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Directions Magazine invites companies, organizations, and industry professionals to contribute press releases that communicate important developments in geospatial technology, mapping, data analytics, and location intelligence. By submitting your press announcements, you gain exposure to a global audience of GIS specialists, spatial analysts, planners, and decision makers who actively seek timely, relevant news that shapes industry discussion and innovation.

Whether you are announcing a new product release, strategic partnership, research milestone, award, or event, contributing your press release helps ensure your story reaches the right audience. The process is designed to be straightforward, allowing contributors to present clear, well-structured announcements that resonate with readers interested in cutting-edge spatial solutions and market trends.

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To maximize the visibility and impact of your announcement, ensure your press release is professionally formatted and focused on newsworthy content. A compelling headline, concise summary, key specifications or results, and clear contact information improve readability and distribution value. Highlight the significance of your announcement and how it contributes to geospatial innovation or addresses real-world challenges in mapping, data workflows, or location-driven decision making.

High-quality submissions help readers quickly understand what is new, why it matters, and how it relates to broader industry themes. Well-written press releases also support search visibility, enhancing the discoverability of your brand and solutions by professionals searching for the latest advances in geospatial technology.

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By contributing press releases, you also participate in a broader industry dialogue that connects innovation, research, and practical application. This exposure can support lead generation, brand recognition, and community engagement while fostering knowledge exchange across global markets.

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Ed. note: This article was updated since it was first published. Figure 6 has been changed and the issue regarding block (see first comment) has been addressed.

The human brain has a limited capacity to store and process large quantities of information. To handle overwhelming complexities of detail the mind will often break down large chunks of data into manageable tracts for processingi. A prominent topic in which information gets segmented is place identification. In geography, areas are frequently divided into smaller regions. In the United States, the country is a collection of states and territories comprised of counties with cities and towns. These regions are further subdivided into officially recognized designations: ZIP Codes, census tract groups and census tracks based on numeric designations.

This article will outline a process used for breaking down cities and towns into alternative regions structured on name recognitionii: neighborhoods, districts or other local areas. Based on the demographic data gathered using these techniques - collected from the 250 largest U.S. cities' neighborhoods - evidence will be given to support the potential benefits to quantifying city data based on neighborhood names and their accompanying structures rather than traditionally used U.S. Censusiii regions. The process defines neighborhood boundaries based on commonly recognized characteristics such as widespread reference by community, as well as natural and human demarcations.

Through defined neighborhood datasets and boundaries, the study will attempt to show that locally correlated attributes with recognizable names can provide cohesive information for a given region. The analysis hopes to convince the reader that neighborhoods, with their flexibility to form organically, prove in many cases to be a better solution to collecting demographic data than census measurements, which are often confined to a fixed quantity amalgamation of census tracts, units that are generally restricted to a set population for a given regioniv.

The U.S. Censusv designates that a census tract typically ranges between 1,500 - 8,000 people, with a stated ideal size being 4,000 individuals. This uniformity for a tract group forces demographic units to conform to a fixed population rather than a neighborhood demographic that may vary in population (e.g. census tracts for San Francisco, California average 4,000 people, while San Francisco neighborhoods range in population from 250 - 37,000 individuals)vi.

By arbitrarily combining fixed measurements, demographic consistency is greatly diminished, in part because fixed population sizes force exclusion of nearby regions that may share characteristics or restrict inclusion of areas with a different distinct identity. This problem becomes more pervasive as groupings become larger, as seen with ZIP Code divisions where size (roughly 2-5 census block groups)vii boundaries are chiefly determined by the amount of mail that can be delivered from a post office, not by determining an area's socio-economic characteristics.

Ethnicity and income also play a roll in defining certain neighborhoods. In most large U.S. cities you will find ethnic communities. These clusters often form the basis of neighborhoods. By definition they will often have members who share a certain amount of continuity in their life style, income and activism. Over time, their activities may inspire similar/like-minded groups to move in, while encouraging others to leave. In San Francisco extreme cases of this can be seen in the density of the Chinese population in "Chinatown" and the gay population found in the Castro. The demographic data below show that neighborhoods come in various sizes with different characteristics.

A neighborhood is a place built on identity. Physical neighborhoods [generally] form around specific geographic characteristics (Identifying Urban Neighborhoods: An Annotated Biography Thomas F. Broden, Ronn Lirkwood, Susan Roberts, John Roos, Thomas Swartz Council of Planning Librarians Institute for Urban Studies Notre Dame (1980)), deriving boundaries from distinct elements: a hill, a seaside, a central district, or from surrounding roads. These distinctions such as "hills" and "valleys" often define desirability (e.g. a higher elevation with a view probably being more valuable than a reclaimed lowland "mudflat"). Other neighborhoods use functional, political or economic differentiation united by a common culture, age and heritage or through distinctive characteristics such as a gated community, commerce designated area, industrial zone or a "seedy part" of town.

To begin our analysis, we need to create a systematic way to define the physical boundaries of neighborhoods from which data can be quantified. From the beginning we understand that describing neighborhood locations precisely could prove controversial. People have different opinions on what constitutes a neighborhoodviii. For this reason we consulted experts in GIS mapping, city planning and real estate sales, as well as ordinary citizens, to supply input on building our neighborhood map designations. While achieving an absolute consensus for defining neighborhoods would be unlikely, our goal is to provide a comprehensive system that generates neighborhood data that many users - especially individuals conducting online queries or doing neighborhood research - would find helpful in seeking local information. After careful study, a systematic multi-step process was created that tries to quantify what defines a physical neighborhood structure (see Process List below). We also realized that if it could be done successfully the social and economic gains could be substantialix for users.

