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This GIS dataset contains point data on pleasant and unpleasant places along everyday active mobility routes that urban residents mapped in five European cities: Helsinki Metropolitan Area (= 1114 respondents), Greater London (=1188), Greater Copenhagen (= 1225), Munich (= 855) and Las Palmas de Gran Canarias (= 582). The data was collected through an online Public Participation GIS survey, titled “Greentravel: A survey on your everyday active travel environment”. It was distributed in December 2023 to January 2024 using a random sampling approach through a panel company in all cities, except in Greater Copenhagen, where respondents were sampled directly through the Danish Registry Data.
The survey was implemented by researchers at the Digital Geography Lab, University of Helsinki, in collaboration with researchers at the University of Copenhagen. The data is GDPR compliant.
The data is provided in shapefile (.shp) format. It comprises of separate shapefiles for pleasant and unpleasant places points for each study city as follows:
Helsinki Metropolitan Area
Greater London
Greater Copenhagen
Munich
Las Palmas de Gran Canarias
Definitions
Active mobility was defined for respondents in the survey as “non-motorised forms of travel such as walking or cycling that you use on a regular daily basis to get to a destination (e.g. go to work, school, shop, but excluding trips for leisure)”. Pleasant and unpleasant categories which survey respondents could identify are defined in the GREENTRAVEL_PPGIS_survey_description document.
The PPGIS survey through which this data was collected is part of the GREENTRAVEL project, funded by the European Union (Grant Number: 101044906). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or European Research Council. Neither the European Union nor European Research Council can be held responsible for them.
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The Geographic Information System (GIS) Analytics market is experiencing robust growth, projected to reach $15.10 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 12.41% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing adoption of cloud-based GIS solutions enhances accessibility and scalability for diverse industries. The growing need for data-driven decision-making across sectors like retail, real estate, government, and telecommunications is a significant catalyst. Furthermore, advancements in artificial intelligence (AI) and machine learning (ML) integrated with GIS analytics are revolutionizing spatial data analysis, enabling more sophisticated predictive modeling and insightful interpretations. The market's segmentation reflects this broad adoption, with retail and real estate, government and utilities, and telecommunications representing key end-user segments, each leveraging GIS analytics for distinct applications such as location optimization, infrastructure management, and network planning. Competitive pressures are shaping the market landscape, with established players like Esri, Trimble, and Autodesk innovating alongside emerging tech companies focusing on AI and specialized solutions. The North American market currently holds a significant share, driven by early adoption and technological advancements. However, Asia-Pacific is expected to witness substantial growth due to rapid urbanization and increasing investment in infrastructure projects. Market restraints primarily involve the high cost of implementation and maintenance of advanced GIS analytics solutions and the need for skilled professionals to effectively utilize these technologies. However, the overall outlook remains extremely positive, driven by continuous technological innovation and escalating demand across multiple sectors. The future trajectory of the GIS analytics market hinges on several factors. Continued investment in research and development, especially in AI and ML integration, will be crucial for unlocking new possibilities. Furthermore, the simplification of GIS analytics software and the development of user-friendly interfaces will broaden accessibility beyond specialized technical experts. Growing data volumes from various sources (IoT, remote sensing) present both opportunities and challenges; efficient data management and analytics techniques will be paramount. The market's success also depends on addressing cybersecurity concerns related to sensitive geospatial data. Strong partnerships between technology providers and end-users will be vital in optimizing solution implementation and maximizing return on investment. Government initiatives promoting the use of GIS technology for smart city development and infrastructure planning will also play a significant role in market expansion. Overall, the GIS analytics market is poised for sustained growth, driven by technological advancements, increasing data availability, and heightened demand for location-based intelligence across a wide range of industries.
GIS Market Size 2025-2029
The GIS market size is forecast to increase by USD 24.07 billion, at a CAGR of 20.3% between 2024 and 2029.
The Global Geographic Information System (GIS) market is experiencing significant growth, driven by the increasing integration of Building Information Modeling (BIM) and GIS technologies. This convergence enables more effective spatial analysis and decision-making in various industries, particularly in soil and water management. However, the market faces challenges, including the lack of comprehensive planning and preparation leading to implementation failures of GIS solutions. Companies must address these challenges by investing in thorough project planning and collaboration between GIS and BIM teams to ensure successful implementation and maximize the potential benefits of these advanced technologies.
By focusing on strategic planning and effective implementation, organizations can capitalize on the opportunities presented by the growing adoption of GIS and BIM technologies, ultimately driving operational efficiency and innovation.
What will be the Size of the GIS 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.
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The global Geographic Information Systems (GIS) market continues to evolve, driven by the increasing demand for advanced spatial data analysis and management solutions. GIS technology is finding applications across various sectors, including natural resource management, urban planning, and infrastructure management. The integration of Bing Maps, terrain analysis, vector data, Lidar data, and Geographic Information Systems enables precise spatial data analysis and modeling. Hydrological modeling, spatial statistics, spatial indexing, and route optimization are essential components of GIS, providing valuable insights for sectors such as public safety, transportation planning, and precision agriculture. Location-based services and data visualization further enhance the utility of GIS, enabling real-time mapping and spatial analysis.
The ongoing development of OGC standards, spatial data infrastructure, and mapping APIs continues to expand the capabilities of GIS, making it an indispensable tool for managing and analyzing geospatial data. The continuous unfolding of market activities and evolving patterns in the market reflect the dynamic nature of this technology and its applications.
How is this GIS Industry segmented?
The GIS 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.
Product
Software
Data
Services
Type
Telematics and navigation
Mapping
Surveying
Location-based services
Device
Desktop
Mobile
Geography
North America
US
Canada
Europe
France
Germany
UK
Middle East and Africa
UAE
APAC
China
Japan
South Korea
South America
Brazil
Rest of World (ROW)
By Product Insights
The software segment is estimated to witness significant growth during the forecast period.
