Beyond Mapping
III
|
Map
Analysis book with companion CD-ROM for hands-on exercises and further reading |
Early
GIS Technology and Its Expression — traces the
early phases of GIS technology (Computer Mapping, Spatial Database Management
and Map Analysis/Modeling)
Contemporary
GIS and Future Directions — discusses
contemporary GIS and probable future directions (Multimedia Mapping and Spatial
Reasoning/Dialog)
Pathways to
GIS — explores different paths of GIS adoption for five disciplines
(Natural Resources, Facilities Management, Public Health, Business and
Precision Agriculture)
A
Multifaceted GIS Community — investigates the technical shifts and
cultural impacts of the rapidly expanding GIS tent of users, application
developers and tool programmers
Innovation
Drives GIS Evolution — discusses the cyclic nature of GIS
innovation (Mapping, Structure and Analysis)
Author’s Notes: The figures in this topic use MapCalcTM software. An educational CD with online text, exercises
and databases for “hands-on” experience in these and other grid-based analysis
procedures is available for US$21.95 plus shipping and handling (www.farmgis.com/products/software/mapcalc/
).
<Click here> right-click to
download a printer-friendly version of this topic (.pdf).
(Back to the Table of Contents)
______________________________
Early GIS Technology and Its
Expression
(GeoWorld October, 2006)
Considerable changes
in both expectations and capabilities have taken place since GIS’s birth in the
late 1960s. In this and a few subsequent
columns, I hope to share a brief history and a probable future of this rapidly
maturing field as viewed from grey-beard experience from over 30 years
involvement in the field (see Author’s Note).
Overview
Information has always been the cornerstone of effective decisions. Spatial information is particularly complex
as it requires two descriptors—Where is What. For thousands of years the link between the
two descriptors has been the traditional, manually drafted map involving pens,
rub-on shading, rulers, planimeters, dot grids, and acetate sheets. Its historical use was for navigation through
unfamiliar terrain and seas, emphasizing the accurate location of physical
features.
More recently, analysis of mapped data has become an important part of
understanding and managing geographic space.
This new perspective marks a turning point in the use of maps from one emphasizing
physical description of geographic space, to one of interpreting mapped data,
combining map layers and finally, to spatially characterizing and communicating
complex spatial relationships. This
movement from “where is what” (descriptive) to "so what and why"
(prescriptive) has set the stage for entirely new geospatial concepts and
tools.
Since the
1960's, the decision-making process has become increasingly quantitative, and
mathematical models have become commonplace.
Prior to the computerized map, most spatial analyses were severely
limited by their manual processing procedures.
The computer has provided the means for both efficient handling of
voluminous data and effective spatial analysis capabilities. From this perspective, all geographic
information systems are rooted in the digital nature of the computerized map.
The coining of the term Geographic Information Systems reinforces this movement
from maps as images to mapped data. In
fact, information is GIS's middle name.
Of course, there have been other, more descriptive definitions of the
acronym, such as "Gee It's Stupid," or "Guessing Is
Simpler," or my personal favorite, "Guaranteed Income Stream."
Computer Mapping (1970s, Beginning Years)
The early 1970's saw computer mapping automate map drafting. The points,
lines and areas defining geographic features on a map are represented as an
organized set of X, Y coordinates. These data drive pen plotters that can
rapidly redraw the connections at a variety of colors, scales, and projections
with the map image, itself, as the focus of the processing.
The pioneering
work during this period established many of the underlying concepts and
procedures of modern GIS technology. An obvious advantage with computer mapping
is the ability to change a portion of a map and quickly redraft the entire
area. Updates to resource maps which could take weeks, such as a forest fire
burn, can be done in a few hours. The less obvious advantage is the radical
change in the format of mapped data— from analog inked lines on paper, to
digital values stored on disk.
Spatial Database Management (1980s, Adolescent
Years)
During 1980's, the change in data format and computer environment was
exploited. Spatial database management systems were developed that
linked computer mapping capabilities with traditional database management
capabilities. In these systems,
identification numbers are assigned to each geographic feature, such as a
timber harvest unit or ownership parcel.
