The GIS component of Virginia's NG9-1-1 deployments is moving in waves, with new groups of localities starting the onboarding process every three months. Well into our third wave, new resources and recommendations on GIS related topics are now available on the VGIN 9-1-1 & GIS page. This is available as a large combined document, Next Generation 9-1-1 GIS Recommendations. However since some information is more useful for localities earlier in their project and other information more useful later, we are also posting each section as its own document. The parts include:1) Boundaries in Next Generation 9-1-12) Preparing Your Data and Provisioning into EGDMS3) Outsourced GIS Data Maintenance and NG9-1-14) Emergency Service Boundary Layers5) Attribution6) What's NextSome of the parts are technical that reflect choices and options to make with boundary lines, or specific recommendations on how to create globally unique IDs or format display name fields. In these areas, we hope to share recommendations from Intrado and point users to specific portions of the NENA GIS Data Model Standard for examples. The current version is 1.1, published February 2021.

Status of Standardized (Level 3) Tax Map Maintenance in Massachusetts

Feature layer containing park maintenance area information in the City of Sioux Falls, South Dakota.

The maintenance requirements for the Real Property Geodatabase are focused on ensuring that the geodatabase design and the database itself will appropriately support the District’s data maintenance activities for tax and record lots and associated information. These include accurate representation of current data, structures and rules that aid quality control, and accurate construction and maintenance of historical data.

Database of Montana maintenance section boundaries created to be accurate according to maintenance chiefs. Sections are subdivisions of larger Maintenence Divisions.

The Geographic Management Information System (GeoMIS) is a FISMA Moderate minor application built using ArcGIS Server and portal, Microsoft SQL, and a web-facing front-end. The system can be accessed over the internet via https://www.usaidgiswbg.com using a web browser. GeoMIS is based on a commercial off-the-shelf product developed by Esri. Esri is creates geographic information system (GIS) software, web GIS and geodatabase management applications and is based in California. GeoMISIt is maintained by an Israeli company, Systematics (see Attachment 3) which is EsriI's agent in Israel. The mission has an annual maintenance contract with Systematics for GeoMIS. GeoMIS has 100 users from USAID staff (USA Direct Hire and Foreign Service Nationals) and 200 users from USAID contractors and grantees. The system is installed at USAID WBG office in Tel Aviv/Israel inside the computer room in the DMZ. It has no interconnections with any other system.

Street Light Maintenance Responsibility

The GIS component of Virginia's NG9-1-1 deployments is moving in waves, with new groups of localities starting the onboarding process every three months. Well into our third wave, new resources and recommendations on GIS related topics are now available on the VGIN 9-1-1 & GIS page. This is available as a large combined document, Next Generation 9-1-1 GIS Recommendations. However since some information is more useful for localities earlier in their project and other information more useful later, we are also posting each section as its own document. The parts include:1) Boundaries in Next Generation 9-1-12) Preparing Your Data and Provisioning into EGDMS3) Outsourced GIS Data Maintenance and NG9-1-14) Emergency Service Boundary Layers5) Attribution6) What's NextSome of the parts are technical that reflect choices and options to make with boundary lines, or specific recommendations on how to create globally unique IDs or format display name fields. In these areas, we hope to share recommendations from Intrado and point users to specific portions of the NENA GIS Data Model Standard for examples. The current version is 1.1, published February 2021.

In California, there are a variety of political entities that are granted self-taxation powers under various California codes in order to perform the basic goal of flood management within an area. This dataset compiles many of the various datasets together to provide the information in one location. It also includes districts that are no longer active political/management entities for archival or historical purposes. The primary type of flood agency in California are known as reclamation districts, and so represent the majority of the records in this database. The quality of the boundary accuracy is highly variable, due to a variety of reasons, including the fact that the original legal boundaries are frequently tied to Swamp Land Survey boundaries that themselves are poorly located by modern mapping standards. This set of boundary delineations represents the latest in a series of nearly 20 significant revisions primarily by DWR Delta Levees Program between 2000-2017 to a dataset first produced by Office of Emergency Services during the 1997 floods. The accuracy and completeness of the data are therefore higher in the Delta than elsewhere. The Division of Flood Management then stored the boundaries in their levee geodatabase that feeds the web mapping application known as FERIX. To produce this final dataset, in 2018 the Division of Engineering Geodetic Branch merged the data used by FERIX, along with other datasets used by the Delta Levees Program, and normalized the attribute table.

