High Impervious Surface Research Articles

Characterizing the local climate of large-scale archaeological parks in the tropics

PurposeThis study aims to compare the local climate characteristics of Angkor Wat, Borobudur and Prambanan parks and determine effective strategies for mitigating thermal conditions that could suit Borobudur and Angkor Wat.Design/methodology/approachThe study employed local climate zone (LCZ) indicators and ten-year historical climate data to identify similarities and differences in local climate characteristics. Satellite imagery processing was used to create maps of LCZ indicators. Meanwhile, microclimate models were used to analyze sky view factors and wind permeability.FindingsThe study found that the three tropical large-scale archaeological parks have low albedo, a medium vegetation index and high impervious surface index. However, various morphological characteristics, aerodynamic properties and differences in temple stone area and altitude enlarge the air temperature range.Practical implicationsBased on the similarities and differences in local climate, the study formulated mitigation strategies to preserve the sustainability of ancient temples and reduce visitors' heat stress.Originality/valueThe local climate characterization of tropical archaeological parks adds to the number of LCZs. Knowledge of the local climate characteristics of tropical archaeological parks can be the basis for improving thermal conditions.

The effect modification of greenspace and impervious surface on the heat-mortality association: Differences by the dissimilarity index

Recent studies have shown that heat-mortality risk differs by level of greenspace and impervious surface. However, these studies do not consider both green spaces and impervious surfaces simultaneously, and further did not fully consider community- and individual-level characteristics. In this study we explored the effect modification of greenspace and impervious surface on the association between heat and mortality and how it differs by race/ethnicity dissimilarity index levels in North Carolina, USA. We aggregated datasets for greenspace, impervious surface estimates, temperature, and mortality for 1275 census tracts for North Carolina, USA, for 2000 to 2016 for 5 warm months (May to September). We used distributed lag non-linear models to estimate the heat-mortality relationship in each census tract. Heat-mortality relative risk (RR) was higher for census tracts with low greenspace than high greenspace (RR comparing risk at 99th temperature and minimum mortality temperature: 1.08 (1.02, 1.15) for low greenspace and 0.97 (0.87, 1.08) for high greenspace). Heat-mortality RR was higher for tracts with high impervious surface than low impervious surface (1.04 (1.00, 1.09) for high impervious surface and 0.94 (0.84, 1.05) for low impervious surface). Census tracts with high dissimilarity value and low greenspace had the highest heat-mortality risk compared to the tracts with high dissimilarity value with and high greenspace (1.13 (1.02, 1.24) for high dissimilarity index and 0.97 (0.86, 1.09) for low dissimilarity index). Communities with low greenspace or high impervious surfaces had higher heat-mortality associations, and this effect modification was higher for high race/ethnicity dissimilarity regions.

Mixtures of long-term exposure to ambient air pollution, built environment and temperature and stroke incidence across Europe

IntroductionThe complex interplay of multiple environmental factors and cardiovascular has scarcely been studied. Within the EXPANSE project, we evaluated the association between long-term exposure to multiple environmental indices and stroke incidence across Europe. MethodsParticipants from three traditional adult cohorts (Germany, Netherlands and Sweden) and four administrative cohorts (Catalonia [region Spain], Rome [city-wide], Greece and Sweden [nationwide]) were followed until incident stroke, death, migration, loss of follow-up or study end. We estimated exposures at residential addresses from different exposure domains: air pollution (nitrogen dioxide (NO2), particulate matter < 2.5 μm (PM2.5), black carbon (BC), ozone), built environment (green/blue spaces, impervious surfaces) and meteorology (seasonal mean and standard deviation of temperatures). Associations between environmental exposures and stroke were estimated in single and multiple-exposure Cox proportional hazard models, and Principal Component (PC) Analyses derived prototypes for specific exposures domains. We carried out random effects meta-analyses by cohort type. ResultsIn over 15 million participants, increased levels of NO2 and BC were associated with increased higher stroke incidence in both cohort types. Increased Normalized Difference Vegetation Index (NDVI) was associated with a lower stroke incidence in both cohort types, whereas an increase in impervious surface was associated with an increase in stroke incidence. The first PC of the air pollution domain (PM2.5, NO2 and BC) was associated with an increase in stroke incidence. For the built environment, higher levels of NDVI and lower levels of impervious surfaces were associated with a protective effect [%change in HR per 1 unit = −2.0 (95 %CI, −5.9;2.0) and −1.1(95 %CI, −2.0; −0.3) for traditional adult and administrative cohorts, respectively]. No clear patterns were observed for distance to blue spaces or temperature parameters. ConclusionsWe observed increased HRs for stroke with exposure to PM2.5, NO2 and BC, lower levels of greenness and higher impervious surface in single and combined exposure models.