For example, a user is able to point to any location on a map and
instantly retrieve information about that location. Alternatively, a user can specify a set of
conditions, such as a specific forest and soil combination, then direct the
results of the geographic search to be displayed as a map.
Early in the
development of GIS, two alternative data structures for encoding maps were
debated. The vector data model closely mimics the manual drafting process
by representing map features (discrete spatial objects) as a set of lines
which, in turn, are stores as a series of X,Y coordinates. An alternative structure, termed the raster data model, establishes an
imaginary grid over a project area, and then stores resource information for
each cell in the grid (continuous map surface).
The early debate attempted to determine the universally best
structure. The relative advantages and
disadvantages of both were viewed in a competitive manner that failed to
recognize the overall strengths of a GIS approach encompassing both formats.
By the
mid-1980's, the general consensus within the GIS community was that the nature
of the data and the processing desired determines the appropriate data
structure. This realization of the
duality of mapped data structure had significant impact on geographic
information systems. From one
perspective, maps form sharp boundaries that are best represented as
lines. Property ownership, timber sale
boundaries, and road networks are examples where lines are real and the data
are certain. Other maps, such as soils,
site index, and slope are interpretations of terrain conditions. The placement of lines identifying these
conditions is subject to judgment and broad classification of continuous
spatial distributions. From this
perspective, a sharp boundary implied by a line is artificial and the data
itself is based on probability.
Increasing
demands for mapped data focused attention on data availability, accuracy and
standards, as well as data structure issues.
Hardware vendors continued to improve digitizing equipment, with manual
digitizing tablets giving way to automated scanners at many GIS
facilities. A new industry for map
encoding and database design emerged, as well as a marketplace for the sales of
digital map products. Regional, national
and international organizations began addressing the necessary standards for
digital maps to insure compatibility among systems. This era saw GIS database development move
from project costing to equity investment justification in the development of
corporate databases.
Map Analysis and Modeling (1990s, Maturing
Years)
As GIS continued its evolution, the emphasis turned from descriptive query to
prescriptive analysis of maps. If early
GIS users had to repeatedly overlay several maps on a light-table, an analogous
procedure was developed within the GIS.
Similarly, if repeated distance and bearing calculations were needed,
the GIS system was programmed with a mathematical solution. The result of this effort was GIS
functionality that mimicked the manual procedures in a user's daily activities. The value of these systems was the savings
gained by automating tedious and repetitive operations.
By the
mid-1980's, the bulk of descriptive query operations were available in most GIS
systems and attention turned to a comprehensive theory of map analysis. The dominant feature of this theory is that
spatial information is represented numerically, rather than in analog fashion
as inked lines on a map. These digital
maps are frequently conceptualized as a set of "floating maps" with a
common registration, allowing the computer to "look" down and across
the stack of digital maps. The spatial
relationships of the data can be summarized (database queries) or
mathematically manipulated (analytic processing). Because of the analog nature of traditional
map sheets, manual analytic techniques are limited in their quantitative
processing. Digital representation, on
the other hand, makes a wealth of quantitative (as well as qualitative)
processing possible. The application of
this new theory to mapping was revolutionary and its application takes two
forms—spatial statistics and spatial analysis.
Meteorologists
and geophysicists have used spatial
statistics for decades to characterize the geographic distribution,
or pattern, of mapped data. The
statistics describe the spatial variation in the data, rather than assuming a
typical response is everywhere. For
example, field measurements of snow depth can be made at several plots within a
watershed. Traditionally, these data are
analyzed for a single value (the average depth) to characterize an entire
watershed. Spatial statistics, on the
other hand, uses both the location and the measurements at sample locations to
generate a map of relative snow depth throughout the watershed. This numeric-based processing is a direct
extension of traditional non-spatial statistics.
Spatial analysis applications, on the other hand, involve context-based processing. For example, forester’s can characterize timber
supply by considering the relative skidding and log-hauling accessibility of
harvesting parcels. Wildlife managers can consider such factors as proximity to
roads and relative housing density to map human activity and incorporate this
information into habitat delineation. Land planners can assess the visual
exposure of alternative sites for a facility to sensitive viewing locations,
such as roads and scenic overlooks.
