Journal articles on the topic 'Impervious surface threshold'

Index-based methods are widely applied to urban impervious surface area (ISA) mapping, but the confusion between ISA and soil remains unsolved. In this article, the near-infrared (NIR)-blue bands were selected as feature space by analyzing the spectra from the US Geological Survey spectral library, and a simple impervious surface ratio index (ISRI) was developed by shifting the NIR-blue coordinate origin toward the convergence point of the fitting lines of ISA and soil. The ISRI was then validated for threshold simulation, separability, and correlation analysis. Results demonstrated that ISRI had a good performance for ISA mapping in four cities in China with different geographic environments, with all extraction accuracies all above 90%. ISRI had a high separability between ISA and soil and was better than other indices (normalized difference built-up index and biophysical composition index). Further, ISRI has a close relationship with the ISA proportion. Therefore, ISRI would be a simple and reliable index for urban ISA mapping.

Impervious surface area (ISA) is an important representation of urban area. It is very popular to extract ISA by using linear spectral mixture analysis (LSMA). However, there are still some defects in this method: underestimated in areas with a large amount of ISA. Hence, we designed a threshold hierarchical method (THM) to test this underestimation and understand which scale is the best to mixture. The capacity of the THM and the optimal threshold in the impervious surface extraction are the focus in this work. In THM model, the medium-resolution image (Landsat 8 OLI) and the high-resolution image (Gaofen-2, GF-2) were used, the LSMA and the object-oriented method (OOM) were applied for the area with a larger amount of impervious surfaces, which was extracted from the Landsat 8 OLI image after finishing the LSMA procedure by a threshold of the ISA abundance data, the GF-2 image was employed to extract the ISA by OOM. The results show that the THM had the capacity to achieve higher ISA extraction accuracy and ameliorate the ISA underestimate problem.

Surface water quality is deteriorating due to the increase of urbanization which increases the load of stormwater and wastewater discharged into rivers. To evaluate the quality of an urban river (Annaba, northeastern Algeria), multivariate statistical analyses were applied to the physicochemical measures of 38 parameters. The application of principal component analysis and factor analysis pointed out 19 dominant components, explaining 83.40% of the variance. Reducing the amount of data will allow a reduction in the number of parameters that need to be analysed to have sufficient information on the water quality. An analysis of the statistical tools' results and effective impervious area leads to an estimation of the urbanization threshold level at which the impact on water quality occurs. Estimating the threshold of impervious areas to abide will ensure urban development while protecting the quality of water and environmental health.

The distribution and dynamic changes in impervious surface areas (ISAs) are crucial to understanding urbanization and its impact on urban heat islands, earth surface energy balance, hydrological cycles, and biodiversity. Remotely sensed data play an essential role in ISA mapping, and numerous methods have been developed and successfully applied for ISA extraction. However, the heterogeneity of ISA spectra and the high similarity of the spectra between ISA and soil have not been effectively addressed. In this study, we selected data from the US Geological Survey (USGS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectral libraries as samples and used blue and near-infrared bands as characteristic bands based on spectral analysis to propose a novel index, the perpendicular impervious surface index (PISI). Landsat 8 operational land imager data in four provincial capital cities of China (Wuhan, Shenyang, Guangzhou, and Xining) were selected as test data to examine the performance of the proposed PISI in four different environments. Threshold analysis results show that there is a significant positive correlation between PISI and the proportion of ISA, and threshold can be adjusted according to different needs with different accuracy. Furthermore, comparative analyses, which involved separability analysis and extraction precision analysis, were conducted among PISI, biophysical composition index (BCI), and normalized difference built-up index (NDBI). Results indicate that PISI is more accurate and has better separability for ISA and soil as well as ISA and vegetation in the ISA extraction than the BCI and NDBI under different conditions. The accuracy of PISI in the four cities is 94.13%, 96.50%, 89.51%, and 93.46% respectively, while BCI and NDBI showed accuracy of 77.53%, 93.49%, 78.02%, and 84.03% and 58.25%, 57.53%, 77.77%, and 64.83%, respectively. In general, the proposed PISI is a convenient index to extract ISA with higher accuracy and better separability for ISA and soil as well as ISA and vegetation. Meanwhile, as PISI only uses blue and near-infrared bands, it can be used in a wider variety of remote sensing images.

Decentralization problems in Africa have caused some infrastructure disparity between country capitals and distant districts. In Ghana, less public investment has created a gap between implementation results and theoretical benefits. Spectral indices are a good approach to extracting impervious surfaces, which is a good method of measuring urbanization. These are restricted by complexity, sensor limitation, threshold values, and high computational time. In this study, we measure the urbanization dynamics of Wa District in Ghana by applying a proposed method of impervious surface extraction index (ISEI), to evaluate the decentralization policy using Landsat images from 1984–2018 and a single S2A data. Comparing our proposed method with five other existing indexes, ISEI provided good discriminated results between target feature and background, with pixel values ranging between 0 and +1. Other indexes produced negative values. ISEI accuracy varied from 84.62–94.00% while existing indexes varied from 73.85–90.00%. Our results also showed increased impervious surface areas of 83.26 km2, which is about 7.72% of total area while the average annual urban growth was recorded as 4.42%. These figures proved that the quantification of decentralization is very positive. The study provides a foundation for urban environment research in the context of decentralization policy.

Monitoring urban compositions spatially and temporally is a crucial issue for urban planning and management. Nowadays, remote sensing techniques have been widely applied for urban compositions extraction. Compared with other remote sensing techniques, spectral indices have significant advantages due to their parameter-free and easy implementation. However, existing indices cannot extract different urban compositions well, and some of them can only extract one composition with less attention to other urban compositions. In this study, based on the water- impervious surface-pervious surface (W-I-P) model, a novel urban composition index (UCI) was developed by analyzing the robust features from the global spectral samples. Additionally, a semi-empirical threshold of UCI was proposed to extract different urban compositions (water, impervious surface area and pervious surface area). Four cities of China were selected as study areas, Landsat-8 images and Google Earth images were used for quantitative analysis. Correlation analysis, separability analysis, and accuracy assessment were conducted among UCI and five other existed indices (single and multiple composition indices) at the urban and global scales. Results indicated that UCI had a stronger correlation with the ISA proportion and a higher separability between each urban composition. UCI also achieved the highest overall accuracy and Kappa coefficient in urban compositions extraction. The suggested semi-empirical threshold was also testified to be reliable and can be a reference for practical application. There is convincing evidence that UCI is a simple, efficient, and reliable index for urban compositions extraction.

There are a great number of index methods used to extract impervious surface from satellite images. However, these indices are not robust enough to detect steel framed roof due to the diversity of impervious materials. The extraction of steel framed roof information by remote sensing technology is becoming increasingly important because of its environmental and socio-economic significance. A new index, Normalized Difference Steel framed roof Index (NDSI) is proposed to extract steel framed roof surface information from TM images. The NDSI was created based on its spectral characteristics of TM image and the steel framed roof information can be extracted fast by NDSI threshold method. Additionally, Shijiazhuang city, which has experienced rapid urbanization, was chosen as the study area. And the classification results show that the new index NDSI can effectively extract steel framed roof information with higher accuracy.

