Abstract
Coastal communities are increasingly vulnerable to changes in climate and weather, as well as sea-level rise and coastal erosion. The impact of these hazards can be very costly, and not just in terms of property damage, but also in lost revenue as many coastal communities are also tourism-based economies. The goal of this study is to investigate the awareness and attitudes of full-time residents and second-home property owners regarding the impact of climate and weather on property ownership and to identify the factors that most influences these attitudes in three coastal counties (Brunswick, Currituck, and Pender) of North Carolina, USA. The majority of previous studies have focused on only full-time residents’ risk perceptions. Given the fact that these coastal communities have a high percentages of second homes, this study fills that research gap by including second-home owners. This study integrates both social (survey data) and physical (geospatial coastal hazards data) aspects of vulnerability into a single assessment to understand the determinants of property owners’ risk perceptions and compare their perceived risks with their physical vulnerability. The study also compared the utility of a global ordinary least square (OLS) model with a local geographically weighted regression (GWR) model to identify explanatory variables in the dataset. The GWR was found to be a slightly better fit for the data with an R2 of 0.248 (compared to 0.206 for the OLS). However, this was still relatively low and indicated that this study likely did not capture all of the factors that influence the perceptions of vulnerability in patterns of property ownership (whether full-time residents or second-home owners). The geospatial variables used to determine coastal vulnerability were found not to significantly impact perceptions related property ownership, but did provide additional insight in explaining spatial patterns of the response variable within each county.
Highlights
The coast of North Carolina is subject to severe weather events, erosion, and flooding in the low-lying coastal plain
This paper investigates the relationships between the dependent variable and a range of independent variables such as changes in temperature and/or humidity, availability of freshwater, sea level and flooding, demographic characteristics, sense of place, sustainability perceptions, slosh, erosion, and flood information in it
Comparing the fit of the global ordinary least squares (OLS) model assuming homogeneity of variables across the study area and local geographically weighted regression (GWR) model with no assumption of homogeneity, we found that the global OLS model produced adjusted R2 value of was 0.206
Summary
The coast of North Carolina is subject to severe weather events, erosion, and flooding in the low-lying coastal plain This can be costly to state and federal governments and leave communities with infrastructure and property damage. Geo-Inf. 2020, 9, x FOR PEER REVIEW ecosystems [4,5] These environmental risks contrast with the attraction of NC’s coastal communities to touristscaonstdanreessitidmeantetds a$2li4kbei.lliTonhi[s1]s. TOuvderyalsl,etehkesAttolanatsiccearntdaiGnulwf choaatstfsahcatvoersexihnibfliuteednacneinthcreeapseerinceptions of full-time rtersoipdiceanl sttsoramndacstievcitoynsidnacerythhe o19m90eso, lweandeinrgs troelgoangrderintegrmthimepeaffctescotns tbhotaht ccolaismtaal tceomamndunwitieesather risks and ecosystems [4,5] These environmental risks contrast with the attraction of NC’s coastal have on prcoompemrutynitoiews ntoetrosuhriispts. This study seeks to ascertain what factors influence the Reseaprecrhcepstiuongsgoefsftusll-ttihmee reimsidpenotrstaanndcseecoonfdacroymhommeuonwintyers mregeamrdbinegrthpe eerffceectpsttihoant cslimoaftecalnidmatic and weather-rewlaeattehder rriisskkssh,aivne oandpdroitpieornty toownsecrisehnipt.ific knowledge and measurements of these risks [6,7] This is due to rRiesskeaprcehrcseupggtieostnssthaessimocpioarttaendcewoiftchomwmeautnhiteyrmaenmdbcerlipmeracteeptiinoflnsuoefnccliimngatirceaancdtiwoneasthtoer-policy and related risks, in addition to scientific knowledge and measurements of these risks [6,7]. This is due to decisions mrisakdpeeracetptthioensloacsasolc, isatteadtew, iathndwefaetdheerraanl dlecvliemlsat.eTinhfeluseencinincgluredacet:iornesatdoipnoeliscsytaondevdaecciusiaotnes in case of storms, mimtiagdaetiaot nthaenlodcapl,rsetpatae,rantidonfedeeffraolrltesv,ealsn. dThflesuecitnucalutdioe:nrseaindinpersosptoeretvyacvuatleuiens.case of storms, This smtiutidgaytiotnaragnedtpsretpharreaetiohniegfhfo-ratsm, aenndiftlyu,cttuoautiorinssti-nbparsoepdertcyovaaslutaels.communities in North Carolina: Brunswick, CuThrrisitsutucdky, atanrgdetPs ethnrdeeerhicgohu-anmteineisty(,Ftioguurirste-b1a)s.edBceocaasutasl ecoBmrmuunnsiwtieisckin, NCourrthritCuacrokl,inaan: d Pender
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