ADHS inspects, certifies and licenses medical health care institutions and providers of medical services, child care centers, business hearing dispensers, and DUI and domestic violence treatment centers. Each month, an extract from the ADHS Division of Licensing SQL view is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create feature classes by facility type. Tabular data is maintained by each respective bureau in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services. Last updated: February 2025Update Frequency: MonthlyData FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

The geographical mapping software market is experiencing robust growth, driven by increasing demand across diverse sectors. The market's expansion is fueled by several key factors: the rising adoption of cloud-based solutions offering enhanced accessibility and scalability, the burgeoning need for precise spatial data analysis in urban planning and water resource management, and the escalating use of GIS technology in geological exploration for resource discovery and environmental monitoring. The market's compound annual growth rate (CAGR) is estimated at 8% between 2025 and 2033, projecting significant market expansion. This growth is further supported by the increasing availability of high-resolution satellite imagery and improved data processing capabilities, leading to more accurate and detailed maps for various applications. While the market shows strong potential, certain restraints, including high software licensing costs and the complexity of some GIS software, may impede growth to some extent. However, the overall trend leans towards increased adoption driven by the significant benefits of enhanced spatial analysis across industries. Market segmentation reveals a strong demand for cloud-based solutions due to their flexibility and cost-effectiveness compared to web-based or on-premise software. Geographically, North America and Europe currently hold significant market shares, reflecting established GIS infrastructure and technological advancement. However, Asia-Pacific is expected to witness substantial growth in the coming years driven by rapid urbanization, infrastructure development, and increased government investment in mapping initiatives. This region's expanding market will be fueled by countries like China and India, with significant potential for market penetration. The key players in this competitive landscape continually innovate, releasing new features and functionalities to maintain their market positions. The focus is increasingly on user-friendliness, integration with other software platforms, and advanced analytical capabilities.

Deprecation notice: This tool is deprecated because this functionality is now available with out-of-the-box tools in ArcGIS Pro. The tool author will no longer be making further enhancements or fixing major bugs.Use Add GTFS to a Network Dataset to incorporate transit data into a network dataset so you can perform schedule-aware analyses using the Network Analyst tools in ArcMap.After creating your network dataset, you can use the ArcGIS Network Analyst tools, like Service Area and OD Cost Matrix, to perform transit/pedestrian accessibility analyses, make decisions about where to locate new facilities, find populations underserved by transit or particular types of facilities, or visualize the areas reachable from your business at different times of day. You can also publish services in ArcGIS Server that use your network dataset.The Add GTFS to a Network Dataset tool suite consists of a toolbox to pre-process the GTFS data to prepare it for use in the network dataset and a custom GTFS transit evaluator you must install that helps the network dataset read the GTFS schedules. A user's guide is included to help you set up your network dataset and run analyses.Instructions:Download the tool. It will be a zip file.Unzip the file and put it in a permanent location on your machine where you won't lose it. Do not save the unzipped tool folder on a network drive, the Desktop, or any other special reserved Windows folders (like C:\Program Files) because this could cause problems later.The unzipped file contains an installer, AddGTFStoaNetworkDataset_Installer.exe. Double-click this to run it. The installation should proceed quickly, and it should say "Completed" when finished.Read the User's Guide for instructions on creating and using your network dataset.System requirements:ArcMap 10.1 or higher with a Desktop Standard (ArcEditor) license. (You can still use it if you have a Desktop Basic license, but you will have to find an alternate method for one of the pre-processing tools.) ArcMap 10.6 or higher is recommended because you will be able to construct your network dataset much more easily using a template rather than having to do it manually step by step. This tool does not work in ArcGIS Pro. See the User's Guide for more information.Network Analyst extensionThe necessary permissions to install something on your computer.Data requirements:Street data for the area covered by your transit system, preferably data including pedestrian attributes. If you need help preparing high-quality street data for your network, please review this tutorial.A valid GTFS dataset. If your GTFS dataset has blank values for arrival_time and departure_time in stop_times.txt, you will not be able to run this tool. You can download and use the Interpolate Blank Stop Times tool to estimate blank arrival_time and departure_time values for your dataset if you still want to use it.Help forum

Abstract: Monthly and annual average solar resource potential for the lower 48 states of the United States of America.