The combination of decameter resolution Sentinel 2 and hectometer resolution VIIRS offers the potential to quantify urban morphology at scales spanning the range from individual objects to global scale settlement networks. Multi-season spectral characteristics of built environments provide an independent complement to night light brightness compared for 12 urban systems. High fractions of spectrally stable impervious surface combined with persistent deep shadow between buildings are compared to road network density and outdoor lighting inferred from night light. These comparisons show better spatial agreement and more detailed representation of a wide range of built environments than possible using Landsat and DMSP-OLS. However, they also show that no single low luminance brightness threshold provides optimal spatial correlation to built extent derived from Sentinel in different urban systems. A 4-threshold comparison of 6 regional night light networks shows consistent spatial scaling, spanning 3 to 5 orders of magnitude in size and number with rank-size slopes consistently near −1. This scaling suggests a dynamic balance among the processes of nucleation, growth and interconnection. Rank-shape distributions based on √Area/Perimeter of network components scale similarly to rank-size distributions at higher brightness thresholds, but show both progressive then abrupt increases in fractal dimension of the largest, most interconnected network components at lower thresholds.

The increase of urbanization level has led to the rapid increase of impervious surface area (ISA). The aim of this work is to clarify the relationship between the ISA and water quality and lay a foundation for the improvement and protection of the water quality in the basin. Taking the Fuxian Lake Basin in Yunnan Province as an example, based on the Landsat ETM+ remote sensing image and the Gram–Schmidt (GS) image fusion algorithm, the four-terminal model and the linear spectral mixture model (LSMM) were used to extract the impervious surface of the watershed from 2006 to 2015. And statistical methods were used to distinguish its relationship with water quality. The results show that the four-terminal model and the linear spectral mixture model can effectively extract the impervious surface information of the Fuxian Lake Basin. The average root mean square error (RMS) of the image decomposition results from 2006 to 2015 was less than 0.02. In the past 10 years, the ISA has changed significantly in the Fuxian Lake Basin. The ISA showed an overall upward trend from 2006 to 2015. It increased from 24.73 km2 in 2006 to 35.14 km2 in 2015, an increase of 10.81 km2. From the value anomaly, the ISA in 2006 and 2009 is lower than the multiyear average, and those in the other years are higher than the multiyear average. The percentage of ISA in the basin was significantly positively correlated with Chemical Oxygen Demand-Mn (CODMn) and total phosphorus (TP) (r is 0.772, 0.763), and the correlation in the flooding season was greater than that in the dry season. The ISA threshold for water quality deterioration is around 10% in the Fuxian Lake Basin. Reducing ISA coverage, controlling ISA to less than 10%, and preventing nonpoint source pollution during flooding season will be the best measures to effectively improve the water quality environment in the basin.

Abstract. For studies of urban development, it is an important method for obtaining the distribution of impervious surface (IS) areas and their dynamic change from remote sensing data. The dilemma of the same spectrum for different features and different spectrums for the same features, posed by the complexity of the IS objects, is the fundamental obstacle encountered in the extraction of urban IS areas. In this study, an automatic extraction method for urban IS areas is proposed and analyzed, based on classification and regression tree (CART) and ensemble learning strategies. The Sentinel-2 MSI data of 30 cities in China from 2018 to 2020 were selected for IS extraction experiments. We perform temporal and spatial modeling of the splitting threshold offset in the classification model to explore the effect of time and space on IS extraction. The obtained offset models show that the temporal variation is not significant, while the spatial offsets have more obvious linear relationships.

A layer of skin and subcutaneous tissue on a bony substratum was modeled as a homogeneous layer of biphasic poroelastic material with uniform thickness. The epidermal surface and the bony interface were taken to be impervious. The soft tissue on the bony interface was assumed either fully adhered or completely free to slide on the bone. The cases for surface pressure loadings and displacement controlled indentations were simulated. The resultant biomechanical responses of the layer, including the transient tissue hydrostatic pressure and the tissue compaction, were presented. A new hypothesis is offered to interpret the threshold pressure-time curve for pressure sores in term of the time required for a particular area in the tissue layer to reach a critical compaction for a given level of applied pressure.

ABSTRACTAn initial modeling approach was applied to analyze how a single, nonmotile, free-living, heterotrophic bacterial cell may optimize the deployment of its extracellular enzymes. Free-living cells live in a dilute and complex substrate field, and to gain enough substrate, their extracellular enzymes must be utilized efficiently. The model revealed that surface-attached and free enzymes generate unique enzyme and substrate fields, and each deployment strategy has distinctive advantages. For a solitary cell, surface-attached enzymes are suggested to be the most cost-efficient strategy. This strategy entails potential substrates being reduced to very low concentrations. Free enzymes, on the other hand, generate a radically different substrate field, which suggests significant benefits for the strategy if free cells engage in social foraging or experience high substrate concentrations. Swimming has a slight positive effect for the attached-enzyme strategy, while the effect is negative for the free-enzyme strategy. The results of this study suggest that specific dissolved organic compounds in the ocean likely persist below a threshold concentration impervious to biological utilization. This could help explain the persistence and apparent refractory state of oceanic dissolved organic matter (DOM). Microbial extracellular enzyme strategies, therefore, have important implications for larger-scale processes, such as shaping the role of DOM in ocean carbon sequestration.

Abstract. Experimental green-roof rainfall–runoff observations have shown a positive impact on stormwater management at the building scale; with a decrease in the peak discharge and a decrease in runoff volume. This efficiency of green-roofs varies from one rainfall event to another depending on precipitation characteristics and substrate antecedent conditions. Due to this variability, currently, green-roofs are rarely officially used as a regulation tool to manage stormwater. Indeed, regulation rules governing the connection to the stormwater network are usually based on absolute threshold values that always have to be respected: maximum areal flow-rate or minimum retention volume for example. In this context, the aim of this study is to illustrate how a green-roof could represent an alternative to solve stormwater management issues, if the regulation rules were further based on statistics. For this purpose, a modelling scheme has been established at the parcel scale to simulate the hydrological response of several roof configurations: impervious, strictly regulated (in terms of areal flow-rate or retention volume), and covered by different types of green-roof matter. Simulations were carried out on a long precipitation time period (23 years) that included a large and heterogeneous set of hydrometeorological conditions. Results obtained for the different roof configurations were compared. Based on the return period of the rainfall event, the probability to respect some regulation rules (defined from real situations) was assessed. They illustrate that green-roofs reduce stormwater runoff compared to an impervious roof surface and can guarantee the respect of the regulation rules in most of the cases. Moreover, their implementation can appear more realistic than that of other infrastructures strictly complying with regulations and demanding significant storage capacity.

