The Nature of Geographic Information Systems

This diagram shows 4 basic parts of a GIS in the context of our relationship with nature. In practice, a GIS consists of people using technology to work with data under various methods in order to meet specific human needs. This has a specific implication of human-centered activity, in contrast to other technologies, databases and theories. Nature underlies all of these parts. The human study of nature gives rise to much of the theory and methods used, and recording of landforms and natural patterns constitutes much of the available spatial and related data. Human needs for health, clean air & water, food, solace and wonder are all part of our relationship with nature. Technology arose historically from our pursuit of dominance over nature (and over each other in wartime).

We will now look at each of these parts in more detail.

The data that a GIS operates on consists of any data bearing a definable relationship to space, including any data about things and events that occur in nature. At one time this consisted of hard-copy data like traditional cartographic maps, surveyor’s logs, demographic statistics, geographic reports and descriptions from the field. Advances in automating and digitizing data in the last several decades have allowed more and more such data to be incorporated into digital form making it accessible to computerized analyses. Advances in spatial data collection, classification and accuracy have allowed more and more standard digital basemaps to become available at different scales.

The technology foundations of GIS have been changing extremely rapidly so this diagram tries to represent not just the technology elements but their trends through time. GIS technology is based on computer hardware and different types of software programs. Extremely rapid development and advancement is typical of both elements. A rule thumb is that they double in analytical and processing power every 3 years, unlike any other industry in the history of humankind. A particular trend in development has been more powerful ways to link computers together, such as the internet, web graphic sites, and "data superhighways" allowing wider and wider distribution of power. This also has the effect of making old-style centralized computer installations less interesting and instead viewing knowledge and data operations as decentralized across a wide variety of players or clients, with an according shift in the central computer to services in support of those clients. A related trend has been the development and acceptance of standards for handling higher and higher level functions, like graphics, allowing these to become standard parts of all computers and freeing software developers to address higher and higher levels of creative functionality, ease of use, and software design (like object orientation). Improved networks and software capability has meant software fields like GIS and Statistics are able to advance and merge in more powerful ways to create commercial-grade software in formerly challenging and specialized application areas like ecological modeling, wildlife management and taxonomic databases

The different analysis, management and application methods used in a GIS come from a lengthy history of theoretical advances in a broad variety of fields, including Landscape Architecture, Mathematics, Geography, Systems Theory, Biology and Political Science. The first figure (above) shows how these fields provide the conceptual models for GIS capability in five general areas, space, features, operation/analysis, integration/synthesis, meaning/significance. The second figure (below) shows an alternate temporal view of how these fields built upon each other over time to create the body of theory comprising GIS today. We will trace the development of just a few of the basic ideas of GIS theory.

Models for describing space: These represent the different models used to describe space, derived mainly from concepts in statistics, topology and cartography.

- Space is a plane of continuous variation, which we can sample at different points. This is a statistical concept of space commonly found in biological hypotheses. This model emphasizes continuity and continuous variation. It is usually managed by dividing space into a regular grid of cells, also called a raster or matrix, where each cell has a value for the variable in question. Additional variables are put into additional layers using the same grid. This sets up a multi-dimensional matrix registered to the ground such as commonly used in multivariate statistical studies of habitat and niche. The concept of space as a regular plane was first formulated by Descartes in 1637 in developing a language of coordinate space for geometric analysis. Gauss and Humbolt carried these ideas further in working together to map the earth’s magnetic field, creating the first thematic map based on systematic sampling. Gauss was also the first to publish methodologies of mathematical statistics. R.A. Fisher finally formalized modern concepts of statistics, sampling on a plane, and multivariate methods in 1930, by which time gridded research sites were in common use among biologists. Raster models are very simple to automate and their use was so widespread among the first GIS programs of the 1960’s and 1970’s that they can be said to have been independently arrived at numerous times.

- Space is a plane of discrete things, which we can classify according to spatial relationships and multiple attributes. This concept, also called a vector model, is mostly topological, and borrows from geometry the notion of discrete things, which we represent in space a points, lines, polygons and surfaces. Topology provides the formal language for defining the invariant relationships between all of these geometric elements regardless of their shape. This model also underlies traditional cartography, which is important in GIS since maps are a primary source of data for GIS. Cartography as an art began with the Renaissance and the first voyages of discovery, receiving considerable impetus with the introduction of the printing press. Navigational usage of maps was limited, however, until Alberti published his treatise on the laws of projective geometry in 1435 which led Mercator to his famous projection, where navigators could sail by taking angles directly from the chart. A true understanding of map projections had to wait until Gauss first formulated the ideas of non-Euclidean geometry in 1800, whereby forms were described not according to their fixed shape, which could vary depending on how you tilted or twisted space in projecting earth’s sphere onto a flat map, but by the unchanging relationships of points to lines, and lines to polygons, thus inspiring his student Reimann to found the formal science of topology in 1851, on which all vector models are based. The specific linkage of vector topological models to relational models for description of attributes, now called the geo-relational model, was developed at ESRI in the 1970’s.