The Global Geographic Information System (GIS) market encompasses a range of applications and technologies, including raster data, urban planning, geospatial data, geocoding APIs, GIS services, routing APIs, aerial photography, satellite imagery, GIS software, geospatial analytics, public safety, field data collection, transportation planning, precision agriculture, OGC standards, location intelligence, remote sensing, asset management, network analysis, spatial analysis, infrastructure management, spatial data standards, disaster management, environmental monitoring, spatial modeling, coordinate systems, spatial overlay, real-time mapping, mapping APIs, spatial join, mapping applications, smart cities, spatial data infrastructure, map projections, spatial databases, natural resource management, Bing Maps, terrain analysis, vector data, Lidar data, and geographic information systems.
The software segment includes desktop, mobile, cloud, and server solutions. Open-source GIS software, with its industry-specific offerings, poses a challenge to the market, while the adoption of cloud-based GIS software represents an emerging trend. However, the lack of standardization and interoperability issues hinder the widespread adoption of cloud-based solutions. Applications in sectors like public safety, transportation planning, and precision agriculture are driving market growth. Additionally, advancements in technologies like remote sensing, spatial modeling, and real-time mapping are expanding the market's scope.
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The Software segment was valued at USD 5.06 billion in 2019
Geographic Information System Analytics Market Size 2024-2028
The geographic information system analytics market size is forecast to increase by USD 12 billion at a CAGR of 12.41% between 2023 and 2028.
The GIS Analytics Market analysis is experiencing significant growth, driven by the increasing need for efficient land management and emerging methods in data collection and generation. The defense industry's reliance on geospatial technology for situational awareness and real-time location monitoring is a major factor fueling market expansion. Additionally, the oil and gas industry's adoption of GIS for resource exploration and management is a key trend. Building Information Modeling (BIM) and smart city initiatives are also contributing to market growth, as they require multiple layered maps for effective planning and implementation. The Internet of Things (IoT) and Software as a Service (SaaS) are transforming GIS analytics by enabling real-time data processing and analysis.
Augmented reality is another emerging trend, as it enhances the user experience and provides valuable insights through visual overlays. Overall, heavy investments are required for setting up GIS stations and accessing data sources, making this a promising market for technology innovators and investors alike.
What will be the Size of the GIS Analytics Market during the forecast period?
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The geographic information system analytics market encompasses various industries, including government sectors, agriculture, and infrastructure development. Smart city projects, building information modeling, and infrastructure development are key areas driving market growth. Spatial data plays a crucial role in sectors such as transportation, mining, and oil and gas. Cloud technology is transforming GIS analytics by enabling real-time data access and analysis. Startups are disrupting traditional GIS markets with innovative location-based services and smart city planning solutions. Infrastructure development in sectors like construction and green buildings relies on modern GIS solutions for efficient planning and management. Smart utilities and telematics navigation are also leveraging GIS analytics for improved operational efficiency.
GIS technology is essential for zoning and land use management, enabling data-driven decision-making. Smart public works and urban planning projects utilize mapping and geospatial technology for effective implementation. Surveying is another sector that benefits from advanced GIS solutions. Overall, the GIS analytics market is evolving, with a focus on providing actionable insights to businesses and organizations.
How is this Geographic Information System Analytics Industry segmented?
The geographic information system analytics 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.
End-user
Retail and Real Estate
Government
Utilities
Telecom
Manufacturing and Automotive
Agriculture
Construction
Mining
Transportation
Healthcare
Defense and Intelligence
Energy
Education and Research
BFSI
Components
Software
Services
Deployment Modes
On-Premises
Cloud-Based
Applications
Urban and Regional Planning
Disaster Management
Environmental Monitoring Asset Management
Surveying and Mapping
Location-Based Services
Geospatial Business Intelligence
Natural Resource Management
Geography
North America
US
Canada
Europe
France
Germany
UK
APAC
China
India
South Korea
Middle East and Africa
UAE
South America
Brazil
Rest of World
By End-user Insights
The retail and real estate segment is estimated to witness significant growth during the forecast period.
The GIS analytics market analysis is witnessing significant growth due to the increasing demand for advanced technologies in various industries. In the retail sector, for instance, retailers are utilizing GIS analytics to gain a competitive edge by analyzing customer demographics and buying patterns through real-time location monitoring and multiple layered maps. The retail industry's success relies heavily on these insights for effective marketing strategies. Moreover, the defense industries are integrating GIS analytics into their operations for infrastructure development, permitting, and public safety. Building Information Modeling (BIM) and 4D GIS software are increasingly being adopted for construction project workflows, while urban planning and designing require geospatial data for smart city planning and site selection.
The oil and gas industry is leveraging satellite imaging and IoT devices for land acquisition and mining operations. In the public sector,
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This data was prepared as input for the Selkie GIS-TE tool. This GIS tool aids site selection, logistics optimization and financial analysis of wave or tidal farms in the Irish and Welsh maritime areas. Read more here: https://www.selkie-project.eu/selkie-tools-gis-technoeconomic-model/
This research was funded by the Science Foundation Ireland (SFI) through MaREI, the SFI Research Centre for Energy, Climate and the Marine and by the Sustainable Energy Authority of Ireland (SEAI). Support was also received from the European Union's European Regional Development Fund through the Ireland Wales Cooperation Programme as part of the Selkie project.
File Formats
Results are presented in three file formats:
tif Can be imported into a GIS software (such as ARC GIS) csv Human-readable text format, which can also be opened in Excel png Image files that can be viewed in standard desktop software and give a spatial view of results
Input Data
All calculations use open-source data from the Copernicus store and the open-source software Python. The Python xarray library is used to read the data.
Hourly Data from 2000 to 2019
Wind -
Copernicus ERA5 dataset
17 by 27.5 km grid
10m wind speed
Wave - Copernicus Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis dataset 3 by 5 km grid
Accessibility
The maximum limits for Hs and wind speed are applied when mapping the accessibility of a site.
The Accessibility layer shows the percentage of time the Hs (Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis) and wind speed (ERA5) are below these limits for the month.
Input data is 20 years of hourly wave and wind data from 2000 to 2019, partitioned by month. At each timestep, the accessibility of the site was determined by checking if
the Hs and wind speed were below their respective limits. The percentage accessibility is the number of hours within limits divided by the total number of hours for the month.
Environmental data is from the Copernicus data store (https://cds.climate.copernicus.eu/). Wave hourly data is from the 'Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis' dataset.
Wind hourly data is from the ERA 5 dataset.
