The global network mapping software market size was valued at USD 2,325.4 million in 2025 and is projected to grow at a CAGR of 12.3% during the forecast period (2025-2033). The rapid growth of cloud-based, on-premises, and hybrid IT environments, coupled with the increasing adoption of network management best practices, are some of the key factors driving market growth. Furthermore, the need to enhance network visibility and control, improve performance, and simplify network troubleshooting is also contributing to the growing demand for network mapping software. Cloud-based and on-premises solutions held a significant market share in 2025. However, the cloud-based segment is expected to witness faster growth during the forecast period. The growing adoption of cloud-based services, the need for remote network management, and the cost-effectiveness of cloud-based solutions are driving the growth of this segment. In terms of application, the small and medium enterprises (SMEs) segment dominated the market in 2025, and it is expected to maintain its dominance throughout the forecast period. The increasing number of SMEs, the need for cost-effective network management solutions, and the growing awareness of network security are driving the growth of this segment. Network mapping software is a tool that helps businesses visualize and manage their networks. It can be used to create diagrams of the network, identify potential problems, and track down performance issues. The software can also be used to automate tasks such as device discovery and configuration.

Network Mapping Software Market Outlook

According to our latest research, the global network mapping software market size reached USD 2.1 billion in 2024, reflecting robust adoption across diverse industries. The market is projected to expand at a CAGR of 11.2% from 2025 to 2033, reaching an estimated USD 5.5 billion by 2033. This growth trajectory is primarily driven by the increasing complexity of enterprise networks, heightened demand for proactive network monitoring, and the growing need for real-time visibility into network infrastructure. The proliferation of cloud computing, hybrid IT environments, and the rising threat landscape further accentuate the necessity for advanced network mapping tools, positioning the market for significant expansion over the coming decade.

A critical growth factor for the network mapping software market is the escalating complexity of modern enterprise networks. As organizations increasingly embrace digital transformation, their network topologies become more intricate, encompassing physical, virtual, and cloud-based resources. This complexity necessitates sophisticated network mapping solutions capable of providing comprehensive visibility and real-time insights into network performance, device connectivity, and data flows. Enterprises are prioritizing investments in network mapping software to streamline network management, reduce downtime, and improve overall operational efficiency. The ability to automate network discovery and maintain up-to-date network diagrams is becoming indispensable for IT teams striving to manage dynamic environments, thus fueling the adoption of advanced network mapping tools.

Another pivotal driver is the heightened focus on cybersecurity and regulatory compliance. With the surge in cyberattacks and the increasing sophistication of threat actors, organizations are compelled to deploy robust network security measures. Network mapping software plays a vital role in identifying vulnerabilities, monitoring unauthorized access, and ensuring compliance with industry regulations such as GDPR, HIPAA, and PCI DSS. The integration of network mapping tools with security information and event management (SIEM) systems enhances threat detection and incident response capabilities. This synergy not only supports compliance initiatives but also strengthens the overall security posture of organizations, further propelling the demand for network mapping software across multiple sectors.

The rapid adoption of cloud computing and hybrid IT environments is also catalyzing market growth. As businesses migrate workloads to the cloud and embrace remote work models, the need for visibility across on-premises, cloud, and hybrid networks becomes paramount. Network mapping software enables IT teams to map, monitor, and manage distributed network assets, ensuring seamless connectivity and performance optimization. The shift towards software-defined networking (SDN) and network function virtualization (NFV) is amplifying the requirement for agile, scalable, and automated network mapping solutions. This trend is particularly pronounced among large enterprises and managed service providers seeking to deliver uninterrupted services and maintain competitive differentiation in an increasingly digital landscape.

From a regional perspective, North America continues to lead the network mapping software market owing to its advanced IT infrastructure, high penetration of cloud technologies, and early adoption of innovative network management solutions. The region is characterized by a strong presence of major technology vendors, a mature cybersecurity ecosystem, and stringent regulatory frameworks. Europe follows closely, driven by digital transformation initiatives, data privacy regulations, and growing investments in network automation. The Asia Pacific region is witnessing the fastest growth, fueled by rapid industrialization, expanding enterprise IT footprints, and increasing awareness of network security best practices. Emerging markets in Latin America and the Middle East & Africa are also exhibiting steady adoption, supported by government-led digitalization programs and the proliferation of connected devices.

In 2023, Google Maps was the most downloaded map and navigation app in the United States, despite being a standard pre-installed app on Android smartphones. Waze followed, with 9.89 million downloads in the examined period. The app, which comes with maps and the possibility to access information on traffic via users reports, was developed in 2006 by the homonymous Waze company, acquired by Google in 2013.

