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In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.
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Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work.
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TwitterCertified businesses enterprises in the District of Columbia as identified by the DC Department of Small and Local Business. A Certified Business Enterprise (CBE) is a business that is headquartered in the District of Columbia and has been certified by the Department of Small and Local Business Development (DSLBD). Businesses with CBE certification receive preferred procurement and contracting opportunities.
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All data associated with the Town of Young Floodplain Risk Management Study and Plan. GIS Data Outputs, Hydraulics, Hydrology, Reporting, Survey. Data and Resources Data associated with Town of Young Floodplain Risk Management Study and PlanZIP (11.5 GB) All Data and GIS data associated with the Town of Young Floodplain Risk Management Study and Plan. Explore More information Download More info Creative Commons Attribution 4.0 International Public License By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution 4.0 International Public License (“Public License”). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions. Section 1 – Definitions. Adapted Material means material subject to Copyright and Similar Rights that is derived from or based upon the Licensed Material and in which the Licensed Material is translated, altered, arranged, transformed, or otherwise modified in a manner requiring permission under the Copyright and Similar Rights held by the Licensor. For purposes of this Public License, where the Licensed Material is a musical work, performance, or sound recording, Adapted Material is always produced where the Licensed Material is synched in timed relation with a moving image. 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Subject to the terms and conditions of this Public License, the Licensor hereby grants You a worldwide, royalty-free, non-sublicensable, non-exclusive, irrevocable license to exercise the Licensed Rights in the Licensed Material to: reproduce and Share the Licensed Material, in whole or in part; and produce, reproduce, and Share Adapted Material. Exceptions and Limitations. For the avoidance of doubt, where Exceptions and Limitations apply to Your use, this Public License does not apply, and You do not need to comply with its terms and conditions. Term. The term of this Public License is specified in Section 6(a). Media and formats; technical modifications allowed. The Licensor authorizes You to exercise the Licensed Rights in all media and formats whether now known or hereafter created, and to make technical modifications necessary to do so. 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Where the Licensed Rights include Sui Generis Database Rights that apply to Your use of the Licensed Material: for the avoidance of doubt, Section 2(a)(1) grants You the right to extract, reuse, reproduce, and Share all or a substantial portion of the contents of the database; if You include all or a substantial portion of the database contents in a database in which You have Sui Generis Database Rights, then the database in which You have Sui Generis Database Rights (but not its individual contents) is Adapted Material; and You must comply with the conditions in Section 3(a) if You Share all or a substantial portion of the contents of the database. For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights. Section 5 – Disclaimer of Warranties and Limitation of Liability. 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The goal of the Lead Safe Certificate program is to prevent lead poisoning by ensuring that all rental homes built prior to 1978 are compliant with the city's Lead Safe Ordinance and maintained free of lead hazards. Any home built before 1978 is reasonably presumed to contain lead-based paint. Residential rental units built before 1978 must have a Lead Safe Certification from the City of Cleveland’s Department of Building and Housing. The Lead Safe Certification is only valid for two years, after which rental property owners must re-apply for certification. For more information about the City's Lead Safe Certification program, please visit this Building & Housing page. RelatedLead Safe Certificate Explorer Data GlossarySee the Attributes section below for details about each column in this dataset.ContactCity of Cleveland, Building and Housing Lead Compliance Program Update FrequencyWeekly on Sundays at 7 AM EST (6 AM during daylight savings)
