Increase In Impervious Surface Area Research Articles

Impact of anthropogenic changes and rainfall variability on river discharge in tropical Central Africa

Abstract The objective of this study is to investigate the effects of rainfall variability and anthropogenic changes on river discharge in the Benoue and the Logone river basins over the last seven decades (1950–2018). To achieve this goal, hydrometeorological data from these basins were analyzed using the Pettitt and Mann–Kendall tests. Our results show that negative rupture was observed in the hydrometeorological time series of these basins at the annual time step in 1970–1971. The deficits associated with this rupture are estimated at −7% for rainfall and −28% for river flows. The wet season shows similar developments. However, from the 1990s onward, there has been a significant increase in the mean annual flows of the Benoue River, which coincides with that of the rainfall during the same decade. This increase over the recent decades could also be expected in response to an increase in impervious surface area in the catchment area, which could compensate for the deficit generated by the post-1990s rainfall deficit through an increase in runoff. Since the filling of the Lagdo Dam in 1983, an increase in all ranges of minimum flow, as well as an increase in the variability of extreme flows, has been detected.

Mapping impervious surface change from remote sensing and GIS data: A case study in Hochiminh city, Vietnam

Impervious surface is artificial surfaces that prevent water from entering the soil. The increase in impervious surface area has led to negative impacts on the urban environment, including an increase in the risk of flooding, a decrease in vegetation cover, and the formation of urban heat islands. This paper presents the results of building a predictive model of impervious surfaces in Hochiminh city from remote sensing and GIS data. Landsat and Sentinel 2 satellite images for the period 2002–2022 are used to classify impervious surfaces and extract input layers about vegetation cover, land surface temperature, combined with GIS data (elevation, slope, aspect, distance to road, distance to hydrology, population density) for modeling and predicting impervious surface changes in future. 03 machine learning algorithms, including Support Vector Machine (SVM), Random Forest (RF), Classification and Regression Trees (CART) and maximum likelihood method are used to classify impervious surfaces from Landsat satellite images, then select the method with the highest accuracy. To predict the future distribution of impervious surface, this study uses Cellular Automata (CA) model and 02 artificial intelligence algorithms (Artificial Neural Network - ANN, Logistic Regression - LR). The results obtained in the study can be effectively used for urban planning, minimizing the impact of the process of increasing the impervious surface on the urban environment

Research on Street Landscape Design Along Urban Rail Transit Lines

The study on the landscape design of urban streets along the rail transit lines is an important topic in urban planning and development. With the acceleration of urbanization, the construction and improvement of urban rail transit systems have become a top priority. However, there are numerous challenges and issues in the landscape design of streets along rail transit lines. In recent years, governments and relevant departments have actively promoted the construction of urban green streets and integrated ecological concepts into landscape design to address the pressures and challenges brought about by urbanization. Drawing on the experiences of ecological city construction, the establishment of urban green streets has become an effective approach to solving the functional and environmental problems of urban streets. By integrating green infrastructure into street design, it is possible to effectively manage stormwater and improve the street environment. Research indicates that the root cause of urban street flooding lies in the increase of impervious surface area, which alters the surface hydrological conditions and impedes the collection and utilization of rainwater. Therefore, the design of urban green streets should focus on functional zoning, awareness of stormwater management, and integration of urban cultural landscapes. Through the application of these design methods, not only can the existing problems of urban streets be solved, but valuable design experience and guidance can also be provided for future urban green street construction.

What drives the changing characteristics of phytoplankton in urban lakes: Climate, hydrology, or human disturbance?

