CoSSI 2017 – COSIT Workshop on Cognitive Scales of Spatial Information

Topic At what scale are we thinking when we read a map, get directions from a navigation system, or do spatial analysis using a GIS? This workshop will investigate whether the concepts underlying external spatial representations (such as fields or objects in a GIS) and computations (such as buffer or overlay) can be assigned a cognitive scale and what that would be. By “cognitive scale”, we refer to the size or extent of spatial phenomena as conceptualized by and in relation to human beings and their perceptual-motor mechanisms (following Montello’s 1998 taxonomy and the 1997 discussion by Freundschuh and Egenhofer). Maps represent environments at a more or less fixed scale and require operations at the figural (more specifically, pictorial) cognitive scale. GIS and related technologies, while clearly not scale-free, offer much more flexible ways of dealing with scale. Are errors like the Economist’s erroneous map of North Korean missile ranges evidence for inadequate ways of dealing with cognitive scale, not just for ignoring the effects of map projections? Discussion Questions The COSIT 2017 workshop will take a fresh look at the various notions and components of scale of digital spatial information and questions they raise. How can we organize spatial information in a way that relates to cognitive scale taxonomies? Can and should we organize spatial information in scale-agnostic ways? Are certain kinds of spatial information limited to certain scales or scale ranges? What about scale in the sense of granularity (referring to the smallest units of study)? How is granularity tied to perceptual and cognitive processes? Has the evolution of scale on paper maps caused particular problems of human understanding? Do operations such as buffering suggest pictorial rather than environmental space thinking? What are the roles and consequences of intentional scale distortions, for example in cartograms or fisheye maps? What are the cognitive implications of the nearly continuous scale changing (zooming) found in modern GIS? What is the role of cognitive scale in virtual reality and other immersive environments? How do findings about geographic information map onto non-geographic spaces (of atoms or galaxies, for example)? How are measurement scales (nominal, ordinal, interval, ratio,…) related to spatial...

Spatial Tech Lunch: Susan Meerdink

Mar 14, 2017 • Categories: Event | Spatial Tech Lunch

On Wednesday, March 22, from 12:00–1:00 pm please join us for the next Spatial Technology Lunch in Phelps Hall room 3512. This semi-regular series, hosted by spatial@ucsb, aims to promote discussion and interaction within the university’s spatial technology community. Please RSVP to Kitty Currier (kcurrier@spatial.ucsb.edu) by Tuesday, March 21. Pizza and drinks will be provided.   Classifying California plant species throughout the drought using airborne hyperspectral imagery Susan Meerdink Abstract: Accurate knowledge of plant species seasonal and inter-annual distributions are required for many research and management agendas that track ecosystem health. Airborne imaging spectroscopy data have been successfully used to map species, but often only in a single season due to data availability. During California’s severe drought, NASA’s Hyperspectral Infrared Imager (HyspIRI) preparatory airborne campaign flew a visible near infrared/shortwave infrared (VSWIR) imaging spectrometer and a thermal infrared (TIR) multi-spectral imager providing the opportunity to improve species discrimination over a broader temporal range. Imagery was acquired in the spring, summer, and fall of 2013–2014 spanning from Santa Barbara to Bakersfield, CA. Overall classification was fairly uniform between seasons with accuracies ranging from 84–93%. However, individual species classification varied much more between dates with accuracies ranging from 10–78%. These results show that while overall image classification across seasons is accurate, classification performance may not be sufficient for applications that focus on a specific species of interest. This research contributes to efforts aimed at monitoring ecosystems across large spatial and temporal scales and ultimately supports many research agendas that are tracking ecosystem health and changes. Susan Meerdink is a Ph.D. Candidate in the UCSB Visualization & Image Processing for Environmental Research (VIPER) lab. She studies the ability to map plant species across seasons in the dynamic and diverse Southern California Mediterranean ecosystem. She uses various technologies to study plant health across environmental gradients and physiology’s effect on optical properties of plant species. Her research leverages a number of tools including novel quantitative methods, land surface temperature, and spectroscopy in the optical and thermal...