Formerly published as TRANS_NOC_GTLF_PUB_UNK_LINE This standard houses linear features on BLM lands as well as transportation features that provide access to BLM transportation routes. In order to meet the local or state field office needs, each state may extend its GTLF data standard to collect data to fulfill local data requirements as long as the state or field office data can be cross-walked into the National GTLF data standard format. This dataset is an ongoing process, updated periodically when better data is available. The National BLM GTLF data provides standardized transportation information for use in BLM programs and analysis. At the core, this standard stores transportation information gathered, inventoried, analyzed and recorded in a BLM Transportation Management Plan or TMP. The TMP analyzes transportation options and incorporates public participation to assist in determining travel routes, modes of travel, and season of use on selected and surrounding BLM managed lands. The Idaho BLM maintains only GTLF routes that have been recorded in a TMP. This route data is identified by COORD_SRC2 = ‘TMP – Plan Name’ and PLAN_ROUTE_DSGNTN_AUTH = ‘BLM’. All other data is considered Non-BLM authoritative, administered and maintained transportation data and is provided only as spatial and tabular reference material. As new or existing transportation data is analyzed and recorded through the TMP process, the resulting data will be incorporated into the Idaho BLM GTLF authoritative data maintenance program. The Idaho BLM GTLF data contains transportation data from many different sources across the state including the TMP process, and as such may contain a variety of spatial and tabular inaccuracies and may include errors of omission or commission. The purpose for collecting and maintaining an Idaho state-wide compilation is to provide a broad overview of the transportation network for properly focused analysis or inventory purposes and to provide connectivity between BLM managed routes and the broader transportation network. As with all spatial data, this Idaho BLM GTLF data only represents an approximate or generalized spatial and tabular description of the actual transportation route. All BLM disclaimers apply to this data and that the use of this data is at the risk of the user. Additional Notes. The purpose of this dataset is to create an Idaho BLM feature class with existing routes. Due to the lack of finalized Travel Management Plans (TMP) throughout the state the best available data was used. Where TMP data was not available we used a larger collection of 1:24,000-scale "Resource Base Data" GIS road features gathered by Idaho BLM and a variety of other data collected from the state. May 4 2018: fields added for use by ID BLM for cartographic purposes. Jan 2020 update to GTLF Schema v3.0. This data set was created and is maintained by the Bureau of Land Management staff in Idaho for only those roads identified by the metadata. All other roads are included only as background source material and are not maintained in GIS or on the ground by BLM. For more information contact us at blm_id_stateoffice@blm.gov.

SPU DWW Mainline Points is a Group Layer containing all Lifecycles, Ownerships, and other variations of Drainage and Wastewater Mainlines Points.Proposed Mainline End Points are planned but not yet installed or as-built.SPU DWW Aba Rem Mainline End Points refers to Abandoned and Removed Mainline End Points.Force Mainline End Points are Mainline End Points under pressure. Detention Lines and Polygons refer to Mainline End Points for Detention Infrastructure.DWW Mainline Connection Points Wyes refer to side sewer and lateral connection points on mainlines.The data is refreshed weekly and is maintained by the SPU GIS Data Maintenance Team.

Streets aggregated by street full name and winter maintenance agency.

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GIS In Telecom Sector Market Size 2024-2028

The GIS in telecom sector market size is forecast to increase by USD 1.91 billion at a CAGR of 14.68% between 2023 and 2028.

Geographic Information Systems (GIS) have gained significant traction In the telecom sector due to the increasing adoption of advanced technologies such as big data, sensors, drones, and LiDAR. The use of GIS enables telecom companies to effectively manage and analyze large volumes of digital data, including satellite and GPS information, to optimize infrastructure monitoring and antenna placement. In the context of smart cities, GIS plays a crucial role in enabling efficient communication between developers and end-users by providing real-time data on construction progress and infrastructure status. Moreover, the integration of LiDAR technology with drones offers enhanced capabilities for surveying and mapping telecom infrastructure, leading to improved accuracy and efficiency.
However, the implementation of GIS In the telecom sector also presents challenges, including data security concerns and the need for servers and computers to handle the large volumes of data generated by these technologies. In summary, the telecom sector's growing reliance on digital technologies such as GIS, big data, sensors, drones, and LiDAR is driving market growth, while the need for effective data management and security solutions presents challenges that must be addressed.