Phytoplankton in shallow urban lakes are influenced by various environmental factors. However, the long-term coupling effects and impact pathways of these environmental variables on phytoplankton remain unclear. This is an emerging issue due to high urbanization and the resultant complex climate, lake hydrology and morphology, human interference, and water quality parameter changes. This study used Tangxun Lake, the largest urban lake in the Yangtze River Economic Belt, as an example to assess for the first time the individual contributions and coupled effects of four environmental variables and fourteen indicators on chlorophyll-a (Chla) concentrations under two scenarios from 2000 to 2019. Additionally, the influence pathways between the environmental variables and Chla concentration were quantified. The results indicated that the Chla concentration was most affected by lake hydrology and morphology, as were the total nitrogen, total phosphorus, and transparency. Especially after urbanization (2015–2019), the coupling effect of human interference, lake hydrology and morphology, and water quality parameters was strongest (18%). This is mainly due to fluctuations in the lake water level and an increase in the shape index of lake morphology, large amounts of nutrients were input, which reduced lake transparency and indirectly changed the Chla content. In addition, due to the rapid development of Wuhan city, the expansion of construction land has led to an increase in impervious surface area and a decrease in lake area. During periods of intense summer rainfall, a substantial amount of pollutants entered the lakes through surface runoff, resulting in decreased lake transparency, and elevated concentrations of nitrogen and phosphorus, indirectly increasing the Chla content. This study provides a scientific basis for aquatic ecological assessment and pollution control in urban shallow lakes.

Prediction of Land Surface Temperature Considering Future Land Use Change Effects under Climate Change Scenarios in Nanjing City, China

Land use and land cover (LULC) changes resulting from rapid urbanization are the foremost causes of increases in land surface temperature (LST) in urban areas. Exploring the impact of LULC changes on the spatiotemporal patterns of LST under future climate change scenarios is critical for sustainable urban development. This study aimed to project the LST of Nanjing for 2025 and 2030 under different climate change scenarios using simulated LULC and land coverage indicators. Thermal infrared data from Landsat images were used to derive spatiotemporal patterns of LST in Nanjing from 1990 to 2020. The patch-generating land use simulation (PLUS) model was applied to simulate the LULC of Nanjing for 2025 and 2030 using historical LULC data and spatial driving factors. We simulated the corresponding land coverage indicators using simulated LULC data. We then generated LSTs for 2025 and 2030 under different climate change scenarios by applying regression relationships between LST and land coverage indicators. The results show that the LST of Nanjing has been increasing since 1990, with the mean LST increased from 23.44 °C in 1990 to 25.40 °C in 2020, and the mean LST estimated to reach 26.73 °C in 2030 (SSP585 scenario, integrated scenario of SSP5 and RCP5.8). There were significant differences in the LST under different climate scenarios, with increases in LST gradually decreasing under the SSP126 scenario (integrated scenario of SSP1 and RCP2.6). LST growth was similar to the historical trend under the SSP245 scenario (integrated scenario of SSP2 and RCP4.5), and an extreme increase in LST was observed under the SSP585 scenario. Our results suggest that the increase in impervious surface area is the main reason for the LST increase and urban heat island (UHI) effect. Overall, we proposed a method to project future LST considering land use change effects and provide reasonable LST scenarios for Nanjing, which may be useful for mitigating the UHI effect.

Extraction of impervious surface with Landsat based on machine learning in Chengdu urban, China

In the process of urbanization, materials such as steel and concrete are widely used in urban construction such as road paving and house building, resulting in an increase in impervious surface area in cities. Rapid urbanization in China today has led to a huge increase in impervious surface area, which has increased the risk of urban waterlogging. Therefore, there are more reasons to conduct research on impervious surface and explore the relationship between impervious surface and urban waterlogging. This research has been done to obtain the optimal model for extracting impervious surface in Chengdu urban area and to explore the correlation between impervious surface changes and urban waterlogging in the same area. In order to obtain the optimal model, five different machine learning and deep learning algorithms such as Naive Bayes (NB), Convolutional Neural Network (CNN), Support Vector Machine (SVM), Capsules Network (CapsNet) and Random Forest (RF) have been used to extract the urban impervious surface in this study. The accuracy of the classification models is evaluated using the overall accuracy (OA), kappa coefficient (KC), and macro F1 (F1). It is found that CNN is the best option to extract the urban impervious surface of Chengdu with an OA of 0.7809. In addition, based on the optimal model to extract the impervious surface of Chengdu, a partial correlation analysis was conducted between urban waterlogging and urban impervious in the study area, it was concluded that there was a positive correlation between the two with a partial correlation coefficient of 0.979.