In our observations, we notice the historical significance of neighborhoods. In many regions, neighborhood names are often passed on through an oral tradition where local inhabitants make reference to a given area, often based on an original name given to a subdivision by a developer (in Berkeley, California districts like the Claremont, Elmwood or by a region's functional use). Then over time neighborhood boundaries are further refined by city professionals that quantify a region's borders by setting demarcations based on zoning, district boundaries or through road construction. Below is an outline of some elements of our 20-step process used to define neighborhoods. Different nations will have variations on how data are collected.

Process List for collecting neighborhood data:

Go to official city sites to see if mapping data are publicly available. Generally follow given city neighborhood boundary definitions closely where available so that data follow the consensus of the community.

View maps that can be used as map backgrounds to raster images; try to have at lease two sources of data to make comparisons.

Visit sites with local information: official city sites, local chamber of commerce sites, etc.

Call local city chamber of commerce, city planning or regional real estate agents to ask for descriptions (identify yourself as part of a research group, where data gathered serve the community).

Visit or send out emails to local real estate agents or local residents to contribute information online.

Many of the datasets collected are in collaboration with city planning offices, chambers of commerce and real estate agencies; we have a policy to offer the aiding community free copies of the processed digital neighborhood maps and demographic data. We also offer the neighborhood data free of charge for academic research and for noble causes (e.g. public health).

Methodology for Recognizing and Defining Physical Neighborhood Boundariesx

Descriptive Boundaries Method: Identifies neighborhoods using existing maps and natural boundaries with a combination of data from city planning offices, chambers of commerce, local real estate firms and other sourcesxi. By comparing neighborhood descriptions with local maps, you can get an understanding of how neighborhoods are perceived by different members of a local community.

Areas where a strong consensus exists - usually confirmed by several independent sources - usually get incorporated into maps first. Old established cities (e.g. Boston, New York) generally have clear distinct neighborhood designations. It appears that with age, a city's established neighborhood identity solidifies over timexii.

When conflicting, ambiguous or non-existing boundaries occur, local organizations within those areas are contacted in hopes of resolving unidentified neighborhood areas. Based on information provided, a best guess estimate is chosen or the area is left blank. The neighborhoods are then traced out by locating major streets and other boundaries. Maps generated with this method often are quite comprehensive. As a neighborhood changes or new information becomes available, modifications can be made.

The above image shows an Indianapolis neighborhood map generated from descriptions of an online newspaper website.

Deduction Method: This method uses maps and satellite images to estimate neighborhood demarcations. Different neighborhoods usually render recognizable patterns (e.g. squiggly patterns often represent hills where the roads are not straight) on satellite images. These patterns often consist of commonalities that neighborhoods share: style, age, landscape or other factors. Based on these differences coupled with a neighborhood's approximate location, an accurate boundary estimate can often be made. Factors such as road accessibility and terrain can play an integral part of a neighborhood's formation. A technique used to measure the Deduction Method's accuracy is to map out a city's neighborhoods with this method - where neighborhood boundaries are known - and compare the results of known neighborhoods to hypothesized samples.

Today different land uses are mostly traced out by humans. In the future OIR (Optical Image Recognition) systems will be able to identify structures, extract commonalities and cluster data based on image patterns. For example, picture data will recognize neighborhood clusters based on relative housing styles or grouped lot sizes. There may even come a time when demographic inferences are made based on the car parked in the driveway.

The above image shows an accurate neighborhood map of San Francisco based on visually identified neighborhoods on a satellite image.

Other images will also give inference to neighborhood qualities; parks, stadiums, golf courses and harbors will be identified and classified by comparing them to stock items in a database with known characteristics. Structural information gleaned can then provide an insight into neighborhood characteristics along with already know, compiled information to give a demographic preference livability score. In our collection we have already collected locations for more than 1.2 million U.S. places of interest that can be factored into a quality of life matrix. As our understanding of neighborhood formation and characteristics increases, we speculate that algorithms will be created that will be able to discern different neighborhood uniqueness, similar to the way pattern recognition software can differentiate different types of buildings, as well as other geographic structures. This neighborhood demographic analysis will be able to aid a user in selecting a neighborhood that most closely resembles a user's desired characteristics.

Scatter Plot Method: This method aggregates a collection of data points to assemble a map from which neighborhood boundaries can be constructed. This method is useful for allowing many users to contribute to the construction of neighborhood boundaries, as well as being able to monitor changes to neighborhood patterns in adjacent areas. For example, real estate agent listings on Craigslist, Realtor.com or Google Base could integrate the scatter plot method to help users to define neighborhood locations. Location aware mobile devices (GPS) will conceivable play a significant roll in creating boundaries as location coordinates become associated with "tagged" descriptive information.

The scatter plot data show that clustering exists between San Francisco neighborhoodsxiii. This method of data collection holds great promise for mapping neighborhoods. As people gain access to GPS-enabled cameras, a flood of corresponding location data should ensue, enabling an ever increasing amount of neighborhood boundary data for users. These data should also provide neighborhood name recognition statistics for given areas.

We produced boundary data at both U.S. government issued TIGER level (red) and the more exacting 1.5 - 3.0 meter quality level (green). TIGER data were needed to aggregate U.S. Census demographic data for neighborhoods and the higher quality data were needed for precision matching of streets.

