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Analytics (AI) Change detection Feature extraction Road assets inventory Utility assets inventory Map data production Geodatabase generation Map data Processing /Classifications
Contour Map Generation Analytics (AI) Change Detection Feature Extraction Imagery Data Processing Ortho mosaic Ortho rectification Digital Ortho Mapping Ortho photo Generation Analytics (Geo AI) Change Detection Map Production Web application development Software testing Data migration Platform development

AI-Assisted Data Mapping Pipeline AI models trained on millions of images are used to predict traffic signs, road markings , lanes for better and faster data processing

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Experience & Expertise -More than Two decade in Map making business with 800+ GIS expertise -Building world class products with our expertise service division & skilled project management -International Brand “Mappls” in California USA, focused on “Advance -Geospatial Services & Autonomous drive Solutions”

Value Added Services -Production environment with continuous improvement culture -Key metrics driven production processes to align customer’s goals and deliverables -Transparency & visibility to all stakeholder -Technology adaptation by culture

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The data provides a summary of the state of development practice for Geographic Information Systems (GIS) software (as of August 2017). The summary is based on grading a set of 30 GIS products using a template of 56 questions based on 13 software qualities. The products range in scope and purpose from a complete desktop GIS systems, to stand-alone tools, to programming libraries/packages.

The template used to grade the software is found in the TabularSummaries.zip file. Each quality is measured with a series of questions. For unambiguity the responses are quantified wherever possible (e.g.~yes/no answers). The goal is for measures that are visible, measurable and feasible in a short time with limited domain knowledge. Unlike a comprehensive software review, this template does not grade on functionality and features. Therefore, it is possible that a relatively featureless product can outscore a feature-rich product.

A virtual machine is used to provide an optimal testing environments for each software product. During the process of grading the 30 software products, it is much easier to create a new virtual machine to test the software on, rather than using the host operating system and file system.

The raw data obtained by measuring each software product is in SoftwareGrading-GIS.xlsx. Each line in this file corresponds to between 2 and 4 hours of measurement time by a software engineer. The results are summarized for each quality in the TabularSummaries.zip file, as a tex file and compiled pdf file.

Geographic Information System (GIS) Market Outlook

The Geographic Information System (GIS) market is witnessing robust growth with its global market size projected to reach USD 25.7 billion by 2032, up from USD 8.7 billion in 2023, at a compound annual growth rate (CAGR) of 12.4% during the forecast period. This growth is primarily driven by the increasing integration of GIS technology across various industries to improve spatial data visualization, enhance decision-making, and optimize operations. The benefits offered by GIS in terms of accuracy, efficiency, and cost-effectiveness are convincing more sectors to adopt these systems, thereby expanding the market size significantly.

A major growth factor contributing to the GIS market expansion is the escalating demand for location-based services. As businesses across different sectors recognize the importance of spatial data analytics in driving strategic decisions, the reliance on GIS applications is becoming increasingly pronounced. The rise in IoT devices, coupled with the enhanced capabilities of AI and machine learning, has further fueled the demand for GIS solutions. These technologies enable the processing and analysis of large volumes of spatial data, thereby providing valuable insights that businesses can leverage for competitive advantage. In addition, government initiatives promoting the adoption of digital infrastructure and smart city projects are playing a crucial role in the growth of the GIS market.

The advancement in satellite imaging and remote sensing technologies is another key driver of the GIS market growth. With enhanced satellite capabilities, the precision and quality of geospatial data have significantly improved, making GIS applications more reliable and effective. The availability of high-resolution satellite imagery has opened new avenues in various sectors including agriculture, urban planning, and disaster management. Moreover, the decreasing costs of satellite data acquisition and the proliferation of drone technology are making GIS more accessible to small and medium enterprises, further expanding the market potential.

The advent of 3D Geospatial Technologies is revolutionizing the way industries utilize GIS data. By providing a three-dimensional perspective, these technologies enhance spatial analysis and visualization, offering more detailed and accurate representations of geographical areas. This advancement is particularly beneficial in urban planning, where 3D models can simulate cityscapes and infrastructure, allowing planners to visualize potential developments and assess their impact on the environment. Moreover, 3D geospatial data is proving invaluable in sectors such as construction and real estate, where it aids in site analysis and project planning. As these technologies continue to evolve, they are expected to play a pivotal role in the future of GIS, expanding its applications and driving further market growth.

Furthermore, the increasing application of GIS in environmental monitoring and management is bolstering market growth. With growing concerns over climate change and environmental degradation, GIS is being extensively used for resource management, biodiversity conservation, and natural disaster risk management. This trend is expected to continue as more organizations and governments prioritize sustainability, thereby driving the demand for advanced GIS solutions. The integration of GIS with other technologies such as big data analytics, and cloud computing is also expected to enhance its capabilities, making it an indispensable tool for environmental management.

