Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
MIT Licensehttps://opensource.org/licenses/MIT
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Certificate of Occupancy
Professional Growth Management - Attract, grow, and retain top talent to serve our seniors and their families with passion, pride, and professionalism.
Dataset contains information on Tempeans receiving post-secondary education, licenses, certificates. Data supports City's Achieve65Tempe goal that 65 percent of Tempe’s adult population access post-secondary education, resulting in a certification to an advanced degree by 2030.This page provides data for the Post-Secondary School Achievement Rate performance measure. Certificate and License estimates from the Arizona Board of Regents.The performance measure dashboard is available at 3.09 Post-Secondary School Achievement Rate.Additional InformationSource: US Census, Arizona Board of RegentsContact: Marie RaymondContact E-Mail: Marie_Raymond@tempe.govData Source Type: Excel / CSVPreparation Method: Numbers retrieved from US Census and Arizona Board of Regents, then combined into a summary spreadsheet. The supporting data sources are also provided.Publish Frequency: annuallyPublish Method: manualData Dictionary
This document is an Elevation Certificate that represents the given Address listed in the title of the document. Some may vary in appearance due to age and documentation updates.
This feature class represents locations of properties that should have elevation certificates in Baltimore County. The points were compiled based on the address information provided on the certificate or other source material. Scanned copies of elevation certificates and other relevant documents are stored in the database as attachments. The attached documents are in PDF format.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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The requirement to hold a Waste Collection Permit is in accordance with section 34(1) of the Waste Management Act 1996 (as amended). A permit is required by anyone collecting Waste on a commercial basis to ensure that the Waste is gathered, sorted and transported correctly. The revised Waste Management (Collection Permit) Regulations 2007 (S.I. 820 of 2007 & S.I. 87 of 2008) came into effect on 1st of June 2008. It is recommended that this dataset is read in conjunction with the ‘Waste Facility Permit Locations SDCC’ dataset.
Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
License information was derived automatically
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.
Open 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.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 ExplorerData GlossaryCOLUMN | DESCRIPTIONRECORD_ID | Unique ID produced by the Accela system.STATUS | Status of the certificate. IS_ACTIVE | Flag that is true if the certificate has a status of Certified, Active, About to Expire, or Exempt, all of which indicate that the associated property is lead safe. All other statuses are coded as false.RECORD_FILE_DATE | Date when the certificate was originally filed.RENTAL_REG_ID | ID of the associated rental registration record in Accela.RENEWAL_RECORD_ID | ID of an associated renewal record in Accela, if applicable.RENEWAL_RECORD_FILE_DATE | File date of the renewal, if applicable.STATUS_DATE | Time of last status update for the certificate.EXPIRATION_DATE | Date on which the certificate will expire.PrimaryAddress | Primary address associated with the certificate.PrimaryAddressZip | Zip code in the primary address.YEAR_BUILT | Year the associated building was constructed.TOTAL_UNITS | Total units in the building associated with the certificate.TOTAL_UNITS_INSPECTED | Total units inspected.INSPECTION_TYPE | Type of inspection.INSPECTION_DATE | Date of inspection. INVESTIGATOR_CERTIFICATION_ID | ID of the investigator who conducted the inspection.REVIEW_DATE | Date of last review.ACCELA_CITIZEN_ACCESS_URL | Link to the record in the Accela Citizen Access portal.DW_Parcel | Associated parcel number. DW_Ward | Associated ward (pre-2025 boundaries).DW_Tract2020 | 2020 Census tract.DW_Neighborhood | Neighborhood.IS_GEOLOCATED | True if the City's geocoder could locate the address. False otherwise.ContactCity of Cleveland, Building and Housing Lead Compliance ProgramUpdate FrequencyWeekly on Sundays at 7 AM EST (6 AM during daylight savings)
Web Map illustration of Garbage Service Area Boundary described in the certificated authority issued to Solid Waste Companies by Utilities and Transportation Commission (UTC). For additional information and questions pertaining to solid waste certificate coverage and issuance please, contact the UTC Licensing Section, 360-664-1223,
This 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
https://www.scottsdaleaz.gov/AssetFactory.aspx?did=69351https://www.scottsdaleaz.gov/AssetFactory.aspx?did=69351
Please click here to view the Data Dictionary, a description of the fields in this table.Certificates of Occupancy issued by the City of Scottsdale.
This group includes the following items:
This document is an Elevation Certificate that represents the given Address listed in the title of the document. Some may vary in appearance due to age and documentation updates.
All applicants for a Basic Business License operating from a commercial location in the District of Columbia must provide a Certificate of Occupancy (C of O) for the premise address from which the business activity is conducted in order to demonstrate the activity does not conflict with building and zoning codes. A certificate of occupancy is needed to occupy any structure other than a single family dwelling. To include the following uses: two family flat, apartment house, and all commercial uses.
This layer includes only parcels where final elevation certificates are available, with all elevations reported in NAVD 1988. Where necessary, conversions from NGVD 1929 to NAVD 1988 were completed using the VERTCON v2.1 program (NOAA NGS, 2018). 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
Map displays large traffic generating developments whose gross floor area or parking spaces meet or exceed the thresholds defined by section 14-312-1 of the Office of the State Traffic Administrations (OSTA) regulations.
This web map shows the cumulative data of certificate of compliance issued from 2018 onwards in Hong Kong. It is a set of data made available by the Lands Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk.
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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The Hills of Governor's Island Dataset for GRASS GIS
This geospatial dataset contains raster and vector data for the Hills region of Governor's Island, New York City, USA. The top level directory governors_island_hills_for_grass is a GRASS GIS location for NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet in US Surveyor's Feet with EPSG code 2263. Inside the location there is the PERMANENT mapset, a license file, data record, readme file, workspace, color table, category rules, and scripts for data processing. This dataset was created for the course GIS for Designers.
Instructions
Install GRASS GIS, unzip this archive, and move the location into your GRASS GIS database
directory. If you are new to GRASS GIS read the first time users guide.
Data Sources
Maps
License
This dataset is licensed under the ODC Public Domain Dedication and License 1.0 (PDDL) by Brendan Harmon.
A community's permit file must have an official record that shows new buildings and substantial improvements in all identified Special Flood Hazard Areas (SFHAs)are properly elevated. This elevation information is needed to show compliance with the floodplain management ordinance. FEMA encourages communities to use the Elevation Certificate developed by FEMA to fulfill this requirement since it also can be used by the property owner to obtain flood insurance. Communities participating in the Community Rating System (CRS) are required to use the FEMA Online Elevation Certificate, FEMA Form FF-206-FY-22-152 (formerly 086-0-33).
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.