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TwitterThis layer includes only parcels where final elevation certificates are available, with elevations reported in the vertical datum provided on the elevation certificate (NAVD 1988 or NGVD 1929).Elevation certificates were collected from the following 10 localities: (1)Chesapeake, (2)Franklin, (3)Hampton, (4)James City County, (5)Newport News, (6)Norfolk, (7)Portsmouth, (8)Southampton County, (9)Virginia Beach, and (10)York County. All elevation certificate information was entered by HRPDC staff. Localities included in the current inventory were able to provide digital elevation certificate copies. This inventory is not complete for the region, and elevation certificates will continue to be added to the database when available. Building attributes and parcels are courtesy of the Hampton Roads Regional Parcels layer and locality GIS departments. Created 2/8/2019
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This feature class is updated every business day using Python scripts and the Permit database. Please disregard the "Date Updated" field as it does not keep in sync with DWR's internal enterprise geodatabase updates. This dataset contains the points of diversion (POD) for water rights based on the coordinate location (XY) provided in the NDWR’s Permit Database. Since there can be multiple permits on the same POD site, this dataset contains duplicate point features where several permits may be stacked on top of each other spatially. The advantage to using this dataset is that all permits in NDWR’s Permit database are available. Use a filter or definition query to restrict the permits needed.Background:NDWR’s Permit Database was created in 1992. Water Right applications are entered into the database with the Township Range and Section (TRS) of the proposed place of use). The Permit Database was designed to automatically create the point of diversion (POD) based on the centroid of the TRS provided.Starting in 2007, the Hydrology section began mapping PODs by the permit application description. Water rights points of diversion are mapped that contain one of the following: coordinate location (XY), bearing/distance based on a monument tie, application map that can be georeferenced, parcel number, or location description that can be identified on a topo map. The workflow for mapping PODs includes updating the auto-generated POD in the Permit Database to the location coordinates derived from mapping the application description. Some older water rights including Vested or Decreed Water Rights may not be mapped due to lack of sufficient location information.The Water Rights Section of NDWR is responsible for reviewing and approving water rights applications, for new appropriations and for changes to existing water rights, as well as evaluating and responding to protests of applications, approving subdivision dedications for water quantity, evaluating domestic well credits and relinquishments, issuing certificates for permitted water rights, conducting field investigations, and processing requests for extensions of time for filing proofs of completion and proofs of beneficial use.Please note that this POD feature class may not contain all water right information on a site or permit. The GIS datasets do not replace the need to review the Permit database and hard copy permit files and are intended for convenience in sharing information on a map, finding a location, seeing spatial patterns, and planning.Code Descriptions:app_status app_status_nameABN ABANDONED (inactive)ABR ABROGATED (inactive)APP APPLICATION (pending)CAN CANCELLED (inactive)CER CERTIFICATE (active)CUR CURTAILED (inactive)DEC DECREED (active)DEN DENIED (inactive)EXP EXPIRED (inactive)FOR FORFEITED (inactive)PER PERMIT (active)REJ REJECTED (inactive)REL RELINQUISHED (inactive)RES RESERVED (pending)RFA READY FOR ACTION (pending)RFP READY FOR ACTION PROTESTED (pending)RLP RELINQUISH A PORTION (active)RSC RESCINDED (inactive)RVK REVOKED (inactive)RVP REVOCABLE PERMIT (active)SUP SUPERSEDED (inactive)SUS SUSPENDED (inactive)VST VESTED RIGHT (pending)WDR WITHDRAWN (inactive)manner of use (mou) use_nameCOM COMMERCIALCON CONSTRUCTIONDEC AS DECREEDDOM DOMESTICDWR DEWATERINGENV ENVIRONMENTALIND INDUSTRIALIRC IRRIGATION-CAREY ACTIRD IRRIGATION-DLEIRR IRRIGATIONMM MINING AND MILLINGMUN MUNICIPALOTH OTHERPWR POWERQM QUASI-MUNICIPALREC RECREATIONALSTK STOCKWATERINGSTO STORAGEUKN UNKNOWNWLD WILDLIFEMMD MINING, MILLING AND DEWATERINGEVP EVAPORATIONsource source_nameEFF EFFLUENTGEO GEOTHERMALLAK LAKEOGW OTHER GROUND WATEROSW OTHER SURFACE WATERRES RESERVOIRSPR SPRINGSTO STORAGESTR STREAMUG UNDERGROUNDDate Field Descriptions:Permit Date—Date the permit was issued.File Date—Date application was filed at the Division.Sent for Publication—Date the notice that the application was filed was sent to the newspaper of record for publication.Last Publication—The last date of publication of said notice in the paper; 30 days from this date is the last day for filing a protest to an application.POC Filed Date—When a Proof of Completion of Work is accepted by this office, it becomes “filed” rather than just received. The filed date is the same as the received date.
