Search

Physical and climatic variables such as Tree Canopy coverage, Normalized Difference Vegetation Index (NDVI), Distance to Roads, Distance to the Coast, Impervious Surface, and Precipitation can affect land surface temperature (LST). This paper examines the relationships using linear regression models and explores LST trends in the Miami Statistical Area (MSA) between 2002 and 2021. This study evaluates the effect of dry and wet seasons as well as day and night data on LST. A multiscale investigation is used to examine LST trends at the MSA scale, the individual county level, and at the pixel level to provide a detailed local perspective. The multiscale results are needed to understand spatiotemporal LST distributions to plan mitigation measures such as planting trees or greenery to regulate temperature and reduce the impacts of surface urban heat islands. The results indicate that LST values are rising in the MSA with a positive trend throughout the 20-year study period. The rate of change (RoC) for the wet season is smaller than for the dry season. The pixel-level analysis suggests that the RoC is primarily in rural areas and less apparent in urban areas. New development in rural areas may trigger increased RoC. This RoC relates to LST in the MSA and is different from global or regional RoC using air temperature. Results also suggest that climatic explanatory variables have different impacts during the night than they do in the daytime. For instance, the Tree Canopy variable has a positive coefficient, while during the day, the Tree Canopy variable has a negative relationship with LST. The Distance to the Coast variable changes from day to night as well. The increased granularity achieved with the multiscale analysis provides critical information needed to improve the effectiveness of potential mitigation efforts. [ABSTRACT FROM AUTHOR]

Steam-assisted gravity oil drainage (SAGD flooding) is a cutting-edge technology for the development of oils which is gradually replacing steam huff and puff and is being used more and more widely. Low-permeability interlayers are generally developed in oil reservoirs in China, which may shield the migration of steam, oil and gas. Targeted acidizing fracturing was proposed to break through the low-permeability interlayers, and hence, the problem that the hindrance to the expansion of the steam chamber led to heat loss and seriously affected the development effect could be solved. A typical kind of well with SAGD flooding actually applied in China, Shuyi District of Liaohe Oilfield, was taken as the example for studying the optimization of crack parameters. Based on the study of reservoir sensitivity characteristics in this well, the formulations of working fluids for targeted acidizing fracturing were developed by optimizing the weight percentages of main acid solution and additives. The formula of '4% hydrochloric acid + 2% polyphosphoric acid + 5% fluoroboric acid + 4% acetic acid' could be used as the acidizing fracturing working fluid for typical blocks of the Shuyi District of Liaohe Oilfield, which can increase the permeability of the natural core by 40.19–57.06%. Studies on targeted acidizing fracturing are beneficial for enhancing the oil recovery of oil reservoirs. [ABSTRACT FROM AUTHOR]

Urbanization and warming climate suggest that health impacts from extreme heat will increase in cities, thus locating vulnerable populations is pivotal. However, heat vulnerability indices (HVI) overwhelmingly interpret one model that may be inaccurate or methodologically flawed without considering how results compare with other HVI. Accordingly, this analysis applied a multimodal approach incorporating underrepresented health and adaptability measures to analyze heat vulnerability more comprehensively and better identify vulnerable populations. The Southeast Florida HVI (SFHVI) blends twenty-four physical exposure, sensitivity, and adaptive capacity indicators using uncommon statistical weights removing overlap, then SFHVI scores were compared statistically and qualitatively with ten models utilizing alternative methods. Urban areas with degraded physical settings, socioeconomic conditions, health, and household resources were particularly vulnerable. Rural and agricultural areas were also vulnerable reflecting socioeconomic conditions, health, and community resources. Three alternative models produced vulnerability scores not statistically different than SFHVI. The other seven differed significantly despite geospatial consistency regarding the most at-risk areas. Since inaccurate HVI can mislead decisionmakers inhibiting mitigation, future studies should increasingly adopt multimodal approaches that enhance analysis comprehensiveness, illuminate methodological strengths and flaws, as well as reinforce conviction about susceptible populations. [ABSTRACT FROM AUTHOR]

Inundation dynamics coupled with seasonal information is critical to study the wetland environment. Analyses based on remotely sensed data are the most effective means to monitor and investigate wetland inundation dynamics. For the first time, this study deployed an automated thresholding method to quantify and compare the annual inundation characteristics in dry and wet seasons in the Everglades, using Landsat imagery in Google Earth Engine (GEE). This research presents the long-term time series maps from 2002 to 2021, with a comprehensive spatiotemporal depiction of inundation. In this paper, we bridged the research gap of space-time analysis for multi-season inundation dynamics, which is urgently needed for the Everglades wetland. Within a GIS-based framework, we integrated statistical models, such as Mann–Kendall and Sen's Slope tests, to track the evolutionary trend of seasonal inundation dynamics. The spatiotemporal analyses highlight the significant differences in wet and dry seasons through time and space. The stationary or permanent inundation is more likely to be distributed along the coastal regions (Gulf of Mexico and Florida Bay) of the Everglades, presenting a warning regarding their vulnerability to sea level rise. [ABSTRACT FROM AUTHOR]