• Richard Dorall, Factle Maps & University of Malaya

• Michael Cho, UC Berkeley iMap co-author

• UC Berkeley Interns and Kathy Dombrowski

• Shawn Newsam, UC Merced - Image Technology

• Center of Entrepreneurship and Technology

iAtkinson, R.C. & Shiffrin, R.M. (1968) Human memory: A proposed system and its control processes. In K.W. Spence and J.T. Spence (Eds.), The psychology of learning and motivation, vol. 8. London: Academic Press.

iiBased on informal sampling of over 25 people who reside in the San Francisco Bay Area to see how many could name their neighborhood vs. census block. A majority could name their neighborhood or a nearby neighborhood; most residents did not know what constituted a census block and only one person responded with a census block answer. It was not confirmed if it actually was a correct answer. In the future a more formal study should be done on the number of people who can accurately define which neighborhood they reside in.

viBased on Kathleen Dombrowski and Bernt Wahl raw neighborhood data, of 150 U.S. cities with 7000 neighborhoods (size, population, density, and demographic statistics) provided by Factle Map Co. based on 2006 MapInfo data.

viiMore information about census blocks and block groups are available in the glossary at the U.S. Census website: http://www.census.gov/

viiiShaping Neighborhoods: A Guide for Health, Sustainability and Vitality, Hugh Barton, Marcus Grant and Richard Guise (2003) Spon Press, London

ixBased on an internal HomeGain study, the firm believes adding neighborhood search terms will boost SEO search revenues (2nd largest online real estate firm) by 20% or millions of dollars (Bernt Wahl, consultant (2005)). Based on the firm's internal data analysis it is estimated that about 20-30% of home buyers would prefer to search for homes that include neighborhood regions. Internal traffic records have shown a strong correlation (internal HomeGain traffic records (2006)). Based on similar correlation study if Google could capture 5% of its $500 million local search revenue from targeted neighborhood results, this would increase revenues by $25 million.

xPortions of descriptions and uses are based on prior collaborations, Malaysian Team - (2001-2008), HomeGain Team (2005-2006), MOT Leading Edge Completion Team (2006)

xiReadings on reputation and sourcing [add comments]

xiiAn exception would be "neighborhood name" gentrification where an established area with a name that is less desirable would try to assimilate an adjacent name or create a new identity (e.g. Temescal becoming Upper Rockridge in Oakland, California).

Mapping the World ... One Neighborhood at a Time - Part One

Turning Data Into Insight with Geographic Visualization

Geographic visualization transforms raw data into visual maps that reveal patterns and relationships invisible in spreadsheets and tables. By anchoring data to geographic locations, organizations gain a more intuitive understanding of how variables interact in space and time. This spatial perspective enhances clarity in complex decision environments, helping leaders identify trends, assess risk distribution, and prioritize actions based on geographic context. Geographic visualization bridges the gap between raw numbers and strategic insight by turning abstractions into concrete visual narratives.

By visually layering information across maps, analysts can combine demographic, environmental, and operational data to reveal multidimensional patterns that drive smarter decisions. These visual representations not only improve comprehension but also promote collaborative analysis, enabling teams from different departments to share a unified spatial viewpoint.

Supporting Strategic Planning and Operational Decisions

In today’s competitive landscape, geographic visualization plays a pivotal role in both strategic planning and operational execution. Planners use spatial maps to evaluate market reach, optimize service locations, and detect underserved areas. Operational teams use the same maps for logistics planning, route optimization, and resource allocation, ensuring that actions align with geographic realities on the ground. Combined with analytical toolsets, geographic visualization helps decision makers balance efficiency with long-term goals.

Organizations that integrate spatial visuals into dashboards and reporting frameworks benefit from faster insight discovery and reduced uncertainty in complex decisions. Whether forecasting demand shifts or evaluating infrastructure investment, maps provide context that enhances both tactical and strategic choices.

Enhancing Communication Across Stakeholders

One of the strongest advantages of geographic visualization lies in its ability to communicate complex analysis clearly across diverse audiences. Visual maps transcend technical jargon and numeric complexity, making insights more accessible to executives, field teams, partners, and external stakeholders. Maps tell a story that aligns spatial patterns with organizational priorities, enabling better alignment and informed dialogue.

Interactive visual tools further extend engagement by allowing users to explore data layers, zoom into areas of interest, and filter results based on specific criteria. This interactivity improves understanding and encourages data-informed participation in planning processes.

Enabling Real-Time Awareness and Adaptive Response

With the rise of real-time data streams and dynamic mapping technologies, geographic visualization now supports immediate situational awareness and adaptive decision support. Live maps fed by sensor data, mobile inputs, and real-time transactions help organizations detect emerging trends, respond to changing conditions, and adjust plans on the fly. This capability is especially valuable in operations such as emergency response, supply chain monitoring, and public health surveillance, where timing and precision are critical.

By blending real-time visualization with spatial analytics, teams gain a powerful decision support system that enhances responsiveness and operational resilience in uncertain environments.

The Role of Geographic Visualization in Data-Driven Decision Making

Herts,UK Cadcorp, the UK developer of the popular Cadcorp SIS - Spatial Information System - range of Windows-based GIS software has passed another OpenGIS conformance test, the third to date for the company. At a recent meeting of the OpenGIS technical committee held in the USA, Cadcorp SIS and the Microsoft COM-based Cadcorp apSIS toolkit ,OLE DB Provider, were certified conformant with the OpenGIS Simple Features specification.

The Simple Features specification defines both a data model for GIS vector data and a database schema for presenting such data via Microsoft OLE DB Provider COM interfaces. OLE DB is a specification for a set of data access interfaces designed to enable a multitude of data stores, of all types and size, to work seamlessly together. These interfaces make up an industry standard for data access and manipulation that can ensure consistency and interoperability in a heterogeneous environment of data and data types.

