Joseph K.
Berry
Keck Visiting Scholar in Geosciences, University of Denver
Berry and Associates // Spatial Information Systems, Colorado USA
Note: This paper is a distillation of several keynotes,
presentations and papers; see Author’s Note at the end of the paper.
<Click
here> for a printer- friendly version of this paper (.pdf).
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.
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.
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.
The previous discussion 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.
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.
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.
Author's Note: This paper
is a distillation of several keynotes, presentations and papers. Online
references include:
§
Spatial
Reasoning in a World of Maps, GeoAlberta Conference,
Edmonton, Alberta, Canada, May, 2006. Keynote Address.
http://www.innovativegis.com/basis/present/GeoAlberta06/GeoAlberta06.htm
§ Getting
Your Arms Around Geospatial Technology, Geospatial Information Systems and Science Forum,
§
GIS
Technology in Environmental Management: A Brief History, Trends and Probable
Future, Global Environmental Policy and Administration, Soden and Steel editors, Marcel Dekker Publishers, 1999,
pgs. 49-76. J.K.
Berry. Book chapter.
http://www.innovativegis.com/basis/present/Global/global3.htm
§
Where
Is GIS? — Driving Forces,
Trends and Probable Future of
Additional papers, presentations and other materials on GIS concepts, considerations and procedures are available online at www.innovativegis.com/basis.