New Spatial Visitor: Ekaterina Egorova

The Center for Spatial Studies is happy to announce the arrival of a visitor to the center, Ekaterina Egorova (September, 2019-March, 2020)


Swiss National Science Foundation, Switzerland


Ekaterina Egorova 

holds a PhD in Geographic Information Science from the University of Zurich, Switzerland. Her

research has concentrated on studying the conceptualization of  remote natural environments

through the prism of textual Volunteered Geographic Information. Her current project, financed

through a grant from the Swiss National Science Foundation, examines the spatial and temporal

aspects of human-environment interaction in the context of nature-based recreation activities, focussing on the Southern Alps, New Zealand.

Ekaterina’s research lies at the intersection of GIScience, spatial cognition and cognitive linguistics, and combines methods from NLP, Geographic Information Retrieval, computational discourse analysis, and spatial analysis. Her interests include the production and processing of geographic information across a variety of contexts, spatial semantics, and methods for the automated extraction of spatial concepts from multimodal geographic information sources.


Her work can be explored at:
Google scholar:
Twitter: @textandspace

Please join us in welcoming Ekaterina to campus! She will be working at 3512 Phelps Hall during her stay–please feel free to contact her — — if your research interests intersect with hers.

Spatial Tech Lunch: Dan Baciu

On Tuesday, November 12, from 12:00–1:00 pm please join us for the next Spatial Technology Lunch in the Center for Spatial Studies (Phelps Hall 3512). This semi-regular series, hosted by spatial@ucsb, aims to promote discussion and interaction within the university’s spatial technology community. Please RSVP here by Friday, November 8. Sandwiches and drinks will be provided.

The Geography of Cultures: New Methods for Decoding, Analysis, and Synthesis

Dan Baciu


Abstract: It is tempting to believe that ideas and culture are free to spread and therefore free of geography. However, the phenomenon of “culture shock” most dramatically questions and limits the validity of such hypothesis: When chasing your dreams and horizons, you may end up in a different culture on a different continent, and, under those circumstances, you may loose your sense of self. Geography and culture are inseparable because geography is an important medium for cultural life.

Although people carry their cultural values with them, they may reach a place where those values no longer apply. So to say, their cultural currency is no longer accepted—but this anecdotal evidence should really only raise interest in new research directions with global implications. At UCSB, Benjamin Cohen has shown that money has surprising geographies with massive political consequences on a global stage. Dan C. Baciu, supported by the Interpretation Lab, continues along this path but goes further in studying the geography of cultures. In an age of information and knowledge, as Alvin and Heidi Toffler contemplated, cultures are the new currencies. Companies are no longer valued for their transaction volume alone, but also for their ability to amass information about people and their cultures. Yet, how are these personal, local, and global scales of culture interconnected? And how do mass and social media shift geographical distributions and reshape entire systems of value?

Studying these questions, Dan Baciu envisioned and probed new methods of extracting geographical information from public media. Instead of relying on gazetteers, his team uses natural language processing and publicly contributed knowledge bases. This makes it possible to create many interconnected layers of geography, history, and cultural circles, allowing for the application of a richer stock of analysis and synthesis methods. In turn, these new possibilities for empirical assessment allow for the testing of new theory about the relationships between individuals, cultural cannons, and shared global geography.

Imagine collecting hundreds of thousands of books, news, social media, and TV for everything called “Chicago school,” “Humanities,” and “Science.” What would these data reveal? Dr. Baciu and his collaborators used supercomputing to decode natural language, and they went on to enrich these data with geographical and historical information. Furthermore, they combined historical evaluations with data analysis, dimensionality reductions, and classification. Finally, to make sense of their results, they developed interfaces to interactively visualize distributions and stratification. Their GeoD and 7D toolkit is expected to be released to the public in a forthcoming research article.

The newly discovered geographical distributions of culture are surprising: There are maps of science, humanities, universities networks, postmodernism, national parks, oceanography, study abroad, and many more. And these geographies are not as you expect them. If you think that the U.S. Dollar is limited to the U.S., and that national parks are where they are, you will be surprised. The new methods allow us to refine our understanding of how culture grows in geographical space.

