Devika Kakkar, Ben Lewis, and Wendy Guan. 5/18/2022. “Interactive analysis of big geospatial data with high-performance computing: A case study of partisan segregation in the United States.” Transactions in GIS. Publisher's VersionAbstract
Researchers are increasingly working with large geospatial datasets that contain hundreds of millions of records. At this scale, desktop GIS systems typically fall short and so new approaches and methods are needed. The objective of this work is to develop new approaches to interactively analyze large datasets and then to demonstrate the usefulness of those approaches using a case study looking at voter, or partisan segregation. Historically, the measurement of partisan segregation has been limited to comparing large geographic areas such as counties or states because researchers only had access to aggregated data. In this case study, however, we measure partisan segregation down to the individual for 180 million U.S. voters using advanced geospatial data science and high-performance computing. This article discusses interactive method development for big geospatial data analysis including techniques used, solutions developed, and processing time statistics.
Lingbo Liu, Ru Wang, Weihe Wendy Guan, Shuming Bao, Hanchen Yu, Xiaokang Fu, and Hongqiang Liu. 2/18/2022. “Assessing Reliability of Chinese Geotagged Social Media Data for Spatiotemporal Representation of Human Mobility.” ISPRS International Journal of Geo-Information, 11, 2. Publisher's VersionAbstract
Understanding the space-time dynamics of human activities is essential in studying human security issues such as climate change impacts, pandemic spreading, or urban sustainability. Geotagged social media posts provide an open and space-time continuous data source with user locations which is convenient for studying human movement. However, the reliability of Chinese geotagged social media data for representing human mobility remains unclear. This study compares human movement data derived from the posts of Sina Weibo, one of the largest social media software in China, and that of Baidu Qianxi, a high-resolution human movement dataset from ‘Baidu Map’, a popular location-based service in China with 1.3 billion users. Correlation analysis was conducted from multiple dimensions of time periods (weekly and monthly), geographic scales (cities and provinces), and flow directions (inflow and outflow), and a case study on COVID-19 transmission was further explored with such data. The result shows that Sina Weibo data can reveal similar patterns as that of Baidu Qianxi, and that the correlation is higher at the provincial level than at the city level and higher at the monthly scale than at the weekly scale. The study also revealed spatial variations in the degree of similarity between the two sources. Findings from this study reveal the values and properties and spatiotemporal heterogeneity of human mobility data extracted from Weibo tweets, providing a reference for the proper use of social media posts as the data sources for human mobility studies.
Xue Liu, Wendy Guan, and Rinki Deo. 1/2022. “Large-Scale High-Resolution Coastal Mangrove Forests Mapping Across West Africa With Machine Learning Ensemble and Satellite Big Data.” Frontiers in Earth Science. Publisher's VersionAbstract
Coastal mangrove forests provide important ecosystem goods and services, including carbon sequestration, biodiversity conservation, and hazard mitigation. However, they are being destroyed at an alarming rate by human activities. To characterize mangrove forest changes, evaluate their impacts, and support relevant protection and restoration decision making, accurate and up-to-date mangrove extent mapping at large spatial scales is essential. Available large-scale mangrove extent data products use a single machine learning method commonly with 30 m Landsat imagery, and significant inconsistencies remain among these data products. With huge amounts of satellite data involved and the heterogeneity of land surface characteristics across large geographic areas, finding the most suitable method for large-scale high-resolution mangrove mapping is a challenge. The objective of this study is to evaluate the performance of a machine learning ensemble for mangrove forest mapping at 20 m spatial resolution across West Africa using Sentinel-2 (optical) and Sentinel-1 (radar) imagery. The machine learning ensemble integrates three commonly used machine learning methods in land cover and land use mapping, including Random Forest (RF), Gradient Boosting Machine (GBM), and Neural Network (NN). The cloud-based big geospatial data processing platform Google Earth Engine (GEE) was used for pre-processing Sentinel-2 and Sentinel-1 data. Extensive validation has demonstrated that the machine learning ensemble can generate mangrove extent maps at high accuracies for all study regions in West Africa (92%–99% Producer’s Accuracy, 98%–100% User’s Accuracy, 95%–99% Overall Accuracy). This is the first-time that mangrove extent has been mapped at a 20 m spatial resolution across West Africa. The machine learning ensemble has the potential to be applied to other regions of the world and is therefore capable of producing high-resolution mangrove extent maps at global scales periodically.
