered to mean 0; X2, X.CTR squared; XY, X.CTR multiplied by Y.CTR; Y2, Y.CTR squared; X3, X.CTR cubed; X2Y, X2 multiplied by Y.CTR; XY2, X.CTR multiplied by Y2; Y3, Y.CTR cubed; EBBSTRESS, ebb tide bed shear stress (N/m2); SWWAVEWORK, southwest wave work per unit of bed area (kg/s2); WSWWAVEWORK, west, southwest wave work per unit of bed area (kg/s2); WATER.G20CM, proportion of time the plot is covered by water >20 cm deep during spring tide (0 - 1); LRGWAVE.STIR, proportion of time large waves stir the plot during spring tide (0 - 1); FLDSTRESS, flood tide bed shear stress (N/m2); and SHELLHASH, bivalve shell hash (g) in the bed sediment. Missing values are indicated by NA.

This dataset is gravity anomaly data of the Auckland and Whangarei volcanic fields (AVF and WVF) in the northern part of North Island. The X-Y coordinate system of this dataset is NZTM, and the Longitude-Latitude coordinate system is NZGD2000. The uploader gathers this data from a series of AVF day trip fieldworks (2021 - 2023), a week-long WVF campaign (2022), correspondences with authors, and the following theses lodged in The University of Auckland's General Library:Auckland Volcanic FieldCaleb John Gasston (2017)Hellen Anne Williams (2003)Sian Julia France (2003)Mazin Al-Salim (2000)Dev Kumar Affleck (1999)Craig Andrew Miller (1996)Shane Robert Moore (1996)David Rout (1991)Grant Willis Roberts (1980)Isla Margaret Nixon (1977)Helen Joan Anderson (partially, 1977)Whangarei Volcanic FieldPaul Johann Röllin (1991)All names and years of the respective data contributors have been included in the CSV files.