Urban stream restorations increase floodplain soil carbon and nutrient retention along a chronosequence

Stream restoration is a common management practice to meet regulatory or voluntary efforts to improve water quality via nutrient and carbon (C) retention, including in the Chesapeake Bay watershed. However, most restoration projects have few quantifiable measures of project success, no standard metrics, and rarely collect pre-restoration data. Storage of nutrients, such as phosphorus (P) and nitrogen (N), in floodplain soils of restored streams can act as an easily quantifiable indicator of restoration success, particularly when the project goals include improved water quality. To determine how floodplains of restored streams change in their P and C storage as time since restoration increases, floodplain surficial soil samples (10 cm depth) were collected from 18 streams in the urbanized Piedmont region of northern Virginia, representing a chronosequence of time (1–10+ yrs.) since restoration as well as unrestored streams with high impervious surface cover (ISC) and unrestored streams with low ISC. The samples were analyzed for total carbon (TC), total nitrogen (TN) and total phosphorus (TP) storage, whereas C turnover rate and equilibrium phosphorus concentration (EPC0) were measured as metrics of C and P loss. These metrics were compared to time since restoration and potential environmental drivers, including soil moisture, pH, median particle size (D50), organic matter content (OM), and bioavailable P, iron (Fe), and aluminum (Al). These stream restorations demonstrated increasing nutrient storage for TC, TN, and TP along the chronosequence to values greater than both unrestored or reference streams, as well as decreasing C turnover and no significant changes in EPC0. Soil wetness and OM, key drivers in nutrient retention, also increased as restoration projects aged increasing C, N, and P storage. Overall, stream restoration did improve soil C, N, and P retention in floodplains as compared to unrestored sites and exceeded those of low ISC ‘reference’ sites.

Spatial and temporal characteristics of near‐surface air temperature across local climate zones in a tropical city

AbstractThe present study examines the temporal and spatial variability of near‐surface air temperature and the canopy layer urban heat island (UHI) in Singapore. Observations collected at 20 locations across the island city‐state and during 6 years make this one of the most extensive studies carried out in a tropical city. Local climate zones (LCZs), defined as urban built and rural land cover types which produce a unique air temperature response, are used to standardize intersite comparison. The results show that the choice of the rural reference can affect the night‐time UHI magnitude by up to 2°C under “ideal” (dry, clear, calm) conditions. The most frequently observed median UHI magnitude increases from 2.8 during all‐weather to 3.7°C during “ideal” conditions, respectively. A seasonality is present with lowest (highest) mean all‐weather values of ~2.0°C (~3.3°C), observed during the wet (dry) December–January (April–October) period. Mean night‐time UHI intensity across seven built‐type LCZs ranges between 1.8 and 3.5°C (2.5 and 4.3°C) for all‐weather (“ideal”) conditions. Corresponding daily values are 1.1–2.3°C (1.5–2.7°C). The lowest (highest) night‐time magnitudes are associated with open low‐rise LCZ 6 (compact high‐rise LCZ 1) built type. In the middle of the day LCZ 1 can experience a cool island effect. The average UHI values presented here give an indication of the extra warmth experienced in the built‐up spaces of Singapore relative to one possible rural reference land cover type (scattered trees LCZ B). Highest daytime heat exposure is observed in LCZs 3 and 8 which are characterized by low building heights, high impervious surface fraction and lack of vegetation. The present results can be used to support the development and evaluation of urban climate models, develop urban planning policies and improve local weather forecasts and the delivery of integrated urban services.

