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Browsing by Author "Gyanwali, Sophiya"

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    Implications for spatial non-stationarity and the neighborhood effect averaging problem (NEAP) in green inequality research: evidence from three states in the USA
    Gyanwali, Sophiya; Karki, Shashank; Jang, Kee Moon; Crawford, Thomas W.; Zhang, Mengxi; Kim, Junghwan (Springer, 2024-09-04)
    Recent studies on green space exposure have argued that overlooking human mobility could lead to erroneous exposure estimates and their associated inequality. However, these studies are limited as they focused on single cities and did not investigate multiple cities, which could exhibit variations in people’s mobility patterns and the spatial distribution of green spaces. Moreover, previous studies focused mainly on large-sized cities while overlooking other areas, such as small-sized cities and rural neighborhoods. In other words, it remains unclear the potential spatial non-stationarity issues in estimating green space exposure inequality. To fill these significant research gaps, we utilized commute data of 31,862 people from Virginia, West Virginia, and Kentucky. The deep learning technique was used to extract green spaces from street-view images to estimate people’s home-based and mobility-based green exposure levels. The results showed that the overall inequality in exposure levels reduced when people’s mobility was considered compared to the inequality based on home-based exposure levels, implying the neighborhood effect averaging problem (NEAP). Correlation coefficients between individual exposure levels and their social vulnerability indices demonstrated mixed and complex patterns regarding neighborhood type and size, demonstrating the presence of spatial non-stationarity. Our results underscore the crucial role of mobility in exposure assessments and the spatial non-stationarity issue when evaluating exposure inequalities. The results imply that local-specific studies are urgently needed to develop local policies to alleviate inequality in exposure precisely.
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    Key Drivers of Coastal Relocation in Spatial Clusters Along the US East Coast
    Gyanwali, Sophiya (Virginia Tech, 2024-07-18)
    Coastal flooding has been increasing in frequency and severity across the US East Coast, adversely impacting the human population. Preferred adaptation strategies, such as protection and accommodation, may prove insufficient under current climate change scenarios and projected future sea level rise, prompting the coastal population to consider relocation as a more efficient disaster risk reduction strategy. This study focuses on the flood-prone urban areas along the US East Coast where residents are more willing to relocate due to coastal flooding. Using the survey data, it evaluates the flood experiences, considerations toward relocation, and preferences for relocation destinations. The extent of top concerns influencing respondents' willingness to relocate, such as crime rate, buyout programs, access to critical services and amenities, and availability of comparable housing, were further explored as indirect relocation drivers. Four study locations with heightened relocation potential were identified across urban areas on the US East Coast. Relocation drivers such as crime and limited access to services and amenities are not significantly present in these study locations. However, the absence of buyout programs and affordable housing options in similar communities leaves low-income households trapped in high-risk zones, exacerbating socioeconomic disparities, and increasing the disproportionate risk faced by marginalized populations. The findings have important implications for policymakers, urban planners, and stakeholders involved in climate adaptation and disaster risk reduction efforts. They highlight the need for targeted interventions to address socioeconomic vulnerabilities, promote equitable access to housing, and enhance the resilience of communities facing coastal hazards.