Purpose: Provide information on the solar resource potential for the for the lower 48 states of the United States of America.

Supplemental Information: This data provides monthly average and annual average daily total solar resource averaged over surface cells of approximatley 40 km by 40 km in size. This data was developed from the Climatological Solar Radiation (CSR) Model. The CSR model was developed by the National Renewable Energy Laboratory for the U.S. Department of Energy. Specific information about this model can be found in Maxwell, George and Wilcox (1998) and George and Maxwell (1999). This model uses information on cloud cover, atmostpheric water vapor and trace gases, and the amount of aerosols in the atmosphere to calculate the monthly average daily total insolation (sun and sky) falling on a horizontal surface. The cloud cover data used as input to the CSR model are an 7-year histogram (1985-1991) of monthly average cloud fraction provided for grid cells of approximately 40km x 40km in size. Thus, the spatial resolution of the CSR model output is defined by this database. The data are obtained from the National Climatic Data Center in Ashville, North Carolina, and were developed from the U.S. Air Force Real Time Nephanalysis (RTNEPH) program. Atmospheric water vapor, trace gases, and aerosols are derived from a variety of sources. The procedures for converting the collector at latitude tilt are described in Marion and Wilcox (1994). Where possible, existing ground measurement stations are used to validate the data. Nevertheless, there is uncertainty associated with the meterological input to the model, since some of the input parameters are not avalible at a 40km resolution. As a result, it is believed that the modeled values are accurate to approximately 10% of a true measured value within the grid cell. Due to terrain effects and other micoclimate influences, the local cloud cover can vary significantly even within a single grid cell. Furthermore, the uncertainty of the modeled estimates increase with distance from reliable measurement sources and with the complexity of the terrain.

Other Citation Details: George, R, and E. Maxwell, 1999: "High-Resolution Maps of Solar Collector Performance Using A Climatological Solar Radiation Model", Proceedings of the 1999 Annual Conference, American Solar Energy Society, Portland, ME.

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

This dataset was developed by the National Renewable Energy Laboratory (NREL) for the U.S. Agency for International Development's (USAID) South Asia Regional Initiative for Energy Cooperation (SARI/E). The dataset contains graphical files of seasonal and diurnal data from over 50 surface weather stations in .pdf format in Afghanistan. The data were output in Geographic Information Systems (GIS) format and incorporated into a Geospatial Toolkit (GsT). The GsT allows the user to examine the resource data in a geospatial context along with other key information relevant to renewable energy development, such as transportation networks, transmission corridors, existing power facilities, load centers, terrain conditions, and land use.

License Info

DISCLAIMER NOTICE This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

Annual average wind resource development potential for the state of Texas.

This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile is in a UTM zone 19, datum WGS 84 projection system.

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

Estimate the potential for producing hydrogen from key renewable resources (onshore wind, solar photovoltaic, and biomass) by county for the United States. This study was conducted to estimate the potential for producing hydrogen from key renewable resources (onshore wind, solar photovoltaic, and biomass) by county in the United States and to create maps that allow the reader to easily visualize the results. To accomplish this objective, the authors analyzed renewable resource data both statistically and graphically utilizing a state-of-the-art Geographic Information System (GIS), a computer-based information system used to create and visualize geographic information.

Land-use and environmental exclusions were applied to represent the most viable resources across the country. While wind, solar, and biomass are considered major renewable resources, other renewable energy resources could also be used for hydrogen production, thus contributing to hydrogen development locally and regionally. These additional resources include offshore wind, concentrating solar power, geothermal, hydropower, photoelectrochemical, and photobiological resources.

This study found that approximately 1 billion metric tons of hydrogen could be produced annually from wind, solar, and biomass resources in the United States. The greatest potential for producing hydrogen from these key renewable resources is in the Great Plains region. In addition, this research suggests that renewable hydrogen has the potential to displace gasoline consumption in most states if and when a number of technical and scientific barriers can be overcome.

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

For all information on highway license fees, please click the link below:https://www.middlesbrough.gov.uk/parking-roads-and-footpaths/roads-and-highways/highway-licences/highway-fees

Abstract: Annual average wind resource potential for the state of South Carolina at a 50 meter height.