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TwitterOpen Database License (ODbL) v1.0https://www.opendatacommons.org/licenses/odbl/1.0/
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The goal of the Lead Safe Certificate program is to prevent lead poisoning by ensuring that all rental homes built prior to 1978 are compliant with the city's Lead Safe Ordinance and maintained free of lead hazards.This tool allows you to do the following:View all certificates associated with a locationSearch for specific certificates by ID or addressFilter certificates by characteristics like active/inactiveSee visualizations of the overall certificate datasetFor more information about the City's Lead Safe Certification program, please visit this Building & Housing page.RelatedLead Safe Certificates DatasetContactCity of Cleveland, Building and Housing Lead Compliance ProgramUpdate FrequencyDaily around 7 AM EST (6 AM during daylight savings)
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TwitterThis dataset attempts to represent the point locations of every educational program in the state of Minnesota that is currently operational and reporting to the Minnesota Department of Education. It can be used to identify schools, various individual school programs, school districts (by office location), colleges, and libraries, among other programs. Please note that not all school programs are statutorily required to report, and many types of programs can be reported at any time of the year, so this dataset is by nature an incomplete snapshot in time.
Maintenance of these locations is a result of an ongoing project to identify current school program locations where Food and Nutrition Services Office (FNS) programs are utilized. The FNS Office is in the Minnesota Department of Education (MDE). GIS staff at MDE maintain the dataset using school program and physical addresses provided by local education authorities (LEAs) for an MDE database called "MDE ORG". MDE GIS staff track weekly changes to program locations, along with comprehensive reviews each summer. All records have been reviewed for accuracy or edited at least once since January 1, 2020.
Note that there may remain errors due to the number of program locations and inconsistency in reporting from LEAs and other organizations. Some organization types (such as colleges and treatment programs) are not subject to annual reporting requirements, so various records included in this file may in fact be inactive or inaccurately located.
Note that multiple programs may occur at the same location and are represented as separate records. For example, an elementary and secondary school may be in the same building, but each has a separate record in the data layer. Users may leverage the "CLASS" and "ORGTYPE" attributes to filter and sort records according to their needs. In general, records at the same physical address will be located at the same coordinates.
This data is also available in CSV format. For that format only, OBJECTID and Shape columns are removed, and the Shape column is replaced by Latitude and Longitude columns.
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TwitterActive non-wholesale non-transmission Natural Gas Utility Service Areas as listed in the Regulatory Commission of Alaska (RCA) Certificate details for regulated utilities. Likely the most comprehensive collection of State of Alaska utility service areas - but not necessarily definitive for every utility. For complicated large city service areas such as water and sewer the GIS department that represents those cities might have the best representation of the service area. There are also utilities that may not be regulated by RCA which will not be in the data. Footprints in general were lifted from existing KML files created by a contractor in the years 2008-2017. Service area changes that have happened since 2008 may not yet be reflected in the footprints. In a few cases legal descriptions had typos which resulted in service areas miles from the community they intended to cover. In the case of the AsOfDate attribute in this dataset only reflects the date of the last syncing of master certificate metadata with RCA Library database - not the current polygon representation.Source: Regulatory Commission of AlaskaThis data has been visualized in a Geographic Information Systems (GIS) format and is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Regulatory Commission of Alaska Library
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TwitterODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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This dataset is OBSOLETE as of 11/18/2024 and will be removed from ArcGIS Online on 11/18/2025.An updated version of this dataset is available at Certified Sustainable Buildings | Open Data Portal | City of Cambridge.A map of the updated data can be found in two places:Certified Sustainable Buildings Map | Open Data Portal | City of CambridgeSustainable Buildings Map - City of Cambridge, MAThis point layer shows the location of sustainable buildings in Cambridge. For inclusion in this layer, a building must do at least one of the following: qualify for the City’s Article 22 regulatory process; be certified by Passive House; be certified by Enterprise Green Communities; or be certified by LEEDunder a LEED version that requires the whole building to meet sustainability standards. Some buildings meet two or more of these criteria. Additionally, this layer contains information about other certifications (Energy Star, Fitwel, and WELL) that may apply to the included buildings. If an included building participates in the City’s BEUDO regulatory process, this layer provides two key emissions figures for the building. Information provided about the applicable sustainable building programs for qualifying buildings includes certification levels, certification types, ratings, or scores. This layer includes data from City and non-City sources.Explore all our data on the Cambridge GIS Data Dictionary.Attributes NameType DetailsDescription BldgID type: Stringwidth: 50precision: 0 Unique ID for database from GIS.