Estimating Large-Scale Interannual Dynamic Impervious Surface Percentages Based on Regional Divisions

Impervious surface information is an important indicator to describe urban development and environmental changes. The substantial increase in impervious surface area will have a significant impact on the regional landscape and environment. Therefore, the timely and accurate acquisition of large-scale impervious surface percentage (LISP) is of great significance for urban management and ecological assessment. However, previous LISP estimation methods often ignored the impact of regional geographic environment and climate differences on remote sensing information, resulting in low overall accuracy and obvious regional differences in the estimated results. Thus, in this study, based on the time-series characteristics of multi-temporal remote sensing images combined with the information on geographical environment and climate heterogeneity, a method of time-series remote sensing image fusion and LISP estimation based on regional divisions was proposed. Firstly, the entire region was divided into several regions according to the spatial differences of Köppen–Geiger climate data and MODIS NDVI time-series data. Subsequently, adaptive time-series image fusion methods and remote sensing feature construction methods were proposed for different regions. Finally, the proposed method was used to estimate the percentage of impervious surfaces in other years in Asia. The results indicate that the overall R2 of each region is better than 0.82, and the estimation models have a good ability to transfer across time and can directly estimate the impervious surface percentage in other years without using additional samples. In addition, compared with other existing impervious surface products, the proposed method has higher overall estimation accuracy and regional consistency.

GISD30: global 30 m impervious-surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform

Abstract. Accurately mapping impervious-surface dynamics has great scientific significance and application value for research on urban sustainable development, the assessment of anthropogenic carbon emissions and global ecological-environment modeling. In this study, a novel and automatic method of combining the advantages of spectral-generalization and automatic-sample-extraction strategies was proposed, and then an accurate global 30 m impervious-surface dynamic dataset (GISD30) for 1985 to 2020 was produced using time-series Landsat imagery on the Google Earth Engine cloud computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and transferred pervious-surface samples in each epoch for every 5∘×5∘ geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal-consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious-surface dynamics. Our global 30 m impervious-surface dynamic model achieved an overall accuracy of 90.1 % and a kappa coefficient of 0.865 using 23 322 global time-series validation samples. Cross-comparisons with five existing global 30 m impervious-surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116×105 km2 in 1985 to 10.871×105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946×105 km2. Therefore, it was concluded that our global 30 m impervious-surface dynamic dataset is an accurate and promising product and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious-surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at https://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b).

Comparison of Impervious Surface Dynamics through Vegetation/High-Albedo/Low-Albedo/Soil Model and Socio-Economic Factors

Hong Kong and Shenzhen have entirely different land-use development policies, resulting in a disparity in the increase rate of impervious surface area. Impervious surface estimation is a significant method for evaluating urbanization, so that countries and cities can deal with their growing populations. The impervious surface area was estimated through Landsat Thematic Mapper (TM) image extraction, the V-H-L-S (vegetation, high-albedo, low-albedo, and soil) model, and linear spectral un-mixing analysis (LSUM). Changes in fractions of endmembers over periods of time were identified and employed to analyze changes in land use and land cover (LULC). The research adopting the V-H-L-S model for classifying land cover and exploring the association of change in impervious surface areas and socio-economic growth over a period of time is limited. In this study, impervious surface estimations for Hong Kong and Shenzhen in 1995, 2005, and 2016 were compared, selecting vegetation, high-albedo, low-albedo, and soil as endmembers. The change rate of the fractions in the four endmembers was calculated to identify changes in land use and land cover during these three specific time periods. The impervious surface was determined to constitute a combination of high-albedo and low-albedo. Moreover, a proportional relationship exists between the increase in impervious surface area, population rate, GDP, and GDP per capita in both Hong Kong and Shenzhen. However, there was a difference in the increase in impervious surface area between Hong Kong and Shenzhen due to the different land-use policies in the country’s two systems.