Spatial
mathematics has evolved similar to spatial statistics by extending conventional
concepts. This "map algebra"
uses sequential processing of spatial operators to perform complex map
analyses. It is similar to traditional
algebra in which primitive operations (e.g., add, subtract, exponentiate) are
logically sequenced on variables to form equations. However in map algebra, entire maps composed
of thousands or millions of numbers represent the variables of the spatial
equation.
Most of the
traditional mathematical capabilities, plus an extensive set of advanced map
processing operations, are available in modern GIS packages. You can add, subtract, multiply, divide,
exponentiate, root, log, cosine, differentiate and even integrate maps. After all, maps in a GIS are just organized
sets of numbers. However, with
map-ematics, the spatial coincidence and juxtaposition of values among and
within maps create new operations, such as effective distance, optimal path
routing, visual exposure density and landscape diversity, shape and pattern.
These new tools and modeling approach to spatial information combine to extend
record-keeping systems and decision-making models into effective decision
support systems.
In many ways,
GIS is “as different as it is similar” to traditional mapping. Its early expressions simply automated
existing capabilities but in its modern form it challenges the very nature and
utility of maps. The next section
focuses on contemporary GIS expressions (2010s) and its probable future
directions.
Contemporary GIS and Future
Directions
(GeoWorld November, 2006)
The previous
section focused on early GIS technology and its expressions as three
evolutionary phases— Computer Mapping (70s), Spatial Database Management (80s)
and Map Analysis/Modeling (90s). These efforts
established the underlying concepts, structures and tools supporting modern
geotechnology. What is radically
different today is the broad adoption of GIS and its new map forms.
In the early
years, GIS was considered the domain of a relatively few cloistered
techno-geeks “down the hall and to the right.”
Today, it is on everyone’s desk, PDA and even cell phone. In just three decades it has evolved from an
emerging science to a fabric of society that depends on its products from
getting driving directions to sharing interactive maps of the family
vacation.
Multimedia Mapping (2010s, Full Cycle)
In fact, the
U.S. Department of Labor has designated Geotechnology as one of the three
“mega-technologies” of the 21st century—right up there with Nanotechnology
and Biotechnology. This broad acceptance
and impact is in large part the result of the general wave of computer
pervasiveness in modern society. We
expect information to be just a click away and spatial information is no
exception.
However,
societal acceptance also is the result of the new map forms and processing
environments. Flagship GIS systems, once
heralded as “toolboxes,” are giving way to web services and tailored
application solutions. There is growing
number of websites with extensive sets of map layers that enable users to mix
and match their own custom views. Data
exchange and interoperability standards are taking hold to extend this
flexibility to multiple nodes on the web, with some data from here, analytic
tools from there and display capabilities from over there. The results are high-level applications that
speak in a user’s idiom (not GIS-speak) and hide the complexity of data
manipulation and obscure command sequences.
In this new environment, the user focuses on the spatial logic of a
solution and is hardly aware that GIS even is involved.
Another
characteristic of the new processing environment is the full integration the
global positioning system and remote sensing imagery with GIS. GPS and the digital map bring geographic
positioning to the palm of your hand.
Toggling on and off an aerial photograph provides reality as a backdrop
to GIS summarized and modeled information.
Add ancillary systems, such as robotics, to the mix and new automated
procedures for data collection and on-the-fly applications arise.
In addition to
the changes in the processing environment, contemporary maps have radical new
forms of display beyond the historical 2D planimetric paper map. Today, one expects to be able to drape spatial
information on a 3D view of the terrain.
Virtual reality can transform the information from pastel polygons to
rendered objects of trees, lakes and buildings for near photographic realism. Embedded hyperlinks access actual photos,
video, audio, text and data associated with map locations. Immersive imaging enables the user to
interactively pan and zoom in all directions within a display.
4D GIS (XYZ and
time) is the next major frontier.
Currently, time is handled as a series of stored map layers that can be
animated to view changes on the landscape.
Add predictive modeling to the mix and proposed management actions
(e.g., timber harvesting and subsequent vegetation growth) can be introduced to
look into the future. Tomorrow’s data
structures will accommodate time as a stored dimension and completely change
the conventional mapping paradigm.