Latitude type: Doublewidth: 8precision: 38 Geographic coordinate from GIS Bldg ID centroid file.
Longitude type: Doublewidth: 8precision: 38 Geographic coordinate from GIS Bldg ID centroid file.
Article22_SystemLevelEquivalenc type: Stringwidth: 150precision: 0
Article22 type: Stringwidth: 3precision: 0 "Yes" indicates Article 22 building.
BEUDO_TotalGHGEmissionsIntensit type: Doublewidth: 8precision: 38
BEUDO type: Stringwidth: 3precision: 0 "Yes" indicates BUEDO building.
BEUDO_SourceEUI type: Doublewidth: 8precision: 38 A critical variable for reporting about BEUDO.
EnergyStar type: Stringwidth: 3precision: 0 "Yes" indicates EnergyStar building.
EnergyStar_CountYearsCert type: SmallIntegerwidth: 2precision: 5 Number of years certified. EnergyStar certification may be renewed annually.
EnergyStar_LastYearCert type: Stringwidth: 4precision: 0 Year of last certification.
EnergyStar_LastCertScore type: SmallIntegerwidth: 2precision: 5 Most recent EnergyStar score.
EnterpriseGC type: Stringwidth: 3precision: 0 "Yes" indicates Enterprise Green Communities building.
EnterpriseGC_CertTemplate type: Stringwidth: 100precision: 0 Certification version.
EnterpriseGC_PointsAchieved type: SmallIntegerwidth: 2precision: 5 Enterprise Green Communities score.
Fitwel type: Stringwidth: 3precision: 0 "Yes" indicates Fitwel building.
Fitwel_StarRating type: SmallIntegerwidth: 2precision: 5 Numerical Fitwel rating.
LEED type: Stringwidth: 3precision: 0 "Yes" indicates LEED building.
LEED_TotalCerts type: SmallIntegerwidth: 2precision: 5 Number of certifications applying to the whole building. The LEED fields contain details about certifications that are "whole-building," not referring to one part of the building only or or to building operations.
LEED_LastCertDate type: Datewidth: 8precision: 0 Date of last certification applying to the whole building.
LEED_LastSystemVersion type: Stringwidth: 100precision: 0 Certification version and rating system.
LEED_LastCertLevel type: Stringwidth: 50precision: 0 LEED certifictation level at which whole building is certified. Certified/Silver/Gold/Platinum: Does not not include "registered" buildings.
PassiveHouse type: Stringwidth: 3precision: 0 "Yes" indicates Passive House building.
PassiveHouse_CertVersion type: Stringwidth: 100precision: 0 Certification version.
WELL type: Stringwidth: 3precision: 0 "Yes" indicates WELL building.
WELL_Version type: Stringwidth: 50precision: 0 Certification version.
WELL_ProjectType type: Stringwidth: 150precision: 0 WELL project type.
WELL_CertLevel type: Stringwidth: 50precision: 0 Certification level. Certified Pilot/Compliance/Bronze/Silver/Gold/Platinum or Health-Safety Rated: Does not include "registered" or "precertified" buildings.
created_date type: Datewidth: 8precision: 0
last_edited_date type: Datewidth: 8precision: 0
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TwitterThis dataset is a collection of records that communicate the locations of child care, family child care and certified child care centers in Minnesota. It was created by downloading licensing information from the Minnesota Department of Human Services (DHS), geocoding the spreadsheet records and converting them to a spatial format.
The following license types are represented:
Child Care Centers: Programs licensed to provide care to children for less than 24 hours a day in a commercial setting.
Family Child Care: Programs licensed to provide care to children for less than 24 hours a day, typically in the provider’s home or a local space, including a church.