Purpose: Provide information on the wind resource development potential within the state of South Carolina.

Supplemental Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a WGS 84 projection system.

Other Citation Details: The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

License Info

This GIS data was developed by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC for the U.S. Department of Energy ("DOE"). The user is granted the right, without any fee or cost, to use, copy, modify, alter, enhance and distribute this data for any purpose whatsoever, provided that this entire notice appears in all copies of the data. Further, the user of this data agrees to credit NREL in any publications or software that incorporate or use the data.

Access to and use of the GIS data shall further impose the following obligations on the User. The names DOE/NREL may not be used in any advertising or publicity to endorse or promote any product or commercial entity using or incorporating the GIS data unless specific written authorization is obtained from DOE/NREL. The User also understands that DOE/NREL shall not be obligated to provide updates, support, consulting, training or assistance of any kind whatsoever with regard to the use of the GIS data.

THE GIS DATA IS PROVIDED "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL DOE/NREL BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER, INCLUDING BUT NOT LIMITED TO CLAIMS ASSOCIATED WITH THE LOSS OF DATA OR PROFITS, WHICH MAY RESULT FROM AN ACTION IN CONTRACT, NEGLIGENCE OR OTHER TORTIOUS CLAIM THAT ARISES OUT OF OR IN CONNECTION WITH THE ACCESS OR USE OF THE GIS DATA.

The User acknowledges that access to the GIS data is subject to U.S. Export laws and regulations and any use or transfer of the GIS data must be authorized under those regulations. The User shall not use, distribute, transfer, or transmit GIS data or any products incorporating the GIS data except in compliance with U.S. export regulations. If requested by DOE/NREL, the User agrees to sign written assurances and other export-related documentation as may be required to comply with U.S. export regulations.

The global Navigation Electronic Map market is experiencing robust growth, projected to reach a market size of $14,750 million in 2025. While the exact CAGR isn't provided, considering the rapid advancements in technology, increasing adoption of GPS-enabled devices, and the expanding use of navigation systems across personal, commercial, and military sectors, a conservative estimate of the CAGR between 2025 and 2033 would be around 8%. This translates to substantial market expansion over the forecast period. Key drivers include the proliferation of smartphones with integrated navigation capabilities, the rising demand for precise location-based services, and the increasing sophistication of mapping technologies, such as the transition from 2D to 3D mapping. The market is segmented by map type (2D and 3D) and application (personal, commercial, and military). The commercial segment is expected to dominate due to its widespread use in logistics, fleet management, and ride-sharing services. Growth is further fueled by the integration of navigation maps with augmented reality (AR) and artificial intelligence (AI) to enhance user experience. However, factors such as data security concerns, licensing costs, and the need for continuous map updates pose challenges to the market's growth. The competitive landscape is marked by a mix of established players like Google, TomTom, and HERE, and regional players catering to specific geographic needs. Geographical expansion, particularly in emerging economies with increasing smartphone penetration, presents significant opportunities for market expansion. The market's strong growth is fueled by several factors. The integration of advanced features like real-time traffic updates, voice guidance, and offline map access significantly enhances user experience and drives adoption. The increasing use of navigation systems in autonomous vehicles is also a significant factor driving market expansion. The commercial sector, encompassing logistics, transportation, and delivery services, shows high growth potential due to the need for efficient route optimization and fleet management. Government initiatives promoting smart city development and infrastructure projects also contribute positively. Furthermore, continuous innovations in mapping technologies, such as high-resolution satellite imagery and improved data processing techniques, ensure the continued relevance and sophistication of navigation electronic maps. The competitive landscape is dynamic, with companies focusing on developing advanced features, strategic partnerships, and geographic expansion to secure market share.

