CDFW BIOS GIS Dataset, Contact: BLM Bureau of Land Management, Description: To identify renewable energy approved and pending lease areas on BLM administered lands. To provide information about solar and wind energy applications and completed projects within the State of California for analysis and display internally and externally.

CDFW BIOS GIS Dataset, Contact: CEC California Energy Commission (CEC), Description: Locations of proposed Solar thermal energy projects for the Renewable Energy Transmission Initiative (RETI), from the California Energy Commission.

Data compiled from California Energy Commission staff from georeferenced electric territory maps and the United States Department of Homeland Security, Homeland Infrastructure Foundation-Level Data (HIFILD), https://hifld-geoplatform.opendata.arcgis.com/datasets/geoplatform::electric-retail-service-territories-2/aboutCommunity Choice Aggregation information provided by Cal-CCA.Boundaries are approximate, for absolute territory information, contact the appropriate load serving entity. Not all electric load serving entities are represented, if you have information on missing territory locations, please contact GIS@energy.ca.gov.For more information on California Load Serving Entities visit this website: https://www.energy.ca.gov/data-reports/energy-almanac/california-electricity-data/electric-load-serving-entities-lses

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.

Energy and utilities data from the Alaska Energy Authority, Alaska Energy Data Gateway. Includes: - Hydroelectric - Hydrokinetic - Wind Power - Thermal Areas - Hot Springs - Sawmills - Energy Regions - Electric Utility Lines - TAPS Pipeline - Volanoes and Vents - Solar PowerSource: Alaska Energy AuthorityThis data is provided as a service in the DCRA Information Portal by the Alaska Department of Commerce, Community, and Economic Development Division of Community and Regional Affairs (SOA DCCED DCRA), Research and Analysis section. SOA DCCED DCRA Research and Analysis is not the authoritative source for this data. For more information and for questions about this data, see: Alaska Energy Data Gateway

The BEPS Program was created by Title III of the Clean Energy DC Omnibus Act of 2018. The BEPS is a minimum threshold of energy performance that will be no lower than the local median ENERGY STAR score by property type (or equivalent metric). The standards were created to drive energy performance in existing buildings to help meet the energy and climate goals of the Sustainable DC plan — to reduce greenhouse gas emissions and energy consumption by 50% by 2032. DOEE established the first set of Standards on January 1, 2021. Standards will then be set every 6 years, creating BEPS Periods (BEPS Period 1, BEPS Period 2, etc.). The 2021 Building Energy Performance Standards and a Guide to the 2021 BEPS are available for viewing on DOEE’s website.To improve transparency and help building owners understand how their building performs relative to the BEPS, DOEE is publishing this BEPS Disclosure that compares a building’s benchmarking data with the BEPS and provides an estimate of the building’s distance from the standard and estimated performance requirement.Please note that this dataset is based on information currently available to DOEE using calendar year 2019 benchmarking data provided by the building owner. Some buildings are still being evaluated and therefore have been designated as “Under Review” in this dataset. Building owners that believe their 2019 calendar year data is incorrect should contact the Benchmarking Help Center (info.benchmark@dc.gov). Additionally, buildings that meet certain criteria may request a variance from the standards by submitting a variance request form on the DOEE website.

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GIS In Utility Industry Market Size 2025-2029

The gis in utility industry market size is forecast to increase by USD 3.55 billion, at a CAGR of 19.8% between 2024 and 2029.

The utility industry's growing adoption of Geographic Information Systems (GIS) is driven by the increasing need for efficient and effective infrastructure management. GIS solutions enable utility companies to visualize, analyze, and manage their assets and networks more effectively, leading to improved operational efficiency and customer service. A notable trend in this market is the expanding application of GIS for water management, as utilities seek to optimize water distribution and reduce non-revenue water losses. However, the utility GIS market faces challenges from open-source GIS software, which can offer cost-effective alternatives to proprietary solutions. These open-source options may limit the functionality and support available to users, necessitating careful consideration when choosing a GIS solution. To capitalize on market opportunities and navigate these challenges, utility companies must assess their specific needs and evaluate the trade-offs between cost, functionality, and support when selecting a GIS provider. Effective strategic planning and operational execution will be crucial for success in this dynamic market.

What will be the Size of the GIS In Utility Industry Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe Global Utilities Industry Market for Geographic Information Systems (GIS) continues to evolve, driven by the increasing demand for advanced data management and analysis solutions. GIS services play a crucial role in utility infrastructure management, enabling asset management, data integration, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage management, and spatial analysis. These applications are not static but rather continuously unfolding, with new patterns emerging in areas such as energy efficiency, smart grid technologies, renewable energy integration, network optimization, and transmission lines. Spatial statistics, data privacy, geospatial databases, and remote sensing are integral components of this evolving landscape, ensuring the effective management of utility infrastructure. Moreover, the adoption of mobile GIS, infrastructure planning, customer service, asset lifecycle management, metering systems, regulatory compliance, GIS data management, route planning, environmental impact assessment, mapping software, GIS consulting, GIS training, smart metering, workforce management, location intelligence, aerial imagery, construction management, data visualization, operations and maintenance, GIS implementation, and IoT sensors is transforming the industry. The integration of these technologies and services facilitates efficient utility infrastructure management, enhancing network performance, improving customer service, and ensuring regulatory compliance. The ongoing evolution of the utilities industry market for GIS reflects the dynamic nature of the sector, with continuous innovation and adaptation to meet the changing needs of utility providers and consumers.