The new methods of analysis and synthesis were driven by theory and questions that preoccupied Dr. Baciu already during his Ph.D.; and the new findings confirm his earlier postulates. For him, the newly discovered geographical distributions are no longer surprising. Although new to humanities scholars, the theoretical foundations of his work are not new to everyone. Equivalent mathematics are a textbook-case of evolutionary dynamics already.

“United we stand” inspires not only collaborative spirit, but also a new research direction in the study of urban culture and diversity. “United” in this context means learning to listen to everyone. Dan C. Baciu has shaped this research direction most recently as Postdoc in English at UC Santa Barbara.

Spatial Data Science Hangout Series: Fall 2019

Spatial Data Science Hangouts Poster

After a successful first run in the last academic year, the Center for Spatial Studies will again be hosting the Spatial Data Hangouts, with the first one on Thursday, 10/17 from 11:30 a.m.12:30 p.m. at 3512 Phelps Hall. All grad students are invited to attend.

With the season for academic jobs starting, the next few spatial data science hangouts will be used to to discuss why and how to apply for a professorship, eg., how to write your cover letters, what makes a good recommendation letter, how to structure your CV, how to score during the on-site interviews and your talk, how to negotiate, and so on.

We will focus on jobs in spatial data science, GIScience, remote sensing, spatial cognition, and so on, but most of what we will discuss applies to academic employment in general. We will do all this in a hands-on, interactive style.

We will be providing a light lunch after the discussion. Please contact Karen Doehner if you plan to attend.


New Spatial Visitor: Weiming Huang

The Center for Spatial Studies is happy to announce the arrival of a visitor to the center, Weiming Huang (September-November, 2019)

Weiming Huang is a Ph.D. student in Geographical Information Science at Lund University, Sweden. His research topic is “Knowledge-based geospatial data integration and visualization with Semantic Web technologies.” His research interests span geospatial semantic web, geospatial semantics, data integration, data visualisation, and machine learning.

His work can be explored at:

Please join us in welcoming Weiming to campus! He will be working at 3512 Phelps Hall during his stay–please feel free to contact him — — if your research interests intersect with his.

Spatial Center Receives NSF Grant

Center for Spatial Studies at the University of California, Santa Barbara participating in NSF C-Accel Pilot

View the complete news release at:

The Center of Spatial Studies at the University of California, Santa Barbara is receiving research funding under the Open Knowledge Network track of the new Convergence Accelerator Pilot (C-Accel) by the National Science Foundation (NSF). Prof. Krzysztof Janowicz leads a diverse team of partners from academia, industry, and federal agencies. The team will develop Artificial Intelligence based models, methods, and services for representing,  retrieving, linking, and predicting spatial and temporal data from a highly diverse set of public knowledge graphs that range across topics such as soil health and the historic slave trade. 

This new NSF Convergence Accelerator Pilot program is set to “bring teams together to focus on grand challenges of national importance that require a convergence approach […] and have a high probability of resulting in deliverables that will benefit society within a fixed term.” NSF is funding several teams under this program in an effort that will lead to the development of public knowledge graphs which in turn have “the potential to drive innovation across all areas of science and engineering, and unleash the power of data and artificial intelligence to achieve scientific discovery and economic growth.” The funding program is highly competitive and had an acceptance rate of only 8.5%.

2019 Spatial Data Science Symposium

Spatial Data Science Symposium

“Setting the Spatial Data Science Agenda”

December 9–11, 2019


Upham Hotel (

Santa Barbara, California


Space and time matter not only for the obvious reason that everything happens somewhere and at some time, but because knowing where and when things happen is critical to understanding why and how they happened or will happen. Spatial data science is concerned with the representation, modeling, and simulation of spatial processes, as well as with the publication, retrieval, reuse, integration, and analysis of spatial data. It generalizes and unifies research from fields such as geographic information science, geoinformatics, geo/spatial statistics, remote sensing, and transportation studies, and fosters the application of methods developed in these fields to outside disciplines ranging from the social to the physical sciences. In doing so, research on spatial data science must  address a variety of new challenges that relate to the diversity of the utilized data and the underlying conceptual models from various domains, the opportunistic reuse of existing data, the scalability of its methods, the support of users not familiar with the language and methods of traditional geographic information systems, the reproducibility of its results that are often generated by complex chains of methods, the uncertainty arising from the use of its methods and data, the visualization of complex spatiotemporal processes and data about them, and, finally, the data collection, analysis, and visualization playing out in near real-time. Spatial data science does not only utilize advanced techniques from fields such as machine learning or big data storage and retrieval, but it also contributes back to them. Recent work, for instance, has shown that spatially-explicit machine learning methods substantially outperform more general data when applied to spatial data even though this spatial component may seem of secondary importance at first glance.