Abstract Impervious surface area (ISA) has different surface characteristics from the natural land cover and has great influence on watershed hydrology. To assess the urbanization effects on streamflow regimes, the authors analyzed the U.S. Geological Survey (USGS) streamflow data of 16 small watersheds in the White River [Indiana (IN)] basin. Correlation between hydrologic metrics (flow distribution, daily variation in streamflow, and frequency of high-flow events) and ISA was investigated by employing the nonparametric Mann–Kendall method. Results derived from the 16 watersheds show that urban intensity has a significant effect on all three hydrologic metrics. The Variable Infiltration Capacity (VIC) model was modified to represent ISA in urbanized basins using a bulk parameterization approach. The model was then applied to the White River basin to investigate the potential ability to simulate the water and energy cycle response to urbanization. Correlation analysis for individual VIC grid cells indicates that the VIC urban model was able to reproduce the slope magnitude and mean value of the USGS streamflow metrics. The urban model also reproduced the urban heat island (UHI) seen in the Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature products, especially for the grids encompassing the city of Indianapolis, IN. The difference of the hydrologic metrics obtained from the VIC model with and without urban representation indicates that the streamflow regime in the White River has been modified because of urban development. The observed data, together with model analysis, suggested that 3%–5% ISA in a watershed is the detectable threshold, beyond which urbanization effects start to have a statistically significant influence on streamflow regime.

Abstract Soil microbial communities potentially serve as indicators for their responses to changes in various ecosystems at scales from a region to the globe. However, changes in wetland soil bacterial communities and how they are related to urbanization intensities remains poorly understood. Here, we collected 60 soil samples along urbanization intensity gradients from 20 wetlands. We measured a range of environmental factors and characterized bacterial communities structure using 16S ribosomal RNA (16S rRNA) gene amplicon sequencing that targeted the V4-V5 region. Our results revealed the dominant soil bacterial phyla included Proteobacteria (39.3%), Acidobacteria (21.4%) and Chloroflexi (12.3%) in the wetlands, and showed a significant divergence of composition in intensive urbanization area (UI_4) than other places. A critical ‘threshold’ exists in the soil bacterial diversity, demonstrating different patterns: a gradual increase in the areas of low-to-intermediate disturbances but a significant decrease in highly urbanized areas where metabolic functions were significantly strong. Additionally, soil pH, total phosphorus (TP), available phosphorus (AP) and ammonia nitrogen (NH4 +-N) made a significant contribution to variations in bacterial communities, explaining 49.6%, 35.1%, 26.2% and 30.7% of the total variance, respectively. pH and NH4 +-N were identified as the main environmental drivers to determine bacterial community structure and diversity in the urban wetlands. Our results highlight collective changes in multiple environmental variables induced by urbanization rather than by the proportion of impervious surface area (ISA), which were potentially attributed to the spatial heterogeneity along different urbanization gradients.

This study was focused on the metropolitan area of Florence in Tuscany (Italy) with the aim of mapping and evaluating thermal summer diurnal hot- and cool-spots in relation to the features of greening, urban surfaces, and city morphology. The work was driven by Landsat 8 land surface temperature (LST) data related to 2015–2019 summer daytime periods. Hot-spot analysis was performed adopting Getis-Ord Gi* spatial statistics applied on mean summer LST datasets to obtain location and boundaries of hot- and cool-spot areas. Each hot- and cool-spot was classified by using three significance threshold levels: 90% (LEVEL-1), 95% (LEVEL-2), and 99% (LEVEL-3). A set of open data urban elements directly or indirectly related to LST at local scale were calculated for each hot- and cool-spot area: (1) Normalized Difference Vegetation Index (NDVI), (2) tree cover (TC), (3) water bodies (WB), (4) impervious areas (IA), (5) mean spatial albedo (ALB), (6) surface areas (SA), (7) Shape index (SI), (8) Sky View Factor (SVF), (9) theoretical solar radiation (RJ), and (10) mean population density (PD). A General Dominance Analysis (GDA) framework was adopted to investigate the relative importance of urban factors affecting thermal hot- and cool-spot areas. The results showed that 11.5% of the studied area is affected by cool-spots and 6.5% by hot-spots. The average LST variation between hot- and cold-spot areas was about 10 °C and it was 15 °C among the extreme hot- and cool-spot levels (LEVEL-3). Hot-spot detection was magnified by the role of vegetation (NDVI and TC) combined with the significant contribution of other urban elements. In particular, TC, NDVI and ALB were identified as the most significant predictors (p-values < 0.001) of the most extreme cool-spot level (LEVEL-3). NDVI, PD, ALB, and SVF were selected as the most significant predictors (p-values < 0.05 for PD and SVF; p-values < 0.001 for NDVI and ALB) of the hot-spot LEVEL-3. In this study, a reproducible methodology was developed applicable to any urban context by using available open data sources.

A Small Perched Perennial Spring has been used for Irrigation for 25 years. With an area of 23.3 ha its water potential basin varies from 90.7 to 979 m3/day so water conductivity of (k=62 cm/day producing between 0.30 to 3.17 lt/sec for lowest to highest rain return period (PR1 to PR100). Water Quantity and Hydraulic conductivity already mentioned were evaluated: Firstly, RPS structure were formed for 100 m of thick impervious lowermost member Lagrima Formation (Kli) overloading for a medium porosity (Klm, Klu) as well as high porosity of Finlay and del Norte Formations (Kf, Kdn). Secondly, Rainfall-Runoff-Recession hydrology model with Recession constant of 0.6 and ratio to pick of 0.2 in the threshold were used trough the simulation. Thus, Base (underground) and Direct (surface) runoff were separated. Finally, water quality and its interaction with host rocks were performed so; two water samples were collected and studied. Both samples were qualified as: Calcic-Bicarbonated (6f-C2) with low salinization risk (C3-S2). Therefore, water could be used for irrigation. In addition, water interaction among Cretaceous rocks of Sierra de Juárez as Lagrima (Kl), Finlay (Kf) and del Norte (Kdn) formations suggests three cases; One; If Calcium reduces Sodium increases given a sodic shale-slate system as: Ca2+HCO3+shales+Na+→Na++HCO3+shales+Ca2, this suggests that water have been confined by rock sourced Cretaceous Lagrima formation (Kli). Two, RPS overloaded recharge layers; Finlay (Kf) and (Kdn) with high karstification potential as high porosity is evident so: Three. If Na+ differ from Cl- thus, the cationic exchange has more Na+ than Cl- so more risk to karstification arises as mentioned before.