In practice, the Cadcorp SIS OLE DB Provider will allow users to present a Cadcorp SIS work session (called a Saved Window Definition, or SWD) as a database and the maps (called Overlays) associated with that work session as tables within that database. Any Windows applications that use Microsoft's ActiveX Data Objects (ADO) will be able to access these Cadcorp SIS work sessions and their maps. This means that any of the wide range of data formats that Cadcorp SIS reads as standard, including indexed datasets of multiple map tiles, can be displayed using a relational model. Cadcorp SIS work sessions can thus be queried by external applications using, for example, Visual Basic, C++, or SQL and the query results passed to other applications, such as those dedicated to advanced statistical analysis and reporting. Furthermore Cadcorp SIS data could be viewed in any client program which uses ActiveX Data Objects.

"There are two main aspects to this work", stated Martin Daly, technical director, Cadcorp. "One is the ongoing commitment to OpenGIS; we are pleased to say that this is our third OpenGIS conformance certificate and others will follow. The other is the fact that OLE DB opens up Cadcorp SIS data to other software applications in a relational database model. By embracing OLE DB we are keeping Cadcorp SIS at the leading edge of Windows database connectivity and offering new options for those users and applications interacting with Cadcorp SIS".

Cadcorp SIS - Spatial Information System - is a suite of Windows-based and Web-enabled end user and developer digital mapping and geographic information system (GIS) software products. The suite comprises: Map Viewer, which provides support for over 45 graphic and data formats, thematics and hard copy; Map Manager, which provides the mainstream user the ability to view, explore, query, symbolise and print digital map and associated tabular data; Map Editor, which in addition to the facilities provided by Map Manager, provides the GIS data custodian with tools to view, manage and edit map and tabular data; and Map Modeller, which adds 3D modelling, terrain analysis and several thematic and analytic mapping tools.

Cadcorp ASC (Active Server Component) extends the functionality of Cadcorp SIS for use over the Internet or a company-wide intranet. It is a dynamic, server-side Web-based GIS, not merely a map publishing tool for pre-authored images. Cadcorp ASC provides a true, interactive Web-based solution for real time map creation and analysis.

Established in 1991, Cadcorp is a leading developer of digital mapping and geographic information systems (GIS) software. With offices in the USA and UK, Cadcorp's distribution and VAR network stretches world-wide. The company also plays a pivotal technical role in the OpenGIS Consortium. Cadcorp SIS is the only complete product family to currently attain OpenGIS conformance certification.

Cadcorp SIS applications exist in municipal government, central government, emergency services, insurance, oil & natural gas, mapping and surveying, commerce, broadcasting and many other markets.

Cadcorp gains another OpenGIS conformance certificate

Join Directions Magazine India for this webinar, which will focus on the market potential for geographic information systems in India. The session will include presentations from two highly respected members of the GIS community in India, and will be moderated by Directions Magazine India's executive editor, Maneesh Prasad.

Dr. Vandana Sharma is the Deputy Director General & Head of the Remote Sensing and GIS Division at the National Informatics Center, and has played a leadership role in many of the large scale GIS projects in India, while working closely with the Planning Commission and various ministries in the central and state government.

Dr. Mukund Rao serves as Member-Secretary of the National GIS Interim Core Group, where he is presentedly involved in buiding the vision of National GIS for India. He has vast experience in GIS and EO Solutions business development/consulting and has been engaged in implementing large GIS projects in India, the Middle East and the Asia/Pacific region, as well as in the U.S. 

In addition to addressing the current status of the Asian/Indian geospatial market, it will also include a question and answer period for the audience, as well as a brief overview of Directions Magazine India magazine and webinar sponsorship opportunities. 

Prospects and Potential for the Indian GIS Market

Readers of this magazine are unlikely to need convincing about the inherent utility of maps. As representations of information, maps enable the analysis of spatial distributions and patterns and are a medium for communication both for and by the mapmaker. In fact, a map is a common metaphor for the arrangement of any type of information because being able to visualize spatial relationships among the data, whether words, numbers, shapes, images, objects, or concepts, helps us interpret and extract meaning.

GIS was designed for mapping geographic space, though a printed map is only one of many GIS products. I remind my students to postpone printing of their layout designs as long as possible, knowing that once hard copy is produced, the connection with the life-giving database is severed. In fields with a long history of, and expectation for, printed maps, such as the geological sciences, there are calls for greater acceptance of data sharing in alternative formats, given the time commitment involved to design, produce and distribute paper products. With improvements in the interoperability of applications and the increased emphasis on web mapping, we can expect fewer projects to yield printed maps in the future.

But regardless of their format, maps remain essential to the process of making decisions, explaining situations, displaying spatial analyses and establishing a setting. This month we begin a series of articles on

, intended to highlight some of the most salient aspects of map design and usage within a modern GIS context. Contributing authors will share their ideas on topics such as representing uncertainty and best practices for communicating via web-based maps, among others. In this article, we begin with some general principles and ideas.

How well a map communicates information to its audience is in large part a function of cartographic design, yet formal training in cartography isn’t very common in a modern education, nor is it required in GIS degree or certificate programs. Companies such as CartoDB and Stamen have prioritized cartographically-informed design options into their user experience. Esri’s Mapping Center provides a great breadth of support and resources, and their annually produced Map Book exemplifies marvelous productions. Plenty of opportunities exist for expert advice and guidance — see the References and Resources section for a few options — but in the end it’s up to the individual mapmaker to produce an effective map or not. Effectiveness is measured by whatever the purpose of the map and the intent of the mapmaker are, but for the sake of this discussion, it’s about how well a map helps to communicate a message. Communication is a two-way street, and mapmakers have little or no control over many variables. First impressions are potent.