Spatial Reasoning and Dialog (Future,
Communicating Perceptions)
The future also
will build on the cognitive basis, as well as the databases, of GIS technology. Information systems are at a threshold that
is pushing well beyond mapping, management, modeling, and multimedia to spatial
reasoning and dialogue. In the past,
analytical models have focused on management options that are technically
optimal— the scientific solution. Yet in
reality, there is another set of perspectives that must be considered— the
social solution. It is this final sieve
of management alternatives that most often confounds geographic-based
decisions. It uses elusive measures, such
as human values, attitudes, beliefs, judgment, trust and understanding. These are not the usual quantitative measures
amenable to computer algorithms and traditional decision-making models.
The step from technically feasible to socially acceptable options is not so
much increased scientific and econometric modeling, as it is
communication. Basic to effective
communication is involvement of interested parties throughout the decision
process. This new participatory
environment has two main elements— consensus building and conflict resolution.
Consensus Building involves
technically-driven communication and occurs during the alternative formulation
phase. It involves a specialist's
translation of various considerations raised by a decision team into a spatial
model. Once completed, the model is
executed under a wide variety of conditions and the differences in outcome are
noted.
From this perspective, an individual map is not the objective. It is how maps change as the different
scenarios are tried that becomes information.
"What if avoidance of visual exposure is more important than
avoidance of steep slopes in siting a new electric transmission line? Where does the proposed route change, if at
all?" What if slope is more
important? Answers to these analytical
queries (scenarios) focus attention on the effects of differing
perspectives. Often, seemingly divergent
philosophical views result in only slightly different map views. This realization, coupled with active
involvement in the decision process, can lead to group consensus.
However, if consensus is not obtained, mechanisms for resolving conflict come
into play. Conflict Resolution extends the Buffalo Springfield’s lyrics,
"nobody is right, if everybody is wrong," by seeking an acceptable management
action through the melding of different perspectives. The socially-driven communication occurs
during the decision formulation phase.
It involves the
creation of a "conflicts map" which compares the outcomes from two or
more competing uses. Each map location
is assigned a numeric code describing the actual conflict of various
perspectives. For example, a parcel
might be identified as ideal for a wildlife preserve, a campground and a timber
harvest. As these alternatives are
mutually exclusive, a single use must be assigned. The assignment, however, involves a holistic
perspective which simultaneously considers the assignments of all other
locations in a project area.
Traditional scientific approaches rarely are effective in addressing the holistic
problem of conflict resolution. Even if
a scientific solution is reached, it often is viewed with suspicion by less
technically-versed decision-makers.
Modern resource information systems provide an alternative approach
involving human rationalization and tradeoffs.
This process
involves statements like, "If you let me harvest this parcel, I will let
you set aside that one as a wildlife preserve." The statement is followed by a persuasive
argument and group discussion. The
dialogue is far from a mathematical optimization, but often comes closer to an
acceptable decision. It uses the
information system to focus discussion away from broad philosophical positions,
to a specific project area and its unique distribution of conditions and
potential uses.
Critical Issues (Future Challenges)
The technical hurdles surrounding GIS have been aggressively tackled over the
past four decades. Comprehensive spatial
databases are taking form, GIS applications are accelerating and even office
automation packages are including a "mapping button." So what is the most pressing issue
confronting GIS in the next millennium?
Calvin, of the
Calvin and Hobbes comic strip, puts it in perspective: "Why waste time
learning, when ignorance is instantaneous?" Why should time be wasted in GIS training and
education? It's just a tool, isn't
it? The users can figure it out for
themselves. They quickly grasped the
operational concepts of the toaster and indoor plumbing. We have been mapping for thousands of years
and it is second nature. GIS technology
just automated the process and made it easier.
Admittedly, this is a bit of an overstatement, but it does set the stage for
GIS's largest hurdle— educating the masses of potential users on what GIS is
(and isn't) and developing spatial reasoning skills. In many respects, GIS technology is not
mapping as usual. The rights, privileges
and responsibilities of interacting with mapped variables are much more
demanding than interactions with traditional maps and spatial records.
At least as
much attention (and ultimately, direct investment) should go into geospatial
application development and training as is given to hardware, software and
database development. Like the automobile
and indoor plumbing, GIS won't be an important technology until it becomes
second nature for both accessing mapped data and translating it into
information for decisions. Much more
attention needs to be focused beyond mapping to that of spatial reasoning, the
"softer," less traditional side of geotechnology.