The microscopic interactions between oil droplets during the coalescence process have an important impact on the stability of the emulsion. In this paper, a model that can present the phenomenon of coalescence of oil droplets was established. Experiments were carried out to evaluate the stability of the emulsion. Combined with molecular dynamics simulation technology, the coalescence behaviors of emulsified oil droplets in fluids produced by oil wells were studied. Factors affecting the coalescence of emulsified oil droplets were analyzed. The results show that the fluid velocity was relatively high at the position where two oil droplets were close to each other. After the coalescence of oil droplets was completed, the emulsion system became stable. There was no obvious correlation between oil droplet size and coalescence time. When two adjacent oil droplets with different radii coalesced, the larger oil droplet moved a shorter distance overall. At the initial moment, there was a clear boundary between the oil film and the water phase. The longer the carbon chain, the more stable the emulsion. Among the following four crude oil molecules with the same number of carbon atoms, chain-like saturated hydrocarbons were the most stable, followed by chain-like carbon–carbon double bonds in component crude oil. Crude oils containing chain-like carbon–carbon triple bonds were the third most stable. Cyclane were the least stable. An increase in the asphaltene content was an important reason for the enhancement of the emulsifying ability and stability in the emulsion system. This work can help improve oil–water separation efficiency, thus reducing storage and transportation burden of crude oil. [ABSTRACT FROM AUTHOR]

Tidal flats are widely recognized as sentinels of coastal environment change, and are also the guardians for beachfront communities. As a result of urban expansion, tidal flats have increasingly received environmental pressures and the surrounding ecosystem has been functionally downgraded. However, the existing studies could not provide an effective method to identify and quantify the interactions between urban areas and tidal flats, which is essential work particularly for the coastal preservations in the United States. Aiming at this environmental crisis, we proposed an approach which quantifies the change patterns from a spatiotemporal perspective. To justify the rationality and feasibility of this approach, this study selected three highly urbanized coastal counties in the southeastern United States as the study area. We analyzed the annual dynamics during 1985~2015, and the generated spatiotemporal regularities were used to identify and quantify the correlations between urban expansion and tidal flat dynamics. This study not only justified that the coastal urban expansion could considerably damage the environment of tidal flats, but also verified an effective approach to investigate the correlations between urban expansion and tidal flat loss on a large spatiotemporal scale. [ABSTRACT FROM AUTHOR]

The Gulf and southeast coastal communities in the United States are particularly vulnerable to tropical cyclones. Coastal areas generally receive the greatest economic losses from tropical cyclones; however, research suggests that losses in the inland zone can occasionally be higher than the coastal zone. Previous research assessing the inland impacts from tropical cyclones was limited to the areas that are adjacent to the coastal zone only, where losses are usually higher. In this study, we assessed the spatial distribution of inland property damage caused by tropical cyclones. We included all the inland counties that fall within the inland zone in the states of Louisiana, Mississippi, and Alabama. Additionally, different factors, including meteorological storm characteristics (tropical cyclone wind and rain), elevation, and county social-economic vulnerability (county social vulnerability index and GDP) were assessed to measure their influence on property damage, using both ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR performs better than the OLS, signifying the importance of considering spatial variations in the explanation of inland property damage. Results from the tristate region suggest that wind was the strongest predictor of property damage in OLS and one of the major contributing factors of property damage in the GWR model. These results could be beneficial for emergency managers and policymakers when considering the inland impacts of tropical cyclones. [ABSTRACT FROM AUTHOR]

Tidal flats (non-vegetated area) are soft-sediment habitats that are alternately submerged and exposed to the air by changeable tidal levels. The tidal flat dynamics research mainly utilizes the cell-level comparisons between the consecutive snapshots, but the in-depth study requires more detailed information of the dynamic activities. To better track, represent, and analyze tidal flats' dynamic activities, this study proposes an integrated approach of a three-level Geographic Information Science (GIS) framework and a graph model. In the three-level GIS framework, the adjacent cells are assembled as the objects, and the objects on different time steps are linked as lifecycles by tracking the predecessor–successor relationships. Furthermore, eleven events are defined to describe the dynamic activities throughout the lifecycles. The graph model provides a better way to represent the lifecycles, and graph operators are utilized to facilitate the event analysis. The integrated approach is applied to tidal flats' dynamic activities in the southwest tip of Florida Peninsula from 1984 to 2018. The results suggest that the integrated approach provides an effective way to track, represent, and analyze the dynamic activities of tidal flats, and it offers a novel perspective to examine other dynamic geographic phenomena with large spatiotemporal scales. [ABSTRACT FROM AUTHOR]