Regionally, North America is currently leading the GIS market, driven by the widespread adoption of advanced technologies and the presence of major GIS vendors. The regionÂ’s focus on infrastructure development and smart city projects is further propelling the market growth. Europe is also witnessing significant growth owing to the increasing adoption of GIS in various industries such as agriculture and transportation. The Asia Pacific region is anticipated to exhibit the highest CAGR during the forecast period, attributed to rapid urbanization, government initiatives for digital transformation, and increasing investments in infrastructure development. In contrast, the markets in Latin America and the Middle East & Africa are growing steadily as these regions continue to explore and adopt GIS technologies.

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This is the final export from the Forest Inventory Module (FIM) system, retired on 6/29/2022.

This layer is a digital inventory of individual forest stands. The data is collected by MNDNR Foresters in each MNDNR Forestry Administrative Area, and is updated on a continuous basis, as needed. Most stands are field checked and their characteristics described. Follows internal MNDNR classification schema. This data originates from the MNDNR's "Forest Inventory Management" system (also referred to as FIM).

This resource was replaced by MNDNR Forest Inventory: https://gisdata.mn.gov/dataset/biota-dnr-forest-inventory

The research project from which this dataset was produced was designed to help bridge the divide in understanding of the possible environmental causes of breast cancer in the United Kingdom. This divide exists between the official cancer research and treatment world, and other unofficial groups of diverse expertise. The geographic information system methodology used (Geographic Information Systems for Participation, or GIS-P) was intended to increase the understanding of the various positions in the debate both for the researchers, but also more importantly, between the communities of interest. The intention was to stimulate debate through the shared understanding that could be achieved by debating the knowledge and viewpoints expressed through the maps. In this respect, debate stimulation was more important than to capture detailed participatory derived spatial data (as has been the case with previous GIS-P projects). In practice, the process proved problematic, which explains the relatively limited quantity of GIS-P data collected.

City of Scottsdale Short-term rental approved licenses. This data is updated daily. Please view the Data Dictionary for a detailed explanation of the data available on this map and the connected table.

This National Geographic Style Map (World Edition) web map provides a reference map for the world that includes administrative boundaries, cities, protected areas, highways, roads, railways, water features, buildings, and landmarks, overlaid on shaded relief and a colorized physical ecosystems base for added context to conservation and biodiversity topics. Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri, National Geographic or any governing authority.This basemap, included in the ArcGIS Living Atlas of the World, uses the National Geographic Style vector tile layer and the National Geographic Style Base and World Hillshade raster tile layers.The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layers referenced in this map.

The Africa Geospatial Analytics market, currently valued at $0.26 billion in 2025, is projected to experience robust growth, driven by increasing government investments in infrastructure development, rising adoption of precision agriculture techniques, and the expanding need for effective resource management across various sectors. The market's Compound Annual Growth Rate (CAGR) of 6.99% from 2025 to 2033 indicates a significant expansion over the forecast period. Key drivers include the escalating demand for accurate location-based services across industries like utilities, defense, and mining, alongside advancements in data analytics technologies, particularly in remote sensing and GIS software. The market segmentation reveals strong demand across diverse end-user verticals, with agriculture, utilities and communications, and defense and intelligence sectors likely to be significant contributors to market growth. The availability of affordable data and cloud-based solutions will further fuel market expansion. However, challenges such as limited internet penetration in certain regions and a scarcity of skilled professionals may act as restraints. Growth will be particularly strong in countries with substantial infrastructure projects and a need for efficient resource management, such as Nigeria, South Africa, and Egypt. The increasing adoption of smart city initiatives and the need for precise mapping for urban planning will further contribute to market expansion. Key players like Atkins, Autodesk, and ESRI are strategically positioning themselves to capture this market growth through partnerships, technological advancements, and tailored solutions for the African context. The market is expected to witness significant innovation in areas like 3D modeling, AI-powered analytics, and big data processing, which will further enhance the capabilities and applications of geospatial analytics in Africa. The projected increase in investment in technological infrastructure across the continent will be a key factor in accelerating market adoption and overall growth. Recent developments include: September 2024: Bayanat, a company in AI-driven geospatial solutions, has teamed up with Vay, renowned for its automotive-grade teledriving (remote driving) technology. Together, they've inked a Memorandum of Understanding (MoU) to enhance teledriving solutions by integrating geospatial data and AI. This collaboration empowers Bayanat, in tandem with Vay, to introduce and broaden the reach of teledriving technology across the Middle East, Africa, and select nations in the Asia Pacific.May 2024: AfriGIS stands out as one of the pioneering geospatial solutions firms, providing verified and validated geospatial data on administrative boundaries tied to postal codes across Africa. AfriGIS has crafted a polygon dataset for 21,600 localities (towns) and 475,000 sub-localities (suburbs) in the last three years. This dataset can be enriched via API with overlays like points of interest, administrative boundaries, cadastral data, deeds, census data, street centrelines, etc.. Key drivers for this market are: Commercialization of spatial data, Increased smart city & infrastructure projects. Potential restraints include: Commercialization of spatial data, Increased smart city & infrastructure projects. Notable trends are: Commercialization of Spatial Data.