GIS’s
development has been more evolutionary, than revolutionary. It responds to contemporary needs as much as
it responds to technical breakthroughs.
Planning and management have always required information as the
cornerstone. Early information systems
relied on physical storage of data and manual processing. With the advent of the computer, most of
these data and procedures have been automated.
As a result, the focus of GIS has expanded from descriptive inventories
to entirely new applications involving prescriptive analysis. In this transition, map analysis has become
more quantitative. This wealth of new processing
capabilities provides an opportunity to address complex spatial issues in
entirely new ways.
It is clear that GIS technology has greatly changed our perspective of a
map. It has moved mapping from a
historical role of provider of input, to an active and vital ingredient in the
"thruput" process of decision-making.
Today's professional is challenged to understand this new environment
and formulate innovative applications that meet the complexity and accelerating
needs of the twenty-first century.
(GeoWorld December, 2006)
When did you get involved with GIS technology? How did you get involved? What was your background? What were your application objectives? Answers to these questions define your personal Geotechnology Adoption Path and are unique as you are.
Reflection on generalized adoption pathways for different disciplines can shed light on why a one-sized, all-purpose GIS paradigm is so illusive. Figure 1 is an attempt at describing alternate pathways for several disciplines in which I have experience (and considerable scar tissue) since the mid-1970s.
Figure1. Adoption pathways vary in mapping
legacies, early applications and initial ownership groups to form differing
geotechnology paradigms.
The ordering of the list is neither arbitrary nor chronological. It reflects the similarities among mapping legacies, early applications and initial ownership groups that characterize various pathways to GIS. It is interesting to note that while Natural Resources and Agriculture share common sociological, cultural, political and biological footings, their geotechnology adoption paths are radically different, and in fact, form polar extremes.
The Natural Resources community was one of the earliest groups to follow the geographers’ rallying cry in the mid-1970s; enticed by the prospect of automating the mapping process. Their extensive paper-map legacy involved tedious aerial photo interpretation and manual cartography to graphically depict resource inventories over very large areas. The early GIS environment was a natural niche for their well-defined mapping processes and products.
Agriculture, on the other hand had little use for traditional maps, as soil maps are far too generalized and broadly report soil properties instead of nutrient concentrations and other field inputs that farmers manage. Their primary uses for traditional maps were in Boy Scouts or hunting/fishing in mountainous terrain far away from the family farm. This perspective changed in the mid-1990s with the advent of yield mapping that tracks where things are going well and not so good for a crop— a field-level glimpse of the geographic distribution of productivity leading to entirely new site-specific crop management practices.
The alternative perspectives of maps as Images of inventory or as Information for decision-making are the dominant determinants of geotechnology adoption paths. GIS entry was early and committed for those with considerable paper-map legacy and well-defined, easily extended applications. While immensely valuable, automation of traditional applications focus on efficiency, flexibility and cost savings and rarely challenge “how things are done,” or move beyond mapping and basic spatial database management.
Disciplines with minimal paper-map legacies, on the other hand, tend to develop entirely new and innovative applications—the adoption tends to be less evolutionary and more revolutionary. For example, precision agriculture is an application that while barely a decade old, is radically changing crop management practices, as well as guidance and control of farm machinery by extending the traditional spatial triad of RS, GIS and GPS to Intelligent Devices and Implements (IDI) for on-the-fly applications.
The character and constituency of the initial ownership group in a discipline also determines the adoption pathway. For example in the U.S. Forest Service and most Natural Resource entities, the nudge toward GIS was primarily controlled by inventory units at regional and higher bureaucracy levels. The early emphasis of this group was on compiling very large and complex spatial databases over a couple of decades before extensive application of these data—sort of “build it and they (applications) will come.”
Contrast this with the Agriculture ownership group comprised of independent crop consultants and individual farmers focusing on a farm landscape of a few hundred acres per field. The database compilation demands are comparatively minor, and more importantly the return on investment stream must be immediate, not decades. Since they didn’t have a mapping legacy, efficiency and cost saving of data collection/management weren’t the drivers; rather crop productivity and stewardship advancements guided the adoption pathway.