The objective of this report is to determine whether electronic vehicle recognition systems (EVR) or automatic license plate recognition systems (ALPR) would be beneficial to the Arizona Department of Transportation (AzDOT). EVR uses radio frequency identification technology tags (RFID) that would be placed on all registered vehicles so that RFID readers could read vehicles’ plate numbers as they pass using the radio frequency signal emitted by the RFID tag. ALPR technology uses cameras and alphanumerical recognition software to read license plates as they pass. The literature review looks into the previous applications of both ALPR and EVR. Departments of Transportation (DOTs), tolling authorities and law enforcement all have used various applications of this advanced electronic technology. Based on the literature review and the benefits section (Chapter 3), the potential benefits of an ALPR / EVR system are: 1. The ability for AzDOT to potentially monitor traffic flow more accurately, 2. The ability to better enforce license and registration compliance, 3. The ability to better enforce auto insurance compliance, 4. The ability to implement a toll, or congestion charge, 5. The ability to aid law enforcement in finding suspected criminals. Chapter 4 determines the potential costs of an ALPR or EVR system and then compares the costs with the total quantifiable benefits using two case studies. In the first case study, an ALPR system was set up on all major valley freeways, and in the second case study, an EVR system was set up on all major valley freeways. The ALPR case study concluded that such an ALPR system could be set up for about $10 million dollars and it could generate up to $400 million dollars in direct benefit per year and up to $1.3 trillion in benefits to highway users per year. The EVR case study concluded that such an EVR system could be set up for about $50 million, and it could generate up to $407 million in direct benefit per year and up to $1.33 trillion in benefits to highway users per year. A direct benefit profits the state directly with cash, while benefits to highway users helps society as a whole but the state receives no revenue. Chapter 5 looked into the legality of a potential ALPR or EVR system. This chapter concluded that AzDOT has the authority to implement an ALPR / EVR system in Arizona. However this section also concluded that AzDOT should seek legislative support to increase public support. This report concludes that at the present ALPR should be further researched and/or implemented by the State of Arizona. The reasons for this recommendation are because of: ALPR’s previous applications, ALPR’s lower up front cost, ALPR’s ability to read out-of-state plates, ALPR’s potential lower degree of public opposition, and the possibility that ALPR would have to back up an EVR system. All in all, these technologies are changing at a rapid rate and a change in any of these variables that generated this recommendation could change this recommendation.

The literature on nighttime conspicuity (visibility) and legibility of non-reflectorized and reflectorized license plated and their accident reduction potential, safety and other benefits was reviewed. A nighttime field study using 20 young subjects using an experimental car and an opposing glare car (both H6054 lowbeams) was conducted to assess the nighttime conspicuity performance (550 ft, 2 license plate display location, 2 seconds exposure time) and the nighttime legibility performance ( 81.2 ft legibility distance, 2 seconds exposure time) of new and used reflective sheeting license plates (Texas plates, 3 numbers and 3 letters). The results of this nighttime field study indicate that under fairly close to real world conditions, the reflective sheeting license plates provide better and statistically significant conspicuity and legibility performance than the beads on paint license plates. A cost analysis considering all costs (including the metal plate, packaging, distribution, etc.) indicates that for a life cycle of 5 years, the yearly costs of the reflective sheeting license plates is about $1.10 while that of the beads on paint license plates is about $1.08. However, calculations indicate that if the reflective sheeting plates are used one year longer than the beads on paint plates (very small conspicuity and legibility performance decrease between Texas new and Texas used would appear to make this life extension feasible) then the reflective sheeting plates would actually have a slight cost advantage over the beads on paint plates for any life cycle time period.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Medical Facilities Licensing licenses and certifies medical health care institutions and providers of medical services to protect the public's health and safety and assure quality customer service through teamwork in a timely, efficient, and responsive manner.Records are created and maintained by Bureau of Medical Facilities Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including medical facilities. Feature types in this layer include: behavioral health-inpatient, home health agencies, hospice, outpatient surgery centers, and outpatient treatment centers.Last Updated: February 2025Update frequency: MonthlyData FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Long-Term Care Licensing licenses and inspects Arizona nursing homes facilities. Long-Term Care staff also perform Medicaid certification inspections for Arizona's Intermediate Care Facilities for the Developmentally Disabled (ICFDD).Records are created and maintained by Bureau of Long-Term Care Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including long-term care facilities. Last Updated: February 2025Updated frequency: MonthlyData FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