Airports have a profound impact on our lives, and uncovering their distribution around the world has great significance for research and development. However, existing airport databases are incomplete and have a high cost of updating. Thus, a fast and automatic worldwide airport detection method can be of significance for global airport detection at regular intervals. However, previous airport detection studies are usually based on single remote sensing (RS) imagery, which seems an overwhelming burden for worldwide airport detection with traversal searching. Thus, we propose a hierarchical airport detection method consisting of broad-scale extraction of worldwide candidate airport regions based on spatial analysis of released RS products, including impervious surfaces from FROM-GLC10 (fine resolution observation and monitoring of global land cover 10) product, building distribution from OSMs (open street maps) and digital surface model from AW3D30 (ALOS World 3D—30 m). Moreover, narrow-scale aircraft detection was initially conducted by the Faster R-CNN (regional-convolutional neural networks) deep learning method. To avoid overestimation of background regions by Faster R-CNN, a second CNN classifier is used to refine the class labeling with negative samples. Specifically, our research focuses on target airports with at least 2 km length in three experimental regions. Results show that spatial analysis reduced the possible regions to 0.56% of the total area of 75,691 km2. The initial aircraft detection by Faster R-CNN had a mean user’s accuracy of 88.90% and ensured that all the aircrafts could be detected. Then, by introducing the CNN reclassifier, the user’s accuracy of aircraft detection was significantly increased to 94.21%. Finally, through an experienced threshold of aircraft number, 19 of the total 20 airports were detected correctly. Our results reveal the overall workflow is reliable for automatic and rapid airport detection around the world with the help of released RS products. This research promotes the application and progression of deep learning.

In traditional approach, the land surface temperature (LST) is estimated by the permanent or portable ground-based weather stations. Due to the lack of adequate distribution of weather stations, a uniform LST could not be achieved. Todays, With the development of remote sensing from space, satellite data offer the only possibility for measuring LST over the entire globe with sufficiently high temporal resolution and with complete spatially averaged rather than point values. the remote sensing imageries with relatively high spatial and temporal resolution are used as suitable tools to uniformly LST estimation. Time series, generated by remote sensed LST, provide a rich spatial-temporal infrastructure for heat island’s analysis. in this paper, a time series was generated by Landsat8 and Landsat7 satellite images to analysis the changes in the spatial and temporal distribution of the Tehran’s LST. In this process, The Normalized Difference Vegetation Index (NDVI) threshold method was applied to extract the LST; then the changes in spatial and temporal distribution of LST over the period 1999 to 2014 were evaluated by the statistical analysis. Finally, the achieved results show the very low temperature regions and the middle temperature regions were reduced by the rate of 0.54% and 5.67% respectively. On the other hand, the high temperature and the very high temperature regions were increased by 3.68% and 0.38% respectively. These results indicate an incremental procedure on the distribution of the hot regions in Tehran in this period. To quantitatively compare urban heat islands (UHI), an index called Urban Heat Island Ratio Index(URI) was calculated. It can reveal the intensity of the UHI within the urban area. The calculation of the index was based on the ratio of UHI area to urban area. The greater the index, the more intense the UHI was. Eventually, Considering URI between 1999 and 2014, an increasing about 0.03 was shown. The reasons responsible for the changes in spatio-temporal characteristics of the LST were the sharp increase in impervious surfaces, increased use of fossil fuels and greening policies.

Urban expansion results in landscape pattern changes and associated changes in land surface temperature (LST) intensity. Spatial patterns of urban LST are affected by urban landscape pattern changes and seasonal variations. Instead of using LST change data, this study analysed the variation of LST aggregation which was evaluated by hotspot analysis to measure the spatial dependence for each LST pixel, indicating the relative magnitudes of the LST values in the neighbourhood of the LST pixel and the area proportion of the hotspot area to gain new insights into the thermal effects of increasing impervious surface area (ISA) caused by urbanization in Fuzhou, China. The spatio-temporal relationship between urban landscape patterns, hotspot locations reflecting urban land cover change in space and the thermal environment were analysed in different sectors. The linear spectral unmixing method of fully constrained least squares (FCLS) was used to unmix the bi-temporal Landsat TM/OLI imagery to derive subpixel ISA and the accuracy of the percent ISA was assessed. Then, a minimum change threshold was chosen to remove random noise, and the change of ISA between 2000 and 2016 was analysed. The urban area was divided into three circular consecutive urban zones in the cardinal directions from the city centre and each circular zone was further divided into eight segments; thus, a total of 24 spatial sectors were derived. The LST aggregation was analysed in different directions and urban segments and hotspot density was further calculated based on area proportion of hotspot areas in each sector. Finally, variations of mean normalized LST (NLST), area proportion of ISA, area proportion of ISA with high LST, and area proportion of hotspot area were quantified for all sectors for 2000 and 2016. The four levels of hotspot density were classified for all urban sectors by proportional ranges of 0%–25%, 25%–50%, 50%–75% and 75%–100% for low-, medium-, sub-high, and high density, and the spatial dynamics of hotspot density between the two dates showed that urbanization mainly dominated in sectors south–southeast 2 (SSE2), south–southwest 2 (SSW2), west–southwest 2 (WSW2), west–northwest 2 (WNW2), north–southwest 2 (NSW2), south–southeast 3 (SSE3) and south–southwest 3 (SSW3). This paper suggests a methodology for characterizing the urban thermal environment and a scientific basis for sustainable urban development.

Thermal regime warming and increased variability can result in human developed watersheds due to runoff over impervious surfaces and influence of stormwater pipes. This study quantified relationships between tree canopy, impervious surface, and water temperature in stream sites with 4 to 62% impervious land cover in their “loggersheds” to predict water temperature metrics relevant to aquatic species thermal stress thresholds. This study identified significant (≥0.7, p < 0.05) negative correlations between water temperature and percent tree canopy in the 5 m riparian area and positive correlations between water temperature and total length of stormwater pipe in the loggershed. Mixed-effects models predicted that tree canopy cover in the 5 m riparian area would reduce water temperatures 0.01 to 6 °C and total length of stormwater pipes in the loggershed would increase water temperatures 0.01 to 2.6 °C. To our knowledge, this is the first time that the relationship between stormwater pipes and water temperature metrics has been explored to better understand thermal dynamics in urban watersheds. The results highlight important aspects of thermal habitat quality and water temperature variability for aquatic species living in urban streams based on thermal thresholds relevant to species metabolism, growth, and life history.

During summer 2020, the most catastrophic flood in the 21st century attacked the Poyang Lake region, one of the flood-prone areas in China. To explore the occurrence mechanism and evolution patterns of this drought-converted flood better, a full lifecycle model is developed in this article. Employing Sentinel-1 Synthetic Aperture Radar (SAR) images, with the advantages of high spatial–temporal resolution and all-day and all-weather working capacity, a bimodal threshold was applied to efficiently extract flood inundation mapping. Thus, 61 Sentinel-1 SAR images in 2020 were used to establish inundation sequences for full lifecycle monitoring. This flood presented an abrupt transformation from drought, a long duration, and the slow receding of water, and its area exceeded 3000 km2 from July to early October. In addition, inundation models that reflect the lake area and water level relationship were introduced to assist near-real-time monitoring. Through hydrological and meteorological analysis, compared with results of previous years (from 2010 to 2019), this study found that the water level from July to October in 2020 was at least 17% higher than the mean level at the same period in history and water volume had increased about 44.13 billion m3 during the flooding period. Similarly, the average precipitation from June to September was significantly higher than the same period of previous years. It was the abnormal sustained heavy precipitation and sharp rising of the water level that caused this catastrophic flood. In particular, the Standardized Precipitation Index (SPI) increased from −1.02 in April to 1.31 in July, indicating that the flood was abruptly converted from drought. The inundated areas of several land types during different periods of the full lifecycle were calculated for damage assessment. It was found that cropland was the most heavily impaired with a maximum inundated area of 1375.67 km2, while other land types including forest, grassland, wetland, and impervious surface were relatively less damaged. The study results demonstrate that flood full lifecycle monitoring based on SAR data is helpful to explore the patterns of flood evolution, analyze causes, and assess damage. Simultaneously, focusing on drought-converted floods contributes to the understanding of flood patterns, which provides relevant management departments with decision support for disaster prevention and mitigation.

