Geography Commons^™

A Novel Big Data Approach To Measure And Visualize Urban Accessibility, Yuqin Jiang, Diansheng Guo, Zhenlong Li, Michael E. Hodgson

Faculty Publications

Accessibility is a topic of interest to multiple disciplines for a long time. In the last decade, the increasing availability of data may have exceeded the development of accessibility modeling approaches, resulting in a modeling gap. In part, this modeling gap may have resulted from the differences needed for single versus multimodal opportunities for access to services. With a focus on large volumes of transportation data, a new measurement approach, called Urban Accessibility Relative Index (UARI), was developed for the integration of multi-mode transportation big data, including taxi, bus, and subway, to quantify, visualize and understand the spatiotemporal patterns of …

Impact Of Metropolization On The Crime Structure (Case Study Of Provincial Capitals In Poland), Natalia Sypion-Dutkowska, Michael Leitner, Marek Dutkowski

Faculty Publications

The aim of this study is to verify the hypothesis that the rapid metropolization process that has been taking place in large Polish cities since the beginning of the second phase of post-communist transition in 2000 leads to their socio-economic diversity, which is manifested, among others, in the differentiation of the level and structure of crime. Introduced into the discourse of this paper are subsequent stages of metropolization, which are called potential, initiating, advanced, and mature and which the examined cities have achieved so far. These stages have led to various economic and social effects, which resulted in changes in …

Assessing Population Exposure To Coastal Flooding Due To Sea Level Rise, Matthew E. Hauer, Dean Hardy, Scott A. Kulp, Valerie Mueller, David J. Wrathall, Peter U. Clark

Faculty Publications

The exposure of populations to sea-level rise (SLR) is a leading indicator assessing the impact of future climate change on coastal regions. SLR exposes coastal populations to a spectrum of impacts with broad spatial and temporal heterogeneity, but exposure assessments often narrowly define the spatial zone of flooding. Here we show how choice of zone results in differential exposure estimates across space and time. Further, we apply a spatio-temporal flood-modeling approach that integrates across these spatial zones to assess the annual probability of population exposure. We apply our model to the coastal United States to demonstrate a more robust assessment …

Regional High-Resolution Benthic Habitat Data From Planet Dove Imagery For Conservation Decision-Making And Marine Planning, Steven R. Schill, Valerie Pietsch Mcnulty, F. Joseph Pollock, Fritjof Lüthje, Jiwei Li, David E. Knapp, Joe D. Kington, Trevor Mcdonald, George T. Raber, Ximena Escovar-Fadul, Gregory P. Asner

Faculty Publications

High-resolution benthic habitat data fill an important knowledge gap for many areas of the world and are essential for strategic marine conservation planning and implementing effective resource management. Many countries lack the resources and capacity to create these products, which has hindered the development of accurate ecological baselines for assessing protection needs for coastal and marine habitats and monitoring change to guide adaptive management actions. The PlanetScope (PS) Dove Classic SmallSat constellation delivers high-resolution imagery (4 m) and near-daily global coverage that facilitates the compilation of a cloud-free and optimal water column image composite of the Caribbean’s nearshore environment. These …

Shape-Based Classification Of Partially Observed Curves, With Applications To Anthropology, Gregory J. Matthews, Karthik Bharath, Sebastian Kurtek, Juliet K. Brophy, George K. Thiruvathukal, Ofer Harel

Faculty Publications

We consider the problem of classifying curves when they are observed only partially on their parameter domains. We propose computational methods for (i) completion of partially observed curves; (ii) assessment of completion variability through a nonparametric multiple imputation procedure; (iii) development of nearest neighbor classifiers compatible with the completion techniques. Our contributions are founded on exploiting the geometric notion of shape of a curve, defined as those aspects of a curve that remain unchanged under translations, rotations and reparameterizations. Explicit incorporation of shape information into the computational methods plays the dual role of limiting the set of all possible completions …