What will be the Size of the GIS In Telecom Sector Market During the Forecast Period?

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The Geographic Information System (GIS) market In the telecom sector is experiencing significant growth due to the increasing demand for electronic information and visual representation of data in various industries. This market encompasses a range of hardware and software solutions, including GNSS/GPS antennas, Lidar, GIS collectors, total stations, imaging sensors, and more. Major industries such as agriculture, oil & gas, architecture, and infrastructure monitoring are leveraging GIS technology for data analysis and decision-making. The adoption rate of GIS In the telecom sector is driven by the need for efficient data management and analysis, as well as the integration of real-time data from various sources.
Data formats and sources vary widely, from satellite and aerial imagery to ground-based sensors and IoT devices. The market is also witnessing innovation from startups and established players, leading to advancements in data processing capabilities and integration with other technologies like 5G networks and AI. Applications of GIS In the telecom sector include smart urban planning, smart utilities, and smart public works, among others.

How is this GIS In Telecom Sector Industry segmented and which is the largest segment?

The GIS in telecom sector industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Product

  Software
  Data
  Services


Deployment

  On-premises
  Cloud


Geography

  APAC

    China


  North America

    Canada
    US


  Europe

    UK
    Italy


  South America



  Middle East and Africa

By Product Insights

The software segment is estimated to witness significant growth during the forecast period. The telecom sector's Global GIS market encompasses software solutions for desktops, mobiles, cloud, and servers, along with developers' platforms. companies provide industry-specific GIS software, expanding the growth potential of this segment. Telecom companies heavily utilize intelligent maps generated by GIS for informed decisions on capacity planning and enhancements, such as improved service and next-generation networks. This drives significant growth In the software segment. Commercial entities offer open-source GIS software to counteract the threat of counterfeit products.
GIS technologies are integral to telecom network management, spatial data analysis, infrastructure planning, location-based services, network coverage mapping, data visualization, asset management, real-time network monitoring, design, wireless network mapping, integration, maintenance, optimization, and geospatial intelligence. Key applications include 5G network planning, network visualization, outage management, geolocation, mobile network optimization, and smart infrastructure planning. The GIS industry caters to major industries, including agriculture, oil & gas, architecture, engineering, construction, mining, utilities, retail, healthcare, government, and smart city planning. GIS solutions facilitate real-time data management, spatial information, and non-spatial information, offering enterprise solutions and transportation applications.

Get a glance at the market report of share of variou

DescriptionThis dataset is an attempt to best represent the boundaries of maintenance responsibilities of each Engineering Region. It is a combination of our Engineering Region boundaries and Maintenance Section boundaries.

    Last Update
    2023


    Update FrequencyAs needed


    Data Owner
    Division of Transportation Development


    Data Contact
    GIS Support Unit


    Collection Method



    Projection
    NAD83 / UTM zone 13N


    Coverage Area
    Statewide


    Temporal



    Disclaimer/Limitations
    There are no restrictions and legal prerequisites for using the data set. The State of Colorado assumes no liability relating to the completeness, correctness, or fitness for use of this data.

For more information please visit the Maps and Records website.This data represents legal agreements that the Department of Public Works has made with property owners related to the maintenance of certain streets and/or alleys. Maintenance Agreements are created when the property owner has identified a certain street and/or alley as being critical to how the property operates. Examples include using an alley for access to parking for a business, loading zones for commercial establishments, private improvements to streets and/or alleys that are not standard to City construction methods, and all other approved encroachments.

This layer displays all the connected and to be connected non-mainline points within the City of Seattle (and the former service area north of the City limits) regardless of ownership. The data source is DWW.non_mainline_pt_pv with the following data query, NMNLPT_LIFECYCLE_CODE IN( 'C' , 'UNK' , 'T' ,'TBC', 'U', 'PC') AND NMNLPT_FEATYPE_CODE <> 'WQS'. The layer is symbolized on the attribute FEATYPE. The labels are based on the attribute FEATYPE. This layer does not display when zoomed out beyond 1:899. Maintained by SPU GIS DWW Data Maintenance staff. Refreshed weekly.