Urban heat island (UHI) attenuation is an essential aspect for maintaining environmental sustainability at a local, regional, and global scale. Although impervious surfaces (IS) and green spaces have been confirmed to have a dominant effect on the spatial differentiation of the urban land surface temperature (LST), comprehensive temporal and quantitative analysis of their combined effects on LST and surface urban heat island intensity (SUHII) changes is still partly lacking. This study took the plain area of Beijing, China as an example. Here, rapid urbanization and a large-scale afforestation project have caused distinct IS and vegetation cover changes within a small range of years. Based on 8 scenes of Landsat 5 TM/7ETM/8OLI images (30 m × 30 m spatial resolution), 920 scenes of EOS-Aqua-MODIS LST images (1 km × 1 km spatial resolution), and other data/information collected by different approaches, this study characterized the interrelationship of the impervious surface area (ISA) dynamic, forest cover increase, and LST and SUHII changes in Beijing’s plain area during 2009–2018. An innovative controlled regression analysis and scenario prediction method was used to identify the contribution of ISA change and afforestation to SUHII changes. The results showed that percent ISA and forest cover increased by 6.6 and 10.0, respectively, during 2009–2018. SUHIIs had significant rising tendencies during the decade, according to the time division of warm season days (summer days included) and cold season nights (winter nights included). LST changes during warm season days responded positively to a regionalized ISA increase and negatively to a regionalized forest cover increase. However, during cold season nights, LST changes responded negatively to a slight regionalized ISA increase, but positively to an extensive regionalized ISA increase, and LST variations responded negatively to a regionalized forest cover increase. The effect of vegetation cooling was weaker than ISA warming on warm season days, but the effect of vegetation cooling was similar to that of ISA during cold season nights. When it was assumed that LST variations were only caused by the combined effects of ISA changes and the planting project, it was found that 82.9% of the SUHII rise on warm season days (and 73.6% on summer days) was induced by the planting project, while 80.6% of the SUHII increase during cold season nights (and 78.9% during winter nights) was caused by ISA change. The study presents novel insights on UHI alleviation concerning IS and green space planning, e.g., the importance of the joint planning of IS and green spaces, season-oriented UHI mitigation, and considering the thresholds of regional IS expansion in relation to LST changes.

The effects of climate change are expected to increase the frequency and magnitude of floods, droughts and heat waves. An emerging method termed adaptation tipping point – opportunity (ATP-O) assesses a system's climate-incurred tipping points and uses opportunities arising from urban developments to introduce adaptation strategies while reducing investment costs. The objective of this research was to apply the ATP-O method to the city of Dordrecht in the Netherlands. The results show that the alternative adaptation strategy proposed (an overland drainage system) would be effective in coping with the effects of climate change where the current management strategy (disconnection of impervious surfaces from sewer systems) fails to do so. The ATP-O also proved helpful in identifying opportunities to adapt at lower costs. This research stimulated discussions between stakeholders on performance objectives, policy development, investment strategies, and flood risk management practices. The sensitivity analysis performed to support such discussion revealed that small variations in acceptability thresholds, associated with policy objectives, can have significant impact on ATP occurrence and timing.

Abstract Paved surfaces, increased precipitation intensities in addition to limited capacity in the sewer systems, cause a higher risk of combined sewer overflows (CSOs). Sustainable drainage systems (SUDS) offer an alternative approach to mitigate CSO by managing the stormwater locally. Seven SUDS scenarios, developed based on the concept of effective impervious area reduction, have been implemented in the Grefsen catchment using the Mike Urban model. This study evaluated the hydrological performance of two SUDS controls (i.e. green roof (GR) and rain garden (RG)) modules of the model and the effect of the SUDS scenarios on the CSOs using event-based and continuous simulations. The Nash–Sutcliffe efficiency (NSE) along with flow duration curves (FDCs) has been used for evaluating the model performance. Event-based evaluations revealed the superior performance of the RG in reducing CSOs for larger precipitation events, while GRs were proven to have beneficial outcomes during smaller events. The study illustrated another way of assessing the continuous simulations by employing the FDCs. The FDCs were assessed against a discharge threshold at the outlet (which authorities can set as design criteria) of the catchment in terms of the extent, each scenario reduced occurrence and duration of outflow that invokes flow in the overflow pipe.

Data on the extension of urban areas are important for analyzing growth dynamics and to support the planning of transport and service provision. Satellite-based remote sensing has proven extremely useful, especially in cities that experience fast spatial growth. Different approaches to satellite-based mapping may, however, produce different results concerning urban categorization and delineation, often making direct comparison misleading. This study analyses four different satellite-based studies of urban land cover in Accra, Ghana and presents a new land cover map based on visual interpretation of segmented Sentinel-2 imagery. The methods and results, as well as the underlying definition of “urban”, are compared and discussed. One method identifies exclusively areas with man-made, impervious surfaces, such as roads and buildings, as proxies for urban extent. Other methods aim to identify a broader set of land cover types, including green spaces, which are treated as part of the mixed urban fabric. Further differences are found in the way urban fringe areas under development are classified depending on their degree of urbanization, and in the distance threshold values used for defining the urban agglomeration. For the most recent maps we identify a difference in the measured size of the Accra agglomeration of almost 100%.

Owing to the limitation of spatial resolution and spectral resolution, deep learning methods are rarely used for the classification of multispectral remote sensing images based on the real spectral dataset from multispectral remote sensing images. This study explores the application of a deep learning model to the spectral classification of multispectral remote sensing images. To address the problem of the large workload with respect to selecting training samples during classification by deep learning, first, linear spectral mixture analysis and the spectral index method were applied to extract the pixels of impervious surfaces, soil, vegetation, and water. Second, through the Euclidean distance threshold method, a spectral dataset of multispectral image pixels was established. Third, a deep learning classification model, ResNet-18, was constructed to classify Landsat 8 OLI images based on pixels’ real spectral information. According to the accuracy assessment, the results show that the overall accuracy of the classification results can reach 0.9436, and the kappa coefficient can reach 0.8808. This study proposes a method that allows for the more optimized establishment of the actual spectral dataset of ground objects, addresses the limitations of difficult sample selection in deep learning classification and of spectral similarity in traditional classification methods, and applies the deep learning method to the classification of multispectral remote sensing images based on a real spectral dataset.