Distinctive roles of two- and three-dimensional urban structures in surface urban heat islands over the conterminous United States

In this study, we investigated how seasonal and diurnal surface urban heat islands (SUHIs) vary with two- and three-dimensional (2D and 3D) urban structure parameters (USPs) and climate settings. Additionally, whether and how 2D and 3D USPs influenced the seasonal hysteresis between SUHIs and background temperatures were explored using remote sensing for 203 cities over the conterminous US. Results show that urban areas with high impervious surface coverage (70%) were “colder” in summer than surrounding rural areas in dry climates. Moreover, the cooling efficiency of vegetation in dry climates was about two times higher than that in wet climates. A hump-shaped relation between sky view factor (SVF) and SUHIs was observed; in regions with low SVF (e.g., SVF < 0.4), the increasing trends of summer diurnal SUHIs with increasing SVF in dry climates attained higher values than those in wet climates. Seasonal hysteresis between background temperatures and SUHIs was largely controlled by 2D and 3D USPs. Urban USPs and climate settings can regulate the timing of peaks and nadirs of annual SUHIs, suggesting that their regulation would benefit SUHI mitigation. Future studies are required to test USP–LST relationships further by using the local climate zone approach under different climatic conditions.

PSO-WELLSVM: An integrated method and its application in urban waterlogging susceptibility assessment in the central Wuhan, China

Urban waterlogging susceptibility assessment can be used in preventing urban waterlogging disaster, which can cause serious damage. An integrated method based on particle swarm optimization (PSO) and weakly labeled support vector machine (WELLSVM), is presented to assess urban waterlogging susceptibility for a certain rainstorm. This method incorporated twelve explanatory factors, including daily precipitation, 3-day cumulated rainfall prior to flood occurrences, elevation, slope, curvature, aspect, topographic wetness index, stream power index, distance to river, leaf area index, impervious surface percentage, distance to road, to perform waterlogging susceptibility analysis. The rainstorm on July 6, 2016 in the main districts of Wuhan, China was used as the scenario to test its feasibility. Cohen's kappa index, accuracy, precision, and recall were used to evaluate the performance of the proposed model. The accuracy of the proposed model (93.6% for training data and 90.1% for testing data) is higher than WELLSVM, support vector machine, and logistic regression, demonstrating the advantages of utilizing unlabeled data and optimized parameter selection. The proposed model can also well identify the waterlogging susceptibility zones. The highest waterlogging susceptibility areas are located in the area with high impervious surface percent, intersections, culverts and overpasses, lakeshore, and riverbank. Elevation and precipitation factors are the most influential factors to waterlogging susceptibility. The proposed model was also tested by the other two storms on July 7, 2013 and June 21, 2019, proving the validity of it. The proposed model is helpful for instant waterlogging susceptibility analysis and can help decision-making of urban waterlogging control.

Improving LSMA for impervious surface estimation in an urban area

ABSTRACT Linear spectral mixture analysis (LSMA) and regression analysis are the two most conventionally used methods to estimate impervious surfaces at the subpixel scale in an urban area. However, LSMA lacks the sensitivity to pixel brightness, which leads to inter variability of endmembers and affects the ability to distinguish features with a similar spectral signature. This research aims to develop LSMA aided by a regression analysis model to estimate impervious surfaces with higher accuracy. A spectral angle mapping (SAM) based regression analysis model is introduced to reduce errors. Based on high-resolution images and field survey data, the SAM-based regression analysis can estimate non-impervious surface and high-impervious surface densities with high accuracy, while less accurate in impervious surfaces with low/medium density. In contrast, LSMA is able to estimate low/medium-density impervious surfaces with higher accuracy. We propose an improved approach by integrating the two methods, regression analysis aided LSMA, for impervious surface estimation. The proposed method increases the overall accuracy of the impervious surface estimation to 85.24%, which is significantly greater than that of the conventional methods.