Relationship between urban size and configuration: Scaling evidence from a hierarchical system in Mexico

Cities continue to grow, and the increase of impervious surface area is becoming a primary indicator of urbanization as well as environmental quality. Evaluating how impervious surfaces are shaped and distributed across urban systems can provide key insights into how cities are impacting global environmental change and how their impacts might change as cities evolve and grow. Many urban characteristics, both physical and social, have been found to follow power law distributions across a system of cities, but it is not yet know whether urban configurational characteristics adhere to these laws. This study seeks to determine if the relationship between impervious surface area as a dimension of urban size and a suite of spatial metrics measuring urban configuration follow power law-like relationship distributions across a hierarchy of cities in the urban system of Mexico. Results suggest that several metrics do follow these characteristic patterns and that configuration complexity increases with city size, but at a slower rate than impervious surface. Scaling exponents, which can provide insights into system dynamics and the mechanisms driving relationships, were sublinear for certain metrics, supporting similar extant work, but deviated from theorized values.

Experimental Study on Water Percolating Concrete

This paper addresses two aspects namely a new method for manufacturing of percolating concrete blocks using different proportions of concrete mixture such as Portland cement, Coarse aggregates, fine aggregates, limestone, and water have been designed. Apart from this an attempt has also been made by adding small quantities of additives such as fly ash, rice husk ash etc. for its strength and suitability on par with the normal Concrete blocks. Another is a partial replacement of cement with supplementary cementation materials such as fly ash and metakaolin in different proportions for reducing high grade cement consumptions been proposed. The design of a Pervious Concrete is made in such a way that it allows the entire surface run off water to percolate down without retaining any drop/quantity in it. Thus, it is named as water percolating Pervious Concrete/ porous concrete. An alternative for reducing cement usage in concrete makes concrete eco-friendly. Thus, there comes an idea of partially replacing cement with supplementary cementations materials, The concern has been growing in recent years towards reducing the pollutants in water conservation and the environment. The continual urbanization has led to the increase in impervious surface area of the cities, further leading to blockage in percolation of precipitation from rainfall. This result is excess surface run off. To counteract this, pervious concrete is the solution. Hence, the pervious concrete having 15% to 35% interconnected pores by volume, allows direct infiltration of water through its structure. Since the strength of this block for highway suitability of roads is not yet tested. The main aim of this paper is to improve the strength characteristics of porous concrete. However, on comparison, with the published data it is suitable for foot paths/ pathways and parking lots and as driveways in the residential and small rural areas where less vehicular traffic. This will help in reducing the risk of water clogging and recharges the nearby ground water level. The Maintenance of the slab is also minimum and can be repaired and cleaned easily. Thus, it is worthy and useful in many ways

Stormwater management impacts of small urbanising towns: The necessity of investigating the ‘devil in the detail’

In many parts of the world, small towns are experiencing high levels of population growth and development. However, there is little understanding of how urban growth in these regional towns will impact urban runoff. We used the case study of Wangaratta, located in South-East Australia, between 2006 and 2016, to investigate land cover changes and their impacts on urban runoff discharge. Detailed spatio-temporal analysis (including neighbourhood composition analysis and supervised classification of aerial imagery) identified that population, land use and land cover changes in Wangaratta, although subtle, were mostly driven by residential growth in the outskirts of the town, where there were large increases in impervious surface area. Overall, the urban growth was minimal. However, in spite of these small changes, a sub-catchment only SWMM model showed that the increase in impervious surface area nevertheless resulted in a statistically significant increase in total runoff across the town. Particularly, this increase was most pronounced for frequent and shorter storms. The analysis of urban development pattern changes coupled with urban hydrological modelling indicated that land cover changes in regional towns, especially when analysed in detail, may result in hydrological changes in the urban region (likely to be exacerbated in coming years by changing climate) and that adaptation efforts will need to adopt a variety of approaches in both existing and growth zones. Our findings highlight the necessity of detailed fine-scale analyses in small towns as even subtle changes will have substantial future implications and robust planning and adaptation decisions are even more important when compared to larger cities due to the greater economic constraints that small towns face and their important relationship with the surrounding hinterlands.