In recent years, building resilient communities to disasters has become one of the core objectives in the field of disaster management globally. Despite being frequently targeted and severely impacted by disasters, the geographical extent in studying disaster resilience of the coastal communities of the United States (US) has been limited. In this study, we developed a composite community disaster resilience index (CCDRI) for the coastal communities of the conterminous US that considers different dimensions of disaster resilience. The resilience variables used to construct the CCDRI were justified by examining their influence on disaster losses using ordinary least squares (OLS) and geographically weighted regression (GWR) models. Results suggest that the CCDRI score ranges from −12.73 (least resilient) to 8.69 (most resilient), and northeastern communities are comparatively more resilient than southeastern communities in the study area. Additionally, resilience components used in this study have statistically significant impact on minimizing disaster losses. The GWR model performs much better in explaining the variances while regressing the disaster property damage against the resilience components (explains 72% variance) than the OLS (explains 32% variance) suggesting that spatial variations of resilience components should be accounted for an effective disaster management program. Moreover, findings from this study could provide local emergency managers and decision-makers with unique insights for enhancing overall community resilience to disasters and minimizing disaster impacts in the study area. [ABSTRACT FROM AUTHOR]

Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion while urban areas with low to moderate expansion have been overlooked, especially in developed countries. In this study, we examined the spatiotemporal dynamics of urban expansion patterns in South Florida, United States (US) over the last 25 years (1992–2016) using Remote Sensing and GIS techniques. The main goal of this paper was to investigate the degree and spatiotemporal patterns of urban expansion at different administrative level in the study area and how spatiotemporal variance in different explanatory factors influence urban expansion in this region. More specifically, this research quantifies the rates, types, intensity, and landscape metrics of urban expansion in Miami-Fort Lauderdale-Palm Beach, Florida Metropolitan Statistical Area (Miami MSA) which is the 7th largest MSA and 4th largest urbanized area in the US using remote sensing (satellite imageries) data from National Land Cover Datasets (NLCD) and Coastal Change Analysis Program (C-CAP) at 30 m spatial resolution. We further investigated the urban growth patterns at the county and city areas that are located within this MSA to portray the local 'picture' of urban growth in this region. Urban expansion in this region can be divided into two time periods: pre-2001 and post-2001 where the former experienced rapid urban expansion and the later had comparatively slow urban expansion. Results suggest that infilling was the dominant type of urban expansion followed by edge-expansion and outlying. Results from landscape metrics represent that newly developed urban lands became more aggregated and simplified in form as the time progressed in the study region. Also, new urban lands were generated away from the east coast and historic cities which eventually created new urban cores. We also used correlation analysis and multiple linear stepwise regression to address major explanatory factors of spatiotemporal change in urban expansion during the study period. Although the influence of factors on urban expansion varied temporally, Population and Distance to Coast were the strongest variables followed by Distance to Roads and Median Income that influence overall urban expansion in the study area. [ABSTRACT FROM AUTHOR]

Most toughening methods for epoxy resins are usually used at the expense of other properties. Some polyhedral oligomeric silsesquioxanes (POSSs) with both a rigid Si-O-Si structure and flexible organic chain segments could be expected to be effective toughening agents. In this study, three reactive polyhedral oligomeric silsesquioxanes with a thiol group (OMPPS), a carboxyl group (OCOPS), and an epoxy group (OGCPS) were synthesized and characterized. They were utilized as modifiers to toughen 3-(oxiran-2-ylmethoxy)- N , N -bis(oxiran-2-ylmethyl)aniline (AFG-90MH)/4,4'-methylenebis(2-ethylaniline) (MOEA) (epoxy resin) with different molar ratios to obtain hybrid resins named OMPPS-EP-i, OCOPS-EP-j, and OGCPS-EP-k. The effects of the amount of modifier added and the length of the organic chain on the cage structure on various properties of the hybrid resins were investigated. The results show that all three modifiers show good compatibility with the epoxy resin. The hybrid resins have a low viscosity at 45~85 °C and can be cured at a low temperature (110 °C). The cured hybrid resins display improved toughness. Typically, the critical stress intensity factor (K IC ) and impact strength of OGCPS-EP-0.6-C are 2.54 MPa∙m -1/2 and 19.33 kJ∙m -2 , respectively, which increased by 58.75% and 22.48% compared with the pristine epoxy resin, respectively. In addition, the glass transition temperature and flexural strength of the hybrid resins are basically unchanged.