{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:05:13Z","timestamp":1760238313613,"version":"build-2065373602"},"reference-count":34,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,7,31]],"date-time":"2020-07-31T00:00:00Z","timestamp":1596153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Adverse weather poses a significant threat to the serviceability of highway infrastructure, as it causes more frequent and severe crash incidents. This study focuses on evaluating the resilience of highway networks by examining the crash-induced safety impact in response to extreme weather events. Unlike traditional service drop-based methods for resilience evaluation, this study endeavors to evaluate highway resilience in a spatial context. Three spatial metrics, including K-nearest neighbors, proximity to highways, and Kernel density hot spot, are introduced and employed to compare and analyze the spatial patterns (magnitude and distribution) of crashes in pre- and post-weather conditions. An illustrative example is also provided to showcase the applications of the proposed spatial resilience metrics for two study areas in the State of Illinois, U.S. The contribution of this study is to provide transportation practitioners with a tool to evaluate highway spatial resilience both visually and quantitatively, and ultimately improve highway safety and operation.<\/jats:p>","DOI":"10.3390\/ijgi9080480","type":"journal-article","created":{"date-parts":[[2020,7,31]],"date-time":"2020-07-31T04:15:31Z","timestamp":1596168931000},"page":"480","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation of Spatial Resilience of Highway Networks in Response to Adverse Weather Conditions"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0882-6590","authenticated-orcid":false,"given":"Fei","family":"Han","sequence":"first","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, The University of New Mexico, MSC01 1070, Albuquerque, NM 87131-0001, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0396-2518","authenticated-orcid":false,"given":"Su","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Civil, Construction and Environmental Engineering, The University of New Mexico, MSC01 1070, Albuquerque, NM 87131-0001, USA"},{"name":"Earth Data Analysis Center, The University of New Mexico, MSC01 1110, Albuquerque, NM 87131-0001, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.3141\/2055-16","article-title":"Effects of adverse weather on traffic crashes: Systematic review and meta-analysis","volume":"2055","author":"Qiu","year":"2008","journal-title":"Transp. Res. Rec."},{"key":"ref_2","unstructured":"Meyer, M.D., Rowan, E., Snow, C., and Choate, A. (2013). Impacts of Extreme Weather on Transportation: National Symposium Summary, American Association of State Highway and Transportation Officials."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1177\/0361198106194800119","article-title":"Whether weather matters to traffic demand, traffic safety, and traffic operations and flow","volume":"1948","author":"Maze","year":"2006","journal-title":"Transp. Res. Rec."},{"key":"ref_4","unstructured":"FHWA, Federal Highway Administration (2020, February 25). How Do Weather Events Impact Roads?, Available online: https:\/\/ops.fhwa.dot.gov\/weather\/q1_roadimpact.htm."},{"key":"ref_5","unstructured":"OCIA (2020, February 17). Critical Infrastructure Security and Resilience Note: Winter Storms and Critical Infrastructure. Available online: http:\/\/www.npstc.org\/download.jsp?tableId=37&column=217&id=3277&file=OCIA_Winter_Storms_and_Critical_Infrastructure_141215.pdf."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"44","DOI":"10.3141\/2604-06","article-title":"Review of Performance Metrics for Community-Based Planning for Resilience of the Transportation System","volume":"2604","author":"Goodchild","year":"2017","journal-title":"Transp. Res. Rec."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"04017004","DOI":"10.1061\/AJRUA6.0000908","article-title":"Novel probabilistic resilience assessment framework of transportation networks against extreme weather events","volume":"3","author":"Nogal","year":"2017","journal-title":"ASCE-ASME J. Risk Uncertain. Eng. Syst. Part A Civ. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1061\/(ASCE)TE.1943-5436.0000415","article-title":"Freight resilience measures","volume":"138","author":"Adams","year":"2012","journal-title":"J. Transp. Eng."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e1701079","DOI":"10.1126\/sciadv.1701079","article-title":"Resilience and efficiency in transportation networks","volume":"3","author":"Ganin","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.jtrangeo.2019.04.006","article-title":"Rail network resilience and operational responsiveness during unplanned disruption: A rail freight case study","volume":"77","author":"Woodburn","year":"2019","journal-title":"J. Transp. Geogr."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.jtrangeo.2015.05.006","article-title":"Assessing the role of network topology in transportation network resilience","volume":"46","author":"Zhang","year":"2015","journal-title":"J. Transp. Geogr."},{"key":"ref_12","unstructured":"Pisano, P.A., Goodwin, L.C., and Rossetti, M.A. (2008, January 20\u201324). US highway crashes in adverse road weather conditions. Proceedings of the 24th Conference on International Interactive Information and Processing Systems for Meteorology, Oceanography and Hydrology, New Orleans, LA, USA."