The global arborist software market was valued at USD 350.79 Million in 2022 and is projected to reach USD 881.04 Million by 2030, registering a CAGR of 12.2% for the forecast period 2023-2030. Factors Affecting Arborist Software Market Growth

Growing awareness of tree care coupled with benefits of arborist software

With increased awareness of environmental conservation and the importance of urban green spaces, there's a rising demand for professional tree care services. Growing environmental education coupled with technology adoption in tree management helps to drive the arborist software demand. Arborist software helps urban planners, municipalities, and property owners effectively manage and care for trees in cities and suburbs. Arborist software streamlines various tasks like tree inventory management, maintenance scheduling, and communication with clients. This leads to improved efficiency and productivity for arborists.

The Restraining Factor of Arborist Software:

Data Security, privacy concerns;

Data security and privacy concerns are indeed significant factors that can impact the adoption of arborist software. Arborist software often stores information about clients' properties, contact details, and potentially even financial information. Many arborist software solutions use location data to map and manage trees. This location data could be misused if it falls into the wrong hands.

Market Opportunity:

Rising need to improve tree inventory practices;

The rising need to improve tree inventory practices is driven by several factors, including urbanization, environmental awareness, and advancements in technology. As cities grow and expand, urban planners need accurate tree inventory data to ensure that trees are integrated into urban design. Tree inventory helps prevent conflicts between infrastructure development and tree preservation. Arborists software helps to create and maintain digital inventories of trees, including information about species, location, size, health, and maintenance history. In addition, features like Geographic Information Systems (GIS), remote sensing, and mobile data collection technologies have made it easier to create, update, and manage tree inventories.

The COVID-19 impact on Arborist Software Market

The COVID-19 pandemic had various impacts on industries and markets, including the arborist software market. During lockdowns and restrictions, some tree care activities might have been deprioritized due to the sudden focus on healthcare sector. However, the pandemic accelerated digital transformation across industries. Arborists who were previously reliant on manual processes might have recognized the benefits of adopting software for tasks like inventory management, reporting, and client communication. Introduction of Arborist Software

An arborist is a professional who specializes in the cultivation, management, and study of trees, shrubs, and other woody plants. Arborists are trained in tree care practices, including planting, pruning, disease and pest management, and overall tree health maintenance. Arborist software are tools used to assist arborists in their work. These software solutions can provide various functionalities to help arborists manage and maintain trees effectively. Arborists can use software to create and maintain digital inventories of trees, including information about species, location, size, health, and maintenance history. Some common features of arborist software include tree inventory management, health assessment, risk assessment, mapping and GIS integration etc.

Polygon geometry with attributes displaying the Department of Maintenance Drainage Division maintenance lots in East Baton Rouge Parish, Louisiana.Metadata

Displays the data from DWW.ditch_culvert_ln_pv with the following query, DCH_LIFECYCLE_CODE IN ( 'C' , 'UNK' , 'T', 'TBC', 'U', 'PC' ) And DCH_FEATYPE_CODE IN ( 'CDC' , 'CRB' , 'SDR' , 'UNK' ). The layer is symbolized on the attribute SYMBOL. Labels are based on the attribute DCH_OWNER_NAME. This layer will not display when zoomed out beyond 1:7,000. Maintained by SPU GIS DWW Data Maintenance staff.Refreshed weekly.

Annual Community Survey data summary for Right of Way (ROW) Landscape Maintenance survey results. The Community Survey question relating to this performance measure focuses on satisfaction with the quality of landscape maintenance along streets and sidewalks. Respondents are asked to rate their satisfaction level with the quality of landscape using a scale of 1 to 5, where 1 means "Very Dissatisfied" and 5 means "Very Satisfied".This page provides details about the ROW Landscape Maintenance performance measure. Community Survey questions may be adjusted over time, so the specific questions asked each year are included in the data.The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.The performance measure dashboard is available at 3.23 Right of Way Landscape Maintenance.Additional InformationSource: Community Attitude SurveyContact: Wydale HolmesContact E-Mail: Wydale_Holmes@tempe.govData Source Type: ExcelPreparation Method: Data received from vendorPublish Frequency: AnnualPublish Method: ManualData Dictionary