Usage of navigation apps in the U.S. As of 2021, less than two in 10 U.S. adults were using a voice assistant in their cars, in order to place voice calls or follow voice directions to a destination. Navigation apps generally offer the possibility for users to download maps to access when offline. Native iOS app Apple Maps, which does not offer this possibility, was by far the navigation app with the highest data consumption, while Google-owned Waze used only 0.23 MB per 20 minutes.

Usage of navigation apps worldwide In July 2022, Google Maps was the second most popular Google-owned mobile app, with 13.35 million downloads from global users during the examined month. In China, the Gaode Map app, which is operated along with other navigation services by the Alibaba owned AutoNavi, had approximately 730 million monthly active users as of September 2022.

The Digital Geomorphic-GIS Map of Gulf Islands National Seashore (5-meter accuracy and 1-foot resolution 2006-2007 mapping), Mississippi and Florida is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (guis_geomorphology.gdb), a 2.) Open Geospatial Consortium (OGC) geopackage, and 3.) 2.2 KMZ/KML file for use in Google Earth, however, this format version of the map is limited in data layers presented and in access to GRI ancillary table information. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (guis_geomorphology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (guis_geomorphology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). The OGC geopackage is supported with a QGIS project (.qgz) file. Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) A GIS readme file (guis_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (guis_geomorphology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (guis_geomorphology_metadata_faq.pdf). Please read the guis_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. Google Earth software is available for free at: https://www.google.com/earth/versions/. QGIS software is available for free at: https://www.qgis.org/en/site/. Users are encouraged to only use the Google Earth data for basic visualization, and to use the GIS data for any type of data analysis or investigation. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri,htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Geological Survey. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (guis_geomorphology_metadata.txt or guis_geomorphology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:26,000 and United States National Map Accuracy Standards features are within (horizontally) 13.2 meters or 43.3 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in Google Earth, ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

Global UAV Mapping Software Market Report 2024 comes with the extensive industry analysis of development components, patterns, flows and sizes. The report also calculates present and past market values to forecast potential market management through the forecast period between 2024-2030. The report may be the best of what is a geographic area which expands the competitive landscape and industry perspective of the market.

This "Best of" Color image service (web mercator projection) allows you to stream Vermont's best available imagery into your GIS or web mapping application. HOW TO USE: The service is available by plugging in the following REST endpoint into your browser, web mapping application, or GIS software.https://maps.vcgi.vermont.gov/arcgis/rest/services/EGC_services/IMG_VCGI_CLR_WM_CACHE/ImageServer NOTE: Clicking the "Download" button to the right will not actually give you the data OR access to the service. Ignore the "Download" button and use the URL above instead. HELP: Refer to the following video describing how you can use VCGI's services in ArcGIS or QGIS.

The Ministry of Natural Resources and Forestry’s Make a Topographic Map is a mapping application that features the best available topographic data and imagery for Ontario. You can: * easily toggle between traditional map backgrounds and high-resolution imagery * choose to overlay the topographic information with the imagery * turn satellite imagery on or off * customize your map by adding your own text * print your custom map Data features include: * roads * trails * lakes * rivers * wooded areas * wetlands * provincial parks * municipal, township and other administrative boundaries You don’t need special software or licenses to use this application. Technical information Using cached imagery and topographic data, the application provides a fast, seamless display at pre-defined scales. The caches are updated annually.