The data in this is Dog Licensee's that shows the number of annual and Lifetime License's purchased in Fingal County Council.A yearly License costs €20 and a Lifetime License costs €140.We will continue to promote the requirement for a Dog License. It is a legal requirement to hold a valid License for any dog you own or are responsible for.Control of Dog Act 1982 & Control of Dogs Act 1992The Dog Warden service looks after stray and unwanted dogs and enforcement in relation to the Control of Dogs Acts. Links to the Control of Dogs Act, 1986, and the Control of Dogs (Amendment) Act, 1992. If you find a stray dog or wish to surrender your dog please contact Environment@fingal.ieor phone: 01-8905000.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Residential Facilities Licensing licenses and regulates Residential Healthcare Facilities, including Assisted Living Centers/Homes and Behavioral Health Residential Facilities, along with Adult Day Health Care Facilities, Adult Foster Care Homes, Behavioral Health Respite Homes, and Behavioral Health Therapeutic Homes.Records are created and maintained by Bureau of Residential Facilities Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including residential facilities. Last Updated: February 2025Update frequency: Monthly Data FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Child Care Licensing regulates and monitors licensed child care facilities, public school child care programs and certified child care group homes statewide.Records are created and maintained by Bureau of Child Care Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including childcare facilities. Last Updated: February 2025Update frequency: Monthly Data FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

ADHS Division of Licensing Mission Statement: To protect the health and safety of Arizonans by providing information, establishing standards, and licensing and regulating health and child care services.The Arizona Department of Health Services-Bureau of Medical Facilities Licensing licenses and certifies medical health care institutions and providers of medical services to protect the public's health and safety and assure quality customer service through teamwork in a timely, efficient, and responsive manner.Records are created and maintained by Bureau of Medical Facilities Licensing staff in the licensing division, while the GIS Team extracts the data and creates GIS layers and shares them publicly. Each month, an extract from the ADHS Division of Licensing SQL database is geocoded using ADHS's internal geocoder, and post-processed using a Python script to create and publish feature classes by facility type, including hospitals. Last Updated: February 2025Update frequency: MonthlyData FAQs:Some records have “license_expiration” earlier than the “rundate” while the “OPERTION_STATUS” is “ACTIVE”, should we treat all records with “OPERATION_STATUS” of “ACTIVE” as open at the time the data is released? Answer: Yes - ACTIVE is all the current licenses. In 2019 there was a perpetual rule change that affected certain facilities so in lieu of an expiration date, we began tracking the annual fee due date in the "license_expiration" field. Per rule, these facilities can submit annual requirements up to 30 days after the fee due date (aka license expiration in the provider database) so we do expect some to be earlier than the run date. Is the FACID of the same facility maintained unique and same throughout all releases? If a facility is purchased by a different company or has it’s name changed, is the FACID changed? Answer: The FACID represents a licensed premise - in many cases the facility ID is maintained when purchased by a different owner but under federal rule, certain facilities may choose to have a new CMS certification number which would require a new FACID be issued for that premise. What’s the unit type of capacities for different categories? Answer: This varies - it can be child capacity, bed count, dialysis station, etc. For Group_Home_for_Individuals_with_a_Developmental_Disability and Residential_Facility, how to tell if the employer’s office is at the facility VS the employer’s office is somewhere else and employees are sent to those facilities? Also is there a way to tell if a facility only has part time workers (Like workers only need to be at the residential facility less than 8hr per day or less than 5 days a week )? Answer: This is not currently available on the public databaseThe data contains a 'COUNTY' field and a "N_County' field - which one should I use to filter results? Answer: N_County - this is the county that's assigned when a record is geocoded using the physical street address, vs one that is assigned manually during the licensing process.

These are the locations of designated trails for the purposes of facilitating public access and recreation on properties managed by the South Florida Water Management District. The types of recreation activities on designated trails varies and may include hiking, biking, equestrian or horseback riding, and vehicular use. The Florida National Scenic Trail (hiking trail) runs through certain District properties, visit www.floridatrail.org. to identify which portions of the FNST are located on District lands. Trail materials and conditions may consist of primitive earthen trails, boardwalks or constructed walkways, District levees and ROWs, grades, old tram roads, and stabilized shell-rock. In certain instances, a no-cost Special Use License issued by the District may be required for some activities as listed in Public Use Rule 40E-7 F.A.C., such as horse-back riding and vehicular use. A list of the areas and activities that require a District’s Special Use License are available on the District’s Recreation website at www.sfwmd.gov/sul.