<p><strong>Abstract.</strong> The occurrence of urban flooding following strong rainfall events may increase as a result of climate change. Urban expansion, aging infrastructure and an increasing number of impervious surfaces are further exacerbating flooding. To increase resilience and support flood mitigation, bespoke accurate flood modelling and reliable prediction is required. However, flooding in urban areas is most challenging. State-of-the-art flood inundation modelling is still often based on relatively low-resolution 2.5&amp;thinsp;D bare earth models with 2&amp;ndash;5&amp;thinsp;m GSD. Current systems suffer from a lack of precise input data and numerical instabilities and lack of other important data, such as drainage networks. Especially, the quality and resolution of the topographic input data represents a major source of uncertainty in urban flood modelling. A benchmark study is needed that defines the accuracy requirements for highly detailed urban flood modelling and to improve our understanding of important threshold processes and limitations of current methods and 3D mapping data alike.</p><p>This paper presents the first steps in establishing a new, innovative multiscale data set suitable to benchmark urban flood modelling. The final data set will consist of high-resolution 3D mapping data acquired from different airborne platforms, focusing on the use of drones (optical and LiDAR). The case study includes residential as well as rural areas in Dudelange/Luxembourg, which have been prone to localized flash flooding following strong rainfall events in recent years. The project also represents a cross disciplinary collaboration between the geospatial and flood modelling community. In this paper, we introduce the first steps to build up a new benchmark data set together with some initial flood modelling results. More detailed investigations will follow in the next phases of this project.</p>

A GIS-based approach is used in this study to obtain a better LCZ map of Berlin in comparison to the remote-sensing-based WUDAPT L0 approach. The LCZ classification of land use/cover can be used, among other applications, to characterize the urban heat island. An improved fuzzy logic method is employed for the purpose of classification of the zone properties to yield the GIS-LCZ map over 100 m × 100 m grid tiles covering the Berlin region. The zone properties are calculated from raster and vector datasets with the aids of the urban multi-scale environmental predictor (UMEP), QGIS and Python scripts. The standard framework is modified by reducing the threshold for the zone property impervious fraction for LCZ E to better detect paved surfaces in urban areas. Another modification is the reduction in the window size in the majority filter during post-processing, compared to the WUDAPT L0 method, to retain more details in the GIS-LCZ map. Moreover, new training areas are generated considering building height information. The result of the GIS-LCZ approach is compared to the new training areas for accuracy assessment, which shows better overall accuracy compared to that of the WUDAPT L0 method. The new training areas are also submitted to the LCZ generator and the resulting LCZ-map gives a better overall accuracy value compared to the previous (WUDAPT) submission. This study shows one shortcoming of the WUDAPT L0 method: it does not explicitly use building height information and that leads to misclassification of LCZs in several cases. The GIS-LCZ method addresses this shortcoming effectively. Finally, an unsupervised machine learning method, k-means clustering, is applied to cluster the grid tiles according to their zone properties into custom classes. The custom clusters are compared to the GIS-LCZ classes and the results indicate that k-means clustering can identify more complex city-specific classes or LCZ transition types, while the GIS-LCZ method always divides regions into the standard LCZ classes.

Land use information plays a vital role in effective management of natural resources in any country. It helps manage water, soil, nutrients and plants, animals and provides relationships between land use dynamics, economics and social conditions both in urban and rural areas. The land use and land cover mapping is always a dynamic issue in every country because of the dynamic nature of the land use. Knowledge of land use change patterns has important implications in sustainable development and sustainable environmental management. Impervious surfaces are generally defined as any anthropogenic materials that water cannot infiltrate. Increase in impervious land in urban area is causing high accumulation of storm water during the wet season and causing widespread flooding.This research develops an improved method for impervious land use detection using object–oriented classification system. Although pixel-based approaches have certain strong merits and remain in widespread use, operating at the spatial scale of the pixel can have major drawbacks. Foremost among these is that a pixel’s spatial extent may not match the extent of the land cover feature of interest. That is pixel’s spatial extent may not match the extent of the land cover feature of interest-the problem of mixed pixels may lead to misclassification. Also, when object of interest is considerably larger than the pixel size such as VHR images, urban area comparisons show that the object oriented approach is superior to pixel based approach in terms of accuracy. Object Oriented classification technique is used to separate urban and non-urban features. Negative values of NDVI helped to classify impervious area. Non elevated impervious surfaces are well addressed by NDVI threshold. LiDAR data is used to separate elevated impervious area. By and large, the research shows that impervious land in urban area can be detected using the developed technique with satisfactory accuracy.

Nepal’s political institutions and administrative units were thoroughly restructured in 2015 with the promulgation of the new Constitution. Several rural areas were combined to meet the definition of urban threshold criteria to classify rural areas into urban categories. Accordingly, over 3,900 local political and administrative units were amalgamated into 753 units, of which, 293 units are classified as urban. Within these newly defined urban areas, many natural environments have been converted into impervious surfaces such as paved roads, sidewalks, and building roofs. These impervious surfaces have drastically increased the amount of surface run-offs—often termed as “urban floods” --under increasing precipitation caused by global climate change. These incidences have negatively impacted to the groundwater recharge processes in the urban areas. Data on groundwater recharge rates are needed in the context of global climate change to understand the status of groundwater recharge processes in the urban areas of Nepal. However, due to various limitations, this study only focuses around the Kathmandu Valley of Nepal to understand: a) how the expansion of urban, peri-urban, and associated areas have resulted in decreasing groundwater recharges; b) how groundwater is affected by the year-to-year variability of precipitation amount (low and high intensity) with the conversion of the natural landscape into built-up areas; and c) how the changing trends in precipitation and evapotranspiration may impact future groundwater availability. This study is based on a review of the literature and the analysis of secondary data available from the government and various social media and authors' professional experiences. The study ends with some recommendations based on experiences from other parts of the world on groundwater recharge processes.

Trees provide ecosystem services that benefit humans and the environment. Unfortunately, urban trees often do not provide maximum services due to abiotic stress and arthropod herbivores and borers. These problems often originate from trees being planted in unsuitable conditions. Cities are warmer than natural areas because impervious surfaces absorb and reradiate heat. Higher temperatures can increase pest insect abundance and water stress, and reduce street tree condition relative to natural forests. For example, the gloomy scale insect [Melanaspsis tenebricosa Comstock (Hemiptera: Diaspididae)], a pest of red maple (Acer rubrum) street trees, is more abundant in warmer than cooler urban sites. Acer rubrum, at warmer urban sites with more M. tenebricosa, are typically in poor condition. Here, researchers demonstrate these relationships and illustrate how impervious surface cover can be used to predict the condition of A. rubrum street trees. impervious surface thresholds were then developed to define suitable planting sites that can be used by individuals with access to GIS software. Researchers present the pace-to-plant technique, which can be used by landscape professionals to quickly estimate impervious surface cover around a planting site. These thresholds predict future tree condition based on planting site impervious surface cover. The hope is that more informed planting will minimize pest infestations and maximize the future vigor and performance of street trees.