Weihe Wendy Guan. 2022. “The Geography of Geography.” In New Thinking in GIScience, edited by Bin Li, Xun Shi, A-Xing Zhu, Cuizhen Wang, and Hui Lin, Pp. 67-74. Singapore: Springer. Publisher's VersionAbstract
There are many definitions for geography, most contain the word space or place. In order to foresee the future of geography, let us first examine the presence of the discipline, in particular, its variation in space. This chapter illustrates the distribution of global leading higher education institutions and compare that with the distribution of those leading the study of geography. Are they mostly overlapping? Or in some countries, do they deviate from each other? Among the leading institutions for the study of geography, are they focusing on physical geography, human geography, geographic information science, or all sub-disciplines? Among the leading institutions that are not strong in the study of geography, what are the related disciplines they choose to focus on? Is there a geographic variation in the composition of geographic education? If yes, how to describe it, and how to explain it? Do these patterns reveal any insight to the future of the discipline?
Akhil Kumar, Yogya Kalra, Weihe Wendy Guan, Vansh Tibrewal, Rupali Batta, and Andrew Chen. 9/29/2021. “COVID-19 impact on excess deaths of various causes in the United States.” Annals of GIS. Publisher's VersionAbstract
Media regarding COVID-19 fatality counts is crucial, affecting policy and health measures nationwide. However, misinformation regarding other causes of death has led to dubious claims about the seriousness of the coronavirus. This research aims to identify the changes in a dozen causes of death during the pandemic using CDC data from 1999 to 2020. Using the Exponential Triple Smoothing (ETS) algorithm, this project estimated the mortality of eleven causes of death for 2020 under the assumption of no COVID-19 pandemic. Using Power BI and Tableau, this data was visualized together with 2020 actual death counts to determine which causes of death were significantly impacted by the coronavirus. The dashboard revealed an increase in several causes of death including Alzheimer’s Disease and Diabetes, a decrease in Chronic Lower Respiratory Disease deaths, and a slight increase in Influenza deaths. These findings, while at odds with much of the media surrounding COVID-19 mortality, are corroborated by adjacent scientific research.
YoungJoon Kim, Jinhyung Lee, Junghwan Kim, and Naoto Nakajima. 2021. “The Disparity in Transit Travel Time between Koreans and Japanese in 1930s Colonial Seoul.” Findings. Publisher's Version
Melinda Laituri, Robert Richardson, Junghwan Kim, Laura Cline, Sebastian Viscuso, and Lee Schwartz. 2021. “Examining second-order impacts of COVID-19 in urban areas.” Annals of GIS. Publisher's Version
Jianwei Huang, Mei-Po Kwan, and Junghwan Kim. 2021. “How Culture and Sociopolitical Tensions Might Influence People’s Acceptance of COVID-19 Control Measures That Use Individual-Level Georeferenced Data.” ISPRS International Journal of Geo-Information, 10, 7. Publisher's Version
Wendy Guan and Liz Hess. 7/6/2020. “Understanding the Ecosystem of Geospatial Research and Service in Universities.” Journal of Map & Geography Libraries . Publisher's VersionAbstract
The study of location and location-based phenomena is a flourishing field. Many universities have grown their research and/or services in this field (often called GIS), established centers that are primarily engaged in the research of GIS, or applying GIS technologies to support researches of other fields. Some straddle “research of” and “research with” GIS in the same center, engaging in both GIScience research, often by researchers in a department or school, and geospatial technology services, often for users across the university. We conducted an online survey to scour the landscape of such centers in universities worldwide, to understand how they are structured, managed, financed, and sustained. The survey also included units as part of a library, department, or lab. Eighty-one valid responses were analyzed, revealing these organizations’ administrative, financial, staffing, and operational status; their history, visions, responsibilities, resources, constrains, challenges, and opportunities. The result showed differences between universities with and without a geography department.
A.D. Gage, F. Carnes, J. Blossom, and et. al. 9/5/2019. “In Low- And Middle-Income Countries, Is Delivery In High Quality Obstetric Facilities Geographically Feasible?” Health Affairs, 38, 9, Pp. 1576-1584. Publisher's Version
Jason Ur and Jeffrey Blossom. 7/5/2019. “Mapping Ancient Landscapes.” In GIS for Science: Applying Mapping and Spatial Analytics, Pp. 142-165. Redlands, CA: Esri Press. Publisher's Version
Weihe Wendy Guan, Matthew W. Wilson, and Anne Kelly Knowles. 5/12/2019. “Evaluating the Geographic in GIS.” Geographical Review, 109, 3, Pp. 297-307. Publisher's VersionAbstract

Despite several decades of discussion and debate around the role of GIS in the discipline of Geography, it would be a stretch to argue that GIS has not irreversibly altered the discipline, both in the scope of research and teaching as well as in the wider imagination of a general public. However, it remains a challenge to incorporate the range of geographic knowledge, born of a diversity of modalities, into operational insights and analytical pre-conditions in a GIS. To be certain, some irreconcilability between GIS and geographical inquiry is to be expected, epistemologically speaking. In what follows, we consider what might be meant by a shift to geographic analysis as scholars from disciplines in the humanities and social sciences turn to GIS as a method of observation, interpretation, analysis, and representation. In this context, we engage in a thought experiment and offer some commentary, fixing the notion of information system, while opening the geographic in GIS to more variable understanding. The point is to pursue greater development of GIS theory and method, encompassing, while not reducing, scientific, social scientific, and humanities research.

