Effects of Increasing Impervious Surface on Water Quality in Ile-Ife Urban Watershed, Southwestern Nigeria

The urban environment has continued to experience changes from increasing impervious surfaces, which alters the proper functioning of the ecological zones and impairs water quality in the watershed. Impervious cover is predominantly used as an indicator to assist in understanding and forecasting the impact of human actions and other related activities on aquatic resources. In this study, the rate of change in land uses using the impervious surface as an indicator, and the percentage of imperviousness on the effect on water quality in the urban watershed were assessed. Ile-Ife was delineated as an urban watershed, and the percentage of imperviousness from 2008 to 2016 and the effect of imperviousness on water bodies were assessed. The study utilized ASTERDEM, Worldview (0.46 m), IKONOS (1.4 m), Landsat (30 m) for 2008 and 2016, GPS and Drone (10 cm). Water sampling was carried out in selected locations as generated by the impervious surface analyst tool, (ISAT). The percentage (%) of impervious surfaces accounted for 59.4% (4567.1/7691.5ha) in 2008 and 70.3% (5408.2/7691.5ha) in 2016, from the total number of lands investigated. The turbidity values from low to high regions were 32.3, 55.9 and 82.4 NUT. Changes in LULC of the watershed led to increased surface temperature, impermeable surfaces, and decreased vegetation, which exposes the area to flooding and reduced water quality. This study emphasized the importance of GIS and its integration into urban changes and water quality assessment.

Evaluating impervious surface growth and its impacts on water environment in Beijing- Tianjin-Tangshan Metropolitan Area

The impervious surface area （ISA） at the regional scale is one of the important environmental factors for examining the interaction and mechanism of Land Use/Cover Change （LUCC）-ecosystem processes-climate change under the interactions of urbanization and global environmental change. Timely and accurate extraction of ISA from remotely sensed data at the regional scale is challenging. This study explored the ISA extraction based on MODIS and DMSP-OLS data and the incorporation of China＇s land use/cover data. ISA datasets in Beijing-Tianjin-Tangshan Metropolitan Area （BTTMA） in 2000 and 2008 at a spatial resolution of 250 m were developed, their spatiotemporal changes were analyzed, and their impacts on water quality were then evaluated. The results indicated that ISA in BTTMA increased rapidly along urban fringe, transportation corridors and coastal belt both in intensity and extents from 2000 to 2008. Three cities （Tangshan, Langfang and Qinhuangdao） in Hebei Province had higher ISA growth rates than Beijing due to the pressure of population-resour- ces-environments in the city resulting in increasingly transferring industries to the nearby areas. The dense ISA distribution in BTTMA has serious impacts on water quality in the Haihe River watershed. Meanwhile, the proportion of ISA in sub-watersheds has significantly linear relationships with the densities of river COD and NH3-N.

Effects of spatial resolution of remotely sensed data on estimating urban impervious surfaces

Impervious surfaces are the result of urbanization that can be explicitly quantified, managed and controlled at each stage of land development. It is a very useful environmental indicator that can be used to measure the impacts of urbanization on surface runoff, water quality, air quality, biodiversity and rnicroclimate. Therefore, accurate estimation of impervious surfaces is critical for urban environmental monitoring, land management, decision-making and urban planning. Many approaches have been developed to estimate surface imperviousness, using remotely sensed data with various spatial resolutions. However, few studies, have investigated the effects of spatial resolution on estimating surface imperviousness. We compare medium-resolution Landsat data with high-resolution SPOT images to quantify the imperviousness in Beijing, China. The results indicated that the overall 91% accuracy of estimates of imperviousness based on TM data was considerably higher than the 81% accuracy of the SPOT data. The higher resolution SPOT data did not always predict the imperviousness of the land better than the TM data. At the whole city level, the TM data better predicts the percentage cover of impervious surfaces. At the sub-city level, however, the ring belts from the central core to the urban-rural peripheral, the SPOT data may better predict the imperviousness. These results highlighted the need to combine multiple resolution data to quantify the percentage of imperviousness, as higher resolution data do not necessarily lead to more accurate estimates. The methodology and results in this study can be utilized to identify the most suitable remote sensing data to quickly and efficiently extract the pattern of the impervious land, which could provide the base for further study on many related urban environmental problems.