This webmap features the USGS GAP application of the vegetation cartography design based on NVCS mapping being done at the Alliance level by the California Native Plant Society (CNPS), the California Dept of Fish and Game (CDFG), and the US National Park Service, combined with Ecological Systems Level mapping being done by USGS GAP, Landfire and Natureserve. Although the latter are using 3 different approaches to mapping, this project adopted a common cartography and a common master crossover in order to allow them to be used intercheangably as complements to the detailed NVCS Alliance & Macrogroup Mapping being done in Calif by the California Native Plant Society (CNPS) and Calif Dept of Fish & Wildlife (CDFW). A primary goal of this project was to develop ecological layers to use as overlays on top of high-resolution imagery, in order to help interpret and better understand the natural landscape. You can see the source national GAP rasters by clicking on either of the "USGS GAP Landcover Source RASTER" layers at the bottom of the contents list.Using polygons has several advantages: Polygons are how most conservation plans and land decisions/managment are done so polygon-based outputs are more directly useable in management and planning. Unlike rasters, Polygons permit webmaps with clickable links to provide additional information about that ecological community. At the analysis level, polygons allow vegetation/ecological systems depicted to be enriched with additional ecological attributes for each polygon from multiple overlay sources be they raster or vector. In this map, the "Gap Mac base-mid scale" layers are enriched with links to USGS/USNVC macrogroup summary reports, and the "Gap Eco base scale" layers are enriched with links to the Naturserve Ecological Systems summary reports.Comparsion with finer scale ground ecological mapping is provided by the "Ecol Overlay" layers of Alliance and Macrogroup Mapping from CNPS/CDFW. The CNPS Vegetation Program has worked for over 15 years to provide standards and tools for identifying and representing vegetation, as an important feature of California's natural heritage and biodiversity. Many knowledgeable ecologists and botanists support the program as volunteers and paid staff. Through grants, contracts, and grass-roots efforts, CNPS collects field data and compiles information into reports, manuals, and maps on California's vegetation, ecology and rare plants in order to better protect and manage them. We provide these services to governmental, non-governmental and other organizations, and we collaborate on vegetation resource assessment projects around the state. CNPS is also the publisher of the authoritative Manual of California Vegetation, you can purchase a copy HERE. To support the work of the CNPS, please JOIN NOW and become a member!The CDFG Vegetation Classification and Mapping Program develops and maintains California's expression of the National Vegetation Classification System. We implement its use through assessment and mapping projects in high-priority conservation and management areas, through training programs, and through working continuously on best management practices for field assessment, classification of vegetation data, and fine-scale vegetation mapping.HOW THE OVERLAY LAYERS WERE CREATED:Nserve and GapLC Sources: Early shortcomings in the NVC standard led to Natureserve's development of a mid-scale mapping-friendly "Ecological Systems" standard roughly corresponding to the "Group" level of the NVC, which facilitated NVC-based mapping of entire continents. Current scientific work is leading to the incorporation of Ecological Systems into the NVC as group and macrogroup concepts are revised. Natureserve and Gap Ecological Systems layers differ slightly even though both were created from 30m landsat data and both follow the NVC-related Ecological Systems Classification curated by Natureserve. In either case, the vector overlay was created by first enforcing a .3ha minimum mapping unit, that required deleting any classes consisting of fewer than 4 contiguous landsat cells either side-side or cornerwise. This got around the statistical problem of numerous single-cell classes with types that seemed improbable given their matrix, and would have been inaccurate to use as an n=1 sample compared to the weak but useable n=4 sample. A primary goal in this elimination was to best preserve riparian and road features that might only be one pixel wide, hence the use of cornerwise contiguous groupings. Eliminated cell groups were absorbed into whatever neighboring class they shared the longest boundary with. The remaining raster groups were vectorized with light simplification to smooth out the stairstep patterns of raster data and hopefully improve the fidelity of the boundaries with the landscape. The resultant vectors show a range of fidelity with the landscape, where there is less apparent fidelity it must be remembered that ecosystems are normally classified with a mixture of visible and non-visible characteristics including soil, elevation and slope. Boundaries can be assigned based on the difference between 10% shrub cover and 20% shrub cover. Often large landscape areas would create "godzilla" polygons of more than 50,000 vertices, which can affect performance. These were eliminated using SIMPLIFY POLYGONS to reduce vertex spacing from 30m down to 50-60m where possible. Where not possible DICE was used, which bisects all large polygons with arbitrary internal divisions until no polygon has more than 50,000 vertices. To create midscale layers, ecological systems were dissolved into the macrogroups that they belonged to and resymbolized on macrogroup. This was another frequent source for godzillas as larger landscape units were delineate, so simplify and dice were then run again. Where the base ecol system tiles could only be served up by individual partition tile, macrogroups typically exhibited a 10-1 or 20-1 reduction in feature count allowing them to be assembled into single integrated map services by region, ie NW, SW. CNPS / CDFW / National Park Service Sources: (see also base service definition page) Unlike the Landsat-based raster modelling of the Natureserve and Gap national ecological systems, the CNPS/CDFW/NPS data date back to the origin of the National Vegetation Classification effort to map the US national parks in the mid 1990's.
These mapping efforts are a hybrid of photo-interpretation, satellite and corollary data to create draft ecological land units, which are then sampled by field crews and traditional vegetation plot surveys to quantify and analyze vegetation composition and distribution into the final vector boundaries of the formal NVC classes identified and classified. As such these are much more accurate maps, but the tradeoff is they are only done on one field project area at a time so there is not yet a national or even statewide coverage of these detailed maps.
However, with almost 2/3d's of California already mapped, that time is approaching. The challenge in creating standard map layers for this wide diversity of projects over the 2 decades since NVC began is the extensive evolution in the NVC standard itself as well as evolution in the field techniques and tools. To create a consistent set of map layers, a master crosswalk table was built using every different classification known at the time each map was created and then crosswalking each as best as could be done into a master list of the currently-accepted classifications. This field is called the "NVC_NAME" in each of these layers, and it contains a mixture of scientific names and common names at many levels of the classification from association to division, whatever the ecologists were able to determine at the time. For further precision, this field is split out into scientific name equivalents and common name equivalents.MAP LAYER NAMING: The data sublayers in this webmap are all based on the US National Vegetation Classification, a partnership of the USGS GAP program, US Forest Service, Ecological Society of America and Natureserve, with adoption and support from many federal & state agencies and nonprofit conservation groups. The USNVC grew out of the US National Park Service Vegetation Mapping Program, a mid-1990's effort led by The Nature Conservancy, Esri and the University of California. The classification standard is now an international standard, with associated ecological mapping occurring around the world. NVC is a hierarchical taxonomy of 8 levels, from top down: Class, Subclass, Formation, Division, Macrogroup, Group, Alliance, Association. The layers in this webmap represent 4 distinct programs: 1. The California Native Plant Society/Calif Dept of Fish & Wildlife Vegetation Classification and Mapping Program (Full Description of these layers is at the CNPS MS10 Service Registration Page and Cnps MS10B Service Registration Page . 2. USGS Gap Protected Areas Database, full description at the PADUS registration page . 3. USGS Gap Landcover, full description below 4. Natureserve Ecological Systems, full description belowLAYER NAMING: All Layer names follow this pattern: Source - Program - Level - Scale - RegionSource - Program = who created the data: Nserve = Natureserve, GapLC = USGS Gap Program Landcover Data PADUS = USGS Gap Protected Areas of the USA program Cnps/Cdfw = California Native Plant Society/Calif Dept of Fish & Wildlife, often followed by the project name such as: SFhill = Sierra Foothills, Marin Open Space, MMWD = Marin Municipal Water District etc. National Parks are included and may be named by their standard 4-letter code ie YOSE = Yosemite, PORE = Point Reyes.Level: The level in the NVC Hierarchy which this layer is based on: Base = Alliances and Associations Mac =