To begin, cognitive processes kick in to action the moment someone visually perceives a map. Visual image processing by the human brain is a rich and multi-step experience. Humans have a natural tendency to decode what they see and seek order out of noise. Shapes and objects may be perceived as a whole image or as individual items or differentiated as figure and ground, as described with Gestalt principles. Color-blind individuals may fail to distinguish hues and shades. Moreover, the role of prior knowledge in map interpretation is complex. The map itself is information newly being considered, but what knowledge does the viewer already have about the map’s area, content and context? What prior knowledge do they have about map reading processes overall? How can you design for experts and novices, when everyone brings different degrees and sources of expertise to the table?

Designing map layouts is often the last step in a GIS project and is typically rushed. Planning for multiple drafts and thoughtfully applying non-default settings is a worthwhile investment of time, since the first view of a map may be the only one.

Accept or doubt? Critique or regard with reservation?

As graphic representations, maps carry a certain gravitas that other images do not. So many examples of manipulated images cross our computer screens that “photoshopped” is a bona fide dictionary entry — although Adobe® prefers “manipulated with Adobe® Photoshop® software.” Of course, published maps are also deliberately altered for military, political, advertising and privacy purposes, among many other reasons, but the public is largely unaware and unassuming of these matters. Acceptance and trust are much more common reactions to a map. Even with the expansion of Do-It-Yourself web mapping sites, so few people in the world have ever made a map with modern digital technologies that they have no idea how easy it is to rearrange or misrepresent information.

People are also unfamiliar with the sources of geographic information on a map and how they’re derived. Our early experiences with printed maps are most likely to be with a government production, such as a topographic map from the U.S. Geological Survey, or a road map with its authoritative lines and standardized symbols. As a child, I for one certainly assumed that they must have been provided by a trustworthy and informed source, whatever that might have been. Blindly trusting satellite navigation maps is one all-too-common example of being misguided.

Map legends ought to be the map to a map. An effective legend is the guiding light to interpreting a map’s symbols and patterns, but even supremely well-designed legends may not get the consideration and close reading they merit. Maybe the map is being used in a crisis situation and the viewer has no time for methodical interpretation. More often, it’s our dislike of reading instructions and user manuals, and our increasingly short attention spans that cause our oversight. Manipulating the symbology of choropleth maps is a frequent activity in an introductory GIS course, designed to illustrate how different classification schemes modify the resulting map. But, again, only a tiny fraction of map readers have ever undertaken such an activity. Even if they take the time to systematically compare colors on the map to categories on the legend, they are more likely to remember their general first impression of where the light and dark colors are, ignoring the breakpoints between classification bins.

There is much to question about what maps represent, but most map readers are not compelled, inspired or able to do so. This is particularly problematic when a map is being used rapidly as an input source for consequential decisions.

Maps are undeniably an influential media for visual communication. Interestingly, the term “visual” is applied in a somewhat misleading way in education and communication. When someone says, “I’m a visual learner,” they are often referring to their preferences for images and graphics over text. But in fact all people, apart from those with visual impairments, are visual learners. Our eyesight is by far our greatest source of information, significantly more than our senses of hearing, touch, smell and taste, combined. “A picture is worth a thousand words” can be interpreted as a preference for an image over words, but the notion of worth also has to do with how effectively and rapidly meaning can be extracted, such as absorbing the gist of a scene or image.

Map reading also involves discerning the spatial relationships among mapped features. The spatial notions of distance, proximity and overlay contribute to dozens of analytical tools in a GIS. Observing patterns that are uniform, clustered or random leads to insights for understanding processes. Here, appreciating map scale is essential, and this is where GIS both complicates and facilitates map reading, by readily allowing zooming in and out, beyond or below optimal map scale levels. Spatial thinking is also required to envision dynamic movement or change, and animation can aid or hinder in explaining such processes. Communicating temporal variability presents a whole other suite of digital decision choices — something that will be discussed more in another article in this series.

So communicating through maps is both a highly visual and spatial experience, and a geospatial one as well. GIS-based mapping enables the visualization of geographic relationships that literally cannot be seen otherwise, such as in hazard risk model results, or point-source effluence and concentrations of ground water pollution, or viewsheds that would have been perceived by historical military leaders. Maps are generalized abstractions of reality, but they are still uniquely capable of serving as an effective proxy for direct experiences in distant or inaccessible portions of the world.

Maps simultaneously contribute visual, spatial, and geospatial knowledge to inform their viewers. A well-designed map can be an auditory sweet spot among sound speakers, or the sensory umami of geographic communication. Their synergistic effect is a powerful one that contributes much to the value of our geographic technology field.

Communicating through Maps: Exploring the complexities and challenges of GIS mapping

The newest data portal from the Census Bureau includes new search tools and more.Website

If you have a suggestion for a data resource you'd like us to add or you've noticed an error, please email us at editors@directionsmag.com.

US Census Bureau

Award winning Esri business partner, GEO Jobe, relocates Center for Research and Engineering to new location in Gulfport, MS.

GULFPORT, Miss. - Oct. 25, 2017 -  GEO Jobe is pleased to announce a new location for our Mississippi-based office and Center for Research and Engineering. As of October, 2017 the office has moved from Biloxi to a new location in Gulfport, MS. Recall, it was in 2015 when GEO Jobe announced the opening of our new Center for Research and Engineering office in Biloxi, MS. This location enables GEO Jobe GIS to better serve clientele along the gulf coast and serve as our primary research & development location for GIS application innovation.