Co-sponsored by Esri, the Center for Spatial Studies at the University of California, Santa Barbara is hosting a symposium entitled “Setting the Spatial Data Science Agenda.” The meeting will bring together academic and industry representatives from fields such as geographic information science, geoinformatics, geo/spatial statistics, remote sensing, and transportation studies, with interest in setting an interdisciplinary research agenda to advance spatial data science methods and practice, both from scientific and engineering viewpoints. We also invite experts from related fields and those that are producers or users of spatial data in the social and physical sciences.


Instead of being restricted by a historically grown partition into small and overlapping communities that deal with spatial data in one way or the other, the overarching goal of this symposium is to put spatial data science at the forefront of a unified field that explores the current research and application landscape to define an agenda for spatial data science for the next 10 years.


About 35 invited and funded experts from academia and industry will convene to share and develop visions, insights, and best practices. Plenary presentations and intense exchanges in small breakout discussion groups offer opportunities for knowledge transfer.

Call for Applications 

To apply, please submit a one-page, paragraph-style bio with a photograph and a short two-page position paper (in PDF format), discussing your perspective on the subject by August 23, 2019. Participants will be selected by the organizing committee and notified of their acceptance by September 9. Our goal is to achieve a balance of participants from a variety of disciplines and from different career levels. Hence, we especially encourage early-career (including graduate students) participants from both the industry and academia to apply. We will cover the full expense of accommodations and reimburse travel expenses up to $1,200 for international participants and $700 for domestic. 

The meeting will be held at the Upham Hotel in downtown Santa Barbara on Dec. 9–11; suggested travel days are Dec. 8 and the afternoon of Dec. 11.

Please see for more information. 

Submit your application directly to Karen Doehner <>.

Please feel free to contact Krzysztof Janowicz <> if you have questions about the event or the call for applications.

spatial@ucsb.local2019: Posters

spatial@ucsb.local2019 main page

The Future of Island Oaks

The Future of Island Oaks

Laura Wolf, Sofie McComb, Claire Powers, Jazmine Uy, Alyssa Winchell

Bren School of Environmental Management, University of California, Santa Barbara
Island oak (Quercus tomentella) is a rare oak species endemic to six islands in the California Island Archipelago (CAIA). Over a century of farming and grazing on the islands degraded core habitat and reduced island oak seedling recruitment. The species was listed as endangered by the IUCN in 2016. Most historical threats have been removed, though island oak regeneration is still restricted and there is concern that impending climate change poses an additional threat that may ultimately lead to extinction. Spatially-constrained, if the island oak’s range shifts or further deteriorates, alternative options are limited. We used MaxEnt, a species distribution model, to identify island oak’s bioclimatic niche on Santa Cruz, Santa Rosa, and Santa Catalina Islands and then predicted where that niche might exist through the end of the century under four climate change scenarios. Model outputs supported three main findings: (1) Island oak’s predicted bioclimatic niche was largely driven by soil moisture availability; (2) Santa Rosa Island had the most predicted suitable habitat under each climate change scenario, while predicted suitable habitat on Santa Cruz and Santa Catalina Islands was minimal; and (3) the bioclimatic habitat occupied by island oak varies substantially between the three islands studied. Improvements in life history information, legacy grazing patterns, and more finely downscaled climate data would substantially increase model validity. Research should focus on identifying mechanisms driving the variation in habitat occupied on each island, while restoration should prioritize habitat augmentation and seedling recruitment, to increase island oak’s resiliency to climate change.
Urbanization and its Effects on the Surrounding Environment
Urbanization poster
Urbanization and its Effects on the Surrounding Environment: Case Study of Beijing and Lanzhou, China