Jeffrey C. Blossom and et. al. 5/11/2019. “Robust Parliamentary Constituency Estimates: Geographic Data Science Approaches.” Economic & Political Weekly, Volume 19, 1, Pp. 66-70. Publisher's Version
Emily Hammer and Jason Ur. 3/12/2019. “Near Eastern Landscapes and Declassified U2 Aerial Imagery.” Advances in Archaeological Practice, Volume 7, Issue 2, Pp. 07-126. Publisher's VersionAbstract
Recently declassified photographs taken by U2 spy planes in the 1950s and 1960s provide an important new source of historical aerial imagery useful for Eurasian archaeology. Like other sources of historical imagery, U2 photos provide a window into the past, before modern agriculture and development destroyed many archaeological sites. U2 imagery is older and in many cases higher resolution than CORONA spy satellite imagery, the other major source of historical imagery for Eurasia, and thus can expand the range of archaeological sites and features that can be studied from an aerial perspective. However, there are significant barriers to finding and retrieving U2 imagery of particular locales, and archaeologists have thus not yet widely used it. In this article, we aim to reduce these barriers by describing the U2 photo dataset and how to access it. We also provide the first spatial index of U2 photos for the Middle East. A brief discussion of archaeological case studies drawn from U2 imagery illustrates its merits and limitations. These case studies include investigations of prehistoric mass-kill hunting traps in eastern Jordan, irrigation systems of the first millennium BC Neo-Assyrian Empire in northern Iraq, and twentieth-century marsh communities in southern Iraq.
Akshay Swaminathan, Rockli Kim, Yun Xu, Jeffrey C Blossom, William Joe, R Venkataramanan, Alok Kumar, and SV Subramanian. 1/12/2019. “Burden of Child Malnutrition in India: A View from Parliamentary Constituencies.” Economic & Political Weekly, 2, 2, Pp. 44-52. Publisher's Version
Yongming Xu, Benjamin Lewis, and Weihe Wendy Guan. 2019. “Developing the Chinese Academic Map Publishing Platform.” ISPRS Int. J. Geo-Inf., 2019, 8, Pp. 567-. Publisher's VersionAbstract
The discipline of the humanities has long been inseparable from the exploration of space and time. With the rapid advancement of digitization, databases, and data science, humanities research is making greater use of quantitative spatiotemporal analysis and visualization. In response to this trend, our team developed the Chinese academic map publishing platform (AMAP) with the aim of supporting the digital humanities from a Chinese perspective. In compiling materials mined from China’s historical records, AMAP attempts to reconstruct the geographical distribution of entities including people, activities, and events, using places to connect these historical objects through time. This project marks the beginning of the development of a comprehensive database and visualization system to support humanities scholarship in China, and aims to facilitate the accumulation of spatiotemporal datasets, support multi-faceted queries, and provide integrated visualization tools. The software itself is built on Harvard’s WorldMap codebase, with enhancements which include improved support for Asian projections, support for Chinese encodings, the ability to handle long text attributes, feature level search, and mobile application support. The goal of AMAP is to make Chinese historical data more accessible, while cultivating collaborative opensource software development.
Paolo Corti, Athanasios Tom Kralidis, and Benjamin Lewis. 2018. “Enhancing discovery in spatial data infrastructures using a search engine.” PeerJ Computer Science, 4, Pp. e152.
Paolo Corti, Benjamin Lewis, and Athanasios Tom Kralidis. 2018. “Hypermap registry: an open source, standards-based geospatial registry and search platform.” Open Geospatial Data, Software and Standards, 3, 1, Pp. 8.
Merrick Lex Berman, Devika Kakkar, Wendy Guan, and Fei Carnes. 8/2/2017. “Enabling Spatiotemporal Analysis and Visualization of Air Pollution in China and India.” In The 25th International Conference on Geoinformatics. Buffalo, NY.
Benjamin Lewis, Weihe Wendy Guan, and Alenka Poplin. 2017. “Evaluating the Current State of Geospatial Software as a Service Platforms: A Comparison Study.” In Citizen Empowered Mapping, Pp. 53-85. Springer. Publisher's VersionAbstract
The goal of this chapter is to evaluate and compare Geospatial Software as a Service (GSaaS) platforms oriented toward providing basic mapping capabilities to non-GIS experts. These platforms allow users to organize spatial materials in layers, perform overlay and basic visual analysis, and share both final maps and the processes used to create them with remote collaborators. The authors gathered data on the characteristics of 15 platforms through an online survey, then summarized the results and created an Excel tool to enable users to sift through the data to identify platforms based on need. This study presents a snapshot of the current GSaaS landscape, summarizes current capabilities, points out weaknesses, and considers the potential of this class of application.