The Gulfport location is a full-service office with a multi-disciplined and talented GIS staff headed by David Hansen, Vice President of GEO Jobe and Director of the Center for Research and Engineering. Hansen has recently grown his team with the addition of several key, new staff members including junior and senior software engineers and, most recently, the addition of an enterprise project manager.

The office is responsible for designing and implementing custom ArcGIS-based solutions as well as  supporting enterprise scale clients. The team is also responsible for the development and support of several popular apps you've grown to love such as Mapfolio and the 2015 Most Innovative ArcGIS Marketplace Award winner, Admin Tools for ArcGIS Online which is used by over 4,000 organizations globally. Both applications can be found on the ArcGIS Marketplace. GEO Jobe GIS is a long time business partner of Esri as well as an early adopter of the ArcGIS Online platform.

"GEO Jobe's Center for Research and Engineering  has served the geospatial community for years creating such solutions as Mapfolio and Admin Tools for ArcGIS Online. It gives me great pleasure to announce that GEO Jobe's Center for Research and Engineering is relocating to a larger space in Gulfport, Mississippi. The increased space will allow us to continue to expand staff and capabilities to innovate and create world class solutions." - David Hansen Vice President of GEO Jobe.

GEO Jobe Center for Research and Engineering

Founded in 1999, GEO Jobe (@geojobegis)  is a geospatial industry leader that currently has the top three most popular apps in the ArcGIS Marketplace including Admin Tools for ArcGIS Online, Mapfolio, and the. While many geospatial firms focus on a specific industry, GEO Jobe has a focus on industry independent solutions and offerings such as providing software development and data hosting expertise and services. GEO Jobe was an early adopter of the ArcGIS Online platform and always strives to extend and push the limits of what is possible using the platform. GEO Jobe has been an Esri business partner for 16 years and has received multiple awards from Esri including the 2015 Innovative Marketplace Provider and the 2013 Organization Use of ArcGIS Online award.

A New Office for GEO Jobe GIS Center for Research and Engineering in Gulfport, Mississippi

The GIS Certification Institute (GISCI) is pleased to announce Es² as the newest GISCI-designated Endorsing Employer. Established in 1996, Es² is Louisiana small business focused on leading-edge geospatial services in GIS, Unmanned Aerial Systems, surveying, and mapping. As an Esri Gold Partner Es² provides GIS professional services to local, state, and federal government agencies, maritime ports, non-profit organizations, universities, and industry clients.
As a licensed engineering and surveying firm, Es² understands the value of professional registrations and certifications. The GISP certification provides employers with the confidence that GIS personnel are not only technically qualified but also of high moral standards. An employee with a GISP is elevated above a similarly qualified non-GISP.
The GISCI appreciates Es²’s support of their employees and the GISP program.
 
The GIS Certification Institute created the GISCI Endorsing Employer Designation Program to help increase the value of GISP® Certification for our primary stakeholders and help facilitate the growth of the GISP Program within the geospatial community. The GISCI will grant the GISCI Endorsing Employer Designation to organizations that meet the criteria established by the GISCI as supportive of GIS Professionals and the GISP Certification process by way of internal activities, programs, and policies. The designation is not only a commitment to GISP Certification for staff, but also to uphold the ideals of the GIS Certification Institute.
The GISCI Endorsing Employer Designation is available to all organizations (public, private/commercial) apart from GISCI member organizations. Organizations seeking the designation must submit a formal application listing the criteria met as verified by the organization’s HR representative. A review committee will evaluate each application and if the organization meets the criteria, the committee will forward the application to the GISCI Board of Directors for approval. Each approved GISCI Endorsing Employer will last for three (3) years, provide the organization with permission to display their organization logo on our website, and provide permission to display the GISCI Endorsing Employer designation on their website. There is no cost to obtain this designation. A list of GISCI Endorsing Organizations can be found on the GISCI website at:

The GIS Certification Institute (GISCI) is a non-profit organization that promotes the advancement of proficient GIS professionals through its international GISP® (Certified GIS Professional) certification program. The Institute fosters rigorous professional and ethical standards, community engagement, and professional mentoring within the GIS industry. GISCI’s member organizations include the American Association of Geographers (AAG), National States Geographic Information Council (NSGIC), University Consortium for Geographic Information Science (UCGIS), and the Urban and Regional Information Systems Association (URISA).

More information about the GISCI is available at www.gisci.org and about Es² at

GISCI Announces Es² as its Newest Endorsing Employer

The U.S. Geological Survey's Larry Moore provides an update on the US Topo effort, the Survey’s general purpose, digital, quadrangle map series. He outlines the successes thus far and the obstacles still ahead in 2013.

century, the foundation of the U.S. Geological Survey’s (USGS) national map series was 7.5-minute topographic maps. This map series was declared complete in 1992. In the 1990s and early 2000s, the USGS mapping program focused its attention on digital data for GIS. In November, 2008, the USGS began defining a new general purpose, digital, quadrangle map series. In 2009, this new series was named “US Topo.” While the older maps were handcrafted products created from primary data sources, US Topo maps are mass-produced from secondary data sources, mostly the GIS databases of The National Map. Because of this difference, the new maps have lower unit cost, better map currency, and better overall coverage, but have less content and do not completely replicate the visual appearance of a hand-drawn map.

The early phases of the US Topo program are discussed in a May, 2011 paper []. In September, 2012, the first three-year production cycle was completed and nearly full coverage of the conterminous United States with a new national map series was achieved.