Guiyu Li, Yingyi He, Jiaxuan Lyu, Haoyu Shi

Department of Geography, University of California, Santa Barbara

In the past decades, China has experienced massive economic growth and urban development. Changes in urban land cover, vegetation healthiness, and temperature distribution are crucial factors to understand the urbanization effects on the surrounding environment. Beijing and Lanzhou, two distinctive cities in terms of size and geographical location, are selected as our study objects. Using Landsat 5 and 8 images from 1993 to 2017 for the two cities, we train our algorithms to classify land cover types, including urban, vegetation, soil, and water. Normalized Difference Vegetation Index (NDVI) is calculated to measure vegetation health. Temperatures are derived using the radiance of the thermal band. Land cover classes are used for NDVI and temperature analysis. Based on the results, both Lanzhou and Beijing experienced urban expansion over the study period. Especially in Beijing, both its scale and urbanization rate are greater compared to those in Lanzhou due to the demographic, topographic, and economic differences. Urbanization influences the total amount of vegetation but does not directly cause a decrease in vegetation healthiness. The temperatures in both cities have increasing trends. The temperatures of urban and soil areas are higher than those of vegetation and water. In Beijing, the urban areas have the highest temperature, and the hot spots correspond with the urban expansion, reflecting a positive urban heat island effect. In contrast, in Lanzhou, the soil areas have higher temperatures than urban areas, which indicates a negative heat island effect. In conclusion, urbanization leads to a positive impact on temperature change but does not decrease vegetation health. Vegetation and water will mitigate the urban heat island effect.

Perspective Taking is Affected by Array, Perspective Shift, and pointing Quadrant
Perspective Taking

Perspective Taking is Affected by Array, Perspective Shift, and pointing Quadrant

Peri Gunalp, Elizabeth Chrastil, Mary Hegarty

University of California, Santa Barbara

Previous research on spatial perspective taking ability has used psychometric tests like the Perspective Taking Test (PTT). The present experiment introduces an experimental task that systematically varies the magnitude of the initial perspective shift and of the pointing response, and examines the effects of the addition of a person in the array. Performance on this computerized PTT indicated that accuracy increased with inclusion of a person in the array compared to a control condition, decreased with increases in initial perspective shift, and was best when pointing to the front in the imaged perspective. These perspective shift and pointing response patterns were consistent regardless of whether a person was included in the task array, suggesting that participants do not modify their strategy when a person is included. Regardless of the size of the initial perspective shift or pointing quadrant, participants seem to be engaging mental transformation and visualization processes.

Academic Discipline's Interactions with Spatial Aptitude
Academic Disciplines and Spatial Aptitude
Academic Discipline’s Interactions with Spatial Aptitude

Emily Cao, Adora Du, Luke Speier, Chuanxiuyue (Carol) He, Mary Hegarty

Hegarty Spatial Cognition Lab, Department of Psychology, University of California, Santa Barbara
Science, technology, engineering, and mathematics are academic disciplines that have been associated with spatial aptitude.Visualizing objects, being aware of spatial relationships, having knowledge of movement and speed, in addition to analyzing complicated systems are all important skills for being successful in STEM disciplines. This study tested the spatial aptitudes of participants from different academic disciplines such as engineering, physical sciences, and social sciences in order to see whether or not there was an actual difference in visuospatial performance. The results found that participants in engineering and STEM disciplines had slightly stronger spatial aptitudes.
Analysis of Students' Familiarity with UCSB Campus
Student's Unfamiliarity Poster

Analysis of Students’ Familiarity with UCSB Campus

Shupeng Wang, Zilong Liu, Eddie Nguyen

Department of Geography, University of California, Santa Barbara
UCSB campus is approximately 989 acres so it can be easy to be unfamiliar with the campus. In this project, we address areas of unfamiliarity within the UCSB campus and explore three possible associations that might influence familiarity on the UCSB campus: Campus Resource Availability, Accessibility, and Activity. The Campus Resource Availability factor highlights how availability of the campus resources, such as computer labs and foods, affect familiarity. The Accessibility factor indicates the influence of accessibility to the campus buildings on familiarity. The Activity factor shows how familiarity is influenced by students’ activity around campus.
The Effects of Drought on Land Fallowing and Crop Health in Agriculture
The Effects of Drought on Land Fallowing and Crop Health in Agriculture