Revealing Public Opinion Towards Covid-19 Vaccines With Twitter Data In The United States: Spatiotemporal Perspective, Tao Hu, Siqin Wang, Wei Luo, Mengxi Zhang, Xiao Huang, Yingwei Yan, Regina Liu, Kelly Ly, Viraj Kacker, Bing She, Zhenlong Li

Faculty Publications

Background: The COVID-19 pandemic has imposed a large, initially uncontrollable, public health crisis both in the United States and across the world, with experts looking to vaccines as the ultimate mechanism of defense. The development and deployment of COVID-19 vaccines have been rapidly advancing via global efforts. Hence, it is crucial for governments, public health officials, and policy makers to understand public attitudes and opinions towards vaccines, such that effective interventions and educational campaigns can be designed to promote vaccine acceptance.

Objective:The aim of this study was to investigate public opinion and perception on COVID-19 vaccines in the United …

Bulk Scanning Method Of A Heavy Metal Concentration In Tailings Of A Gold Mine Using Swir Hyperspectral Imaging System, Yongsik Jeong, Jaehyung Yu, Lei Wang, Kwang Jae Lee

Faculty Publications

This work introduces a bulk data acquisition method using a hyperspectral imaging system (HIS) to measure chromium (Cr) concentration in the soil samples obtained from tailings of a gold mine considering of the spectral competition between heavy metal elements. The chemical, mineralogical, and spectroscopic analyses in a laboratory environment revealed that heavy metal elements' competitive geochemical behaviors were manifested as spectral competitions between heavy metal elements in tailings. The heavy metal elements can be classified into two groups based on their geochemical behaviors: chromium-nickel (Cr-Ni) and zinc-arsenic-cadmium-lead (Zn-As-Cd-Pb). We found an inverse relationship between the two groups in their spectral …

Gap-Filling Of 8-Day Terra Modis Daytime Land Surface Temperature In High-Latitude Cold Region With Generalized Additive Models (Gam), Dianfan Guo, Cuizhen Wang, Shuying Zang, Jinxi Hua, Zhenghan Lv, Yue Lin

Faculty Publications

Land surface temperature (LST) is a crucial parameter driving the dynamics of the thermal state on land surface. In high-latitude cold region, a long-term, stable LST product is of great importance in examining the distribution and degradation of permafrost under pressure of global warming. In this study, a generalized additive model (GAM) approach was developed to fill the missing pixels of the MODIS/Terra 8-day Land Surface Temperature (MODIS LST) daytime products with the ERA5 Land Skin Temperature (ERA5ST) dataset in a high-latitude watershed in Eurasia. Comparison at valid pixels revealed that the MODIS LST was 4.8–13.0 °C higher than ERA5ST, …

Rgb Indices And Canopy Height Modelling For Mapping Tidal Marsh Biomass From A Small Unmanned Aerial System, Grayson R. Morgan, Cuizhen Wang, James T. Morris

Faculty Publications

Coastal tidal marshes are essential ecosystems for both economic and ecological reasons. They necessitate regular monitoring as the effects of climate change begin to be manifested in changes to marsh vegetation healthiness. Small unmanned aerial systems (sUAS) build upon previously established remote sensing techniques to monitor a variety of vegetation health metrics, including biomass, with improved flexibility and affordability of data acquisition. The goal of this study was to establish the use of RGB-based vegetation indices for mapping and monitoring tidal marsh vegetation (i.e., Spartina alterniflora) biomass. Flights over tidal marsh study sites were conducted using a multi-spectral camera on …

Odt Flow: Extracting, Analyzing, And Sharing Multi-Source Multi-Scale Human Mobility, Zhenlong Li, Xiao Huang, Tao Hu, Huan Ning, Xinyue Ye, Binghu Huang, Xiaoming Li