Certified Child Care Center: Child care providers that are not required to be licensed, but are certified by DHS to be eligible to accept Child Care Assistance Program payments.
The approximately 10,000 records are combined into one layer, which can be queried to separate by license type. This version focuses on a smaller set of core attributes than can be found on DHS's Licensing Information Lookup Page; see that page for all the attributes: https://licensinglookup.dhs.state.mn.us/
Records represent licenses active as of the date shown in the Time Period of Content field. The official current status of licenses can be checked at the DHS licensing information lookup page.
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TwitterThis group includes the following items:
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TwitterThis data set shows the Summer Food Sites located within Allegheny County for children (18 years and younger) for breakfast and lunch during summer recess. OPEN SITES are food sites open to all children and CLOSED SITES are food sites reserved for children who are participating in other activities at the site. For more information on sites and program details call 1-800-851-3838 .
If viewing this description on the Western Pennsylvania Regional Data Center’s open data portal (http://www.wprdc.org), this dataset is harvested on a weekly basis from Allegheny County’s GIS data portal (http://openac.alcogis.opendata.arcgis.com/). The full metadata record for this dataset can also be found on Allegheny County’s GIS portal. You can access the metadata record and other resources on the GIS portal by clicking on the “Explore” button (and choosing the “Go to resource” option) to the right of the “ArcGIS Open Dataset” text below.
Category: Education and Human and Social Services
Organization: Allegheny County
Department: Department of Human Services - Office of Community Services
Temporal Coverage: 28th July, 2017
Data Notes:
Coordinate System: Pennsylvania State Plane South Zone 3702; U.S. Survey Foot
Development Notes: none
Other: none
Frequency - Data Change: As needed
Frequency - Publishing: As needed
Data Steward Name: Sumiya Tarannum
Data Steward Email: Sumiya.tarannum@alleghenycounty.us
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TwitterThis group includes the following items:
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TwitterPrivate wells in this layer come from the Department of Environmental Conservation's Water Supply Data Composite. Managed by the Water Supply Division's Well Driller and Well Location Program, the database contains private well information submitted by Vermont licensed well drillers. Licensed well drillers have been required to submit well completion reports (well logs) to the state since 1966. Well tags have been required since 1986. NOTE: the data contained here is only as accurate as what was submitted - many wells were completed, but not reported, many reports have missing information, were recorded inaccurately or poorly located geographically. Help us improve our database. Click the appropriate link within the feature's attributes to report a missing/inaccurate well report.Data is updated daily.For the Lithology Reports associated with Private Wells, download the Lithology Reports here: Private Wells - Lithology Reports
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TwitterApril 1, 2025: data feeds from DMV are currently offline while the agency works to migrate reporting systems. The most recent data available is from December 2024. Open Data DC is working with DMV to restore data feeds as soon as possible.On behalf of the District Department of Transportation (DDOT), which regulates parking in the District, DC DMV issues three types of disability placards or permits, one-week permits, temporary placards, and long-term placards, all described below.One-Week PermitsYou can get a one-week disability permit if you only require the placard for a week or less (or you have a visitor who requires it), you have a short-term disability, or your vehicle with disability tags is being repaired. For a one-week permit, you do not need a doctor’s certification. The one-week permit is not renewable within a one-year period.Temporary PlacardsYou can get a temporary disability placard if you have a physical condition that substantially impairs your mobility that is expected to last no longer than 8 years. Your medical practitioner must certify the application and indicate the expected length of your disability. If you find you need your disabled privileges longer, you must submit a new application with a medical practitioner's certification.Long-Term PlacardsYou can get a long-term disability if you have a long-term disability. The list of qualifying disabilities is included on the application for the placard. You do not need a medical practitioner's certification if you have an obvious missing lower extremity or you use a motorized wheelchair.The long-term placard is valid up to 8 years to coincide with the expiration of your driver license or identification card. To renew it, you must submit a new application with a medical practitioner's certification.Temporary and long-term placards expire on the last day of the month and year indicated on the placard.Placards or permits should be hung from the rearview mirror while the vehicle is parked in a space authorized for the disabled and must be displayed and readable from the front windshield. They must be removed from the rearview mirror while the vehicle is in motion.