The primary strategic goal of the US Topo program is to refresh the national map series for all U.S. states and territories on a regular three-year cycle. For the conterminous 48 states alone, this requires publishing 18,000 maps per year or 72 maps every work day. This production goal has been met for three consecutive years, and between late 2009 and late 2012, the conterminous 48 states were completely covered with new topographic maps.

Maps created in early 2009 were simple image maps without contours or hydrography. These were named “Digital Map – Beta” and are now regarded as experimental and temporary. These maps were removed from public view as they were replaced with contour maps in 2012. In future three year cycles, the older maps will be retained as historical data and will continue to be available for download. The second three year cycle of US Topo production began in October, 2012.

Figure 1 shows map production rates and illustrates the progress on the basic problem of mass production. Each year the production system has become more stable, and in 2012, a steady state was reached with production almost exactly matching targets.

US Topo map production, June, 2009–September, 2012. The primary strategic goal of the program is to refresh the national map series for the United States on a regular three-year cycle. This pace of map production was achieved for the first three-year cycle, 2010–2012.

The second strategic goal of the program is continuous product improvement, which can be divided into two broad categories.

The old topographic maps were created from primary sources, including extensive field observation. It is currently not possible to duplicate the content of those maps from The National Map databases, but a goal of US Topo is to add more data layers each year as data are obtained from authoritative sources and integrated into The National Map. The major improvements and content milestones to date are:

June, 2009 – Production of basic image maps started.

October, 2009 – Contour and hydrography layers added.

May, 2010 – Road data source changed from Census Bureau to commercially licensed data from TeleAtlas/TomTom.

October, 2010 – Production of maps over National Forests started, with National Forest boundaries and roads provided by the U.S. Forest Service.

April, 2011 – State and county boundaries added.

October, 2011 – Timber coverage layer added.

May, 2012 – Railroads added for selected track provided by the Federal Railroad Administration.

May, 2012 – Public Land Survey System data added for selected western states; data provided by the Bureau of Land Management.

Additional content planned for 2013 includes a shaded relief layer, National Parks and other selected federal land boundaries, and recreational trails in National Forests. In all cases, new content depends on receiving data from authoritative sources. For non-natural map features, the USGS no longer gathers data by direct field observation or from primary sources.

Continuous content improvement does have some minor drawbacks for map users. Adding a new feature class improves the quality of maps containing that feature, but temporarily reduces the consistency of the series as a whole. To minimize this problem, the USGS typically adds new content for an entire state at one time. To further help with symbol clarity, an attachment containing cartographic symbols used on US Topo maps will be included in the US Topo GeoPDF starting in the spring of 2013. The three to five year goal is to have a legend on each US Topo showing the feature set at the time the map was made.

Traditional maps are part scientific documents and part works of art, and computers cannot yet create the graceful appearance of a traditional hand-drawn map from normal GIS data. Challenges include text placement, integration of different feature classes, and positioning crowded features while maintaining clarity. US Topo maps’ visual appearance is superior to a typical GIS display, but still falls short of traditional USGS topographic map presentation standards.

Nevertheless, the first US Topo production cycle included many improvements to automated map layout. The production software can now automatically avoid most overprints of both text and features. Label density, especially for road and street names, has steadily improved. Contours and water bodies are more tightly integrated than in 2010. The overall appearance and readability of the maps has improved even as more content has been added and unit production cost has decreased.

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The images compare the linework content of a 2009 “Digital Map – Beta” (left) with the 2012 US Topo of the same area (right). The orthophoto layer is turned off in both images. Although US Topo still does not have all the feature classes of traditional USGS topographic maps, much progress has been made since the program started. More feature classes will be added in 2013. US Topo maps also have content the old topographic maps did not, such as the orthoimage layer.

Placement of name labels for physiographic features is still a significant issue. This is not primarily a software problem, but a more basic data problem. Most GIS data consists of spatial objects (points, lines, and polygons). Proper names are attached to these objects as attributes, and software can use the geometry of the spatial object to infer how text labels should be placed. However, for almost all nonwater natural features in the United States (such as canyons, mountains, plateaus, and mesas), no spatial database has ever been constructed. The official database of natural feature names, the Geographic Names Information System (GNIS), began in the 1970s as a digital repository for the records of the Board on Geographic Names (BGN). Defining boundaries for canyons and mountains was problematic, and at the time was of questionable value, and was therefore not attempted. The USGS has begun work on a national database of spatial objects for natural features, but this is an expensive, multi-year effort. The current lack of such a database is one obstacle to increasing the visual quality of mass-produced maps in a national map series.

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Text placement for some natural features is still a problem. Water feature names are associated with GIS geometry in the National Hydrography Dataset, so the label “Trout Cr” follows the stream as on a traditional map. Because “Sulphur Mountain” is a small feature, the name is associated with a single point (the hill summit), so this label is also placed correctly. However, “Hayden Valley” and “Crater Hills” are large areal features, and their labels cannot be placed properly by software because the names are associated with single points, not areas, in the Geographic Names Information System.

US Topo and Geographic Information Systems

US Topo was designed for map users who are not GIS specialists. The product’s primary purpose is to present GIS data as traditional maps that can be used on normal office computers without specialized software or expertise. The program creates no new data, but only repackages existing data. Almost all the data that goes into a US Topo are available in GIS formats free of charge from The National Map databases (roads, which are commercially licensed data, are the major exception).

Nevertheless, traditional symbolized and annotated maps have value even for advanced GIS users, and there is demand to have a GIS-loadable version of US Topo maps. This was not anticipated when the product was designed, and it is not a simple problem. One solution would be for GIS vendors to implement geospatial PDF import; this is technically difficult, and at this writing very little software of this kind is available. Another solution would be for the USGS to create companion products that mirror US Topo content and presentation, but are in GIS-friendly formats. The USGS is working on such products, and will probably begin serving some layers in 2014. These products will be in Esri geodatabase format with an associated template to define symbolization.