Spatiotemporal Patterns of Impervious Surface Area and Water Quality Response in the Fuxian Lake Watershed.

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.

半干旱区城市环境下油松林分蒸腾特征及其影响因子

PDF HTML阅读 XML下载 导出引用 引用提醒 半干旱区城市环境下油松林分蒸腾特征及其影响因子 DOI: 10.5846/stxb201811262571 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家科技支撑计划项目（2015BAD07B06-4） The stand transpiration characteristics of Pinus tabulaeformis and its influential factors in a semi-arid urban environment Author: Affiliation: Fund Project: The research and demonstration on the cultivation and management technology system of water-saving urban landscape forests in Inner Mongolia and Beijing 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在城市环境下，由于不透水地面面积的增加，土壤-植物-大气之间水汽循环减弱，水汽调节能力差，因而研究城市树木蒸腾对环境因子的响应对于城市进行合理的水汽调节具有重要意义。于2017年生长季，在内蒙古呼和浩特市区树木园内选择58年生油松（Pinus tabulaeformis Carr.）作为研究树种，采用热扩散法测定其树干液流，并同步监测气象因子和土壤含水量变化，利用彭曼公式计算冠层气孔导度。结果表明：（1）生长季内，油松林分蒸腾存在明显日、月变化，晴天天气下林分蒸腾日变化呈单峰曲线，月林分蒸腾量5月最大，其次是7月、8月、6月和9月，分别为20.96、19.89、18.09、17.25 mm和7.49 mm。（2）油松林分蒸腾与饱和水汽压差、太阳总辐射、土壤含水量和风速均存在极显著相关关系（P<0.01），太阳总辐射、饱和水汽压差和土壤含水量是影响林分蒸腾的主要环境因子（R2=0.47、R2=0.31和R2=0.16），风速对林分蒸腾的影响程度最小（R2=0.12）；不同降雨量对林分蒸腾的影响作用不同，10 mm以上的日降雨量对油松林分蒸腾作用明显。（3）除环境因子外，油松叶片气孔通过响应环境变化控制蒸腾作用，当饱和水汽压差<1.5 kPa时，叶片气孔对饱和水汽压差的响应更敏感；当太阳总辐射<250 W/m2时，叶片气孔对蒸腾起促进作用，超过该阈值，叶片气孔关闭从而抑制树木蒸腾。 Abstract:The water vapor cycle between soil-plant-atmosphere is weakened and its ability for regulation is poor due to the increase in impervious surface areas in urban environments. Therefore, it is of great significance to study the transpiration response of urban trees to environmental factors amidst reasonable water vapor regulation in urban areas. In the growing season of 2017, 58-year-old Pinus tabulaeformis Carr. was selected as a research tree species for sap flow measurement, by thermal diffusion, at the Hohhot arboretum, Inner Mongolia. We measured meteorological factors and soil water content simultaneously and estimated canopy stomatal conductance using the Penman Formula. The results showed that (1) stand transpiration of P. tabulaeformis had obvious daily and monthly changes in the growing season. The diurnal stand transpiration variation graph showed a single peak curve on sunny days. Monthly stand transpiration reached the maximum in May, followed by July, August, June and September, which was 20.96, 19.89, 18.09, 17.25 mm and 7.49 mm, respectively. (2) There were extreme significant correlations between stand transpiration and vapor pressure deficits, global radiation, soil water content, and wind speed (P<0.01). Global radiation, vapor pressure deficit, and soil water content were the main environmental factors affecting forest transpiration (R2=0.47, R2=0.31 and R2=0.16), and wind speed had the smallest impact on forest transpiration (R2=0.12). Different rainfall events had varied effects on stand transpiration, but a significant effect when daily rainfall exceeded 10 mm. (3) In addition to environmental factors, leaf stomata of P. tabulaeformis controlled transpiration in response to environmental factors. Leaf stomata were more sensitive to vapor pressure deficits when it was < 1.5 kPa, whereas, global radiation, when < 250 W/m2, promoted transpiration. When the threshold was exceeded, leaf stomata would close to suppress tree transpiration. 参考文献 相似文献 引证文献