Faculty Publications

In response to the soaring needs of human mobility data, especially during disaster events such as the COVID-19 pandemic, and the associated big data challenges, we develop a scalable online platform for extracting, analyzing, and sharing multi-source multi-scale human mobility flows. Within the platform, an origin-destination-time (ODT) data model is proposed to work with scalable query engines to handle heterogenous mobility data in large volumes with extensive spatial coverage, which allows for efficient extraction, query, and aggregation of billion-level origin-destination (OD) flows in parallel at the server-side. An interactive spatial web portal, ODT Flow Explorer, is developed to allow users …

Spatial Disparities Of Covid-19 Cases And Fatalities In United States Counties, Sarah L. Jackson, Sahar Derakhshan, Leah Blackwood, Logan Lee, Qian Huang, Margot Habets, Susan L. Cutter

Faculty Publications

This paper examines the spatial and temporal trends in county-level COVID-19 cases and fatalities in the United States during the first year of the pandemic (January 2020–January 2021). Statistical and geospatial analyses highlight greater impacts in the Great Plains, Southwestern and Southern regions based on cases and fatalities per 100,000 population. Significant case and fatality spatial clusters were most prevalent between November 2020 and January 2021. Distinct urban–rural differences in COVID-19 experiences uncovered higher rural cases and fatalities per 100,000 population and fewer government mitigation actions enacted in rural counties. High levels of social vulnerability and the absence of mitigation …

Measuring Global Multi-Scale Place Connectivity Using Geotagged Social Media Data, Zhenlong Li, Xiao Huang, Xinyue Ye, Yuqin Jiang, Yago Martin, Huan Ning, Michael E. Hodgson, Xiaoming Li

Faculty Publications

Shaped by human movement, place connectivity is quantified by the strength of spatial interactions among locations. For decades, spatial scientists have researched place connectivity, applications, and metrics. The growing popularity of social media provides a new data stream where spatial social interaction measures are largely devoid of privacy issues, easily assessable, and harmonized. In this study, we introduced a global multi-scale place connectivity index (PCI) based on spatial interactions among places revealed by geotagged tweets as a spatiotemporal-continuous and easy-to-implement measurement. The multi-scale PCI, demonstrated at the US county level, exhibits a strong positive association with SafeGraph population movement records …

Measuring Global Multi-Scale Place Connectivity Using Geotagged Social Media Data, Zhenlong Li, Xiao Huang, Yuqin Jiang, Yago Martin, Huan Ning, Michael E. Hodgson, Xiaoming Li

Faculty Publications

Shaped by human movement, place connectivity is quantified by the strength of spatial interactions among locations. For decades, spatial scientists have researched place connectivity, applications, and metrics. The growing popularity of social media provides a new data stream where spatial social interaction measures are largely devoid of privacy issues, easily assessable, and harmonized. In this study, we introduced a global multi-scale place connectivity index (PCI) based on spatial interactions among places revealed by geotagged tweets as a spatiotemporal-continuous and easy-to-implement measurement. The multi-scale PCI, demonstrated at the US county level, exhibits a strong positive association with SafeGraph population movement records …

Resettlement Capacity Assessments For Climate Induced Displacements: Evidence From Ethiopia, Solomon Zena Walelign, Susan L. Cutter, Paivi Lujala

Faculty Publications

Climate change migration is increasing and necessitates a re-examination of resettlement planning and processes. Although evidence-based selection of host places would improve climate change resettlement outcomes, few methods for the selection of host communities exist. Consequently, the information base on which most resettlement programs select a host place is often inadequate. This article proposes an empirical methodology to assess resettlement capacity. The methodology uses a hierarchical aggregation approach, where resettlement capacity indicator values are aggregated first into sub-dimension resettlement capacity scores, then further into dimension resettlement capacity scores, and finally into an overall resettlement capacity index. The aggregation allows for …