Now turn your attention to the relative positions of the three disciplines in the center of the table. Business’ heritage closely follows that of Agriculture— negligible mapping legacy with radically innovative applications involving a relatively diverse, unstructured and independent user community. Mapping in the traditional sense of “precise placement of physical features” is the farthest thing from the mind of a sales/marketing executive. But a cognitive map that segments a city into different consumer groups, or characterizes travel-time advantages of different stores, or forms a sales prediction surface by product type for a city are fodder for decisions that fully consider spatial information and patterns. From the start, geo-business focused on new ways of doing business and return on investment, not traditional mapping extensions.
Contrast this paradigm with that of a Facilities Management engineer responsible for a transportation district, or an electric transmission network, or an oil pipeline—considerable mapping legacy that exploits basic mapping and spatial database capabilities to better inventory installed assets within a large, structured, utility-based industry. Like Natural Resources, the initial on-the-line mapping entry to GIS is broadening to more advanced applications, such as optimal path routing, off-the-line human/environmental impact analysis and integration of video mapping of assets and surrounding conditions.
Now consider Public Health’s pathway— minimal paper-map legacy primarily for graphic display of aggregated statistics within very large governmental agencies. Its adoption of geotechnology has lagged the other disciplines. This is particularly curious as it has a well-developed and well-funded research component similar to those in Natural Resources and Agriculture. While these units have been proactive in GIS adoption, the heritage of Public Health research is deeply rooted in traditional statistics and non-spatial modeling that has hindered acceptance of advanced spatial statistics and map analysis techniques. The combination of minimal paper-map legacy and minimal enthusiasm for new applications within large bureaucracies has delayed geotechnology adoption in Public Health—a revolution in waiting.
I have used the Geotechnology Adoption Pathways table in numerous workshops and college courses. Invariably, it incites considerable discussion as students ponder their own pathway and extrapolate personal experiences to those of other students and related disciplines. At a minimum, the lively discussion encourages students to think outside their disciplinary box and confirms the multifaceted GIS community that we’ll explore in the next section.
(GeoWorld January, 2007)
While mapping
has been around for thousands of years, its digital expression is only a few
decades old. My first encounter with a
digital map was as an undergrad research assistant in the 1960s with Bob
Colwell’s cutting-edge remote sensing program at UC Berkeley. A grad student had hooked up some
potentiometers to the mechanical drafting arm of a stereographic mapping
device.
The operator
would trace a dot at a constant elevation around the 3D terrain model of hills
and valleys created by a stereo pair of aerial photos. Normally, the mechanical movements of the dot
would drag a pen on a piece of paper to draw a contour line. But the research unit translated the movement
into X, Y coordinates that were fed into a keypunch machine—kawapa, kawapa,
kawapa. After a few months of tinkering,
the “digital contour lines” for the school forest were imprisoned in a couple
of boxes of punch cards.
The next phase of
simply connecting the dots proved the hardest.
Although UC Berkeley was a leading research university with over 42,000
students, there was only one plotter available.
And like the Egyptian period there were only a couple of folks on campus
who could write the programming hieroglyphics needed to control the beast. Heck, computer science itself was just a
fledgling discipline and GIS was barely a gleam in a few researchers’ eyes.
Figure 1.
The evolution of the Geotechnology Community has broadened its
membership in numbers, interests, backgrounds and depth of understanding.
The old-timer’s
story sets the stage for a discussion of the human-ware evolution in
geotechnology (see figure 1). In the
1970s the GIS community consisted of a few hundred research types chipping away
at the foundation. A shared focus of
just getting the technology to work emphasized appropriate data structures,
display capabilities and a few rudimentary operations. In fact, during this early period a
“universal truth” in data structure was sought that fueled a decade of academic
crusades between vector-heads and raster-heads.
My remote sensing background put me in the dwindling raster camp that
eventually circled the wagons around the pixel (picture element) and image
processing that effectively split GIS and RS for a decade.