Methods to extract impervious surface areas from satellite images

Impervious surface area(ISA)is an important parameter for many environmental or socioeconomic relevant studies.The unique characteristics of remote sensing data made it the primary data source for ISA mapping at various scales.This paper summarizes general ISA mapping procedure and major techniques and discusses impacts of scale issues on selection of remote sensing data and corresponding algorithms.Previous studies have indicated that ISA mapping remains a challenge,especially in urban–rural frontiers and in covering a large area.Effectively employing rich spatial information in high spatial resolution imagery through texture and objectbased methods is valuable.Data fusion of multi-resolution images and spectral mixture analysis are common approaches to reduce the mixed pixel problem in medium spatial resolution images such as Landsat.Coarse spatial resolution images such as MODIS and DMSP-OLS are valuable for national and global ISA mapping but more research is needed to effectively integrate multisource/scale data for improving mapping performance.Development of an optimal procedure corresponding to specific study areas and purposes is required to generate accurate ISA mapping results.

Impervious surface extraction based on different methods from multiple spatial resolution images:a comprehensive comparison

Many efforts have been devoted to extracting impervious surfaces based on different methods from multiple spatial resolution images.Differences in extraction methods and spatial resolutions are significant and have led to discrepant performances in terms of the impervious surface extraction accuracy.However,which extraction method is more suitable for which kind of spatial resolution image in practice is poorly understood.This study systematically compared the performances of 12 methods of impervious surface extraction for four spatial resolution images(i.e.Landsat 8[30 m],Sentinel-2A[20 m],Sentinel-2A[10 m],and Gaofen-2[4 m])in three testing areas.The results indicated that for the mediumspatial resolutions of 30 and 20 m,the support vector machine(SVM)method was considered as the optimal classification method with the highest accuracy of impervious surface extraction.For the high-spatial resolutions of 10 and 4 m,the object based image analysis(OBIA)method obtained the highest accuracy of the impervious surface distribution.Furthermore,the perpendicular impervious surface index(PISI)outperformed the other indices in obtaining the impervious surface distribution,with the highest accuracy for four spatial resolution images.These comprehensive assessments can provide a valuable guidance for future impervious surface extraction from different spatial resolutions.

Multi-resolution integration of land cover for sub-pixel estimation of urban impervious surface and forest cover

A methodology is presented for estimating percent coverage of impervious surface(IS)and forest cover(FC)within Landsat thematic mapper(TM)pixels of urban areas.High-resolution multi-spectral images from Quickbird(QB)play a key role in the sub-pixel mapping process by providing information on the spatial distributions of ISs and FCs at 2.4 m ground sampling intervals.Thematic classifications,also derived from the Landsat imagery,have then been employed to define relationships between 30 m Landsat-derived greenness values and percent IS and FC.By also utilizing land cover/land use classification derived from Landsat and defining unique relationships for urban sub-classes(i.e.residential,commercial/industrial,open land),confusion between impervious and fallow agricultural lands has been overcome.Test results are presented for Ottawa-Gatineau,an urban area that encompasses many aspects typical of the North American urban landscape.Multiple QB scenes have been acquired for this urban centre,thereby allowing us to undertake an in-depth study of the error budgets associated with the fractional inference process.

Understanding the effects of the impervious surfaces pattern on land surface temperature in an urban area

It is well known that urban impervious surface （IS） has a warming effect on urban land surface temperature （LST）. However, the influence of an IS＇s structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM＋ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis （LSMA）, and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.

Mapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution

Impervious surface mapping is essential for urban environmental studies.Spectral Mixture Analysis(SMA)and its extensions are widely employed in impervious surface estimation from medium-resolution images.For SMA,inappropriate endmember combinations and inadequate endmember classes have been recognized as the primary reasons for estimation errors.Meanwhile,the spectral-only SMA,without considering urban spatial distribution,fails to consider spectral variability in an adequate manner.The lack of endmember class diversity and their spatial variations lead to over/underestimation.To mitigate these issues,this study integrates a hierarchical strategy and spatially varied endmember spectra to map impervious surface abundance,taking Wuhan and Wuzhou as two study areas.Specifically,the piecewise convex multiple-model endmember detection algorithm is applied to automatically hierarch-ize images into three regions,and distinct endmember combinations are independently developed in each region.Then,spatially varied endmember spectra are synthesized through neighboring spectra using the distance-based weight.Comparative analysis indicates that the proposed method achieves better performance than Hierarchical SMA and Fixed Four-endmembers SMA in terms of MAE,SE,and RMSE.Further analysis suggests that the hierarch-ical strategy can expand endmember class types and considerably improve the performance for the study areas in general,specifically in less developed areas.Moreover,we find that spatially varied endmember spectra facilitate the reduction of heterogeneous surface material variations and achieve the improved performance in developed areas.

