For conversion of GPS to KML we used the GPS datatypes such asGPGGAwhich is described as Global Positioning System Fix Data andGPRMCwhichis described as Recommended minimum specific GPS/Transit data. To begin with, we first created two data frames with the given GPS data, by filtering out GPGGA and GPRMC types. As per our observation, we could see that GPGGAtype gave us information like Longitude, Latitude, Altitude, and Fix Quality (ifits 0 0 then it is invalid). On the other hand, GPRMC type fetched information like T Time, Speed in knots and Navigation receiver warning. Out of the other information from GPRMC datatype, we were only interested in speed and re-ceive warning. So we copied those columns and combined these columns into pandas data frame created for type GPGGA. Moving to the next part which is conversion of data. We converted the Latitude and Longitude of$GPGGA us-ing formula DDMMSSSS eg, 4533.35 is 45 degrees and 33.35 minutes. ”.35” of a minute is exactly 21 seconds. We checked for the direction and assigned proper sign as per the directon (W is -ve and E is +ve). We then converted all the numeric columns in dataframe for further calculation. Finally created a tuple with latitude, longitude and speed. This list of tuples was added as coordinates. One of the major challenge was to understand the GPS data.

Maps are currently experiencing a paradigm shift from static representations to dynamic platforms that capture, visualize and analyse new data, bringing different possibilities for exploration and research. The first objective of this paper is to present a map that illustrates, for the first time, the real flow of casual cyclists and bike messengers in the city of Madrid. The second objective is to describe the development and results of the Madrid Cycle Track initiative, an online platform launched with the aim of collecting cycling routes and other information from volunteers. In the framework of this initiative, different online maps are presented and their functionalities described. Finally, a supplemental video visualizes the cyclist flow over the course of a day.

Context

Selected activities from Strava for use in Kaggle Kernels only. GPX files from a GPS device.

Content

Laramie_Enduro_2014.gpx

Laramie_Enduro_2015.gpx

Laramie_Enduro_2016.gpx

West_Laramie_Bike_Ride.gpx

Colorado_Belford_Oxford_and_Missouri_Mountains_Hike.gpx

Colorado_Longs_Peak_and_Chasm_Lake_Hike.gpx

Berenthanti_Ghorepani_Ghandruk_Loop_Hike_Day_1_of_3_.gpx

Berenthanti_Ghorepani_Ghandruk_Loop_Hike_Day_2_of_3_.gpx

Berenthanti_Ghorepani_Ghandruk_Loop_Hike_Day_3_of_3_.gpx

Acknowledgements

Strava

Inspiration

Strava Labs

Since the early 1990s, the GFZ has operated a global GNSS station network with currently about 70 stations for precise satellite clock & orbit determination, realization of the terrestrial reference frame, radio occultation measurements or studies on crust dynamics. A subset of these stations contributes also to the tracking networks of the International GNSS Service (IGS) and the EUREF Permanent GNSS Network (EPN). Other stations contribute to GFZ observatories (IPOC, DESERVE, TERENO), to the GPS Atmosphere Sounding Project (GASP), to WMO Global Climate Observing System Reference Upper-Air Network (GRUAN) or to other external cooperations. We offer data of 51 GFZ GNSS stations under this DOI. Nearly all stations are equipped with Javad or Septentrio hardware. Depending on the location and hardware they provide data of GPS (L1 / L2 / L5), GLONASS (L1 / L2 / L3), Galileo (E1 / E5a / E5b / E6), BeiDou (B1 / B2 / B3), QZSS (L1 / L2 / L5 / L6), NAVIC (L5), and SBAS (L1 / L5). The GNSS Station Nework Site (https://isdc.gfz-potsdam.de/gnss-station-network/) provides direct access to the 1s and 30s sampled RINEX data (near real-time, file based) and to real-time streams. Real-time streams are available for stations contributing to the IGS. Raw data GNSS binary raw observations are available upon request. All GFZ Stations follow the site guidelines of the International GNSS Service (https://kb.igs.org/hc/en-us/articles/202011433-Current-IGS-Site-Guidelines) Station specific metadata can be found at our metadata portal SEMISYS. An overview of the list of stations with direct links to the station specific metadata in semisys is available via ftp://datapub.gfz-potsdam.de/download/10.5880.GFZ.1.1.2020.001/2020-001_Ramatschi-et-al_List-of-GFZ-GNSS-Stations-with-links-to-SEMISYS.pdf.