The 1980s saw
steady growth in GIS and the community expanded from few hundred researchers to
a few thousand pacesetters focused on applying the infant technology. The community mix enlarged to include more
traditional programmers on the systems side and systems managers, data
providers and GIS specialists in a few of the mapping-oriented organizations on
the application side. Most of this
effort focused on vector processing of discrete spatial objects (point, line
and polygon features). While the
greatest effort was on developing databases, great strides in cartographic
modeling were made to mimic manual map analysis, such as intersection, overlay,
buffer and geo-query. At the same time,
advances in hardware and software began to bring GIS in reach of more and more
organizations; however GIS continued to be a specialized unit “down the hall
and to the right.”
Now compare the
community lines for the 1970s and 1980s in the figure. First note the extension to more professional
experiences—some defining entirely new fields, such as GIS specialist. In addition, the 1980s line flattens a bit to
indicate that the average “depth of expert spatial knowledge” within the
community declined from that of the laser-focused research types. Finally note that the “keel of knowledge”
shifted right toward the system managers and application focus.
These trends in
the GIS community mix accelerated in the 1990s.
On the system side professional programmers restructured, extended and
enhanced the old unstructured FORTRAN and BASIC code of the early innovators
into comprehensive flagship GIS systems with graphical interfaces. The GIS developers stopped coding their own
systems and used the toolkits to develop customized solutions for individual
industries and organizations. System
managers, data providers and GIS specialists provided the utility and
day-to-day attention demanded by the operational systems coming on line.
On the
application side, a maturing GPS industry was fully integrated and RS returned
to the geotechnology fold. As a result,
hundreds of thousands of general users of these systems with varying
backgrounds and application interests found GIS on their desktops and joined
the community mix. The shift toward
applications diminished the depth of knowledge and further shifted its keel to
the right. At one point this prompted me
to suggest that GIS was “a mile wide and an inch deep,” as many in the wave of
new comers to GIS did so through an enlarged job description and a couple of
training courses.
If that is the
case, then we are now ten miles wide and a quarter-inch deep. In retrospect and a bit of reflection on the
2000s community line suggests that is exactly where we should be. While there are large numbers of
deeply-keeled GIS experts, there are orders of magnitude more users of
geotechnology. The evolution from a
research-dominated to a user-dominated field confirms that geotechnology has
come of age. In part, this is a natural
condition of all computer-based disciplines brought on by ubiquitous personal
computers and Internet connections. The
dominant focus of this phase, from webmaster to the end user, is on accessing
spatial information. Couple this with
the current multimedia clamor and 3D visualization, such as Google Earth, a
whole new form of a map is becoming the norm.
So what is
under the flap of the ever enlarging tent of GIS? My guess is that it will become a fabric of
society with most public users not even knowing (or caring) that they are using
geotechnology. At the same time, a
growing number of general users will become more comfortable with the
technology and demand increased capabilities, particularly in spatial analysis,
statistics and modeling.
This will
translate into new demands on developers for schizophrenic systems that are
tiered for various levels of users. Most
users will be satisfied with simply accessing digital forms of traditional
maps, geo-query and driving directions, while other more knowledgeable users,
will access GIS models to run sophisticated map analyses and scenarios for
planning and decision-making.
Also I suspect
that the 2010s will see a whole new community line with two keels like a
catamaran—one on the right (GIS specialist, General Users and Public Users)
emphasizing applications involving millions and another on the left (General
Programmers, GIS Developers and System Managers) emphasizing systems involving
thousands. This dualistic community will
completely change the evolutionary character of the GIS community into a
radically different revolutionary group.
The biggest
challenge we face is educating future GIS professionals and users to “think
with maps” instead of just “mapping.”
The digital nature of modern maps has forever changed what a map is and
how it can be used. Map analysis
capabilities will serve as the catalyst that enables us to fully address
cognitive aspects of geographic space, as well as characterizing discrete
physical features.
Innovation Drives GIS
Evolution
(GeoWorld August, 2007)
What I find interesting is that current geospatial innovation is being
driven more and more by users. In the early
years of GIS one would dream up a new spatial widget, code it, and then attempt
to explain to others how and why they ought to use it. This sounds a bit like the proverbial “cart
in front of the horse” but such backward practical logic is often what moves
technology in entirely new directions.