Urbanization and climate change jointly shift land surface phenology in the northern mid-latitude large cities

Abstract: Land surface phenology (LSP) has been widely used as the “footprint” of urbanization and global climate change. Shifts of LSP have cascading effects on food production, carbon sequestration, water consumption, biodiversity, and public health. Previous studies mainly focused on investigating the effects of urbanization on the spatial patterns of LSP by comparing phenological metrics, e.g. start of season (SOS) and end of season (EOS), between urban center and the surrounding rural regions. However, it remains unclear how urbanization-induced land cover conversions and climate change jointly influence the temporal variations of SOS and EOS within the urban ecosystem. To fill this knowledge gap, we utilized daily two-band enhanced vegetation index, daily meteorological record, and annual land cover dataset to investigate the respective impacts of urbanization and climate change on temporal shifts of LSP between the post- and the pre-urbanization periods over 196 large cities in the northern mid-latitudes. We found 51% of the cities experienced an advanced SOS with an average of −6.39 ± 5.82 days after urbanization has occurred, while the remaining 49% of the cities had a delayed SOS with an average of 7.56 ± 5.63 days. We also found a later EOS at 53% of the cities and an earlier EOS at 47% of the cities with an average of 8.43 ± 7.59 and −5.57 ± 4.99 days between the post- and pre-urbanization periods, respectively. Multiple linear regression analysis indicates that climate variables (i.e. temperature, precipitation, and insolation) play dominant roles in regulating the temporal shifts of LSP. Furthermore, the earlier SOS and later EOS were significantly correlated with the amplitude of urbanization (i.e. increase of impervious surface area) in cities after controlling for effects of climate factors. These patterns were generally consistent across eight climate zones. Our findings provide critical information in modeling natural and anthropogenic effects on urban ecosystem, with important benefits for urban sustainability and biodiversity conservation.

Prediction of ecological effects of potential population and impervious surface increases using a remote sensing based ecological index (RSEI)

The ecological impact of urban development and population increase is an area of increasing relevance as human modification of the landscape continues unabated. The prediction of this impact will help inform urban planning and decision making around population growth, impervious surface (IS) increase and associated ecological effects. The Xiong’an New Area is a state-level new area to be established in North China. The population growth goal for the area is going to reach 2.5 million and the area is planned to expand to 2000 km2. The potential population growth and area expansion will result in a massive increase in IS area and thus may impact the regional ecological quality. A clear understanding of the impact would help to minimize the influence of the new area’s development on regional ecological quality. Therefore, this study investigated current land cover types and ecological status in the Xiong’an New Area using feature inversion techniques and the improved remote sensing-based ecological index (RSEI). Statistical models were developed to predict ecological effects responding to the forthcoming population and associated IS increase in the new area. This was achieved by relating population growth to IS area increase and exploring the relationships between IS area and RSEI. The results show that the area’s land surface has not been intensively developed and the current ecological status is good. The RSEI-based prediction shows that IS area has a noteworthy effect on regional ecological conditions. The variation of IS proportions in the new area can result in a significant shift of RSEI. A balance amount of total IS area in the 2000 km2 new area is 433 km2. Exceeding/reducing the amount would result in a decline/rise of the area’s ecological quality. Introducing a quantity of IS area-related population density (IPD) reveals that the area’s ecological quality is actually related to IPD rather than to traditional population density when the total area and future population of the new area are given. Therefore, the forthcoming regional master planning for the new area should include specific efforts to control IS area increase.