Availability
A device's availability to produce electricity depends on the device's reliability and the time to repair any failures. The repair time depends on weather
windows and other logistical factors (for example, the availability of repair vessels and personnel.). A 2013 study by O'Connor et al. determined the
relationship between the accessibility and availability of a wave energy device. The resulting graph (see Fig. 1 of their paper) shows the correlation between
accessibility at Hs of 2m and wind speed of 15.0m/s and availability. This graph is used to calculate the availability layer from the accessibility layer.
The input value, accessibility, measures how accessible a site is for installation or operation and maintenance activities. It is the percentage time the
environmental conditions, i.e. the Hs (Atlantic -Iberian Biscay Irish - Ocean Wave Reanalysis) and wind speed (ERA5), are below operational limits.
Input data is 20 years of hourly wave and wind data from 2000 to 2019, partitioned by month. At each timestep, the accessibility of the site was determined
by checking if the Hs and wind speed were below their respective limits. The percentage accessibility is the number of hours within limits divided by the total
number of hours for the month. Once the accessibility was known, the percentage availability was calculated using the O'Connor et al. graph of the relationship
between the two. A mature technology reliability was assumed.
Weather Window
The weather window availability is the percentage of possible x-duration windows where weather conditions (Hs, wind speed) are below maximum limits for the
given duration for the month.
The resolution of the wave dataset (0.05° × 0.05°) is higher than that of the wind dataset
(0.25° x 0.25°), so the nearest wind value is used for each wave data point. The weather window layer is at the resolution of the wave layer.
The first step in calculating the weather window for a particular set of inputs (Hs, wind speed and duration) is to calculate the accessibility at each timestep.
The accessibility is based on a simple boolean evaluation: are the wave and wind conditions within the required limits at the given timestep?
Once the time series of accessibility is calculated, the next step is to look for periods of sustained favourable environmental conditions, i.e. the weather
windows. Here all possible operating periods with a duration matching the required weather-window value are assessed to see if the weather conditions remain
suitable for the entire period. The percentage availability of the weather window is calculated based on the percentage of x-duration windows with suitable
weather conditions for their entire duration.The weather window availability can be considered as the probability of having the required weather window available
at any given point in the month.
Extreme Wind and Wave
The Extreme wave layers show the highest significant wave height expected to occur during the given return period. The Extreme wind layers show the highest wind speed expected to occur during the given return period.
To predict extreme values, we use Extreme Value Analysis (EVA). EVA focuses on the extreme part of the data and seeks to determine a model to fit this reduced
portion accurately. EVA consists of three main stages. The first stage is the selection of extreme values from a time series. The next step is to fit a model
that best approximates the selected extremes by determining the shape parameters for a suitable probability distribution. The model then predicts extreme values
for the selected return period. All calculations use the python pyextremes library. Two methods are used - Block Maxima and Peaks over threshold.
The Block Maxima methods selects the annual maxima and fits a GEVD probability distribution.
The peaks_over_threshold method has two variable calculation parameters. The first is the percentile above which values must be to be selected as extreme (0.9 or 0.998). The
second input is the time difference between extreme values for them to be considered independent (3 days). A Generalised Pareto Distribution is fitted to the selected
extremes and used to calculate the extreme value for the selected return period.
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This file contains European countries in a shapefile format that can be used in python, R or matlab. The file has been created by Drin Marmullaku based on GADM version 4.1 (https://gadm.org/) and distributed according to their license (https://gadm.org/license.html).
Please cite as: Sevdari, Kristian; Marmullaku, Drin (2023). Shapefile of European countries. Technical University of Denmark. Dataset. https://doi.org/10.11583/DTU.23686383 This dataset is distributed under a CCBY-NC-SA 4.0 license
Using the data to create maps for publishing of academic research articles is allowed. Thus you can use the maps you made with GADM data for figures in articles published by PLoS, Springer Nature, Elsevier, MDPI, etc. You are allowed (but not required) to publish these articles (and the maps they contain) under an open license such as CC-BY as is the case with PLoS journals and may be the case with other open access articles. Data for the following countries is covered by a a different license Austria: Creative Commons Attribution-ShareAlike 2.0 (source: Government of Austria)
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The global Geographic Information System (GIS) tools market size was valued at approximately USD 10.8 billion in 2023, and it is projected to reach USD 21.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2032. The increasing demand for spatial data analytics and the rising adoption of GIS tools across various industries are significant growth factors propelling the market forward.
One of the primary growth factors for the GIS tools market is the surging demand for spatial data analytics. Spatial data plays a critical role in numerous sectors, including urban planning, environmental monitoring, disaster management, and natural resource exploration. The ability to visualize and analyze spatial data provides organizations with valuable insights, enabling them to make informed decisions. Advances in technology, such as the integration of artificial intelligence (AI) and machine learning (ML) with GIS, are enhancing the capabilities of these tools, further driving market growth.
Moreover, the increasing adoption of GIS tools in the construction and agriculture sectors is fueling market expansion. In construction, GIS tools are used for site selection, route planning, and resource management, enhancing operational efficiency and reducing costs. Similarly, in agriculture, GIS tools aid in precision farming, crop monitoring, and soil analysis, leading to improved crop yields and sustainable farming practices. The ability of GIS tools to provide real-time data and analytics is particularly beneficial in these industries, contributing to their widespread adoption.
The growing importance of location-based services (LBS) in various applications is another key driver for the GIS tools market. LBS are extensively used in navigation, logistics, and transportation, providing real-time location information and route optimization. The proliferation of smartphones and the development of advanced GPS technologies have significantly increased the demand for LBS, thereby boosting the GIS tools market. Additionally, the integration of GIS with other technologies, such as the Internet of Things (IoT) and Big Data, is creating new opportunities for market growth.
Regionally, North America holds a significant share of the GIS tools market, driven by the high adoption of advanced technologies and the presence of major market players. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, owing to increasing investments in infrastructure development, smart city projects, and the growing use of GIS tools in emerging economies such as China and India. Europe, Latin America, and the Middle East & Africa are also expected to contribute to market growth, driven by various government initiatives and increasing awareness of the benefits of GIS tools.