How is this GIS In Utility Industry Industry segmented?

The gis in utility industry industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. ProductSoftwareDataServicesDeploymentOn-premisesCloudGeographyNorth AmericaUSCanadaEuropeFranceGermanyRussiaMiddle East and AfricaUAEAPACChinaIndiaJapanSouth AmericaBrazilRest of World (ROW).

By Product Insights

The software segment is estimated to witness significant growth during the forecast period.In the utility industry, Geographic Information Systems (GIS) play a pivotal role in optimizing operations and managing infrastructure. Utilities, including electricity, gas, water, and telecommunications providers, utilize GIS software for asset management, infrastructure planning, network performance monitoring, and informed decision-making. The GIS software segment in the utility industry encompasses various solutions, starting with fundamental GIS software that manages and analyzes geographical data. Additionally, utility companies leverage specialized software for field data collection, energy efficiency, smart grid technologies, distribution grid design, renewable energy integration, network optimization, transmission lines, spatial statistics, data privacy, geospatial databases, GIS services, project management, demand forecasting, data modeling, data analytics, grid modernization, data security, field data capture, outage ma

CDFW BIOS GIS Dataset, Contact: CEC California Energy Commission (CEC), Description: Environmentally sensitive areas and areas with land uses/ownership that restrict/prevent renewable energy project and transmission infrastructure development. From Black & Veatch consultants via the California Energy Commission for the RETI process.

From Databasin: https://drecp.databasin.org/datasets/c61b0e256e494fc5b6958d6c3999a19a/Development Focus Areas (DFAs). Designation on BLM-administered lands within which solar, wind, and geothermal renewable energy development and associated activities are allowable uses and that have been determined to be of low or lower resource conflict. The intent is to incentivize and streamline such development in these areas.Variance Process Lands (VPLs). Designation on BLM-administered lands that are available for solar, wind, and geothermal renewable energy development. Renewable energy projects on VPLs have minimal streamlining and must comply with a specific set of CMAs. Renewable energy applications in VPLs will follow the variance process described in the Western Solar Plan ROD.

To address the global challenge of reducing greenhouse gas emissions contributing to climate change, it is essential to explore innovative, renewable, and sustainable energy solutions. Bioenergy, derived from biological sources, plays a vital role by providing renewable options for heat, electricity, and vehicle fuel. Biofuels from food crops like sugarcane and cassava demonstrate the potential of agricultural products for energy generation, while jatropha is cultivated primarily for oil. This learning activity focuses on land suitability mapping for these selected crops in Florida, incorporating criteria such as temperature, rainfall, soil type, soil pH, and topography. The analysis evaluates the land requirements of food and energy crops within the Food-Energy-Water (FEW) nexus framework, addressing potential land-use conflicts. Geographic Information Systems (GIS) are employed to identify optimal regions for energy crop cultivation, promoting sustainable practices that balance food security, water conservation, and renewable energy production. The modules are developed and designed for undergraduate students, particularly those enrolled in any of courses such as environmental science, GIS, natural resource management, agricultural science and remote sensing. Students will apply GIS and remote sensing techniques to analyze interactions among food, energy, and water resources, focusing on resilient crops. The activity incorporates the 4DEE framework – Core Ecological Concepts, Ecological Practices, Human-Environment Interactions, and Cross-Cutting Themes to enhance understanding of the FEW nexus. Through hands-on projects addressing real-world ecological challenges, students will develop critical skills in geospatial data analysis, data interpretation, and ethical considerations, preparing them for sustainable resource management. Likewise on part of the instructors, the activity is designed for those with intermediate to advanced GIS expertise, particularly in ArcGIS Pro and Google Earth Engine for spatial analysis and a basic understanding and application of the Food-Energy-Water (FEW) Nexus to guide students in making informed land-use decisions that support sustainable development goals.

Annex 1 - plants powered by RES in the Lazio Region; Annex 2 - Electricity consumptions, RES electricity production and percentages of electricity consumption from local RES for each Lazio Municipality; Annex 3 - Additional PV power and PV surface for each Lazio Municipality

The base exclusions consist of two main categories of exclusion – the protected area layer and the techno-economic exclusion layer. The base exclusions form the fundamental exclusion set that the additional criteria of the Core and SB 100 Terrestrial Climate Resilience Study screens are added to. The merged footprints of these primary two layers are modified by the Bureau of Land Management Land Use Plan Amendment (LUPA) development focus areas (DFAs) and variance process lands, and the general public lands in the DRECP. These areas allow for renewable energy applications and are therefore exempt (erased) from the base exclusions layer, even if the protected area layer or techno-economic exclusion layer identified the area as an exclusion. The DFAs are partitioned by technology type so that only the DFAs that allow solar energy are applied in this modification. The area of California remaining after removing the base exclusions is called the resource potential basemap. It forms the starting point (or base) used in renewable resource estimation and defines where environmental and land-use datasets can be applied in exploring implications. More information about this layer and its use in electric system planning is available in the Land Use Screens Staff Report in the CEC Energy Planning Library. Change Log: Version 1.1 (January 22, 2024 10:49 AM) Layer revised with latest protected area layer, which allows for gaps to remain when combining all components.