Determination of NPS Pollutant Unit Loads from Different Landuses

This study aimed to estimate pollutant unit loads for different landuses and pollutants that reflected long-term runoff characteristics of nonpoint source (NPS) pollutants and recent environmental changes. During 2008–2014, 2026 rainfall events were monitored. The average values of antecedent dry days, total rainfall, rainfall intensity, rainfall duration, runoff duration, and runoff coefficient for each landuse were 3.8–5.9 d, 35.2–65.0 mm, 2.9–4.1 mm/h, 12.5–20.4 h, 12.4–27.9 h, and 0.24–0.45, respectively. Uplands (UL) exhibited high suspended solids (SS, 606.2 mg/L), total nitrogen (TN, 7.38 mg/L), and total phosphorous (TP, 2.27 mg/L) levels, whereas the runoff coefficient was high in the building sites (BS), with a high impervious surface ratio. The event mean concentration (EMC) for biological oxygen demand (BOD) was the highest in BS (8.0 mg/L), while the EMC was the highest in BS (in the rainfall range &lt;10 mm) and UL and forest land (in the rainfall range &gt;50 mm). The unit loads for BOD (1.49–17.76 kg/km2·d), TN (1.462–10.147 kg/km2·d), TP (0.094–1.435 kg/km2·d), and SS (15.20–327.70 kg/km2·d) were calculated. The findings can be used to manage NPS pollutants and watershed environments and implement relevant associated management systems.

Growing in the city: Urban evolutionary ecology of avian growth rates.

IntroductionRapid environmental change driven by urbanization offers a unique insight into the adaptive potential of urban‐dwelling organisms. Urban‐driven phenotypic differentiation is increasingly often demonstrated, but the impact of urbanization (here modelled as the percentage of impervious surface (ISA) around each nestbox) on offspring developmental rates and subsequent survival remains poorly understood. Furthermore, the role of selection on urban‐driven phenotypic divergence was rarely investigated to date.Methods and ResultsData on nestling development and body mass were analysed in a gradient of urbanization set in Warsaw, Poland, in two passerine species: great tits (Parus major) and blue tits (Cyanistes caeruleus). Increasing levels of impervious surface area (ISA) delayed the age of fastest growth in blue tits. Nestling body mass was also negatively affected by increasing ISA 5 and 10 days after hatching in great tits, and 10 and 15 days in blue tits, respectively. High levels of ISA also increased nestling mortality 5 and 10 days after hatching in both species. An analysis of selection differentials performed for two levels of urbanization (low and high ISA) revealed a positive association between mass at day 2 and survival at fledging.DiscussionThis study confirms the considerable negative impact of imperviousness—a proxy for urbanization level—on offspring development, body mass and survival, and highlights increased selection on avian mass at hatching in a high ISA environment.

Correcting the Pixel Blooming Effect (PiBE) of DMSP-OLS nighttime light imagery

In the last two decades, the advance in nighttime light (NTL) remote sensing has fueled a surge in extensive research towards mapping human footprints. Nevertheless, the full potential of NTL data is largely constrained by the blooming effect. In this study, we propose a new concept, the Pixel Blooming Effect (PiBE), to delineate the mutual influence of lights from a pixel and its neighbors, and an integrated framework to eliminate the PiBE in radiance calibrated DMSP-OLS datasets (DMSPgrc). First, lights from isolated gas flaring sources and a Gaussian model were used to model how the PiBE functions on each pixel through point spread function (PSF). Second, a two-stage deblurring approach (TSDA) was developed to deconvolve DMSPgrc images with Tikhonov regularization to correct the PiBE and reconstruct PiBE-free images. Third, the proposed framework was assessed by synthetic data and VIIRS imagery and by testing the resulting image with two applications. We found that high impervious surface fraction pixels (ISF > 0.6) were impacted by the highest absolute magnitude of PiBE, whereas NTL pattern of low ISF pixels (ISF < 0.2) was more sensitive to the PiBE. By using TSDA the PiBE in DMSPgrc images was effectively corrected which enhanced data variation and suppressed pseudo lights from non-built-up pixels in urban areas. The reconstructed image had the highest similarity to reference data from synthetic image (SSIM = 0.759) and VIIRS image (r = 0.79). TSDA showed an acceptable performance for linear objects (width > 1.5 km) and circular objects (radius > 0.5 km), and for NTL data with different noise levels (<0.6σ). In summary, the proposed framework offers a new opportunity to improve the quality of DMSP-OLS images and subsequently will be conducive to NTL-based applications, such as mapping urban extent, estimating socioeconomic variables, and exploring eco-impact of artificial lights.