The GIS tools market can be segmented by component into software, hardware, and services. The software segment is anticipated to dominate the market due to the increasing demand for advanced GIS software solutions that offer enhanced data visualization, spatial analysis, and decision-making capabilities. GIS software encompasses a wide range of applications, including mapping, spatial data analysis, and geospatial data management, making it indispensable for various industries. The continuous development of user-friendly and feature-rich software solutions is expected to drive the growth of this segment.
Hardware components in the GIS tools market include devices such as GPS units, remote sensing devices, and plotting and digitizing tools. The hardware segment is also expected to witness substantial growth, driven by the increasing use of advanced hardware devices that provide accurate and real-time spatial data. The advancements in GPS technology and the development of sophisticated remote sensing devices are key factors contributing to the growth of the hardware segment. Additionally, the integration of hardware with IoT and AI technologies is enhancing the capabilities of GIS tools, further propelling market expansion.
The services segment includes consulting, integration, maintenance, and support services related to GIS tools. This segment is expected to grow significantly, driven by the increasing demand for specialized services that help organizations effectively implement and manage GIS solutions. Consulting services assist organizations in selecting the right GIS tools and optimizing their use, while integration services ensure seamless integr
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Access to those reports within the Historic England Research Reports series that relate to geographically defined sites such as a building where a building assessment or dendrochronology has been carried out, or a field covered by a geophysical survey. It important to note that there a lot of reports in the database that do not have a spatial location e.g. those that are thematic. These are still available via the Research Reports database.
Spatial data relating to reports within the Historic England Research Reports series. This is point data for the grid reference given in the report, or where this was not available from other sources. The majority of reports relate to discrete features such as a building where a building assessment or dendrochronology has been carried out, or a field covered by a geophysical survey. However, there are also a small number of thematic reports that have contained detailed gazetteers allowing multiple links to the same report e.g. Police Stations, Jewish Cemeteries and Shropshire Inns. The most extreme example of this is the Gas Industry report where over 1500 points are used. There are also a number of large area projects covering extensive regions. Because this is a point layer, these are merely covered by a centre point for the feature.
Data updated frequently.
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The Geographic Information System (GIS) Services market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, we can infer substantial expansion based on the identified market drivers and trends. The burgeoning adoption of GIS technology in environmental management, infrastructure development, and precision agriculture is fueling market expansion. The integration of GIS with advanced analytics, such as AI and machine learning, is further enhancing its capabilities and broadening its applications. This leads to increased efficiency, improved decision-making, and cost optimization across various industries. The market's segmentation, encompassing diverse application areas like environmental agencies, utility companies, and telecommunications, highlights its widespread utility. Furthermore, the geographical distribution across North America, Europe, Asia Pacific, and other regions underscores a global market with significant growth potential in both developed and emerging economies. Given the rapid technological advancements and increasing data availability, the GIS services market is projected to maintain a strong growth trajectory in the coming years, surpassing previous estimates for market size. We estimate the market size in 2025 to be approximately $15 Billion, with a conservative CAGR of 8% projected through 2033. This growth will be fueled by continued technological advancements and increasing reliance on data-driven decision making in various sectors. The competitive landscape is marked by a mix of established players and emerging technology providers. Companies like Intellias, EnviroScience, and Infosys BPM are leading the charge, leveraging their expertise in GIS technology and data analytics. The presence of numerous regional players also reflects the market's geographically diverse growth. The market's future growth will likely hinge on factors such as the development of more sophisticated GIS software and analytics tools, the increased adoption of cloud-based GIS solutions, and the continuous integration of GIS with other technologies like IoT and blockchain. Addressing potential restraints, such as high initial investment costs for some organizations, will be crucial for sustained market growth.
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This is the authors’ version of the work. It is based on a poster presented at the Wageningen Conference on Applied Soil Science, http://www.wageningensoilmeeting.wur.nl/UK/ Cite as: Bosco, C., de Rigo, D., Dewitte, O., Montanarella, L., 2011. Towards the reproducibility in soil erosion modeling: a new Pan-European soil erosion map. Wageningen Conference on Applied Soil Science “Soil Science in a Changing World”, 18 - 22 September 2011, Wageningen, The Netherlands. Author’s version DOI:10.6084/m9.figshare.936872 arXiv:1402.3847
Towards the reproducibility in soil erosion modeling:a new Pan-European soil erosion map
Claudio Bosco ¹, Daniele de Rigo ¹ ² , Olivier Dewitte ¹, Luca Montanarella ¹ ¹ European Commission, Joint Research Centre, Institute for Environment and Sustainability,Via E. Fermi 2749, I-21027 Ispra (VA), Italy² Politecnico di Milano, Dipartimento di Elettronica e Informazione,Via Ponzio 34/5, I-20133 Milano, Italy
Soil erosion by water is a widespread phenomenon throughout Europe and has the potentiality, with his on-site and off-site effects, to affect water quality, food security and floods. Despite the implementation of numerous and different models for estimating soil erosion by water in Europe, there is still a lack of harmonization of assessment methodologies. Often, different approaches result in soil erosion rates significantly different. Even when the same model is applied to the same region the results may differ. This can be due to the way the model is implemented (i.e. with the selection of different algorithms when available) and/or to the use of datasets having different resolution or accuracy. Scientific computation is emerging as one of the central topic of the scientific method, for overcoming these problems there is thus the necessity to develop reproducible computational method where codes and data are available. The present study illustrates this approach. Using only public available datasets, we applied the Revised Universal Soil loss Equation (RUSLE) to locate the most sensitive areas to soil erosion by water in Europe. A significant effort was made for selecting the better simplified equations to be used when a strict application of the RUSLE model is not possible. In particular for the computation of the Rainfall Erosivity factor (R) the reproducible research paradigm was applied. The calculation of the R factor was implemented using public datasets and the GNU R language. An easily reproducible validation procedure based on measured precipitation time series was applied using MATLAB language. Designing the computational modelling architecture with the aim to ease as much as possible the future reuse of the model in analysing climate change scenarios is also a challenging goal of the research.