Today, everybody around the world is living and working under the coverage of Geographic Information system (GIS) application and services such as the Google Earth, GPS and much more. Big Data visualization tools are increasingly creating a wonder in the world of GIS. GIS has diverse application, from geo-positioning services to 3D demonstrations and virtual reality. Big Data and its tools of visualization has boosted the field of GIS. This article seeks to explore how Big data visualization has expanded the field of Geo- spatial analysis with the intention to present practicable GIS-based tools required to stay ahead in this field.

The dataset contains plant species occurrence records in the upper to mid Tana River Basin, digitized from preserved specimens at the East African Herbarium (EA), Nairobi. The dataset is a subset of the EA BRAHMS database generated over several years through various projects and day-to-day digitization efforts. Specimen records from the Tana River Basin were extracted from the EA BRAHMS dataset then cleaned and formatted in Darwin Core Standard. Data cleaning was done using Open Refine Software as well as the GPS Visualizer tool to generate altitude values from coordinates. Elevation data from GPS Visualizer is controlled from a variety of reputable sources including SRTM, ASTER, USGS and Google Maps. Other cleaning tasks included correcting spellings, filling in missing data, checking the taxonomy, dates, and subnational administrative areas. Records without coordinates were georeferenced using GEOLocate, Google Maps, and Gazetteers. The field altitude (m) was automatically generated from GPS Visualizer (https://www.gpsvisualizer.com/elevation) to generate missing elevation values. The process involved uploading a CSV format file with latitude and longitude values to the website which then sampled these coordinates against inbuilt elevation profile files (Digital Elevation Models) to give altitude values at specified coordinates. Most coordinates were also retrieved from gazetteers as they are legacy data.

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.

Uncorrected GPS/GNSS observational data collected using an Altus APS3G GNSS receiver on a 2m survey pole by Anne Hellie on the 19th and 20th of January, 2018 (UTC time).

The excel file “Uncorrected_data.xlsx” contains the output of eight different data files collected (SILLS to SILLS 7). The data has been compiled into the worksheet “Uncorrected_data”. The other worksheets contain copies of the notes from Carlson Surv PC (the software used to collect the points), along with a lot more metadata.

Using ArcGIS 10.3 and the XtoolsPro extension, “Uncorrected_data” has been made into an ArcGIS shapefile (*.shp) and GoogleEarth *.kml file. Both are named “4318_2018”, with their appropriate extensions.

Note that since these points were collected in autonomous mode (with no RTK or SBAS solutions), these are uncorrected data points, and have poor accuracy, particularly in the vertical (see the VSDV field for the vertical standard deviation).

The accuracy of these positions can be substantially improved by differentially correcting/post-processing the data. This can be done with the open source software RTKLIB. Using the Septentrio software (SBF converter), the raw data files (*.sbf files collected by the Septentrio unit) have been converted into Rinex *.obs files to facilitate this process. The base station files for the appropriate time period can be downloaded from the Geoscience Australia Geodesy ftp server. The closest base station (CORS) is located at Casey and known as “cas1”. ftp://ftp.ga.gov.au/geodesy-outgoing/gnss/data/highrate/2018/

NGO Kotkaklubi (Eagle Club) and 5D Vision Ltd have developed an online portal birdmap.5dvision.ee, to visualize GPS data of migratory birds. Current dataset serves as a copy of source data for this visualization. The portal operates since 2006. Birds of 12 different species have been monitored, total number of individuals has been more than 160. Currently over 850 thousand occurrences (GPS fixes) are stored in the database. The data is managed via web-based backend that enables different methods of importing gps data (Movebank, manual upload for different receiver data formats). As the dataset covers long period of monitoring different species, various types of GPS transmitters have been used. Illustrated data about species and individuals can also be added. To enable publishing of the data to GBIF, synchronization to PlutoF biological data management platform was developed. The aim of the Birdmap portal is to increase awareness, international communication about nature and its protection by combining the possibilities and advancements of modern technology with this attractive natural phenomenon as well as providing researches and decision-makers with visualized spatial data for using in environmental analysis of possible influence of large-scale infrastructure projects. (Due to legal reasons exact location data of species with highest protection category in Estonia, belonging to Estonian territory, are not disclosed in this dataset and are available on request.)