5-Digit and 3-Digit ZIP Code data for Maptitude mapping software are from Caliper Corporation and contain boundaries and demographic data.

This interactive application was created to share the incredible adventure my wife Liz and I undertook for our Honeymoon to Yellowstone National Park for it's 150th Anniversary. Along the trip we traveled nearly 4,000 miles to visit 6 National Parks, numerous trails and campsites, dozens of geysers, hot springs, breweries, etc.

A survey was created via Survey123 Connect to capture the data along our journey. The web application was built in Experience Builder to emulate a dashboard with the Feature Info widget to display survey records including media starting from the beginning of the journey and a List widget to further aid in navigating the records. Since this application was designed in Experience Builder, it is also Tablet and Mobile friendly but I recommend viewing the application from a desktop for the best viewing and navigation experience.

SASB Mapping Tools Market Outlook

According to our latest research, the Global SASB Mapping Tools market size was valued at $1.2 billion in 2024 and is projected to reach $4.7 billion by 2033, expanding at a robust CAGR of 16.8% during the forecast period from 2025 to 2033. The primary driver for this impressive growth is the accelerating demand for transparent, standardized sustainability reporting frameworks across financial institutions and corporates worldwide. As environmental, social, and governance (ESG) disclosure becomes a central focus for stakeholders, the adoption of SASB mapping tools—designed to align corporate disclosures with the Sustainability Accounting Standards Board (SASB) framework—is surging. This trend is further supported by regulatory pressures, investor expectations, and the increasing integration of ESG factors into business strategy and investment decisions.

Regional Outlook

North America currently commands the largest share of the global SASB Mapping Tools market, accounting for approximately 42% of the total market value in 2024. This dominance is attributed to the region's mature regulatory environment, high level of digitalization among enterprises, and proactive adoption of ESG standards by both corporates and financial institutions. The United States, in particular, has seen a significant uptick in SASB-aligned disclosures, driven by investor demand for robust ESG data and the presence of leading technology providers offering advanced mapping solutions. The region's well-established consulting ecosystem and the increasing pressure from regulatory bodies such as the SEC to enhance ESG transparency have further cemented North America's leadership position in this market.