References [1] Rusco, E., Montanarella, L., Bosco, C., 2008. Soil erosion: a main threats to the soils in Europe. In: Tóth, G., Montanarella, L., Rusco, E. (Eds.), Threats to Soil Quality in Europe. No. EUR 23438 EN in EUR - Scientific and Technical Research series. Office for Official Publications of the European Communities, pp. 37-45 [2] Casagrandi, R. and Guariso, G., 2009. Impact of ICT in Environmental Sciences: A citation analysis 1990-2007. Environmental Modelling & Software 24 (7), 865-871. DOI:10.1016/j.envsoft.2008.11.013 [3] Stallman, R. M., 2005. Free community science and the free development of science. PLoS Med 2 (2), e47+. DOI:10.1371/journal.pmed.0020047 [4] Waldrop, M. M., 2008. Science 2.0. Scientific American 298 (5), 68-73. DOI:10.1038/scientificamerican0508-68 [5] Heineke, H. J., Eckelmann, W., Thomasson, A. J., Jones, R. J. A., Montanarella, L., and Buckley, B., 1998. Land Information Systems: Developments for planning the sustainable use of land resources. Office for Official Publications of the European Communities, Luxembourg. EUR 17729 EN [6] Farr, T. G., Rosen, P A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., Roth, L., Seal, D., Shaffer, S., Shimada, J., Umland, J., Werner, M., Oskin, M., Burbank, D., Alsdorf, D., 2007. The Shuttle Radar Topography Mission. Review of Geophysics 45, RG2004, DOI:10.1029/2005RG000183 [7] Haylock, M. R., Hofstra, N., Klein Tank, A. M. G., Klok, E. J., Jones, P. D., and New, M., 2008. A European daily high-resolution gridded dataset of surface temperature and precipitation. Journal of Geophysical Research 113, (D20) D20119+ DOI:10.1029/2008jd010201 [8] Renard, K. G., Foster, G. R., Weesies, G. A., McCool, D. K., and Yoder, D. C., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning with the Revised Universal Soil Loss Equation (RUSLE). Agriculture handbook 703. US Dept Agric., Agr. Handbook, 703 [9] Bosco, C., Rusco, E., Montanarella, L., Panagos, P., 2009. Soil erosion in the alpine area: risk assessment and climate change. Studi Trentini di scienze naturali 85, 119-125 [10] Bosco, C., Rusco, E., Montanarella, L., Oliveri, S., 2008. Soil erosion risk assessment in the alpine area according to the IPCC scenarios. In: Tóth, G., Montanarella, L., Rusco, E. (Eds.), Threats to Soil Quality in Europe. No. EUR 23438 EN in EUR - Scientific and Technical Research series. Office for Official Publications of the European Communities, pp. 47-58 [11] de Rigo, D. and Bosco, C., 2011. Architecture of a Pan-European Framework for Integrated Soil Water Erosion Assessment. IFIP Advances in Information and Communication Technology 359 (34), 310-31. DOI:10.1007/978-3-642-22285-6_34 [12] Bosco, C., de Rigo, D., Dewitte, O., and Montanarella, L., 2011. Towards a Reproducible Pan-European Soil Erosion Risk Assessment - RUSLE. Geophys. Res. Abstr. 13, 3351 [13] Bollinne, A., Laurant, A., and Boon, W., 1979. L’érosivité des précipitations a Florennes. Révision de la carte des isohyétes et de la carte d’erosivite de la Belgique. Bulletin de la Société géographique de Liége 15, 77-99 [14] Ferro, V., Porto, P and Yu, B., 1999. A comparative study of rainfall erosivity estimation for southern Italy and southeastern Australia. Hydrolog. Sci. J. 44 (1), 3-24. DOI:10.1080/02626669909492199 [15] de Santos Loureiro, N. S. and de Azevedo Coutinho, M., 2001. A new procedure to estimate the RUSLE EI30 index, based on monthly rainfall data and applied to the Algarve region, Portugal. J. Hydrol. 250, 12-18. DOI:10.1016/S0022-1694(01)00387-0 [16] Rogler, H., and Schwertmann, U., 1981. Erosivität der Niederschläge und Isoerodentkarte von Bayern (Rainfall erosivity and isoerodent map of Bavaria). Zeitschrift fur Kulturtechnik und Flurbereinigung 22, 99-112 [17] Nearing, M. A., 1997. A single, continuous function for slope steepness influence on soil loss. Soil Sci. Soc. Am. J. 61 (3), 917-919. DOI:10.2136/sssaj1997.03615995006100030029x [18] Morgan, R. P C., 2005. Soil Erosion and Conservation, 3rd ed. Blackwell Publ., Oxford, pp. 304 [19] Šúri, M., Cebecauer, T., Hofierka, J., Fulajtár, E., 2002. Erosion Assessment of Slovakia at regional scale using GIS. Ecology 21 (4), 404-422 [20] Cebecauer, T. and Hofierka, J., 2008. The consequences of land-cover changes on soil erosion distribution in Slovakia. Geomorphology 98, 187-198. DOI:10.1016/j.geomorph.2006.12.035 [21] Poesen, J., Torri, D., and Bunte, K., 1994. Effects of rock fragments on soil erosion by water at different spatial scales: a review. Catena 23, 141-166. DOI:10.1016/0341-8162(94)90058-2 [22] Wischmeier, W. H., 1959. A rainfall erosion index for a universal Soil-Loss Equation. Soil Sci. Soc. Amer. Proc. 23, 246-249 [23] Iverson, K. E., 1980. Notation as a tool of thought. Commun. ACM 23 (8), 444-465. DOI:10.1145/358896.358899 [24] Quarteroni, A., Saleri, F., 2006. Scientific Computing with MATLAB and Octave. Texts in Computational Science and Engineering. Milan, Springer-Verlag [25] The MathWorks, 2011. MATLAB. http://www.mathworks.com/help/techdoc/ref/ [26] Eaton, J. W., Bateman, D., and Hauberg, S., 2008. GNU Octave Manual Version 3. A high-level interactive language for numerical computations. Network Theory Limited, ISBN: 0-9546120-6-X [27] de Rigo, D., 2011. Semantic Array Programming with Mastrave - Introduction to Semantic Computational Modeling. The Mastrave project. http://mastrave.org/doc/MTV-1.012-1 [28] de Rigo, D., (exp.) 2012. Semantic array programming for environmental modelling: application of the Mastrave library. In prep. [29] Bosco, C., de Rigo, D., Dewitte, O., Poesen, J., Panagos, P.: Modelling Soil Erosion at European Scale. Towards Harmonization and Reproducibility. In prep. [30] R Development Core Team, 2005. R: A language and environment for statistical computing. R Foundation for Statistical Computing. [31] Stallman, R. M., 2009. Viewpoint: Why “open source” misses the point of free software. Commun. ACM 52 (6), 31–33. DOI:10.1145/1516046.1516058 [32] de Rigo, D. 2011. Multi-dimensional weighted median: the module "wmedian" of the Mastrave modelling library. Mastrave project technical report. http://mastrave.org/doc/mtv_m/wmedian [33] Shakesby, R. A., 2011. Post-wildfire soil erosion in the Mediterranean: Review and future research directions. Earth-Science Reviews 105 (3-4), 71-100. DOI:10.1016/j.earscirev.2011.01.001 [34] Zuazo, V. H., Pleguezuelo, C. R., 2009. Soil-Erosion and runoff prevention by plant covers: A review. In: Lichtfouse, E., Navarrete, M., Debaeke, P Véronique, S., Alberola, C. (Eds.), Sustainable Agriculture. Springer Netherlands, pp. 785-811. DOI:10.1007/978-90-481-2666-8_48