Chronology of Gloomy Scale (Hemiptera: Diaspididae) Infestations on Urban Trees.

Pest abundance on urban trees often increases with surrounding impervious surface. Gloomy scale (Melanaspis tenebricosa Comstock; Hemiptera: Diaspididae), a pest of red maples (Acer rubrum L.; Sapindales: Sapindaceae) in the southeast United States, reaches injurious levels in cities and reduces tree condition. Here, we use a chronosequence field study in Raleigh, NC, to investigate patterns in gloomy scale densities over time from the nursery to 13 yr after tree planting, with a goal of informing more efficient management of gloomy scale on urban trees. We examine how impervious surfaces affect the progression of infestations and how infestations affect tree condition. We find that gloomy scale densities remain low on trees until at least seven seasons after tree planting, providing a key timepoint for starting scouting efforts. Scouting should focus on tree branches, not tree trunks. Scale density on tree branches increases with impervious surface across the entire studied tree age range and increases faster on individual trees that are planted in areas with high impervious surface cover. There is a lag between the onset of pest infestations and a decline in tree condition, indicating that gloomy scale management should begin prior to a visible decline in tree condition. Our results inform management of gloomy scale in cities.

An Integrated Approach to Modelling of Flood Hazards in the Rapidly Growing City of Osogbo, Osun State, Nigeria

In recent times, the swift and uncoordinated urban expansion in the medium sized city of Osogbo has increasingly encroached on the environmental sensitive areas. This uncoordinated exploitation of the ecological fragile areas for urban development has triggered urban flooding, which poses serious threat to human lives and properties in the city. This study therefore utilized geospatial technologies to generate flood hazard model for medium sized cities in developing countries in general and Nigeria in particular with a view to identifying hotspots and providing measures to forestall flood occurrences. The study used Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM), Landsat 7- 2000 and Operational Land Imager 8 (OLI)- 2015 images. Multi-criteria evaluation method was used to derive the physical characteristics of watersheds from the data to delineate the areas vulnerable to flooding. Flood inundation characteristics were simulated using Hydrologic Engineering Centre-River Analysis System (HEC-RAS) model with GIS interface and found discharge of over 500 m3/s for the 100-year profile period to be high, given the size of the analyzed basin (207.41 km2). The flood hazard map showed that 3.92, 103.38 and 100.11 km2 were least, moderately and highly vulnerable areas respectively. Most prone areas were built-ups with high impervious surface in the basin area where floodplain traversed high and moderate vulnerability zones. The study advocates consistent use of dynamic model within GIS for floodplain delineation and management planning to reduce the flood hazards.

Urbanization reduces and homogenizes trait diversity in stream macroinvertebrate communities.