A foundation of integrated pest management (IPM) in urban landscapes is to put the right plant in the right place. This preventive tactic can reduce plant stress, pest infestations, and subsequent pesticide applications. Many urban tree species have more insect and mite pests in urban landscapes than in surrounding natural areas. This is due in part to stress created by impervious surfaces, such as roads and sidewalks that can increase air temperature and reduce soil moisture. For red maples (Acer rubrum), more impervious surface area leads to more stress and worse tree condition. This publication focuses on selecting red maple planting sites that will help reduce tree stress and scale insect pests by maximizing surfaces permeable to water.

Urbanization leads to changes in land use, and the expansion of impervious surfaces leads to an increase in flood vulnerability. Predicting and analyzing these landscape pattern changes are important in the early stages of urban planning. In practice, the threshold for obtaining comprehensive and detailed hydrological and meteorological data is high, which makes it difficult for landscape and urban planners to quickly evaluate urban floods. To compensate for these trends, we took Nanjing, China, as the study site and discussed the leading flood vulnerability landscape patterns based on quantitative assessments. We introduced catastrophe theory to integrate three indicators and seven subfactors for flood vulnerability assessment: exposure, including precipitation; sensitivity, including elevation, slope, soil and drainage density; and adaptability, including land use and forest coverage. Then, we calculated the landscape pattern metrics (shape index, fractal dimension index, related circumscribing circle, contiguity index and landscape division index) at the class level. Finally, we divided the city into four subregions, established regression models for the subregions and the whole city, and deduced the leading flood vulnerability landscape patterns in each region and the whole city. We found that the leading landscape patterns varied among different regions. According to the research results, the landscape pattern indexes identified in this paper can be interpreted intuitively, which can provide a reference for modifying the planning layout of regional green infrastructure, optimizing the vulnerability of urban floods, and providing a basis for further improving Nanjing urban planning and alleviating the urban flood vulnerability. The methods proposed herein also will benefit land use and green infrastructure management in other regions lacking meteorological and hydrological data.