Operational level forest inventory data was acquired in 2019 and provided the basis for mapping, quantifying and assessing area-wide forest and commercial timber resources and for establishing the AAC for SSE. Forest inventory data from 2019 and the analysis in 2020 provides the following forest management benefits: Updated Timber Type data layer (map) contained in the State’s GIS for SSE Data acquired and analyzed through the forest inventory project was entered into the State’s GIS to create an updated timber type layer (map) of the commercial forest timber base in SSE containing individual timber stands. Updated timber type descriptors for each individual stand include stand species composition, stand density and per acre timber volume. SSE Forest Inventory Report July 17, 2020 4 Using the GIS to analyze the relationships between the commercial timber resource and other forest resources (transportation network, fish and wildlife habitat, cultural resources, etc.) allows the DOF to undertake and complete complex forest planning documents such as the Five-Year Schedules of Timber Sales (FYSTS), and Forest Land Use Plans (FLUPs) used to guide both broad scale and site-specific forest management activities. The GIS also allows DOF to track changes to the commercial timber base resulting from management activities including timber harvest, stand regeneration/reforestation, and timber stand improvement projects such as precommercial tree thinning. Updated Annual Allowable Cut for SSE The GIS timber type map for SSE, updated with the 2019 forest inventory data, formed the basis for area (acreage) and timber volume (board feet) figures necessary to calculate an updated AAC. The new GIS timber type map and associated data files along with newly available LiDAR data provided the raw data necessary to perform the growth and yield modelling to estimate timber volume and characteristics in the developing young growth stands over the course of the rotation.

The State of Alaska and the Forest Service entered into a Challenge Cost-share agreement in June 2015, to complete a timber stand inventory in young-growth forest. This work supports collecting, analyzing, and using forest resource information to implement sound, sustainable forest management practices across Southeast Alaska, while offering training and developing job opportunites for rural residents in natural resource fields. This layer depicts the polygons that are planned to be field-sampled for the timber cruise.

This document provides an overview on the provisioning of GIS data to support NG9-1-1 services. This document is intended to provide guidance to local GIS and PSAP authorities on the following: The required GIS datasets to support the i3 Emergency Call Routing Function (ECRF) and Location Validation Function (LVF) The validation processes to synchronize the GIS datasets to the Master Street Address Guide (MSAG) and Automatic Location Information (ALI) datasets Geospatial call routing readiness The short term and long term NG9-1-1 GIS data maintenance workflow proceduresAdditional resources and recommendations on GIS related topics are available on the VGIN 9-1-1 & GIS page.

CDFW BIOS GIS Dataset, Contact: Chris Stermer, Description: The database represents 702 point locations and associated stand assessment data collected in aspen stands in the in the Eagle Lake Ranger District, Lassen National Forest. Data were gathered during the summers of 2001-2005. Observations were conducted by trained Forest Service crews. Assessments were conducted in aspen stands in the region, or stands identified during field surveys. This dataset is considered to be a complete inventory of aspen in these watersheds.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The TOP 2015 imagery was mosaiced and manipulated using image processing and segmentation techniques (e.g. unsupervised image classification, normalized difference vegetation index, etc.) to highlight any subtle vegetation signature differences. All of the preliminary results were evaluated for usefulness and the best examples were first converted to digital lines and polygons, were next combined with other relevant AMIS GIS layers (such as the roads network), and the results were used as the base layer for the new AMIS vegetation mapping effort. Building off the base layer, all relevant lines and polygons were exported as shapefiles and converted to ArcGIS coverages. The resulting coverages were run through a series of smoothing routines provided in the ArcGIS software. Following the smoothing, all digital line-work was manipulated to remove extraneous lines, eliminate small polygons, and merged polygons that split obvious stands of homogeneous vegetation. The cleaning stage was considered complete when all resulting polygons matched homogenous stands of vegetation apparent on the TOP 2015 imagery. At this point, the mapping shifted to manual techniques and all vegetation lines and polygons were visually inspected and manually moved, edited and/or updated as needed.

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

City of Scottsdale makes no guarantee of the accuracy of data provided to us by Rentalscape regarding potential unlicensed short-term rentals. This data is updated daily. Please view the Data Dictionary for a detailed explanation of the data available on this map and the connected table.