THE AREAS COVERED BY THE FIRE ARE RELATED TO THE EVENTS WHICH OCCURRED FROM 2003 UNTIL 2010. THEY WERE RECORDED BY THE STATION COMMANDS OF THE STATE FORESTRY CORPS OF THE STATE OF LIGURIA AND ACQUIRED BY THE OFFICES OF THE SAME FORESTRY CORPS. THE DATA ARE NOT VALID PURSUANT TO PARAGRAPH 2, ART. 10 OF L. 353/2000. FOR FURTHER DETAILS, YOU CAN ALSO CONSULT THE AREAS TRAVELED BY FIRE - YEAR 1996/2002 SC. 1:10000 AND AREAS IN FIRE - YEAR 2011 SC. 1:10000. - COVERAGE: ENTIRE REGIONAL TERRITORY - ORIGIN: ACQUISITION ON THE INFORMATION SYSTEM OF THE MOUNTAIN, GPS SURVEY AND DIGITIZATION ON TECHNICAL AND/OR CADASTRAL MAP.

The construction of this data model was adapted from the Telvent Miner & Miner ArcFM MultiSpeak data model to provide interface functionality with Milsoft Utility Solutions WindMil engineering analysis program. Database adaptations, GPS data collection, and all subsequent GIS processes were performed by Southern Geospatial Services for the Town of Apex Electric Utilities Division in accordance to the agreement set forth in the document "Town of Apex Electric Utilities GIS/GPS Project Proposal" dated March 10, 2008. Southern Geospatial Services disclaims all warranties with respect to data contained herein. Questions regarding data quality and accuracy should be directed to persons knowledgeable with the forementioned agreement.The data in this GIS with creation dates between March of 2008 and April of 2024 were generated by Southern Geospatial Services, PLLC (SGS). The original inventory was performed under the above detailed agreement with the Town of Apex (TOA). Following the original inventory, SGS performed maintenance projects to incorporate infrastructure expansion and modification into the GIS via annual service agreements with TOA. These maintenances continued through April of 2024.At the request of TOA, TOA initiated in house maintenance of the GIS following delivery of the final SGS maintenance project in April of 2024. GIS data created or modified after April of 2024 are not the product of SGS.With respect to SGS generated GIS data that are point features:GPS data collected after January 1, 2013 were surveyed using mapping grade or survey grade GPS equipment with real time differential correction undertaken via the NC Geodetic Surveys Real Time Network (VRS). GPS data collected prior to January 1, 2013 were surveyed using mapping grade GPS equipment without the use of VRS, with differential correction performed via post processing.With respect to SGS generated GIS data that are line features:Line data in the GIS for overhead conductors were digitized as straight lines between surveyed poles. Line data in the GIS for underground conductors were digitized between surveyed at grade electric utility equipment. The configurations and positions of the underground conductors are based on TOA provided plans. The underground conductors are diagrammatic and cannot be relied upon for the determination of the actual physical locations of underground conductors in the field.

GPS data were recorded on the Sonobuoy Workstation as daily text files containing the raw NMEA 0183 sentences from an independent Garmin GPS receiver located at the acoustic workstation.

We have installed 20 new Global Positioning System (GPS) markers in the West Pamir and the Tajik Depression and measured 25 markers once a year between 2013 and 2016 in survey mode. The stations are positioned along two dense NW-SE oriented profiles with an average spacing of 5-10 km. The profiles cross the Darvaz and the Vakhsh/Ilyak fault and thus monitor the recent slip of these two profiles, which are expected to accommodate the gravity-driven westward extrusion of the West Pamir into the Tajik Depression. Some of the stations include millimeter to centimeter offsets potentially caused by the 2015 Mw7.2 Sarez, Pamir, earthquake.

Explore the historical Whois records related to gpsvisualizer.com (Domain). Get insights into ownership history and changes over time.

Regional list of Monumental Trees approved with Executive Decree n. 3143/2022. The data are taken from the census of monumental trees carried out by the Municipalities, pursuant to Law 10/2013, in collaboration with the Forest Carabinieri - Coverage: Entire regional coverage - Origin: GPS survey

These aerogeophysical data were collected as part of the ICECAP (International Collaborative Exploration of the Cryosphere through Airborne Profiling) collaboration in 2015/16 (ICP7) and 2016/17 (ICP8). These data were in part funded by the US National Science Foundation (grant PLR-1543452 to UTIG), Antarctic Gateway, ACE-CRC the G. Unger Vetlesen Foundation, and supported by the Australian Antarctic Division through project AAS-4346.