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TwitterThis ArcGIS Instant App leverages the nearby functionality with the Medi-Cal Licensed Narcotic Treatment Program Facility Listing to enable members of the public to find providers or services near a specific location. New as of 5/8/25
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TwitterThe datasets in this zip file are in support of Intelligent Transportation Systems Joint Program Office (ITS JPO) report FHWA-JPO-16-385, "Analysis, Modeling, and Simulation (AMS) Testbed Development and Evaluation to Support Dynamic Mobility Applications (DMA) and Active Transportation and Demand Management (ATDM) Programs — Evaluation Report for ATDM Program," https://rosap.ntl.bts.gov/view/dot/32520 and FHWA-JPO-16-373, "Analysis, modeling, and simulation (AMS) testbed development and evaluation to support dynamic mobility applications (DMA) and active transportation and demand management (ATDM) programs : Dallas testbed analysis plan," https://rosap.ntl.bts.gov/view/dot/32106 The files in this zip file are specifically related to the Dallas Testbed. The compressed zip files total 2.2 GB in size. The files have been uploaded as-is; no further documentation was supplied by NTL. All located .docx files were converted to .pdf document files which are an open, archival format. These pdfs were then added to the zip file alongside the original .docx files. These files can be unzipped using any zip compression/decompression software. This zip file contains files in the following formats: .pdf document files which can be read using any pdf reader; .cvs text files which can be read using any text editor; .txt text files which can be read using any text editor; .docx document files which can be read in Microsoft Word and some other word processing programs; . xlsx spreadsheet files which can be read in Microsoft Excel and some other spreadsheet programs; .dat data files which may be text or multimedia; as well as GIS or mapping files in the fowlling formats: .mxd, .dbf, .prj, .sbn, .shp., .shp.xml; which may be opened in ArcGIS or other GIS software. [software requirements] These files were last accessed in 2017.
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TwitterThis dataset is the geocoded addresses of the LPA office in California. This dataset's source is DDW's SDWIS contacts database and this publicly available document: https://www.waterboards.ca.gov/drinking_water/programs/documents/web_contact_info_district_lpa.pdfThe dataset was last updated in December 2020 and will be updated as needed.Contact for this dataset/layer is DDW GIS workgroup, DDW-GIS-workgroup@waterboards.ca.gov.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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In this course, you will explore a variety of open-source technologies for working with geosptial data, performing spatial analysis, and undertaking general data science. The first component of the class focuses on the use of QGIS and associated technologies (GDAL, PROJ, GRASS, SAGA, and Orfeo Toolbox). The second component of the class introduces Python and associated open-source libraries and modules (NumPy, Pandas, Matplotlib, Seaborn, GeoPandas, Rasterio, WhiteboxTools, and Scikit-Learn) used by geospatial scientists and data scientists. We also provide an introduction to Structured Query Language (SQL) for performing table and spatial queries. This course is designed for individuals that have a background in GIS, such as working in the ArcGIS environment, but no prior experience using open-source software and/or coding. You will be asked to work through a series of lecture modules and videos broken into several topic areas, as outlined below. Fourteen assignments and the required data have been provided as hands-on opportunites to work with data and the discussed technologies and methods. If you have any questions or suggestions, feel free to contact us. We hope to continue to update and improve this course. This course was produced by West Virginia View (http://www.wvview.org/) with support from AmericaView (https://americaview.org/). This material is based upon work supported by the U.S. Geological Survey under Grant/Cooperative Agreement No. G18AP00077. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the opinions or policies of the U.S. Geological Survey. Mention of trade names or commercial products does not constitute their endorsement by the U.S. Geological Survey. After completing this course you will be able to: apply QGIS to visualize, query, and analyze vector and raster spatial data. use available resources to further expand your knowledge of open-source technologies. describe and use a variety of open data formats. code in Python at an intermediate-level. read, summarize, visualize, and analyze data using open Python libraries. create spatial predictive models using Python and associated libraries. use SQL to perform table and spatial queries at an intermediate-level.