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The Geographic Information System (GIS) industry is experiencing robust growth, projected to maintain a Compound Annual Growth Rate (CAGR) of 10.80% from 2025 to 2033. This expansion is driven by increasing adoption across diverse sectors, including agriculture, utilities, mining, construction, transportation, and oil and gas. The rising need for precise location-based data for efficient operations, optimized resource management, and informed decision-making fuels this market growth. Advancements in hardware, such as high-resolution sensors and drones, coupled with sophisticated software capabilities like advanced spatial analytics and cloud-based GIS solutions, are key contributors. Furthermore, the proliferation of location-based services (LBS) and the growing adoption of telematics and navigation systems are expanding the applications of GIS technology. While data security concerns and the need for skilled professionals present some challenges, the overall market outlook remains positive. The segmentation of the GIS market reveals a strong demand across various components (hardware and software) and functionalities (mapping, surveying, telematics and navigation, and location-based services). North America currently holds a significant market share due to early adoption and technological advancements, but regions like Asia are exhibiting rapid growth fueled by infrastructure development and increasing digitalization. Leading companies like Bentley Systems, Esri, Trimble, and Hexagon AB are at the forefront of innovation, continuously developing and implementing advanced GIS solutions to meet the evolving needs of different industries. The forecast for the next decade points to further market consolidation, with leading players investing heavily in research and development to enhance their product offerings and expand their market reach. The continued integration of GIS with other technologies such as AI and IoT will further drive market expansion and create new opportunities for growth. Comprehensive Coverage GIS Industry Report (2019-2033) This in-depth report provides a comprehensive analysis of the Geographic Information System (GIS) industry, projecting robust growth from $XXX million in 2025 to $YYY million by 2033. The study covers the historical period (2019-2024), base year (2025), and forecast period (2025-2033), offering invaluable insights for businesses, investors, and policymakers. Keywords: GIS market, GIS software, GIS hardware, GIS solutions, geospatial technology, location intelligence, mapping software, surveying equipment, spatial analysis, geospatial analytics. Recent developments include: November 2022 : The new Geodata Portal and broadband maps for the state will be accessible starting on November 18, 2022, according to a statement from the Connecticut Office of Policy and Management (OPM). This announcement was made on GIS Day 2022, which encourages people to learn about geography and the practical uses of GIS that can improve society., November 2022 : The lt. governor of the Indian state, Jammu and Kashmir, launched a GIS-based system in the region. It highlights the significance of GIS technology in addressing new challenges and exploring new opportunities and its real-world applications, accelerating growth in business, government, and society.. Key drivers for this market are: Growing role of GIS in smart cities ecosystem, Integration of location-based mapping systems with business intelligence systems. Potential restraints include: Integration issues with traditional systems, Data quality and accuracy issues. Notable trends are: The Rising Smart Cities Development and Urban Planning to Drive the Market Growth.
How are processes of political development structured across space and time by preexisting institutions? This article develops a spatiotemporal theory of institutional change by analyzing the evolving infrastructural power of the European Union’s legal order using geospatial methods. Specifically, the authors theorize that the pattern and pace of the domestic spread of EU law has been shaped by preexisting state institutions—particularly by the degree to which national judiciaries are hierarchically organized. To assess this claim, the article compares patterns of domestic judicial enforcement of EU law across France (a unitary state with a centralized judiciary), Italy (a weaker unitary state with a centralized judiciary), and Germany (a federal state with a decentralized judiciary). Developing a geospatial approach to the study of legal integration and historical institutionalism more broadly, the authors leverage an original geocoded data set of cases referred to the EU’s European Court of Justice by national courts to visualize how the subnational penetration of Europe’s supranational legal order is conditioned by state institutions.
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Europe GIS in Telecom Sector market USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 13.5% from 2024 to 2031. increasing investments in digital infrastructure and the rising adoption of advanced GIS solutions across telecommunications is expected to aid the sales to USD XX million by 2031
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The Geographic Information System (GIS) Services market is experiencing robust growth, driven by increasing adoption across various sectors. While the provided data lacks specific market size figures, based on industry reports and observed trends in related technology sectors, we can estimate a 2025 market size of approximately $15 billion USD. This reflects the significant investments being made in spatial data infrastructure and the growing demand for location-based analytics. Assuming a Compound Annual Growth Rate (CAGR) of 8%, the market is projected to reach roughly $25 billion by 2033. Key drivers include the rising need for precise mapping and location intelligence in environmental management, urban planning, and resource optimization. Furthermore, advancements in cloud-based GIS platforms, the increasing availability of big data, and the development of sophisticated geospatial analytics tools are fueling market expansion. The market is segmented by service type (Analyze, Visualize, Manage, Others) and application (primarily Environmental Agencies, but also extending to various sectors such as utilities, transportation, and healthcare). North America currently holds a significant market share due to early adoption and advanced technological infrastructure. However, regions like Asia-Pacific are demonstrating rapid growth, driven by increasing urbanization and infrastructure development. While the lack of readily available detailed market figures presents a challenge for complete precision in projection, the overall trend points to a considerable expansion of the GIS services sector over the forecast period. The competitive landscape is characterized by a mix of large multinational corporations like Infosys and Intellias and smaller, specialized firms like EnviroScience and R&K Solutions, reflecting the diverse needs of the market. These companies compete based on their technological capabilities, industry expertise, and geographical reach. The ongoing integration of GIS with other technologies, such as artificial intelligence (AI) and machine learning (ML), will further shape the market landscape, creating opportunities for innovation and differentiation. Challenges include the high initial investment costs associated with implementing GIS solutions and the need for skilled professionals to effectively utilize these technologies. However, the long-term benefits of improved decision-making and operational efficiency are driving wider adoption despite these hurdles. The future growth of the GIS services market hinges on the continued development of innovative technologies and the increasing awareness of the value that location-based insights provide across various industries.