Seasonal effects of impervious surface estimation in subtropical monsoon regions

Accurate impervious surface estimation(ISE)is challenging due to the diversity of land covers and the vegetation phenology and climate.This study investigates the variation of impervious surfaces estimated from different seasons of satellite images and the seasonal sensitivity of different methods.Four Landsat ETM?images of four different seasons and two popular methods(i.e.artificial neural network(ANN)and support vector machine(SVM))are employed to estimate the impervious surface on the pixel level.Results indicate that winter(dry season)is the best season to estimate impervious surface even though plants are not in their growing season.Less cloud and less variable source areas(VSA)(seasonal water body)become the major advantages of winter for the ISE,as cloud is easily confusedwith bright impervious surfaces,andwater in VSA is confusedwith dark impervious surfaces due to their similar spectral reflectance.For the seasonal sensitivity of methods,ANN appears more stable as its accuracy varied less than that obtained with SVM.However,both the methods showed a general consistency of the seasonal changes of the accuracy,indicating that winter time is the best season for impervious surfaces estimation with optical satellite images in subtropical monsoon regions.

Change of impervious surface area and its impacts on urban landscape:an example of Shenyang between 2010 and 2017

Introduction:One of the most striking features of urbanization is the replacement of the original natural land cover type by artificial impervious surface area(ISA).However,the extent of the contribution of various environmental factors,especially the growth of 3D space to ISA expansion,and the scope and mechanism of their influences in dramatically expanding cities,are yet to be determined.The boosted regression tree(BRT)model was adopted to analyze the main influencing factors and driving mechanisms of ISA change in Shenyang,China between 2010 and 2017.Outcomes:The nearly complete-coverage ISA(≥0.7)increased from 42%in 2010 to 47%in 2017.The percentage of landscape with a high ISA fraction increased,while the landscape evenness and diversity of ISA decreased.The BRT analysis revealed that elevation,regional population density,and landscape class had the largest influences on the change of urban ISA,contributing 22.55%,18.16%,and 11.18%to the model,respectively.Conclusion:Overall,topographic and socioeconomic factors had the greatest influence on urban ISA change in Shenyang,followed by land use type and building pattern indices.The trend of high aggregation was strong in large commercial and residential areas.The 3D expansion of the city had an influence on its areal expansion.

Geospatial Analysis of Urban Heat Island Effects and Tree Equity

In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.

Pollutant loads of surface runoff in Wuhan City Zoo, an urban tourist area

The pollutant loads of surface runoff in an urban tourist area have been investigated for two years in the Wuhan City Zoo, China. Eight sampling sites, including two woodlands, three animal yards, two roofs and one road, were selected for sampling and study. The results indicate that pollutants ranked in a predictable order of decreasing load （e.g. animal yard〉roof〉woodland〉road）, with animal yards acting as the key pollution source in the zoo. Pollutants were transported mainly by particulate form in runoff. Particulate nitrogen and particulate phosphorous accounted on average for 61%, 78% of total pollutant, respectively, over 13 monitored rainfall events. These results indicate the treatment practices should be implemented to improve particulate nutrient removal. Analysis of the M（V） curve indicate that no first flush effect existed in the surface runoff from pervious areas （e.g. woodland, animal ground yard）, whereas a first flush effect was evident in runoff from impervious surfaces （e.g. animal cement yard, roof, road）.

Effects of urbanization on groundwater level in aquifers of Binh Duong Province,Vietnam

The purpose of this paper was to assess the impact of urbanization on the groundwater level(GWL)in aquifers of Binh Duong(BD)Province.The research method is to analyze the trend of GWL,the recharge capacity of surface over time and the relationship between them.The data of the GWL used in the study are the average values in the dry and rainy seasons of 35 observation wells from 2011 to 2018,which are in Pleistocene and Pliocene aquifers.The ability to recharge groundwater from the surface in this study was represented by the curve number(CN),a parameter used in hydrology for calculating direct runoff or infiltration from rainfall.The land use data to identify the CN was analyzed from the Landsat images.The results show that besides over-exploitation,the change of surface characteristic due to the urbanization development process is also the cause of the GWL decline.The analysis of seasonal GWL data shows that the increase in impervious surface area is the cause of GWL decline in the Pleistocene aquifer,which is more evident in the rainy season than in the dry season.The statistical results also show that in the rainy season and in shallow aquifers,a higher CN change can be found with the wells that had a remarkable GWL decline compared to the remaining wells.