- Locations in space are described using coordinates. This concept originated with Descartes when he first invented the science of analytical geometry and provided a numeric method (coordinates) for describing shapes in space. Coordinates can be thought of as defining a grid across space.

Models for describing features: (things in space) Classified features are differentiated using distinct boundaries. This reflects another concept as old as science. Nature is fuzzy, class boundaries are not. Applying a class boundary to nature is an act of applying a discipline’s sharp world view over blurry natural patterns to see if interesting conclusions, questions, or decisions are produced.

Models for creating meaningful results: Operation and analysis - Spatial analysis includes questions of adjacency, containment, exclusion, proximity, subdivision, grouping, orientation, movement, time. Spatial Analysis is based on the ideas of spatial overlay and spatial sets which derive from set theory operations, such as intersection and union, defined by Cantor in 1874. It also draws from developments in simulation and modeling in the early days of computers. Early GIS developers coined the term "map algebra" in the 1960’s to describe spatial operations on gridded data, and the developing field that later came to be called computational geometry provided early algorithms for spatial analysis in the 1970’s.

- Integration and synthesis - Spatial data from different sources can be integrated by restructuring, generalizing and transforming (Maguire and Dangermond 1991). Restructuring is the process whereby data from different models is recast into a common model (i.e. raster into vector). Generalizing is where detailed data is smoothed out and/or aggregated to make it align better with less detailed data. Transforming is where data is changed to a new coordinate system, a new scale, or a new map projection in order for it to match the other data sets. - A basemap standard provides the common framework against which other spatial data can be processed to ensure compatibility. Two different maps can be made to match each other using the methods above, but a more long-term solution is to select a neutral base map for use as a common foundation across projects. The idea of standard basemap control dates back to Cassini, and in 1891 a program to develop a standard international map of the world was begun, which was not concluded until the US Defense Mapping Agency finished the Digital Chart of the World in 1992.

- User Needs Analysis - GIS projects must explicitly define the needs, capacities and expectations of the project users if they are to be successful. This is based on formal methods for user needs analysis and project design developed by the very first GIS (Tomlinson 1962), and drawn in turn from concepts in cybernetics and systems theory. - Human environments can be designed to be in harmony with natural environments. This is a fundamental assumption of Landscape Architecture, with served as the birthplace of the GIS industry at Harvard in the 1960’s and 1970’s. The ideas were first formulated by Geddes in 1904, leading to the international development of town and country planning.

Humans have basic needs for food & water, shelter, and health. Through most of our history these have been directly derived from nature and the various industries that provide them are current users of GIS technology, such as transport, forestry, and utility companies. Humans have also often shown a basic and often selfish desire for power, such as exclusive control over land and resources. The careless pursuit of these "basic" needs is a fundamental cause of the current extinction crisis, however, the use of GIS as a planning and management technology among some of these industries and a growing interest in sustainability holds hope that enough bridges can be built between opposite camps, organizations and disciplines to slow and stop these causes. Around these basic needs is a set of less self-centered needs regarding a person’s place among others and in the world. The need to belong is very strong and expresses itself at many different levels from family to church to community to humanity as a whole. This also includes the equally strong need to belong to a place in the natural world, ranging from landscapes of childhood memories and dreams to parks and bioregions. The need for beauty and awe is an important part of the character of the west and the human connection with wilderness. It is also why the arts are such a fundamental part of the human experience, and why humans are so profoundly moved by proximity to things that touch the deepest levels of their subconscience such as wilderness, wildlife and great art. The desire to protect wilderness and wild nature is common in the computer industry as a whole and the GIS industry in particular. The millions paid to acquire the notebooks of the greatest artist in history Leondardo, came not from the arts but from the pioneer of personal computing. Humans also have a need to explore, to engage their curiosity in trying to comprehend the awesome, beautiful universe around them. We also have a corollary need to communicate and teach. This need is most evident in the sciences, which have the additional distinction of trying to understand universal truths about what the world is and how it works, and trying to do it objectively so that others can understand it as well through independent verification. Finally, humans have the need to believe in something beyond themselves, which commonly expresses itself as religious faith. The details of that faith don’t matter so much as the ability of faith itself, when exercised in love, to inspire humans to work selflessly in service to others, especially those in need. Stewardship of a piece of wild land differs little from leading a congregation in this regard, the conscious act of placing the needs of strangers before the needs of oneself is uniquely human.