The Asia Pacific region is projected to be the fastest-growing market, with a CAGR exceeding 20% from 2025 to 2033. Rapid economic development, coupled with increasing awareness of sustainability and ESG reporting, is driving substantial investments in SASB mapping tools across countries like China, Japan, India, and Australia. Governments in the region are rolling out new policies and guidelines to standardize ESG disclosures, compelling organizations to adopt structured frameworks such as SASB. The influx of foreign investments, especially from ESG-focused funds, is prompting local enterprises to align their reporting standards with global best practices, fueling the demand for sophisticated mapping tools. Additionally, the rise of cloud-based solutions is making these tools more accessible to a broader spectrum of organizations, including SMEs.

Emerging economies in Latin America and the Middle East & Africa are gradually increasing their adoption of SASB mapping tools, albeit at a slower pace compared to developed regions. The primary challenges in these regions include limited awareness of ESG frameworks, varying regulatory landscapes, and a lack of standardized reporting requirements. However, multinational corporations with operations in these markets are driving localized demand as they seek to harmonize ESG disclosures across their global footprint. Policy reforms and capacity-building initiatives by international organizations are expected to facilitate broader adoption over the next decade. Nonetheless, the market in these regions remains fragmented, with significant opportunities for growth as regulatory clarity and stakeholder demand for ESG transparency continue to evolve.

Report Scope

Discover the booming market for EV route planner apps! This analysis reveals key trends, growth projections (CAGR 25%), leading companies (Tesla, ChargePoint, etc.), and regional market share, offering valuable insights for investors and industry professionals. Explore the future of EV navigation.

Chapter 6: sUAS for Wildlife Conservation – Assessing Habitat Quality of the Endangered Black-Footed Ferret Donna M. Delparte, Kristy Bly, Travis Stone, Sarah Olimb, Michael Kinsey, Matthew Belt, Thomas Calton Advances in high spatial resolution mapping capabilities and the new rules established by the Federal Aviation Administration in the United States for the operation of Small Unmanned Aircraft Systems (sUAS) have provided new opportunities to acquire aerial data at a lower cost and more safely versus other methods. A similar opening of the skies for sUAS applications is being allowed in countries across the world. Also, sUAS can access hazardous or inaccessible areas during disaster events and provide rapid response when needed. Applications of Small Unmanned Aircraft systems: Best Practices and Case Studies is the first book that brings together the best practices of sUAS applied to a broad range of issues in high spatial resolution mapping projects. Very few sUAS pilots have the knowledge of how the collected imagery is processed into value added mapping products that have commercial and/or academic import. Since the field of sUAS applications is just a few years old, this book covers the need for a compendium of case studies to guide the planning, data collection, and most importantly data processing and map error issues, with the range of sensors available to the user community. Written by experienced academics and professionals, this book serves as a guide on how to formulate sUAS based projects, from choice of a sUAS, flight planning for a particular application, sensors and data acquisition, data processing software, mapping software and use of the high spatial resolution maps produced for particular types of geospatial modeling.

The Customer Journey Mapping Software market is an increasingly vital segment within the broader field of customer experience management. As organizations strive to enhance their interactions with consumers, these software solutions provide valuable insights into the entire customer journey-from initial awareness th

Healthcare Data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain point geographic files of healthcare organizations, providers, and hospitals and an boundary file of Primary Care Service Areas.

Folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. These files can be used to mark the state boundaries on the map of INDIA using folium library and the CSV also contains the state data and how to use it in our notebooks. I have used it in one of my kernels which can be viewed.

The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON, and TopoJSON overlays. Due to extensible functionalities I find folium the best map plotting library in python. Do give it a try and use it in your kernels.

The Ministry of Natural Resources and Forestry’s Make a Topographic Map is a mapping application that features the best available topographic data and imagery for Ontario. You can: * easily toggle between traditional map backgrounds and high-resolution imagery * choose to overlay the topographic information with the imagery * turn satellite imagery on or off * customize your map by adding your own text * print your custom map Data features include: * roads * trails * lakes * rivers * wooded areas * wetlands * provincial parks * municipal, township and other administrative boundaries You don’t need special software or licenses to use this application. Technical information Using cached imagery and topographic data, the application provides a fast, seamless display at pre-defined scales. The caches are updated annually.