These new products may also provide better support for mobile applications.

US Topo maps are distributed through an http download service. The USGS maintains two interfaces to this service, the “Map Locator and Downloader” application at , and The National Map Viewer at .

Demand for US Topo maps has increased with supply, and in 2012, demand increased sharply as full coverage of the 48 states was approached.

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. The rate of map download has increased rapidly as coverage has improved, and in mid-2012 was near 4,000 maps per day, a large number for a USGS data product. A total of about 1.8 million maps were downloaded from USGS web sites between July, 2009 and October, 2012.

Demand for bulk distribution (deliveries of thousands of products at one time) has also grown. An efficient and standard mechanism for bulk distribution remains to be developed, though the USGS recognizes the need and is considering several possibilities. For now, bulk deliveries are accomplished by either loading files on customer-provided portable hard drives, or by sending customers a customized batch file that automates multiple downloads. The USGS is also hopeful that private companies will rehost US Topo maps and provide a wider range of delivery options.

For some applications—including outdoor recreation, wildfire management and suppression, and some kinds of emergency response—paper maps are still important. The US Topo maps present new challenges for creating and distributing paper maps.

The layered PDF format makes it easy to print the maps to scale, and to print any desired combination of layers. However, printing a full map sheet requires a large-format plotter, equipment not normally owned by individuals or small offices. High-quality or weather-resistant plots require more specialized and expensive equipment. The USGS is pursuing a printing contract that will allow the USGS to continue to sell paper maps. In the long run we are hopeful that printing can be partially or completely privatized.

Another aspect of the printing problem is that US Topo maps contain too many data layers to print together. Printing the contours over the orthoimage, for example, often makes both layers almost unreadable. This problem will get worse as more data layers are added. This may mean that the standard paper topographic map is truly a thing of the past, and the future belongs to customized, print-on-demand products.

US Topo in Alaska, Hawaii and U.S. Territories

The first years of the US Topo program concentrated on covering the conterminous 48 states, but in the next few years the program will address other areas:

Hawaii is scheduled for production in early 2013.

Planning for Alaska began in 2012 with inter-agency discussions and creation of a few prototype maps. Production of US Topo maps at 1:25,000 scale will start in 2013. The production schedule will be driven by the availability of new elevation and image data being collected by the Alaska Statewide Digital Mapping Initiative. About 12,000 maps are needed to cover Alaska. Full state coverage is expected by about 2017.

New elevation and image data over Puerto Rico and the Virgin Islands are being collected by the Army Corps of Engineers. When these new datasets are available, hopefully in 2013, US Topo maps at 1:20,000 scale will be created for these areas.

The Pacific Territories are also traditionally within the USGS mapping domain. The US Topo program intends to produce maps over these areas, but no schedules have yet been set.

The Historical Topographic Map Collection

A separate USGS project, the Historical Topographic Map Collection (HTMC), is scanning the entire USGS topographic map library. This collection consists of about 200,000 map sheets dating back to 1884. The initial production phase of this project is nearly complete, and high-resolution scans in GeoPDF format have been published and are available to the public for free download.

As the second threeyear production cycle for US Topo begins in late 2012, earlier US Topo maps will remain available and will become part of the historic collection, creating a single, freely available library of USGS topographic maps covering more than 130 past years and extending into the future.

The primary goal of the US Topo program, defined in November, 2008, is to refresh the topographic map series for the entire country on a three-year cycle. In the first cycle (2010–2012), the necessary production pace was achieved and sustained for the conterminous 48 states. This accomplishment lays the foundation for improving the product and expanding the program in the years ahead.

The emphasis on a rapid map-production cycle is unprecedented in USGS mapping programs, and perhaps in any national mapping program. In all older USGS topographic programs, a primary goal was to make every map error-free. This goal, plus the fact that traditional maps were compiled and finished by hand, necessarily meant that any particular area would be mapped infrequently. The US Topo program changes this traditional philosophy, and asserts that the map series as a whole is better served by automated production, on a short refresh cycle, using the best available authoritative data sources.

The program achieved its goals for the first production cycle, and is now expanding in several directions, including adding more content and improving the readability of the base product, defining hardcopy products, defining and producing GIS-friendly products, and covering U.S. areas of interest outside the conterminous 48 states.

The National Map home page has more information.

US Topo maps are derived from The National Map GIS data. These source data can be downloaded through several different interfaces, including The National Map viewer.

See also the US Topo home page or the Historical Topographic Map Collection (HTMC).

US Topo and HTMC maps are published in PDF format, and can be downloaded free of charge through either The National Map viewer, or the “Map Locator and Downloader” application at the USGS Map Store.

Contours on US Topo maps are derived from the National Elevation Dataset

The Alaska Statewide Digital Mapping Initiative

“Pacific Territories” refers to Pacific lands within the scope of the Department of Interior Office of Insular Affairs

Questions about US Topo maps, including requests for more information about bulk delivery, can be emailed to

.(JavaScript must be enabled to view this email address)

US Topo - A New National Map Series, 2012 Update

A detailed 3D computer model from Bluesky is being used to communicate a £250 million transformation of the town centre of Huddersfield, UK. Created from the most up to date, nationwide coverage of aerial photography, the Bluesky model forms part of AECOM’s visualisation of plans prepared for Kirklees Council. Including a 3D fly through and realistic animations the AECOM presentation will form part of an online platform used to consult and engage with the community over the forthcoming months.

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