The global GIS Receiver market is experiencing robust growth, driven by increasing adoption in diverse sectors like surveying, construction, and precision agriculture. The market, valued at approximately $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several key factors. Firstly, the rising demand for precise geospatial data is creating significant opportunities for GIS receiver manufacturers. Secondly, technological advancements, such as the integration of improved GNSS technologies and higher accuracy sensors, are enhancing the capabilities and appeal of GIS receivers. Furthermore, the increasing penetration of affordable and user-friendly GIS software solutions is broadening the market's addressable audience. The market segmentation reveals a healthy demand across various receiver types (all-in-one and stand-alone) and applications (survey and mapping being dominant). Competition is intense, with established players like Hexagon, Trimble, and Topcon facing challenges from emerging regional competitors. The market's future growth trajectory is significantly influenced by factors like government investments in infrastructure projects, the expansion of smart cities initiatives, and the growing adoption of precision agriculture techniques. While the market presents significant opportunities, certain restraints need to be considered. The high initial investment cost associated with procuring advanced GIS receivers can act as a barrier for entry, particularly for small and medium-sized enterprises (SMEs). Furthermore, the market's growth is susceptible to fluctuations in economic conditions and government spending patterns. Another challenge arises from the complexities involved in data processing and interpretation, requiring specialized skills and expertise. However, the ongoing development of more user-friendly software and training programs are expected to alleviate this concern. The geographical distribution of the market shows a relatively even spread, with North America and Europe maintaining a strong presence, followed by a rapidly expanding Asia-Pacific region. This report provides a detailed analysis of the global GIS receiver market, a sector projected to exceed $5 billion in revenue by 2028. We delve into market concentration, key trends, dominant regions, product insights, and future growth catalysts. This in-depth study is invaluable for businesses involved in surveying, mapping, construction, and other sectors leveraging GNSS technology.

City of Scottsdale Short-term rental licenses currently pending. This data is updated daily. Please view the Data Dictionary for a detailed explanation of the data available on this map and the connected table.

The GIS in telecom sector market stands at 2,164.8 million in 2024 and it is expected to reach 4,516.6 million by 2030, registering a CAGR of 13.2% during 2025-2030.

The research focus in the field of remotely sensed imagery has shifted from collection and warehousing of data ' tasks for which a mature technology already exists, to auto-extraction of information and knowledge discovery from this valuable resource ' tasks for which technology is still under active development. In particular, intelligent algorithms for analysis of very large rasters, either high resolutions images or medium resolution global datasets, that are becoming more and more prevalent, are lacking. We propose to develop the Geospatial Pattern Analysis Toolbox (GeoPAT) a computationally efficient, scalable, and robust suite of algorithms that supports GIS processes such as segmentation, unsupervised/supervised classification of segments, query and retrieval, and change detection in giga-pixel and larger rasters. At the core of the technology that underpins GeoPAT is the novel concept of pattern-based image analysis. Unlike pixel-based or object-based (OBIA) image analysis, GeoPAT partitions an image into overlapping square scenes containing 1,000'100,000 pixels and performs further processing on those scenes using pattern signature and pattern similarity ' concepts first developed in the field of Content-Based Image Retrieval. This fusion of methods from two different areas of research results in orders of magnitude performance boost in application to very large images without sacrificing quality of the output.

GeoPAT v.1.0 already exists as the GRASS GIS add-on that has been developed and tested on medium resolution continental-scale datasets including the National Land Cover Dataset and the National Elevation Dataset. Proposed project will develop GeoPAT v.2.0 ' much improved and extended version of the present software. We estimate an overall entry TRL for GeoPAT v.1.0 to be 3-4 and the planned exit TRL for GeoPAT v.2.0 to be 5-6. Moreover, several new important functionalities will be added. Proposed improvements includes conversion of GeoPAT from being the GRASS add-on to stand-alone software capable of being integrated with other systems, full implementation of web-based interface, writing new modules to extent it applicability to high resolution images/rasters and medium resolution climate data, extension to spatio-temporal domain, enabling hierarchical search and segmentation, development of improved pattern signature and their similarity measures, parallelization of the code, implementation of divide and conquer strategy to speed up selected modules.

The proposed technology will contribute to a wide range of Earth Science investigations and missions through enabling extraction of information from diverse types of very large datasets. Analyzing the entire dataset without the need of sub-dividing it due to software limitations offers important advantage of uniformity and consistency. We propose to demonstrate the utilization of GeoPAT technology on two specific applications. The first application is a web-based, real time, visual search engine for local physiography utilizing query-by-example on the entire, global-extent SRTM 90 m resolution dataset. User selects region where process of interest is known to occur and the search engine identifies other areas around the world with similar physiographic character and thus potential for similar process. The second application is monitoring urban areas in their entirety at the high resolution including mapping of impervious surface and identifying settlements for improved disaggregation of census data.