An Operational Overview Of The Export Processes In The Ocean From Remote Sensing (Exports) Northeast Pacific Field Deployment, David A. Siegel, Ivona Cetinić, Jason R. Graff, Craig M. Lee, Norman Nelson, Mary Jane Perry, Inia Soto Ramos, Deborah K. Steinberg, Ken Buesseler, Roberta Hamme, Andrea J. Fassbender, David Nicholson, Melissa M. Omand, Marie Robert, Andrew Thompson, Vinicius Amaral, Michael Behrenfeld, Claudia Benitez-Nelson, Kelsey Bisson, Emmanuel Boss, Philip W. Boyd, Mark Brzezinski, Kristen Buck

Faculty Publications

The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with …

Analyzing Satellite Ocean Color Match-Up Protocols Using The Satellite Validation Navy Tool (Savant) At Moby And Two Aeronet-Oc Sites, Adam Lawson, Jennifer Bowers, Sherwin Ladner, Richard Crout, Christopher Wood, Robert Arnone, Paul Martinolich, David Lewis

Faculty Publications

The satellite validation navy tool (SAVANT) was developed by the Naval Research Laboratory to help facilitate the assessment of the stability and accuracy of ocean color satellites, using numerous ground truth (in situ) platforms around the globe and support methods for match-up protocols. The effects of varying spatial constraints with permissive and strict protocols on match-up uncertainty are evaluated, in an attempt to establish an optimal satellite ocean color calibration and validation (cal/val) match-up protocol. This allows users to evaluate the accuracy of ocean color sensors compared to specific ground truth sites that provide continuous data. Various match-up constraints may …

Per-Pixel Cloud Cover Classification Of Multispectral Landsat-8 Data, Salome E. Carrasco, Torrey J. Wagner, Brent T. Langhals

Faculty Publications

Random forest and neural network algorithms are applied to identify cloud cover using 10 of the wavelength bands available in Landsat 8 imagery. The methods classify each pixel into 4 different classes: clear, cloud shadow, light cloud, or cloud. The first method is based on a fully connected neural network with ten input neurons, two hidden layers of 8 and 10 neurons respectively, and a single-neuron output for each class. This type of model is considered with and without L2 regularization applied to the kernel weighting. The final model type is a random forest classifier created from an ensemble of …

Suas For 3d Tree Surveying: Comparative Experiments On A Closed-Canopy Earthen Dam, Cuizhen Wang, Grayson R. Morgan, Michael E. Hodgson

Faculty Publications

Defined as “personal remote sensing”, small unmanned aircraft systems (sUAS) have been increasingly utilized for landscape mapping. This study tests a sUAS procedure of 3D tree surveying of a closed-canopy woodland on an earthen dam. Three DJI drones—Mavic Pro, Phantom 4 Pro, and M100/RedEdge-M assembly—were used to collect imagery in six missions in 2019–2020. A canopy height model was built from the sUAS-extracted point cloud and LiDAR bare earth surface. Treetops were delineated in a variable-sized local maxima filter, and tree crowns were outlined via inverted watershed segmentation. The outputs include a tree inventory that contains 238 to 284 trees …

Spatiotemporal Patterns Of Human Mobility And Its Association With Land Use Types During Covid-19 In New York City, Yuqin Jiang, Xiao Huang, Zhenlong Li

Faculty Publications

The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in New York City. With New York City open data, human mobility pattern changes were detected by different categories of land use, including residential, parks, transportation facilities, and workplaces. This study further compares human mobility patterns by …

Assessment Of Normalized Water-Leaving Radiance Derived From Goci Using Aeronet-Oc Data, Mingjun He, Shuangyan He, Xiaodong Zhang, Feng Zhou, Peiliang Li

Faculty Publications

The geostationary ocean color imager (GOCI), as the world’s first operational geostationary ocean color sensor, is aiming at monitoring short-term and small-scale changes of waters over the northwestern Pacific Ocean. Before assessing its capability of detecting subdiurnal changes of seawater properties, a fundamental understanding of the uncertainties of normalized water-leaving radiance (nLw) products introduced by atmospheric correction algorithms is necessarily required. This paper presents the uncertainties by accessing GOCI-derived nLw products generated by two commonly used operational atmospheric algorithms, the Korea Ocean Satellite Center (KOSC) standard atmospheric algorithm adopted in GOCI Data Processing System (GDPS) and the NASA standard atmospheric …

High-Latitude Snowfall As A Sensitive Indicator Of Climate Warming: A Case Study Of Heilongjiang Province, China, Lijuan Zhang, Cuizhen Wang, Yongshen Li, Yutao Huang, Fan Zhang, Tao Pan

Faculty Publications

While global distribution and dynamics of snow extent and snow depth have been intensely studied, the response of snowfall events to global warming is complex and remains unclear in current literature. This study explores historical snowfall records since the 1960s at 62 meteorological stations in Heilongjiang Province, and examines the snowfall responses in this most northerly high-latitude snow zone of China. Results confirm a significant increase of annual average temperature with a turn-over year in 1987, representing a shift of a cooler to warmer climate. Our study reports five most sensitive snowfall indicators of the warmer climate: snow intensity, snow …

Synoptic Atmospheric Circulation Patterns Associated With Deep Persistent Slab Avalanches In The Western United States, Andrew R. Schauer, Jordy Hendrikx, Karl W. Birkeland, Cary J. Mock

Faculty Publications

Deep persistent slab avalanches are capable of destroying infrastructure and are usually unsurvivable for those who are caught. Formation of a snowpack conducive to deep persistent slab avalanches is typically driven by meteorological conditions occurring in the beginning weeks to months of the winter season, and yet the avalanche event may not occur for several weeks to months later. While predicting the exact timing of the release of deep persistent slab avalanches is difficult, onset of avalanche activity is commonly preceded by rapid warming, heavy precipitation, or high winds. This work investigates the synoptic drivers of deep persistent slab avalanches …

Urban-Rural Differences In Covid-19 Exposures And Outcomes In The South: A Preliminary Analysis Of South Carolina, Qian Huang, Sarah Jackson, Sahar Derakhshan, Logan Lee, Erika Pham, Amber Jackson, Susan L. Cutter

Faculty Publications

As the COVID-19 pandemic moved beyond the initial heavily impacted and urbanized Northeast region of the United States, hotspots of cases in other urban areas ensued across the country in early 2020. In South Carolina, the spatial and temporal patterns were different, initially concentrating in small towns within metro counties, then diffusing to centralized urban areas and rural areas. When mitigation restrictions were relaxed, hotspots reappeared in the major cities. This paper examines the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1st—September 5th, 2020. We first describe the initial diffusion of the …

Applying Spatial Video Geonarratives And Physiological Measurements To Explore Perceived Safety In Baton Rouge, Louisiana, Alina Ristea, Michael Leitner, Bernd Resch, Judith Stratmann

Faculty Publications

Spatial crime analysis, together with perceived (crime) safety analysis have tremendously benefitted from Geographic Information Science (GISc) and the application of geospatial technology. This research study discusses a novel methodological approach to document the use of emerg-ing geospatial technologies to explore perceived urban safety from the lenses of fear of crime or crime perception in the city of Baton Rouge, USA. The mixed techniques include a survey, spatial video geonarrative (SVG) in the field with study participants, and the extraction of moments of stress (MOS) from biosensing wristbands. This study enrolled 46 participants who completed geonarratives and MOS detection. A …