More than one-half of the world's population lives in urban areas, so quantifying the effects of urbanization on ecological communities is important for understanding whether anthropogenic stressors homogenize communities across environmental and climatic gradients. We examined the relationship of impervious surface coverage (a marker of urbanization) and the structure of stream macroinvertebrate communities across the state of Maryland and within each of Maryland's three ecoregions: Coastal Plain, Piedmont, and Appalachian, which differ in stream geomorphology and community composition. We considered three levels of trait organization: individual traits, unique combinations of traits, and community metrics (functional richness, functional evenness, and functional divergence) and three levels of impervious surface coverage (low [<2.5%], medium [2.5% to 10%], and high [>10%]). The prevalence of an individual trait differed very little between low impervious surface and high impervious surface sites. The arrangement of trait combinations in community trait space for each ecoregion differed when impervious surface coverage was low, but the arrangement became more similar among ecoregions as impervious surface coverage increased. Furthermore, trait combinations that occurred only at low or medium impervious surface coverage were clustered in a subset of the community trait space, indicating that impervious surface affected the presence of only a subset of trait combinations. Functional richness declined with increasing impervious surface, providing evidence for environmental filtering. Community metrics that include abundance were also sensitive to increasing impervious surface coverage: functional divergence decreased while functional evenness increased. These changes demonstrate that increasing impervious surface coverage homogenizes the trait diversity of macroinvertebrate communities in streams, despite differences in initial community composition and stream geomorphology among ecoregions. Community metrics were also more sensitive to changes in the abundance rather than the gain or loss of trait combinations, showing the potential for trait-based approaches to serve as early warning indicators of environmental stress for monitoring and biological assessment programs.

GLOBE students, teachers, and scientists demonstrate variable differences between urban and rural leaf phenology

AbstractThe urban heat island effect, classically associated with high impervious surface area (ISA), low vegetation fractional cover (Fr), and high land surface temperature (LST), has been linked to changing patterns of vegetation phenology, especially spring growth. In this study, a collaboration with the Global Learning and Observations to Benefit the Environment (GLOBE) program, we investigated the effect of the urban environment on the timing of leaf budburst of native deciduous trees in seven cities: Asia (Tokyo, Japan; Bangkok and Korat, Thailand), Europe (Jyväskylä, Finland; Bishkek, Kyrgyzstan), Africa (Dakar, Senegal), and North America (Fairbanks, Alaska). The cities differed not only in population size but also in climate and vegetation type. Using Landsat satellite imagery from each city, we calculated LST, Fr, and ISA, and classified sites within each study area as rural or urban. The timing of leaf flushing, measured by students using GLOBE budburst protocols, was statistically different within all cities, with absolute differences ranging from 1 to 23 days. We assessed the classic urban phenology paradigm, which proposes higher LST, lower Fr, and earlier budburst in urban areas of temperate cities. Of the four temperate cities, Tokyo followed the classic paradigm, but no other city demonstrated consistent support. Urban budburst was advanced in three of the four temperate cities, but in only one of the three tropical cities. Results suggest that while vegetation phenology is consistently different between urban and rural areas, a uniform paradigm based on the explanatory variables in this study did not emerge. Although not testable here, it is likely that alterations to chilling requirements in temperate climates and humidity in tropical climates may also influence observed budburst differences.

Evaluation of Impervious Surface Estimates in a Rapidly Urbanizing Watershed

Accurate measurement of impervious surface (IS) cover is an essential indicator of downstream water quality and a critical input variable for many water quality and quantity models. This study compares IS estimates from a recently developed satellite imagery/land cover approach with a more traditional aerial photography/land use approach. Both approaches are evaluated against a high-quality validation set consisting of planimetric data merged with manually-delineated areas of soil disturbance. The study area is the rapidly urbanizing 127 km 2 Cub Run watershed in northern Virginia, located on the fringe of the Washington, D.C. metropolitan region. Results show that photo-interpreted IS estimates of land class are higher than satellite-derived IS estimates by 100 percent or more, even in land uses conservatively assigned high IS values. Satellite-derived IS estimates by land class correlate well with planimetric reference data (r � 0.95) and with published ranges for similar sites in the region. Basin-wide mean IS values, difference grids, and regression and density plots validate the use of satellite-derived/land cover-based IS estimates over photo-interpreted/land use-based estimates. Results of this site-specific study support the use of automated, satellite-derived IS estimates for planning and management within rapidly urbanizing watersheds where a GIS system is in place, but where time-sensitive, high quality planimetric data is unavailable.