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1061\/(ASCE)0733-947X(2008)134:5(191)","article-title":"Spatial analysis of weather crash patterns","volume":"134","author":"Khan","year":"2008","journal-title":"J. Transp. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.jtrangeo.2009.05.002","article-title":"Long-term trends in weather-related crash risks","volume":"18","author":"Andrey","year":"2010","journal-title":"J. Transp. Geogr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/S0001-4575(02)00148-3","article-title":"Selecting exposure measures in crash rate prediction for two-lane highway segments","volume":"36","author":"Qin","year":"2004","journal-title":"Accid. Anal. Prev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s40534-015-0068-0","article-title":"Identification of crash hotspots using kernel density estimation and kriging methods: A comparison","volume":"23","author":"Thakali","year":"2015","journal-title":"J. Mod. Transp."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1016\/j.aap.2018.10.014","article-title":"Accident risk of road and weather conditions on different road types","volume":"122","author":"Malin","year":"2019","journal-title":"Accid. Anal. Prev."},{"key":"ref_18","unstructured":"Carson, J.L. (2010). Best Practices in Traffic Incident Management (No. FHWA-HOP-10-050), Federal Highway Administration, Office of Transportation Operations."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.foreco.2012.02.002","article-title":"A nearest-neighbor imputation approach to mapping tree species over large areas using forest inventory plots and moderate resolution raster data","volume":"271","author":"Wilson","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1109\/TITS.2015.2498408","article-title":"Improvement of search strategy with k-nearest neighbors approach for traffic state prediction","volume":"17","author":"Oh","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.trc.2015.11.002","article-title":"A spatiotemporal correlative k-nearest neighbor model for short-term traffic multistep forecasting","volume":"62","author":"Cai","year":"2016","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1108\/PIJPSM-04-2013-0039","article-title":"Kernel density estimation and hotspot mapping","volume":"37","author":"Hart","year":"2014","journal-title":"Policing: An International J. Police Strateg. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/j.aap.2008.12.014","article-title":"Kernel density estimation and K-means clustering to profile road accident hotspots","volume":"41","author":"Anderson","year":"2009","journal-title":"Accid. Anal. Prev."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.jtrangeo.2013.05.009","article-title":"Detecting traffic accident clusters with network kernel density estimation and local spatial statistics: An integrated approach","volume":"31","author":"Xie","year":"2013","journal-title":"J. Transp. Geogr."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"684","DOI":"10.1177\/0361198119845367","article-title":"Case study of crash severity spatial pattern identification in hot spot analysis","volume":"2673","author":"Lee","year":"2019","journal-title":"Transp. Res. Rec."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.jtrangeo.2016.11.011","article-title":"Spatial investigation of aging-involved crashes: A GIS-based case study in Northwest Florida","volume":"58","author":"Ulak","year":"2017","journal-title":"J. Transp. Geogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1038\/nclimate2227","article-title":"Changing the resilience paradigm","volume":"4","author":"Linkov","year":"2014","journal-title":"Nat. Clim. Chang."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.aap.2014.06.017","article-title":"A review of the effect of traffic and weather characteristics on road safety","volume":"72","author":"Theofilatos","year":"2014","journal-title":"Accid. Anal. Prev."},{"key":"ref_29","unstructured":"(2020, February 17). National Weather Service, Available online: https:\/\/www.weather.gov\/."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"623","DOI":"10.1016\/j.jsr.2008.10.008","article-title":"Differences in urban and rural accident characteristics and medical service utilization for traffic fatalities in less-motorized societies","volume":"39","author":"Li","year":"2008","journal-title":"J. Saf. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1136\/ip.2004.005959","article-title":"Fatal motor vehicle crashes in rural and urban areas: Decomposing rates into contributing factors","volume":"11","author":"Zwerling","year":"2005","journal-title":"Inj. Prev."},{"key":"ref_32","unstructured":"Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis, CRC press."},{"key":"ref_33","unstructured":"Levine, N. (2004). CrimeStat III: A Spatial Statistics Program for the Analysis of Crime Incident Locations (Version 3.0)."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4","DOI":"10.5038\/2375-0901.11.2.4","article-title":"Hazardous bus stops identification: An illustration using GIS","volume":"11","author":"Pulugurtha","year":"2008","journal-title":"J. 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