Background: Between 2011 and 2018, the NASA Dawn spacecraft visited asteroid (4) Vesta and dwarf planet (1) Ceres to investigate the surfaces of both protoplanets through optical and hyperspectral imaging and their composition through gamma-ray and neutron spectroscopy from orbit.
For both Vesta and Ceres, a geologic mapping investigation was realized based on optical and hyperspectral data as well as a photogrammetrically derived digital terrain model. For the global mapping investigation, mappers employed Geographic Information System (GIS) software to map 15 quadrangles. The results were published as individual map sheets alongside research papers discussing the geologic evolution. The style of collaborative mapping to produce a consistent global view represented by individual quadrangle maps is comparably new despite abundantly available mapping experiences. Ongoing data acquisition during mapping created considerable challenges for the coordination and homogenization of mapping results.

To handle this issue simultaniously to the active mission phase as best as possible a GIS-based environment was needed in order to conduct one homogenous dataset (w.r.t. geometrical and visual character) that represents one geologically-consistent map at the end. Therefore, the mapping team was supported by an predefined mapping template which was generated in the proprietary ArcGIS environment. The template contains different layers (called feature classes) for the different object/geomoetry types and contains predefined attribute values as well as cartographic symbols. The cartographic symbols follow international standards as far as possible. The colours for the geological units refering to established colour values used in geologic maps, e.g., standardized planetary maps generated by USGS, but considering individual needs and requests within the mapping team, too.

The data product pubished here based on the mentioned GIS-based template and represents the merged global GIS-dataset of the 15 individually conducted geological maps of Ceres within the Dawn Mission. The detailed descriptions of all those scientific interpretions are published in the papers listed within the reference section. Based on team-internal decisions the dataset is provided within the properitary format of ESRIs ArcGIS environment. However, in order to use the data product also outside this software environment, single shapefiles with additional information about the symbology are also included. All available data are available within the compressed folder and the readme-file gives some informative remarks for the useage of the data

Additional remark: The data set provided here does not represent a holistic (in term of topological and scientifical) unification of the 15 individual mapping data as primarily geometric and content-related inconsistencies at quadrangle boundaries prohibited a unified compilation. On the one side, this is due to the fact that the the aim of the mapping project was not to produce a uniform global map, but rather to gain a first impression of the geology of Ceres and publish associated scientific papers. On the other side, that the geological mapping project ran parallel to the regular mission phase, and a finalizing review process for creating a global geological dataset wasn´t scheduled in the mission planning. This deficiency cannot be remedied simply by merging topological missmatches or changing the visualisation. Rather it will require ongoing and detailed scientific discussion of the interpretation results, which could be solved within an updating version of the global map.

This application is used to help people locate heat relief from May to September in Maricopa County. The Heat Relief Network is made up of municipalities, nonprofit organizations, faith-based community, and businesses and is kept up to date throughout the summer. This is a custom JavaScript application built in-house by Jack Fairfield. Survey123 is used to gather the Heat Relief Network partner applications. The feature service is maintained and updated through portal on a hosted ArcGIS Server.

High-density linkage maps are important tools for genome biology and evolutionary genetics by quantifying the extent of recombination, linkage disequilibrium and chromosomal rearrangements across chromosomes, sexes and populations. They provide one of the best ways to validate and refine de novo genome assemblies, with the power to identify errors in assemblies increasing with marker density. However, assembly of high-density linkage maps is still challenging due to software limitations. We describe Lep-MAP2, a software for ultra-dense genome-wide linkage map construction. Lep-MAP2 can handle various family structures and can account for achiasmatic meiosis to gain linkage map accuracy. Simulations show that Lep-MAP2 outperforms other available mapping software both in computational efficiency and accuracy. When applied to two large F2-generation recombinant crosses between two nine-spined stickleback (Pungitius pungitius) populations, it produced two high-density (~6 markers/cM) linkage maps containing 18 691 and 20 054 SNPs. The two maps showed a high degree of synteny, but female maps were 1.5 to 2 times longer than male maps in all linkage groups, suggesting genome-wide recombination suppression in males. Comparison with the genome sequence of the three-spined stickleback (Gasterosteus aculeatus) revealed a high degree of interspecific synteny with a low frequency (<5%) of interchromosomal re-arrangements. However, a fairly large (ca. 10Mb) translocation from autosome to sex chromosome was detected in both maps. These results illustrate the utility and novel features of Lep-MAP2 in assembling high-density linkage maps, and their usefulness in revealing evolutionarily interesting properties of genomes, such as strong genome-wide sex-bias in recombination rates.