The global market for solar resource assessment software is experiencing robust growth, driven by the increasing demand for renewable energy and the need for efficient solar power plant development. The market size in 2025 is estimated at $250 million, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth is fueled by several key factors: the expanding solar energy sector globally, stringent government regulations promoting renewable energy adoption, advances in software capabilities offering more accurate and detailed assessments, and the decreasing costs of solar technology making it more accessible. The segment for paid, commercial applications currently dominates the market share, reflecting the preference of large-scale solar developers for sophisticated, feature-rich software solutions that ensure optimal project planning and profitability. However, the free and personal application segments are also showing promising growth, catering to smaller-scale projects, educational institutions, and individual users exploring solar energy options. Geographic expansion into developing economies with high solar irradiance presents significant opportunities for market expansion. The continued growth trajectory is expected to be influenced by factors such as technological advancements leading to improved prediction accuracy and integration with other renewable energy modeling tools. Increased investment in research and development within the sector, coupled with the expanding adoption of cloud-based software solutions, will contribute to market expansion. However, challenges such as the need for accurate and reliable meteorological data, the complexity of software usage for non-experts, and the potential for market saturation in certain regions might impede growth to some degree. Nevertheless, the long-term outlook for the solar resource assessment software market remains positive, with a substantial increase in market value projected throughout the forecast period, driven by the relentless push towards global decarbonization and the escalating adoption of sustainable energy solutions.

IMPORTANT NOTICE This item has moved to a new organization and entered Mature Support on February 3rd, 2025. This item is scheduled to be Retired and removed from ArcGIS Online on July 30th, 2025. We encourage you to switch to using the item on the new organization as soon as possible to avoid any disruptions within your workflows. If you have any questions, please feel free to leave a comment below or email our Living Atlas Curator (livingatlascurator@esri.ca) The new version of this item can be found here Stations containing prime movers, electric generators, and auxiliary equipment for converting mechanical, chemical into electric energy with an installed capacity of 1 Megawatt or more generated from renewable energy, including biomass, hydroelectric, pumped-storage hydroelectric, geothermal, solar, wind, and tidal.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.Maintenance and Update Frequency: As Needed For more information visit Renewable Energy Power Plants

ArcGIS can help harness the business intelligence and instrumentation data streaming from field sensors to accelerate decision making to better support your business. We will discuss the value of BI integration and IoT data, how to consume it efficiently and present in a form for intelligent and swift decision making c/o of interactive dashboards..

This dataset contains information about the biomass resources generated by county in the United States. It includes the following feedstock categories: crop residues, forest residues, primary mill residues, secondary mill residues, and urban wood waste. The estimates are based on county-level statistics and/or point-source data gathered from the U.S. Department of Agriculture (USDA), USDA Forest Service, EPA and other organizations, which are further processed using relevant assumptions and conversions.

The GIS database has been developed under the project "Renewable Energy Mapping: Small Hydro Tanzania". This study is part of a technical assistance project, ESMAP funded, being implemented by Africa Energy Practice of the World Bank in Tanzania which aims at supporting resource mapping and geospatial planning for small hydro. Please refer to the country project page for additional outputs and reports: http://esmap.org/re_mapping_TNZ The GIS database contains the following datasets: Administrative Boundaries Hydrology Protected Areas Satellite Imagery Land Cover Geology Topography Population Infrastructure: Power/ Transport each accompanied by a metadata file Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Tanzania Small Hydro GIS Atlas, 2018, https://energydata.info/dataset/tanzania-small-hydro-gis-database-2018"

Data compiled from California Energy Commission staff from georeferenced electric territory maps and the United States Department of Homeland Security, Homeland Infrastructure Foundation-Level Data (HIFILD), https://hifld-geoplatform.opendata.arcgis.com/datasets/geoplatform::electric-retail-service-territories-2/aboutBoundaries are approximate, for absolute territory information, contact the appropriate load serving entity.For more information on California Load Serving Entities visit this website: https://www.energy.ca.gov/data-reports/energy-almanac/california-electricity-data/electric-load-serving-entities-lses

Annual average wind resource potential for the United States (low resolution)

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.

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 Wind Power Density at 50-m Above Ground Level in the form of a GIS shapefile. The data were output in Geographic Information Systems (GIS) format and incorporated into a Geospatial Toolkit (GsT) which is provided in data resources. 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.