Long-range cross-correlation between urban impervious surfaces and land surface temperatures

The thermal effect of urban impervious surfaces （UIS） is a complex problem. It is thus necessary to study the relationship between UIS and land surface temperatures （LST） using complexity science theory and methods. This paper investigates the long-range cross- correlation between UIS and LST with detrended cross- correlation analysis and multifractal detrended cross- correlation analysis, utilizing data from downtown Shanghai, China. UIS estimates were obtained from linear spectral mixture analysis, and LST was retrieved through application of the mono-window algorithm, using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data for 1997-2010. These results highlight a positive long-range cross-correlation between UIS and LST across People＇s Square in Shanghai. LST has a long memory for a certain spatial range of UIS values, such that a large increment in UIS is likely to be followed by a large increment in LST. While the multifractal long-range cross- correlation between UIS and LST was observed over a longer time period in the W-E direction （2002-2010） than in the N-S （2007-2010）, these observed correlations show a weakening during the study period as urbanization increased.

Spectral data treatments for impervious endmember derivation and fraction mapping from Landsat ETM＋ imagery： a comparative analysis

Various spectral data preprocessing approaches have been used to improve endmember extraction for urban landscape decomposition, yet little is known of their comparative adequacy for impervious surface mapping. This study tested four commonly used spectral data treatment strategies for endmember derivation, including original spectra, image fusion via principal component analysis, spectral normalization, and the minimum noise fraction （MNF） transformation. Land cover endmembers derived using each strategy were used to build a linear spectral mixture analysis （LSMA） model in order to unmix treated image pixels into fraction maps, and an urban imperviousness map was generated by combining the fraction maps representing imperviousness endmembers. A cross-map comparative analysis was then performed to rank the four data treatment types based on such common evaluation indices as the coefficient of determination （R2） and root mean square error （RMSE）. A Landsat 7 ETM~ multispectral image covering the metropolitan region of Shanghai, China was used as the primary dataset, and the model results were evaluated using high-resolution color- infrared aerial photographs of roughly the same time period. The test results indicated that, with the highest R2 （0.812） and the lowest RMSE （0.097） among all four preprocessing treatments, the endmembers in the form of MNF-transformed spectra produced the best model output for characterizing urban impervious surfaces. The outcome of this study may provide useful guidance for future impervious surface mapping using medium-resolution remote sensing data.

Spatio-temporal characteristics of intra-urban land cover in the cities of China and USA from 1978 to 2010

Urban land cover has major impacts on a city＇s ecosystem services and the inherent quality of its urban residential environment. The spatio-temporal distribution of impervious surface area and green areas in Chinese cities has exhibited a significantly marked difference in comparison with USA cities. This study focused on monitoring and comparing the spatio-temporal dynamics, land cover patterns and characteristics of functional regions in six Chinese （n=3） and USA （n=3） cities. The study data were collated from Landsat TM/MSS imagery during the period 1978-2010. Results indicate that Chinese cities have developed compactly over the past three decades, while development has been notably dispersed among USA cities. Mean vegetation coverage in USA cities is approximately 2.2 times that found amongst Chinese urban agglomerations. Land use types within Chinese cities are significantly more complex, with a higher density of impervious surface area. Conversely, the central business district （CBD） and residential areas within USA cities were compdsed of a lower proportion of impervious surface area and a higher proportion of green land. Results may be used to contribute to future urban planning and administration efforts in both China and the USA.

