How do geographic information systems depend on space?

One of the great benefits of engaging with space is understanding Earth better. Data collected from satellites inform our understanding about the relationship between humanity and the rest of the planetary system. One particular way of making sense of space-collected data is via geographic information systems. To learn more about these systems, we spoke to Joshua Sargent, an environmental scientist specializing in GIS. He explains how he came to acquire this specialization and how space-collected data inform environmental science.

What is GIS and how does it depend on space technologies?

A geographic information system (GIS) essentially is a way of managing spatial datasets for making decisions and displaying information. This can be achieved by using a variety of software products, some of which are commercial (such as ArcGIS) and others that are open source (such as QGIS). In general, GIS organizes two types of data: vector (“points, lines, or polygons”) and raster (“images”). Examples of vector data are the location of a tree, the outline of a river, or the boundary of a town. An example of raster data is a photograph of the ground, as taken from an airplane. In addition to cataloging data, GIS software commonly offer several analysis tools for data processing.

Worldwide, GIS primarily relies on space technologies for two key data inputs: global navigation satellite system (GNSS) receiver data and satellite imagery. GNSS data is a vector point dataset and satellite images are raster datasets. For clarification, the term GNSS more generally refers to a satellite array used for geospatial positioning on a global scale. Several polities have their own, including Russia, China, and the European Union. However, GNSS data are more commonly referred to as global positioning system (GPS) data, named after the specific satellite system maintained by the United States. By using highly accurate calculations of time, GPS data can identify the location of features on Earth. By using the location as an attribute of the data, these features can be mapped within GIS.

Satellite imagery is generated by an alternative set of satellites. Just as with GNSS satellites, there are different arrays currently in orbit. While many of these are maintained by national government organizations, some are maintained by private industry. In general, they take a wide range of photos of the Earth in the form of multi-spectral images. Most of these images are taken within the visible spectrum of light, but several satellites also collect data within the adjacent infrared electromagnetic wavelengths. In addition, imaging satellites can have different levels of pixel resolution detail (between 30 meters to sub-meter per pixel) and different temporal resolutions (from one image taken every 16 days to daily). As these images are taken from space, they regularly require complex adjustments before they can be accurately used. Once corrected, these images can function as the backgrounds to maps generated in GIS or, if further processed, they can be used to identify physical features and environmental conditions.

GIS is not limited to space technology data inputs. Specifically, much of the value of GIS is derived from the combination of several layers of data ranging from global to local scale. It can also incorporate localized information, either collected (such as field observation attributes and aerial photography) or hypothetical and user-generated (such as models of proposed construction or management areas). Historical documents containing maps and plans can even be digitized and incorporated into GIS to make new observations about the past.

What applications does GIS have for environmental science?

Environmental science is quite a broad topic and is subdivided into five key fields: atmospheric sciences, ecology, environmental chemistry, geosciences, and environmental social sciences. While each field of environmental science differs, they do share the common need to know where something is or where something has happened. By combining environmental observations with locations, people can observe the types of relationships that drive environmental science research. This is largely based upon the First Law of Geography, which states that “everything is related to everything else, but near things are more related than distant things.”

For more specific applications of GIS for environmental science, I can share a few examples from projects that I have worked on. During university, I had opportunities to help map natural resources with field-collected GPS coordinates. These varied from the soil classifications over a landscape, to the boundaries of wetland habitats in an area, and even to the locations of collected wild rabbit pellets for DNA research. I also had courses in remotely identifying land cover and land use changes from a series of satellite images.

In a GIS-professional capacity, I have worked on various other environmental projects. I utilized GIS to help assess the potential adverse environmental effects of proposed development plans. I worked on a three-year project using maps produced with GIS to calculate and communicate estimates of natural hazard damages from coastal flooding to petroleum industry representatives. Most recently, I have used GIS software to process drone imagery for slope analysis of agricultural fields. All in all, I believe that GIS serves as an excellent tool to link location data with environmental phenomena.

Why are you interested in GIS and environmental science?

I should begin with my interest in environmental science, as it came first. My interest in the environment developed out of my frequent interactions with nature through the Boy Scouts of America. By completing a series of merit badges and camping trips, I developed a personal drive to understand natural processes and assist in protecting natural resources.

Sometime during high school, I decided that I wanted to become an environmental scientist. Fortunately, I had several teachers who noticed this and encouraged my ambitions. One teacher informed me that to be a successful environmental scientist, I would need to learn about four key things at university: fieldwork procedures, environmental policies, wetlands, and something called “GIS.” While at university, I would learn more about all of those things, especially GIS.

Once I had completed courses associated with basic environmental science concepts, GIS and remote sensing courses were available to me as electives. For clarification, the university organized these courses under the same natural resource science department; this meant that GIS was taught as a skillset from the perspective of environmental science professors. I believe this greatly benefited me. While initially challenging, I soon discovered that I enjoyed learning how to use this software as a tool for environmental problem solving and decision making. I also developed an affinity for maps and the art of cartography. Throughout my bachelor’s and master’s degrees, I would arrange my schedule to include as many of these courses as possible.

Outside of university, I worked with state, federal, and private environmental organizations in various capacities. From collecting field GPS data to synthesizing geospatial data into maps for communicating results, my GIS skills were a beneficial asset to my environmental science background. They complemented one another and sometimes even allowed me to work on projects for which I otherwise would not have been considered.

As I have recently returned to academic research, I am still benefiting from my knowledge of environmental and spatial sciences. My PhD research relies on modelling historic and potential flooding impacts to low-lying, rural areas along the New Zealand coast. Alongside environmental components, I am learning to introduce aspects of social science into my work. My eventual goal is to develop models that incorporate both human and natural systems’ feedback that assist in coastal flood hazard and risk decision making.