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The Geographic Information System (GIS) software market is experiencing robust growth, driven by increasing demand for location intelligence across diverse sectors. The market, estimated at $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. This expansion is fueled by several key factors. The surge in adoption of cloud-based GIS solutions offers scalability and cost-effectiveness, attracting both individual users and large enterprises. Furthermore, advancements in technologies like AI and machine learning are enhancing the analytical capabilities of GIS software, leading to improved decision-making in areas such as urban planning, resource management, and disaster response. The increasing availability of geospatial data and the growing need for precise location-based services further contribute to market growth. Segmentation reveals a significant portion of the market is driven by enterprise applications, leveraging GIS for complex analysis and operational efficiency. While the on-premise segment remains relevant, the cloud-based segment is experiencing faster growth, reflecting the shift towards flexible and accessible solutions. Competitive rivalry among established players like Esri, Google, and Pitney Bowes, alongside innovative startups, fuels continuous product development and market innovation. Geographic variations in market penetration are notable. North America and Europe currently dominate the market, but the Asia-Pacific region is demonstrating rapid growth, fueled by substantial infrastructure development and increasing government investments in digital mapping initiatives. However, challenges remain. High initial investment costs for sophisticated GIS software can be a barrier for smaller businesses. Additionally, data security and privacy concerns, particularly concerning sensitive geospatial data, need careful management. Future growth will depend on addressing these constraints, promoting wider adoption among smaller enterprises and individuals, and fostering a robust ecosystem for data sharing and collaboration. The market's future is bright, propelled by technological advancements and an ever-increasing reliance on location-based insights across various industries.
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The GIS in Utility Industry market is experiencing robust growth, projected to reach $2.42 billion in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 19.8% from 2025 to 2033. This expansion is fueled by several key drivers. Increasing demand for improved operational efficiency and asset management within utility companies is a primary factor. GIS technologies provide utilities with powerful tools to optimize grid management, streamline maintenance operations, and enhance service delivery. Furthermore, the growing adoption of cloud-based GIS solutions offers enhanced scalability, accessibility, and cost-effectiveness, accelerating market penetration. The integration of advanced technologies such as IoT sensors, AI, and machine learning into GIS platforms further improves data analysis capabilities, enabling predictive maintenance and proactive risk mitigation. While the initial investment in GIS infrastructure can be a restraint for some smaller utility providers, the long-term cost savings and improved operational efficiency are compelling arguments for adoption. Market segmentation reveals a significant demand for software solutions, followed by data and services components. Cloud deployment models are rapidly gaining popularity, surpassing on-premises deployments due to their inherent advantages. Geographically, North America and Europe currently hold significant market share, driven by advanced technological infrastructure and high adoption rates. However, rapidly developing economies in APAC, particularly China and India, are expected to show substantial growth in the coming years, presenting attractive opportunities for market expansion. The competitive landscape is populated by a mix of established players and emerging technology providers, leading to innovation and competitive pricing. The diverse range of GIS solutions available caters to specific utility needs, including electric power, water, gas, and telecom. Software solutions form the core of the market, providing the tools for data visualization, analysis, and management. Data services, including high-resolution imagery and spatial data analytics, are crucial for effective decision-making. The market's future trajectory is positive, propelled by ongoing technological advancements and the urgent need for efficient and resilient utility infrastructure. The increasing focus on sustainability and renewable energy further amplifies the demand for GIS solutions that support grid modernization and the integration of distributed energy resources. The industry's focus will shift towards integrating GIS with other technologies to enhance decision-making processes and operational efficiency, and continued innovation in data analytics and AI will further refine GIS capabilities within the sector.
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The global Geographic Information System (GIS) Tools market is experiencing robust growth, projected to reach $2979.7 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.5% from 2025 to 2033. This expansion is driven by several key factors. Firstly, the increasing adoption of cloud-based GIS solutions offers scalability, cost-effectiveness, and improved accessibility for businesses of all sizes, particularly SMEs seeking efficient resource management. Secondly, the rising demand for precise location-based data analysis across diverse sectors like urban planning, environmental monitoring, and precision agriculture fuels market growth. Furthermore, technological advancements, including the integration of AI and machine learning capabilities within GIS platforms, enhance analytical power and facilitate more sophisticated spatial decision-making. Finally, government initiatives promoting smart cities and digital transformation worldwide further stimulate market expansion. The market is segmented by application (SMEs, Large Enterprises) and type (Cloud-Based, On-Premises), reflecting the diverse needs of various user groups. Large enterprises, with their extensive spatial data requirements and resources, are expected to drive significant market share, while cloud-based solutions are poised for faster growth due to their flexible deployment models. The regional landscape reveals a dynamic distribution of market share. North America, particularly the United States, holds a prominent position, driven by high technological adoption rates and the presence of major GIS solution providers. Europe follows closely, fueled by increasing government investments in infrastructure development and digitalization initiatives. The Asia-Pacific region is expected to experience significant growth, propelled by rapid urbanization and the expanding adoption of GIS technologies in developing economies like China and India. While the on-premises segment currently dominates, the cloud-based segment is anticipated to exhibit higher growth in the forecast period, driven by its inherent advantages in scalability, accessibility, and cost-efficiency. Competitive dynamics are shaped by both established players like IBM TRIRIGA and emerging technology companies, leading to innovation and diversification of GIS tool offerings. The market's future hinges on continuous technological innovation, the growing adoption of location intelligence across sectors, and the expansion of robust infrastructure supporting data accessibility and management.