哈尔滨市中心城区不透水面时空变化及驱动力分析（英文）

Associated with the rapid economic development of China, the level of urbanization is becoming a serious concern. Harbin, the capital city of Heilongjiang Province, China and one of the political, economic, cultural, and transportation centers of the northeastern region of China, has experienced rapid urbanization recently. To examine the spatial patterns of long-term urbanization and explore its driving forces, we employed the impervious surface fraction derived from remote sensing image as a primary indicator. Specifically, urban imper- vious surface information for the central city of Harbin in 1984, 1993, 2002, and 2010 was extracted from Landsat Thematic Mapper image using a Linear Spectral Mixture Analysis （LMSA）. Then, the spatial and temporal variation characteristics and the driving factors of percent impervious surface area （ISA） changes were analyzed throughout this 26-year period （1984 to 2010）. Analysis of results suggests that： （1） ISAs in the central city of Harbin con- stantly increased, particularly from 1993 to 2010, a rapid urbanization period; （2） the gravity center of impervious surface area in the central city was located in Nangang District in 1984, moving southeast from 1984 to 1993, northwest from 1993 to 2002, and continuing toward the southeast from 2002 to 2010; and （3） the urban growth of the central city can be character- ized as edge-type growth.

北京市不同功能区不透水地表时空变化差异分析（英文）

Impervious surface(IS) is often recognized as the indicator of urban environmental changes. Numerous research efforts have been devoted to studying its spatio-temporal dynamics and ecological effects, especially for the IS in Beijing metropolitan region. However, most previous studies primarily considered the Beijing metropolitan region as a whole without considering the differences and heterogeneity among the function zones. In this study, the subpixel impervious surface results in Beijing within a time series(1991, 2001, 2005, 2011 and 2015) were extracted by means of the classification and regression tree(CART) model combined with change detection models. Then based on the method of standard deviation ellipse, Lorenz curve, contribution index(CI) and landscape metrics, the spatio-temporal dynamics and variations of IS(1991, 2001, 2011 and 2015) in different function zones and districts were analyzed. It is found that the total area of impervious surface in Beijing increased dramatically during the study period, increasing about 144.18%. The deflection angle of major axis of standard deviation ellipse decreased from 47.15° to 38.82°, indicating the major development axis in Beijing gradually moved from northeast-southwest to north-south. Moreover, the heterogeneity of impervious surface’s distribution among 16 districts weakened gradually, but the CI values and landscape metrics in four function zones differed greatly. The urban function extended zone(UFEZ), the main source of the growth of IS in Beijing, had the highest CI values. Its lowest CI value was 1.79 that is still much higher than the highest CI value in other function zones. The core function zone(CFZ), the traditional aggregation zone of impervious surface, had the highest contagion index(CONTAG) values, but it contributed less than UFEZ due to its small area. The CI value of the new urban developed zone(NUDZ) increased rapidly, and it increased from negative to positive and multiplied, becoming animportant contributor to the rise of urban impervious surface. However, the ecological conservation zone(ECZ) had a constant negative contribution all the time, and its CI value decreased gradually. Moreover, the landscape metrics and centroids of impervious surface in different density classes differed greatly. The high-density impervious surface had a more compact configuration and a greater impact on the eco-environment.

A standardized dataset of built-up areas of China’s cities with populations over 300,000 for the period 1990-2015

China’s urbanization has attracted a lot of attention due to its unprecedented pace and intensity in terms of land,population,and economic impact.However,due to the lack of consistent and harmonized data,little is known about the patterns and dynamics of the interaction between these different aspects over the past few decades.Along with the implementation of the 2030 Agenda for Sustainable Development,a standardized dataset for assessing the sustainability of urbanization in China is needed.In this paper,we used remote sensing data from multiple sources(time-series of Landsat and Sentinel images)to map the impervious surface area(ISA)at five-year intervals from 1990 to 2015 and then converted the results into a standardized dataset of the built-up area for 433 Chinese cities with 300,000 inhabitants or more.This dataset was produced following the well-established rules adopted by the United Nations(UN).Validation of the ISA maps in urban areas based on the visual interpretation of Google Earth images showed that the average overall accuracy(OA),producer’s accuracy(PA)and user’s accuracy(UA)were 91.24%,92.58%and 89.65%,respec-tively.Comparisons with other existing urban built-up area datasets derived from the National Bureau of Statistics of China,the World Bank and UN-habitat indicated that our dataset,namely the stan-dardized urban built-up area dataset for China(SUBAD-China),provides an improved description of the spatiotemporal character-istics of the urbanization process and is especially applicable to a combined analysis of the spatial and socio-economic domains in urban areas.Potential applications of this dataset include combin-ing the spatial expansion and demographic information provided by UN to calculate sustainable development indicators such as SDG 11.3.1.The dataset could also be used in other multidimensional syntheses related to the study of urbanization in China.