This data collection represents geolocated, time registered geophysical observations (L2 data). These data are derived from L0 and L1B data published as separate datasets. The data format are space delimited ASCII files, following the formats used for UTIG/AAD/NASA's predecessor ICECAP/OIB project at NASA's NSIDC DAAC. Fields are described in the # delimited detailed header for each granule.

The TectoVision GNSS network in Greece was set up using European Research Council funding in partnership between German and Greek institutions. The project aims to deepen our understanding of suspected microplate motions in Greece. A total of 72 GNSS stations are planned for the TectoVision network. Two types of GNSS station equipment is used, reflected by the 4 character station ID. Stations with ID beginning with 'TT' were installed using the tinyBlack receiver. The stations with ID beginning 'TM' were set up using the Minimum Cost GNSS System (MCGS) design. RINEX (v3.05 as of May 2024) data at 30 seconds sampling interval are provided. Most of the data are sent over mobile internet via routers that are connected to the receivers via LAN cable. If required, the RINEX files can be converted to other versions using the GFZ software GFZRNX (Nischan, 2016). Raw observation data can be made available upon specific request.

Hardware: The GFZ developed tinyBlack receiver combines cost efficient L2C GNSS receivers (here Swiftnav Piksi) with PC-based data logger package, internal storage, and interfaces. The control software is designed for remote operation ensuring long-term continuous tracking. The tinyBlack receivers provided by the GFZ spin-off maRam UG (Germany) are installed in combination with Harxon GPS500 survey antennas. The tinyBlack stations provide GPS (L1/L2), GLONASS (G1/G2), and Galileo (E1/E5b) data.

The low-cost MCGS stations are coming in 2 versions from a GNSS technology transfer project at GFZ. Both versions operate a ublox F9P receiver and an integrated chip-antenna with a pyramidal antenna radome. One version provides GPS (L1/L2), Glonass (G1/G2), Galileo (E1/E5b) and also Beidou (B1/B2) data. The other version (currently only 3 systems installed) is designed for low power operation in remote areas with data telemetry over a narrrow bandwidth radio link. This version delivers only GPS (L1/L2) data without doppler observations at a reduced data rate of 60 seconds.

Monumentation: There is a variety of monumentation for these stations, with the design of the monumentation being low-cost. Most are connected to a thread that is attached to a stainless steel pin which is glued into masonry or bedrock. Most sites are installed on rooftops of public buildings. The MCGS is sometimes clamped to an existing sturdy pole connected to the roof of the building. Some stations are connected to an extending stainless-steel arm that we have drilled into the side of a building. Photos of the station are provided with the standard GNSS station log-files (as metadata). If the instrumentation at existing monuments is later changed to other hardware types, the station ID retain the original TT and TM 4-character IDs.

Metadata: Station-specific metadata records are stored in IGS sitelog files available via ftp.

The data is owned by the municipality of Mele and was acquired as part of the project of the provincial hub of the Metropolitan City of Genoa and CST Liguria. The data model complies with national standards as per D.M. of 11/10/2011 - Coverage: entire municipal territory - Origin: GPS surveys - Year: 2009

THE AREAS INCURRED BY THE FIRE ARE RELATED TO EVENTS WHICH OCCURRED IN 2020. THEY WERE DETECTED BY THE LIGURIA CARABINIERI FOREST REGION COMMAND AND ACQUIRED BY THE OFFICES OF THE SAME COMMAND. THE DATA ARE NOT VALID PURSUANT TO PARAGRAPH 2, ART. 10 OF Law 353/2000. TO FIND OUT MORE, YOU CAN ALSO CONSULT AREAS COVERED BY FIRE - YEAR 1996/2002 SC. 1:10000 AND AREAS COVERED BY FIRE - YEAR 2003/2019 SC. 1:10000. COVERAGE: ENTIRE REGIONAL TERRITORY. ORIGIN: ACQUISITION ON THE INFORMATION SYSTEM OF THE MOUNTAIN, GPS SURVEY AND DIGITIZATION ON TECHNICAL PAPER AND/OR CADASTRAL PAPER

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai