Social and Behavioral Sciences Commons^™

The Town That Built Its Own River: La Plaza Del Cerro At Taos County New Mexico, José A. Rivera Ph.D

Faculty Publications

Cerro is an unincorporated community in Taos County, New Mexico, and is situated near New Mexico State Highway 522 heading north to the Colorado border. Nearby is Cerro de Guadalupe, a peak that has an elevation of 8,796 feet and Cerro at 7,490 feet. The connection to Guadalupe Mountain gave the town its original name as “La Plaza del Cerro de Guadalupe.” Cerro was established in the early 1850s by settlers who arrived from nearby Questa and Taos. By itself, Guadalupe Mountain did not provide sufficient water to sustain an agrarian economy based on farming and livestock ranching as was …

Informe Tecnico De Los Trabajos De Campo Del Proyecto De Investigación Arqueológica Cerro San Isidro, Valle De Nepeña, Costa De Ancash -- Temporada 2022, David Chicoine, Jeisen Navarro

Faculty Publications

No abstract provided.

The Role Of A Green Bank In South Carolina: A Market & Feasibility Assessment, Jory Fleming, Claire Windsor

Faculty Publications

A market and feasibility report that explores the role of a green bank in South Carolina. This report is the culmination of a multi-year process that included a comprehensive market assessment and interviews with over 60 organizations across South Carolina. It demonstrates that a green bank could play a vital role in South Carolina by creating a dedicated institution working to accelerate the flow of capital to projects that seek to reduce carbon pollution and increase resilience to climate impacts.

Composite Style Pixel And Point Convolution-Based Deep Fusion Neural Network Architecture For The Semantic Segmentation Of Hyperspectral And Lidar Data, Kevin T. Decker, Brett J. Borghetti

Faculty Publications

Multimodal hyperspectral and lidar data sets provide complementary spectral and structural data. Joint processing and exploitation to produce semantically labeled pixel maps through semantic segmentation has proven useful for a variety of decision tasks. In this work, we identify two areas of improvement over previous approaches and present a proof of concept network implementing these improvements. First, rather than using a late fusion style architecture as in prior work, our approach implements a composite style fusion architecture to allow for the simultaneous generation of multimodal features and the learning of fused features during encoding. Second, our approach processes the higher …

Structural Problems Of Latin American Cities 450 Years After Caracas’ Foundation, Fabio Capra-Ribeiro

Faculty Publications

Latin American cities face many problems that compromise them from different angles such as lack of infrastructure, government fragmentation, and environmental degradation. At the same time, each city tries to come up with its own solutions, but there are so many difficulties that in many cases it is difficult to keep attention and efforts focused on all these directions. For these reasons, this research aims to define some of the most common problems faced by cities in Latin America. Disseminating these similarities could help to face those problems, since, if local governments recognize that they face the same situations as …

Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam

Faculty Publications

Lack of instrument sensitivity to low electron density (N_e) concentration makes it difficult to measure sharp N_e vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region N_e from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …

A Comparison Of Sporadic-E Occurrence Rates Using Gps Radio Occultation And Ionosonde Measurements, Rodney Carmona, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

Sporadic-E (E_s) occurrence rates from Global Position Satellite radio occultation (GPS-RO) measurements have shown to vary by a factor of five between studies, motivating the need for a comparison with ground-based measurements. In an attempt to find accurate GPS-RO techniques for detecting E_s formation, occurrence rates derived using five previously developed GPS-RO techniques are compared to ionosonde measurements over an eight-year period from 2010–2017. GPS-RO measurements within 170 km of a ionosonde site are used to calculate E_s occurrence rates and compared to the ground-truth ionosonde measurements. The techniques are compared individually for each ionosonde site …

The Times, They Are A-Changin’: Tracking Shifts In Mental Health Signals From Early Phase To Later Phase Of The Covid-19 Pandemic In Australia, Siqin Wang, Xiao Huang, Tao Hu, Mengxi Zhang, Zhenlong Li, Huan Ning, Jonathan Corcoran, Asaduzzaman Khan, Yan Liu, Jiajia Zhang Ph.D., Xiaoming Li Ph.D.

Faculty Publications

Introduction Widespread problems of psychological distress have been observed in many countries following the outbreak of COVID-19, including Australia. What is lacking from current scholarship is a national-scale assessment that tracks the shifts in mental health during the pandemic timeline and across geographic contexts.

Methods Drawing on 244 406 geotagged tweets in Australia from 1 January 2020 to 31 May 2021, we employed machine learning and spatial mapping techniques to classify, measure and map changes in the Australian public’s mental health signals, and track their change across the different phases of the pandemic in eight Australian capital cities.

Results Australians’ …

Unmanned Aerial Remote Sensing Of Coastal Vegetation: A Review, Grayson R. Morgan, Michael E. Hodgson, Cuizhen Wang, Steven R. Schill

Faculty Publications

Coastal wetlands contribute greatly to our coasts economically and ecologically. The utility of coastal wetland vegetation, along with the multitude of dynamic forces they encounter, suggests the need of regular monitoring for sustainable management. While traditional in situ survey methods and remote sensing from space and manned platforms have provided means to monitor and study the coastal zone thus far, the recent developments of small unmanned aerial systems (sUAS) fill a small void between traditional in situ survey methods and the high spatial resolution of manned aircraft imagery. As an on-demand personal remote sensing device, an sUAS can be deployed …

‘Big’ And ‘Little’ Quo Vadis? In The United States, 1913–1916: Using Gis To Map Rival Modes Of Feature Cinema During The Transitional Era, Jeffrey Klenotic

Faculty Publications

This article emanates from a geospatial database of over 600 premieres of the Cines company’s Quo Vadis? (1913), an eight-reel film distributed by George Kleine, and nearly 250 premieres of the Quo Vadis Film Company’s Quo Vadis? (1913), a three-reel film of ambiguous origins distributed by Paul De Outo. By mapping local premieres of both films across the United States from 1913 through 1916, the data show with spatiotemporal precision the spread of Quo Vadis? as one of cinema’s early blockbuster titles. Yet within this national phenomenon, the two films’ footprints reveal differing cultural geographies served by competing efforts to …

Machine Learning Land Cover And Land Use Classification Of 4-Band Satellite Imagery, Lorelei Turner [*], Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

Land-cover and land-use classification generates categories of terrestrial features, such as water or trees, which can be used to track how land is used. This work applies classical, ensemble and neural network machine learning algorithms to a multispectral remote sensing dataset containing 405,000 28x28 pixel image patches in 4 electromagnetic frequency bands. For each algorithm, model metrics and prediction execution time were evaluated, resulting in two families of models; fast and precise. The prediction time for an 81,000-patch group of predictions wasmodels, and >5s for the precise models, and there was not a significant change in prediction time when a …

At-Sensor Radiometric Correction Of A Multispectral Camera (Rededge) For Suas Vegetation Mapping, Cuizhen Wang

Faculty Publications

Rapid advancement of drone technology enables small unmanned aircraft systems (sUAS) for quantitative applications in public and private sectors. The drone-mounted 5-band MicaSense RedEdge cameras, for example, have been popularly adopted in the agroindustry for assessment of crop healthiness. The camera extracts surface reflectance by referring to a pre-calibrated reflectance panel (CRP). This study tests the performance of a Matrace100/RedEdge-M camera in extracting surface reflectance orthoimages. Exploring multiple flights and field experiments, an at-sensor radiometric correction model was developed that integrated the default CRP and a Downwelling Light Sensor (DLS). Results at three vegetated sites reveal that the current CRP-only …

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 …

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 …

Using Mobile Device Data To Track The Effects Of The Covid-19 Pandemic On Spatiotemporal Patterns Of National Park Visitation, John A. Kupfer, Zhenlong Li, Huan Ning, Xiao Huang

Faculty Publications

Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices and released by SafeGraph as part of their Social Distancing Metric dataset. Based on comparisons with visitation statistics released by the U.S. National Park Service, our results confirmed that mobility records from digital devices can effectively capture park visitation patterns but with much finer spatiotemporal granularity. In general, triggers …

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 …

Using Mobile Device Data To Track The Effects Of The Covid-19 Pandemic On Spatiotemporal Patterns Of National Park Visitation, John A. Kupfer, Zhenlong Li, Huan Ning, Xiao Huang

Faculty Publications

Effective quantification of visitation is important for understanding many impacts of the COVID-19 pandemic on national parks and other protected areas. In this study, we mapped and analyzed the spatiotemporal patterns of visitation for six national parks in the western U.S., taking advantage of large mobility records sampled from mobile devices and released by SafeGraph as part of their Social Distancing Metric dataset. Based on comparisons with visitation statistics released by the U.S. National Park Service, our results confirmed that mobility records from digital devices can effectively capture park visitation patterns but with much finer spatiotemporal granularity. In general, triggers …

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 …

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 …

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 …

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 …

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, Ml Rohrer, R. P. Conroy, D. C. Schuster, J. J. Kennedy, K. 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, C. 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 …

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.

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 …