Formation transfrontalière UniGR: Master in Border Studies (MA) - Source: UniGR
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
RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development.Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis.Further metadata/references can be found here: http://gisweb.ciat.cgiar.org/RTBmaps/DataAvailability_RTBMaps.htmlDISCLAIMER, ACKNOWLEDGMENTS AND PERMISSIONS:This service is provided by Roots, Tubers and Bananas CGIAR Research Program as a public service. Use of this service to retrieve information constitutes your awareness and agreement to the following conditions of use.This online resource displays GIS data and query tools subject to continuous updates and adjustments. The GIS data has been taken from various, mostly public, sources and is supplied in good faith.RTBMaps GIS Data Disclaimer• The data used to show the Base Maps is supplied by ESRI.• The data used to show the photos over the map is supplied by Flickr.• The data used to show the videos over the map is supplied by Youtube.• The population map is supplied to us by CIESIN, Columbia University and CIAT.• The Accessibility map is provided by Global Environment Monitoring Unit - Joint Research Centre of the European Commission. Accessibility maps are made for a specific purpose and they cannot be used as a generic dataset to represent "the accessibility" for a given study area.• Harvested area and yield for banana, cassava, potato, sweet potato and yam for the year 200, is provided by EarthSat (University of Minnesota’s Institute on the Environment-Global Landscapes initiative and McGill University’s Land Use and the Global Environment lab). Dataset from Monfreda C., Ramankutty N., and Foley J.A. 2008.• Agroecology dataset: global edapho-climatic zones for cassava based on mean growing season, temperature, number of dry season months, daily temperature range and seasonality. Dataset from CIAT (Carter et al. 1992)• Demography indicators: Total and Rural Population from Center for International Earth Science Information Network (CIESIN) and CIAT 2004.• The FGGD prevalence of stunting map is a global raster datalayer with a resolution of 5 arc-minutes. The percentage of stunted children under five years old is reported according to the lowest available sub-national administrative units: all pixels within the unit boundaries will have the same value. Data have been compiled by FAO from different sources: Demographic and Health Surveys (DHS), UNICEF MICS, WHO Global Database on Child Growth and Malnutrition, and national surveys. Data provided by FAO – GIS Unit 2007.• Poverty dataset: Global poverty headcount and absolute number of poor. Number of people living on less than $1.25 or $2.00 per day. Dataset from IFPRI and CIATTHE RTBMAPS GROUP MAKES NO WARRANTIES OR GUARANTEES, EITHER EXPRESSED OR IMPLIED AS TO THE COMPLETENESS, ACCURACY, OR CORRECTNESS OF THE DATA PORTRAYED IN THIS PRODUCT NOR ACCEPTS ANY LIABILITY, ARISING FROM ANY INCORRECT, INCOMPLETE OR MISLEADING INFORMATION CONTAINED THEREIN. ALL INFORMATION, DATA AND DATABASES ARE PROVIDED "AS IS" WITH NO WARRANTY, EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO, FITNESS FOR A PARTICULAR PURPOSE. By accessing this website and/or data contained within the databases, you hereby release the RTB group and CGCenters, its employees, agents, contractors, sponsors and suppliers from any and all responsibility and liability associated with its use. In no event shall the RTB Group or its officers or employees be liable for any damages arising in any way out of the use of the website, or use of the information contained in the databases herein including, but not limited to the RTBMaps online Atlas product.APPLICATION DEVELOPMENT:• Desktop and web development - Ernesto Giron E. (GeoSpatial Consultant) e.giron.e@gmail.com• GIS Analyst - Elizabeth Barona. (Independent Consultant) barona.elizabeth@gmail.comCollaborators:Glenn Hyman, Bernardo Creamer, Jesus David Hoyos, Diana Carolina Giraldo Soroush Parsa, Jagath Shanthalal, Herlin Rodolfo Espinosa, Carlos Navarro, Jorge Cardona and Beatriz Vanessa Herrera at CIAT, Tunrayo Alabi and Joseph Rusike from IITA, Guy Hareau, Reinhard Simon, Henry Juarez, Ulrich Kleinwechter, Greg Forbes, Adam Sparks from CIP, and David Brown and Charles Staver from Bioversity International.Please note these services may be unavailable at times due to maintenance work.Please feel free to contact us with any questions or problems you may be having with RTBMaps.
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This GIS dataset contains point data on pleasant and unpleasant places along everyday active mobility routes that urban residents mapped in five European cities: Helsinki Metropolitan Area (= 1114 respondents), Greater London (=1188), Greater Copenhagen (= 1225), Munich (= 855) and Las Palmas de Gran Canarias (= 582). The data was collected through an online Public Participation GIS survey, titled “Greentravel: A survey on your everyday active travel environment”. It was distributed in December 2023 to January 2024 using a random sampling approach through a panel company in all cities, except in Greater Copenhagen, where respondents were sampled directly through the Danish Registry Data.
The survey was implemented by researchers at the Digital Geography Lab, University of Helsinki, in collaboration with researchers at the University of Copenhagen. The data is GDPR compliant.
The data is provided in shapefile (.shp) format. It comprises of separate shapefiles for pleasant and unpleasant places points for each study city as follows:
Helsinki Metropolitan Area
Greater London
Greater Copenhagen
Munich
Las Palmas de Gran Canarias
Definitions
Active mobility was defined for respondents in the survey as “non-motorised forms of travel such as walking or cycling that you use on a regular daily basis to get to a destination (e.g. go to work, school, shop, but excluding trips for leisure)”. Pleasant and unpleasant categories which survey respondents could identify are defined in the GREENTRAVEL_PPGIS_survey_description document.
The PPGIS survey through which this data was collected is part of the GREENTRAVEL project, funded by the European Union (Grant Number: 101044906). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or European Research Council. Neither the European Union nor European Research Council can be held responsible for them.