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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
Because the Esri Education Institution Agreement offers discounted license fees, certain categories of uses are not permitted under the terms of the agreement. Sometimes it is unclear whether a particular use is permitted under the terms of the Esri Education Institution Agreement or requires a standard commercial license. We prepared this document to provide a framework within which license administrators and Esri staff can make informed and reasoned decisions about such matters. We welcome your inquiries if questions remain.
description: 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.; abstract: 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.
description: 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.; abstract: 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.
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The Vermont Fish & Wildlife Department maintains developed fishing access areas. These sites provide public access to waters in Vermont for shore fishing opportunities and launching of water craft. The department manages access areas with concrete or gravel ramps for launching and retrieving of boats. Additionally, there are access areas where non-motorized vessels can easily be launched. All access areas are open to hunting, trapping, fishing, and boating. Management and administration of all access areas is primarily funded through the sale of motorboat registration fees and the Sport Fish Restoration Program (SFR). The SFR Program was created to restore and better manage America's declining fishery resources and was modeled after the successful Wildlife Restoration Program. Excise taxes on fishing equipment, motorboat and small engine fuels, import duties, and interest are collected and appropriated from the Sport Fish Restoration and Boating Trust Fund. The Vermont Fish & Wildlife Department uses these monies for acquiring land as well as developing and maintaining boat and fishing access areas. These excise tax dollars, coupled with motorboat registration fees, have been the predominate source of funding for the access program over the last 20 years. Prior to the use of motorboat registration fees, angler license dollars were used in a similar fashion.
Auditor ResponsibilitiesReal Estate Appraisal and AssessmentThe Lucas County Auditor sets fair and equitable values for each parcel in Lucas County. By Ohio law, the County Auditor must complete a reappraisal every 6 years and an update based on market trends 3 years after a reappraisal. An update was conducted in 2021 and a reappraisal will occur in 2024.Lucas County Real Estate Appraisal and AssessmentWeights and MeasuresThe Lucas County Auditor protects County residents and businesses by ensuring all commercial weighing and measuring devices are accurate. Weights & Measures checks gas pumps, price scanners, meat and produce scales.Lucas County Weights & Measures DepartmentLicensingLicensing for dogs, kennels, vendors, and cigarettes are issued by the Lucas County Auditor.Lucas County Vendor and Cigarette Licensing InformationLucas County Dog Licensing InformationSteward of Public FundsThe Lucas County Auditor is the watchdog of County funds. As Lucas County’s Chief Financial Officer, the Auditor:• Accounts for hundreds of millions of dollars received by Lucas County each year.• Issue payments for all County obligations, including the distribution of taxes to townships, villages, cities, school districts, libraries, and County agencies.• Administer and distribute tax and license revenues including real estate taxes, personal property taxes, motor vehicle license fees, gasoline taxes, estate taxes, manufactured home taxes, local government funds, and other state subsidies.• Administer the Lucas County payroll.• Produce the County’s annual financial report.
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
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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.
MIT Licensehttps://opensource.org/licenses/MIT
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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.
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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.