Brody Brand, Jessica Martinez, McKenzie Sime

Departments of Geography and EEMB, University of California, Santa Barbara
In this project, we aimed to discern the effects of both drought severity and water source on agriculture. Looking at three counties in April of 2011, 2014, and 2018, we assessed the percentage of cropland that had been fallowed and the health of crops using an NDVI and an NDWI. We found that Linn County, Oregon, which has no shortage of water, had the least fallowed land and the healthiest crops. In Merced County and Imperial County, California, we found that there was some variation in the percentage of fallowed land with drought severity and no variation in crop health with drought. Water source did not seem to have an effect for the 2014 drought.
Effects of Human Land Use on Invasive Species Density in Hawaii
Hawaii's Invasive Species

Effects of Human Land Use on Invasive Species Density in Hawaii

Juli Ann Lingenberg, Noelle Pruett, McKenzie Sime

Departments of EEMB and Geography, University of California, Santa Barbara
In this project, we aimed to discover which land use type had invasive species observations in the highest density in Hawaii. Using a land use map from the Hawaii State Land Use Commission (LUC) and species observations for 15 invasive species from iNaturalist, we found the density of observations in each of our four land use types (urban, rural, agriculture, and conservation). Urban areas had the highest density (8x the average). We then looked at buffers around the urban areas of differing distances and found that the further a buffer went out from an urban area, the lower the density of observations became.
The City of Thousand Oaks Community Energy Action Plan
Thousand Oaks Energy Plan

The City of Thousand Oaks Community Energy Action Plan: Residential Energy Consumption

Carrie Simmons, GIS Aide

City of Thousand Oaks Public Works Department

This analysis is a guiding component to the City of Thousand Oaks Community Energy Action Plan (CEAP). The main goals of this plan are to reduce fossil fueled based energy usage and increase energy efficiency and resilience in The City of Thousand Oaks. This data and analysis will be able to inform City staff on what areas or demographics should be targeted and how to strategically implement programs and outline steps to lower overall energy consumption. Staff plan to use this energy consumption data over a variety of parameters such as building age, solar panel usage, income, population density, home ownership versus renters, and much more. Over time this analysis may become part of the Cities Climate Action Plan which has a goal of addressing activities to reduce greenhouse gases (GHG). This analysis is an initial step to seeing how we can use this data to create programs and policies to meet our climate goals.

Communities of Interest at Different Scales
Communities of Interest at Different Scales

Communities of Interest at Different Scales

Daniel W. Phillips

Department of Geography, University of California, Santa Barbara
When drawing boundaries of electoral districts, officials commonly rely on four criteria besides equal population: contiguity, compactness, respect for administrative regions, and respect for communities of interest (COIs). That last criterion is not as easily defined, as what exactly constitutes a COI is open to interpretation. This research evaluates the merits of one potential method for identifying and defining COIs, by surveying residents and asking them to draw the boundaries of their COI on a map. Those areas covered by many respondents’ drawings would thus constitute the core of people’s cognitive COI. A study conducted in Santa Barbara County, California demonstrates that this method results in clearly-defined and coherent COIs that somewhat correspond to the existing electoral districts. The study also reveals that survey participants, despite the fact that all of them live in the same district at three different levels of government, conceive of separate urban and rural COIs. Furthermore, the extent of the map given to participants has a large effect on the size of the COI that they draw. These results indicate the importance of the urban-rural dichotomy and the effects of scale in defining what a COI really is.
2018 Posters
spatial@ucsb.local2018 poster

spatial@ucsb.local2019: Poster and Plenary Session



Thursday, June 6, 2018

Corwin Pavilion

Invitation & Agenda Speakers Posters

The annual spatial@ucsb.local2019 Poster and Plenary Session was held on Wednesday, June 6, 2018 at Corwin Pavilion.

This year’s theme for the event was Spatial Data for Smarter Cities. Keynotes were delivered by Mahnoosh Alizadeh (Electrical and Computer Engineering, UC Santa Barbara), Konstadinos (Kostas) Goulias (Dept. of Geography, UC Santa Barbara), and Kurt Shellhause (Water Resources Engineer, Kasraie Consulting). Representatives from the private sector and industry and campus-wide academics in the humanities, sciences, social sciences, and engineering programs had the opportunity to showcase how spatial thinking facilitates research and creativity. A total of 38 posters were submitted for viewing. Some of these have been posted to this website.