In The Practice of Everyday Life, Walking in the City, Michel de Certeau celebrates the glorious sublimity of an Icarian moment as his gaze from the 110th floor of the World Trade Centre soars over Manhattan. Having taken such a voluptuous pleasure (92) in the view myself, and watched the twin towers collapse into rubble on my television screen last September, as I re-visit the aerial site through de Certeau, his words resonate strongly with the oneiric force of memory, myth and the wonder of urban possibility. For while theorising, does de Certeau not write his own story of the city as dream, as imaginative longing, consuming and producing an urban 'text' (93) as he reads from on high? Participating in the logic of one of the city's opportunities, a tourist attraction, his analytic practice is a creative expression of his own subjective experience. Theoretically, the story begins in the labyrinth of the cityscape, where the urban text is humanised by its mobile, unpredictable practitioners whose everyday operations style, invent and generate ways of being and becoming. What de Certeau offers us is something quite beautiful and noble, almost consolatory, in the idea of an artful, other spatiality that slips, undetected, into the banal routine of daily existence. To explore how lived space (96) is authorised by its heroic practitioners, made other, as it is inscribed into and outside the historic, social and economic realities or strategies of the urban environment, I resort to fiction, where the certain strangeness (93) of the everyday surfaces to be read. Colum McCann's novel, This Side of Brightness, takes us down below de Certeau's down below to the subterranean spaces of the New York City subway tunnels where the central character, Treefrog, estranged from his family, makes his home: his dark nest, high in the tunnel (McCann 2). Treefrog's escape into this murky, cavernous netherworld is a disappearing act for this is where no ordinary practitioners of the city live 'down below,' [down] below the thresholds at which [an everyday] visibility begins. (de Certeau 93) Seeking refuge, this is where the city's resident asylum seekers migrate, claiming exile as a right. To be outcast is an autonomous and pragmatic spatial tactic, a self-imposed, self-composed state of being as other. Here, survival is a process of resistance, an illegal occupation. Errant and devious, the lifestyle choice these urban consumers make violates the civil ordinances of the city. Venturing topside, Treefrog repels, offends and embarrasses the ordinary practitioners of the city travelling on the subway (96, 240) and in the reading room at the public library (93). The disgust and fear aroused by his stench and squalid appearance make no allowance for pity or pride. In these aboveground collective social spaces his unhygienic, undomesticated presence is not proper; it signals defiance in its fetid, imposing refusal to be controlled or to disappear. Treefrog is an anonymous manifestation of the cityscape. Disguised by long hair, a beard, ragged clothes, filth and dirt (242), his real identity is undetectable: Clarence Nathan Walker is invisible. Seemingly primitive, this sight is decidedly modern in its ubiquitous depiction of the contemporary urban indigent. A place of wounded spirits, Treefrog's 'mole' neighbourhood confesses the shame of an overwhelming suffering born of the streets. Papa Love's grief is monumentalised in the surreal gargantuan murals and portraits of the dead he paints on the walls of the tunnel. Crack addicts, Angela and Elijah, get high, wasted, underground. A symbolic toilet seat hangs wreath-like on Faraday's front door; as a doorbell (128). Dean, the Trash Man, collects the discarded remains of an urban consumer society and installs them in his 'front yard' as an assemblage of ready-made materials and found objects. Textually, his 'work' orchestrates a cacophony of human ruin and putrescence: the mounds of human faeces and the torn magazines and the empty containers and the hypodermic needles with blobs of blood at their tips like poppies erupting in a field...the broken bottles and rat droppings and a baby carriage and smashed TV and squashed cans and discarded cardboard boxes and shattered jars and orange peels and crack vials and a single teddy bear with both its eyes missing, its belly nibbled into by rats. (56) In this community, housing isolates, shelters and incarcerates, each inhabitant has their own cubicle, concrete bunker, solitary cell (56). In contrast to this depressed existential vista, before his incarnation as Treefrog, Clarence Nathan knows the sublime erotic charge of towering over New York City, expressed by de Certeau. Working construction on the city's skyscrapers, he seeks ascension, going, willfully, higher than any walking man in Manhattan....Beneath him, Manhattan becomes a blur of moving yellow taxis and dark silhouettes. There is something in this rising akin to desire, the gentle rock from side to side, the cooling breeze, the knowledge that he is the one who will pierce the virginity of space where the steel hits the sky....The elevator clangs and stops. Clarence Nathan finishes his coffee, tosses the paper cup and walks across the metal decking towards two ladders which jut up in the air. For a joke the men call this area the POST: The Place of Shrivelled Testicles. No ordinary man will go further. The nimblest Clarence Nathan and Cricket...climb three ladders to the very top of the building, where columns of steel reach up into the air. (195-6) Unaffected by vertigo and impervious to the danger, there is a seeming nonchalance, a banality, to Clarence Nathan's activity as he finishes his coffee, tosses the paper cup and gets to work; this is a practice of everyday life for him. And yet this productive activity, governed by city council planning and approval, contains a liberatory ruse, an 'anthropological,' poetic and mythic experience of space, (93) as proposed by de Certeau. High above, he performs a transcendent manoeuvre, a magic trick, creating and constructing space out of thin air, nothing. Icarian, Clarence Nathan's desire seems not for scopic pleasure but for the pure visceral elation of being unrestrained, unprotected, autonomous, above and beyond the rest of the world. At such a height Clarence Nathan does not speculate or even think he forgets where he is, that his 'body even exists.' (177) Surpassing rational comprehension and linguistic expression, his elevation articulates an unadulterated liberation, an erotics of feeling and an ecstasy of being: [s]ometimes, for a joke, Clarence Nathan takes out his harmonica at the top of the column and blows into it using just one hand. The wind carries most of the tune away, but occasionally the notes filter down to the ironworkers below. The notes sound billowy and strained, and for this the men sometimes call him Treefrog, a name he doesn't much care for. (198) From this pivotal point, high on the extreme vertical axis of the cityscape, Clarence Nathan has much further to fall when he loses his balance mentally, descending into an abyss of human despair. Being down is not deep enough. Going underground, Clarence Nathan reclaims this haunted, burrowed space of the city as a legacy bequeathed to him by his grandfather, one of the sandhogs who dug the tunnels of the New York subway, and reinvents himself as Treefrog. An appropriate moniker for this uncivilised, otherworldly realm, [a]ll darkness and dampness and danger, (7) sometimes it is the only name he can remember (29). Foregrounding memory and myth, McCann's fable weaves the creation story of a family through the interstices of a city's legends and official history, allowing us to read the appropriation, the othering, of the city's spaces by its inhabitants in the practice of their lives as ephemeral markings of artistic activity. Through the incantation of spatial and narrative trajectories, as de Certeau suggests, [a] migrational, or metaphorical, city thus slips into the clear text of the planned and readable city (93). Writing himself into these catacombs, literally, Treefrog embraces his interment, his burial rights, as a return to his primordial home: In his notebook Treefrog writes: Back down under the earth, where you belong. Back down under the earth where you belong....He could make a map of those words, beginning at the B and ending at the g where all beginning begins and ends and they would make the strangest of upground and belowground topographies. (139) So as not to forget the strange topographies of existence, Treefrog inscribes them on the surface of his skin: [h]is chest is scrimshawed with stabwounds and burns and scars. So many mutilations of his body. Hot paper clips, blunt scissors, pliers, cigarettes, matches, blades they have all left their marks. (30) Mapping an abstract expression, intimately, these are the warrior scars of the initiate. Belowground, Clarence Nathan eludes the clinical strategies of his obsessive-compulsive post-traumatic stress disorder; he avoids the nuthouse (228). Here, in retreat, as Treefrog, he is free to create, dream and imagine, unrestrained and unexamined; it is an elegant self-prescribed remedy. For Clarence Nathan, the tunnels are therapeutic and restorative. Ultimately, they enable him to be resurrected back into the light, upground, leaving Treefrog, like a discarded doppelgänger, to the shadows of the tunnels (242-3). An ironic compensation for his mental instability, Clarence Nathan's gift of perfect physical balance, his inheritance, (170) determines his survival underground. Safe and secure with his cave positioned high in the tunnel wall, Treefrog's daily movements are dependent upon the demonstration of an agile bodily grace, a mobility that defies gravity in its series of acrobatic swings and precarious tight-rope walking. Enhancing the danger and difficulty of his daring by performing blindfolded, Treefrog negotiates space intuitively: he walks onto the catwalk with his eyelids shut. The narrow beam requires supreme balance below him is a twenty foot drop to the tunnel. He swings his way down to the second beam ten feet below, crouches, then leaps and drops soundlessly to the gravel, knees bent, heart thumping. He opens his eyes to the darkness. (25) Mimetically Treefrog appropriates this eternal nocturnal realm and makes it his own, a part of himself, he feels the darkness, smells it, belongs to it. (23) As from his subterranean perch Treefrog fills the emptiness with the eerie, improvised strains of his harmonica, the stale, dank, tired air of the tunnels, is filtered through the human body, and used to make something strangely ethereal, beautiful, fresh and new: in the miasmic dark, Treefrog played, transforming the air, giving back to the tunnels their original music (2). Treefrog accepts this other spatiality, carved into and out of the urban environment, as a gift, and his performance reciprocates a generosity that signals hope and healing; '[t]he world, he knows, can still spring its small and wondrous surprises (53). McCann presents the tunnels of New York City as an urban wilderness, a lawless frontier. And yes, Treefrog's community is comprised of "demonic subterraneans madmen, perverts, addicts, criminals, murderers," but challenging Blanche Gelfant's account of the lower states, this reverse spatial direction does not necessarily signify a metaphorical mobilisation of values downward into the unexplored depths of moral disorder (417). Rather, in This Side of Brightness, moral disorder is a condition of ordinary, everyday existence aboveground, where violence, chaos, vulnerability, persecution, terror, inequality, kindness, disregard, compassion, indifference, awe, tragedy, compose, socially, [a] landscape of loving and hating. A palpable viciousness in the air. And yet a tenderness too. Something about this part of the world being so alive that its own heart could burst from the accumulated grief. As if it all might suddenly fulminate under the gravity of living. (185) Figured imaginatively through Treefrog the tunnels become an enchanted otherworldly space, '[a] heaven of hell,' (70) in which darkness, solitude and anonymity have the miraculous power to strengthen and absolve. Amidst the waste and detritus a beauty is brutally, painfully laid bare. For Treefrog, for Clarence Nathan, the tunnels are an emotional and psychological sanctuary and their appropriation is a courageous life-affirming act: it is only underground that...men become men, integrated, whole (37). References de Certeau, Michel. The Practice of Everyday Life. Trans. Steven Rendall. Berkeley: U of California P, 1988. Gelfant, Blanche. Residence Underground: Recent Fictions of the Subterranean City. The Sewanee Review. 83 (1975): 406-38. McCann, Colum. This Side of Brightness. London: Phoenix House, 1998. Citation reference for this article MLA Style Williams, Marisa. "Going Underground" M/C: A Journal of Media and Culture 5.2 (2002). [your date of access] < http://www.media-culture.org.au/0205/underground.php>. Chicago Style Williams, Marisa, "Going Underground" M/C: A Journal of Media and Culture 5, no. 2 (2002), < http://www.media-culture.org.au/0205/underground.php> ([your date of access]). APA Style Williams, Marisa. (2002) Going Underground. M/C: A Journal of Media and Culture 5(2). < http://www.media-culture.org.au/0205/underground.php> ([your date of access]).