An Evaluation Of The Performance Of The Twentieth Century Reanalysis Version 3, L. C. Slivinski, G. P. Compo, P. D. Sardeshmukh, J. S. Whitaker, C. Mccoll, R. J. Allan, P. Brohan, X. Yin, C. A. Smith, L. J. Spencer, R. S. Vose, M. Rohrer, R. P. Conroy, D. C. Schuster, J. J. Kennedy, L. Ashcroft, S. Brönnimann, M. Brunet, D. Camuffo, R. Cornes, T. A. Cram, F. Domínguez-Castro, J. E. Freeman, J. Gergis, E. Hawkins, P. D. Jones, H. Kubota, T. C. Lee, A, M. Lorrey, J. Luterbacher, Cary J. Mock, R. K. Przybylak, C. Pudmenzky, V. C. Slonosky, B. Tinz, B. Trewin, X. L. Wang, C. Wilkinson, K. Wood, P. Wyszyński

Faculty Publications

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a ‘‘best estimate’’ of the weather, including extreme events, it also provides an …

Measuring Building Height Using Point Cloud Data Derived From Unmanned Aerial System Imagery In An Undergraduate Geospatial Science Course, David L. Kulhavy, I-Kuai Hung, Daniel R. Unger, Reid Viegut, Yanli Zhang

Faculty Publications

The use of Unmanned Aerial Systems (UAS), also known as drones is increasing in geospatial science curricula within the United States. Within the Arthur Temple College of Forestry and Agriculture (ATCOFA) at Stephen F. Austin State University, Texas, seniors in the geospatial science program complete capstone projects to evaluate current geospatial technology to investigate complex ecological, social and environmental issues. Under the umbrella of a student initiated and designed senior project, students designed a study to estimate height of buildings with UAS data incorporating UAS data, LP360 and ArcScene programs, and Pictometry web-based interface. Results from a statistical analysis of …

Datos Preliminares De La Temporada 2019 Del Proyecto De Investigación Arqueológica Cerro San Isidro, Distrito De Moro, Ancash, David Chicoine, Jeisen Navarro

Faculty Publications

No abstract provided.

Content Controlled Spectral Indices For Detection Of Hydrothermal Alteration Minerals Based On Machine Learning And Lasso-Logistic Regression Analysis, Kyuhun Shim, Jaehyung Yu, Lei Wang, Sangin Lee, Sang Mo Koh, Bum Han Lee

Faculty Publications

This article introduced the quantity controlled spectral indices working at mineral contents higher than 5 wt.% for detection of sericite, chlorite, and pyrophyllite, which are the representative alteration minerals of phyllic, propylitic, and advanced argillic hydrothermal alterations. The X-ray diffraction analysis revealed that the samples are mostly pure with minor content of quartz. The absorption features of target minerals showed systematic decrease in absorption depth with decrease in the mineral content, and the changes varied by mineral types. A total of 1253 target mineral spectra and 605 nontarget mineral spectra were classified by a random forest model, which achieved an …

A Short Text Classification Method Based On Convolutional Neural Network And Semantic Extension, Haitao Wang, Keke Tian, Zhengjiang Wu, Lei Wang

Faculty Publications

In order to solve the problem that traditional short text classification methods do not perform well on short text due to the data sparsity and insufficient semantic features, we propose a short text classification method based on convolutional neural network and semantic extension. Firstly, we propose an improved similarity to improve the coverage of the word vector table in the short text preprocessing process. Secondly, we propose a method for semantic expansion of short texts, which adding an attention mechanism to the neural network model to find related words in the short text, and semantic expansion is performed at the …

Mapping Flat, Deep, And Slow: On The 'Spirit Of Place' In New Cinema History, Jeffrey Klenotic

Faculty Publications

This essay engages in a creative, heuristic, and reflexive consideration of the ‘localities’ of cinema audiences by exploring New Cinema History as a place. New Cinema History is conceptualised as a place continually produced in and through its interactions with the heterogeneous multiplicities of situated audiences and experiences of cinema that form the topoi of its landscape of inquiry. In reflecting on how this placialised landscape has been and might be represented, I argue that New Cinema History’s ‘spirit of place’ is most productive when rendered within a ‘splatial’ framework that draws upon practices of flat, deep, and slow mapping …