Changes in urban-related precipitation in the summer over three city clusters in China

The impacts of urban surface expansion on the summer precipitations over three city clusters [Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD)] in eastern China under different monsoonal circulation backgrounds were explored using the nested fifth-generation Penn State/NCAR Mesoscale Model version 3.7 (MM5 V3.7), including the urban-related thermal and dynamical parameters. Ten-year integrations were performed using satellite image data from 2000 and 2010 to represent the urban surface distributions and expansions in China. Changes in the precipitation revealed obvious subregional characteristics, which could be explained by the influences of the vertical wind velocity and moisture flux. With urban-related warming, vertical wind motion generally intensified over urban surface-expanded areas. Meanwhile, the increase in impervious surface areas induced rapid rainwater runoff into drains, and the Bowen ratio increased over urban areas, which further contributed to changes in the local moisture fluxes in these regions. The intensities of the changes in precipitation were inconsistent over the three city clusters, although the changes in vertical motion and local evaporation were similar, which indicates that the changes in precipitation cannot be solely explained by the changes in the local evaporation-related moisture flux. The changes in precipitation were also influenced by the changes in the East Asian summer monsoon (EASM) circulation and the corresponding moisture flux, which are expressed in marked subregional characteristics. Therefore, the influence of urban-related precipitation over the three city clusters in China, for which changes in moisture flux from both the impacted local evaporation and EASM circulation should be considered, varied based on the precipitation changes of only a single city.

Assessing Impervious Surface Changes in Sustainable Coastal Land Use: A Case Study in Hong Kong

In Hong Kong, reclamation is the main method for developing new land use areas as most country parks and mountains are protected under a land policy that emphasizes conservation for their high ecological value. Therefore, the land use for urbanized area in Hong Kong is limited, which has become an issue of concern. Hong Kong’s population is increasing; however, the amount of available land use is insufficient to meet the demand. Developing a high density of buildings is one of the critical strategies of Hong Kong’s government. Highly dense development may result in an urban heat island as well as health problems. In this study, we present an assessment of urban impervious surface changes in coastal megacities like Hong Kong based on satellite images. Landsat satellite images are employed to analyze urban impervious surface changes from 1995 to 2015 in coastal urban areas of Hong Kong. The results show that the increase of impervious surface area is almost the same as the increase in land reclamation area. This suggests that Hong Kong’s land use policy, which underlines conservation for high ecological value and reclamation, may be able to maintain its sustainable development of coastal land use.

Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco

Abstract Fez is the most ancient of the imperial cities of Morocco. In Fez the rate of population growth has been spectacular in recent times (484,300 inhabitants in 1982 and 1,129,768 in 2014). The accelerated rate of population growth has generated a large urban sprawl in all its forms and serious environmental problems. In this research, we have analyzed the relationship between urbanization and land use changes and their impact on cityscape in Fez and the importance of the increase in impervious surface areas. Satellite imageries and census data have been used to identify different patterns of land use change and growth of the city for the period 1984–2013. Classification and analysis of the satellite imageries were performed using Erdas imagine and ArcGIS Software. Urban sprawl in Fez was assessed over 29 years (1984–2013). The overall accuracy of land cover change maps, generated from post-classification change detection methods and evaluated using several approaches, ranged from 78% to 87%. The maps showed that between 1984 and 2013 the amount of urban or developed land increased by about 121%, while rural cover by agriculture and forest decreased respectively by 11% and 3%.

IMPACT OF LAND USE ON URBAN WATER-LOGGING DISASTER: A CASE STUDY OF BEIJING AND NEW YORK CITIES

Urban water-logging disasters are induced by multiple causes, such as land use structure, limited capacity of drainage system, climate change and lack of enforcement. Significant increase of impervious surface area is the main cause of urban water-logging disaster in big cities like Beijing. This article takes Beijing 7.21 storm and New York hurricane Sandy as examples, and explains the cause of urban water-logging from the perspective of land use structure. In this study, the infiltration and retention capacity for various land use types and regional total retention storage capacity are analysed based on the Landsat TM satellite imagery of Beijing City and New York City in 2011. To estimate the impact of the land use structure, a comparison of retention capacity and runoff in two regions has been carried out using precipitation and runoff data. The results show that the significant increase of impervious surface decreases the retention capacity and becomes the main cause of urban water-logging disaster. Waters is a major factor in retention capacity, while green and cultivated land can enhance the retention effect. Reducing impervious surface, protecting waters and increasing green fields can be implemented in combination with other structural best management practice (BMPs) to control and prevent urban water-logging disaster.