“User-driven innovation,” on the other hand, is in part an oxymoron, as
innovation—“a creation, a new device or
process resulting from study and experimentation” (Dictionary.com)—is
usually thought of as canonic advancements leading technology and not
market-driven solutions following demand. At the moment, the over 500 billion dollar
advertising market with a rapidly growing share in digital media is dominating
attention and the competition for eyeballs is directing geospatial innovation
with a host of new display/visualization capabilities.
User-driven GIS innovation will become more and more schizophrenic with a
growing gap between the two clans of the GIS user community as shown in figure
1.
Figure 1. Widening gap in the GIS user community.
Another interesting point is that “radical” innovation often comes from
fields with minimal or no paper map legacy, such as agriculture and retail
sales, because these fields do not have pre-conceived mapping applications to
constrain spatial reasoning and innovation.
In the case of Precision
Agriculture, geospatial technology (GIS/RS/GPS) is coupled with robotics
for “on-the-fly” data collection and prescription application as tractors move
throughout a field. In Geo-business, when you swipe your credit
card an analytic process knows what you bought, where you bought it, where you
live and can combine this information with lifestyle and demographic data
through spatial data mining to derive maps of “propensity to buy” various
products throughout a market area. Keep
in mind that these map analysis applications were non-existent a dozen years
ago but now millions of acres and billions of transactions are part of the geospatial
“stone soup” mix.
As shown in figure 2 the evolution of GIS is more cyclical than
linear. My greybeard perspective of over
30 years in GIS suggests that we have been here before. In the 1970s the research and early
applications centered on Computer Mapping
(display focus) that yielded to Spatial
Data Management (data structure/management focus) in the next decade as we
linked digital maps to attribute databases for geo-query. The 1990s centered on GIS Modeling (analysis focus) that laid the groundwork for whole
new ways of assessing spatial patterns and relations, as well as entirely new
applications such as precision agriculture and geo-business.
Figure 2.
GIS Innovation/Development cycles.
Today, GIS is centered on Multimedia
Mapping (mapping focus) which brings us full circle to our beginnings. While advances in virtual reality and 3D
visualization can “knock-your-socks-off” they represent incremental progress in
visualizing maps that exploit dramatic computer hardware/software
advances. The truly geospatial
innovation awaits the next re-focusing on data/structure and analysis.
The bulk of the current state of geospatial analysis relies on “static coincidence modeling” using a
stack of geo-registered map layers. But
the frontier of GIS research is shifting focus to “dynamic flows modeling” that tracks movement over space and time in
three-dimensional geographic space. But
a wholesale revamping of data structure is needed to make this leap.
The impact of the next decade’s evolution will be huge and shake the very
core of GIS—the Cartesian coordinate system itself …a spatial referencing
concept introduced by mathematician Rene Descartes 400 years ago.
The current 2D square for geographic referencing is fine for “static
coincidence” analysis over relatively small land areas, but woefully lacking
for “dynamic 3D flows.” It is likely
that Descartes’ 2D squares will be replaced by hexagons (like the patches
forming a soccer ball) that better represent our curved earth’s surface …and
the 3D cubes replaced by nesting polyhedrals for a consistent and seamless
representation of three-dimensional geographic space. This change in referencing extends the current
six-sides of a cube for flow modeling to the twelve-sides (facets) of a
polyhedral—radically changing our algorithms as well as our historical
perspective of mapping (see April
2007 Beyond Mapping column for more discussion).
The new geo-referencing framework provides a needed foothold for solving
complex spatial problems, such as intercepting a nuclear missile using
supersonic evasive maneuvers or tracking the air, surface and groundwater flows
and concentrations of a toxic release.
While the advanced map analysis applications coming our way aren’t the
bread and butter of mass applications based on historical map usage
(visualization and geo-query of data layers) they represent natural extensions
of geospatial conceptualization and analysis …built upon an entirely new set
analytic tools, geo-referencing framework and a more realistic paradigm of
geographic space.
______________________________
Author’s
Note: I have been
involved in research, teaching, consulting and GIS software development since
1971 and presented my first graduate course in GIS Modeling in 1977. The discussion in these columns is a
distillation of this experience and several keynotes, plenary presentations and
other papers—many are posted online at www.innovativegis.com/basis/basis/cv_berry.htm.
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