Impervious Surface Change Research Articles

An evaluation of monthly impervious surface dynamics by fusing Landsat and MODIS time series in the Pearl River Delta, China, from 2000 to 2015

Researchers have been attending increasingly to impervious surface dynamics to better understand the urbanization process and its impacts on urban environments. Previously, numerous studies have only estimated and mapped impervious surface dynamics at annual or decadal time scales. It is challenging to estimate impervious surface dynamics at a finer time scale, such as on a monthly scale, while using a single source of medium spatial resolution satellite imagery. However, urban infrastructure construction could cause changes in impervious surfaces in a short period of time. This paper aimed at developing a new methodology for evaluating monthly impervious surface dynamics by fusing Landsat and MODIS time series. The Pearl River Delta in China, is located in a humid subtropical region and was selected as the study area due to its dramatic urbanization in the past three decades. Available Landsat images with cloud cover <90%, 7-Day MODIS NDVI 250m smooth time series, and daily MODIS LST 1000m time series from 2000 to 2015 were downloaded. These data were used to develop temporal features of land covers (i.e., monthly Landsat NDVI and LST time series) and to monitor impervious surface dynamics using semi-supervised time series fuzzy clustering method. The results showed the effectiveness of temporal features in differentiating land covers. Additionally, the average overall classification accuracy yielded reasonable accuracies (up to 89.36%). The proposed methodology has illustrated numerous, considerable advantages over previous methods. It has offered consistent maps of impervious surfaces on a monthly time scale as well as enhanced distinguishability of land covers with similar spectral characteristics. This study can be utilized to establish relationships between urban expansion, climate change, urban environment, population, and other socio-economic variables on a monthly basis. The study is also crucial for predicting the timing, duration, and density of ecological change for increased impervious surfaces.

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.

Assessing urban development trends in representative Local Administrative Units before and after the Greek economic crisis

This study maps and quantifies urban development in four areas in Northern Greece for the last decade using remote sensing and urban sprawl indices. It aims to correlate the results with the effects of the Greek economic crisis on the construction activity. The remotely sensed data used are two multispectral cloud-free Landsat 5 Thematic Mapper (TM) images (from 2003 and 2009) and one Landsat 8 Operational Land Imager (OLI) image from 2014. A supervised Support Vector Machine (SVM) classifier is applied to produce land cover maps. The maps accuracy is assessed using high resolution airborne and Google Earth imagery for the 2003, 2009 and 2014 images. The high overall built-up area classification accuracy achieved ranges between 85.8% and 87.8%. The derived maps are further assessed to identify and monitor the impervious surface changes. A set of urban sprawl indices is applied to quantitatively analyse the spatial characteristics and spatial imprint of built-up area through time. The analysis of this dynamic phenomenon reveals that the economic crisis not only decreased the number of new constructions but also altered the way new construction occurs.

A procedure for quantifying runoff response to spatial and temporal changes of impervious surface in Qinhuai River basin of southeastern China

Quantitative assessment of the hydrological response to urbanization has been a major concern in hydrology and water resources management. In this study, a procedure combining different statistical methods and a hydrological model to quantify annual runoff response to spatial and temporal variations of impervious surface areas was proposed and applied to the Qinhuai River basin, an urbanized basin located in southeastern China, over the period from 1986 to 2013. The landscape indicators, such as impervious area and number of impervious patches were used to measure the spatial configuration of urbanization and quantify the runoff response to urbanization. Impervious area data were derived from the Landsat images using superior ensemble learning method of rotation forest. The Mann–Kendall test, Sen's estimator, Pettitt test and double mass curve method were applied to examine gradual trend and abrupt changes for hydro-meteorological data series. A hydrological model based on stepwise regression analysis was built and used to explore the relation among annual runoff and precipitation, potential evapotranspiration and landscape indicators. The results showed that annual runoff and runoff coefficient had significant increasing trends and an abrupt change after year 2001 when the watershed impervious area reached 8.6%. The average annual runoff increased by 60%, of which, urbanization was responsible for 59% of the increase, while precipitation changes were responsible for the remaining 1% in the study region. The annual runoff response to impervious area showed a nonlinear relationship, and was more sensitive in dry years than wet years. The changes of impervious area were more remarkable in connecting the existed impervious patches than in developing the new ones beginning in the early 2000s, which increased the watershed's drainage capacity and resulted in the abrupt change of runoff response. The study demonstrated that the proposed procedure was efficient to quantify the runoff responses to urbanization using landscape metrics of impervious surface.

Mapping 2000–2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 2000–2010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approachAn independent validation dataset was also developed using Google Earth™ imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 ± 7.84 km2.

Correlate Mapping of Impervious Surfaces as Flood Risk Assessment Strategy in Owerri, Southeastern Nigeria

Owerri is rapidly growing in population and built environment, with corresponding, high increase in pavements or paved surfaces. This study explores the integrated approach of Remote Sensing (RS) and Geographic Information systems (GIS) techniques in flood management with the goal of mapping areas vulnerable to flood hazard and, increase in paved surfaces. Digital elevation dataset from Shuttle Radar Topographical Mission (SRTM) were downloaded from USGS explorer. Also, Landsat 5 ETM of 1986, Landsat 7 ETM+ of 2000 and Landsat 8 ETM+ of 2016 imageries were obtained and subjected to supervised classification, using maximum likelihood classifier with ERDAS Imagine 2014. The derived map displayed the spatial and statistical variations of the classified Land Use and Land Cover (LULC) of 1986, 2000 and 2016. The result showed impervious surface rising from 1986 values of 31,625.93 Ha, to 47,979.09 Ha in 2000 and 50,297.33 Ha in 2016, implying approximately 31.2% in 1986, 47.31% in 2000 and 49.61 in 2016. The mean change in impervious surface from 1986 to 2000 was 16.1% compared with 2.3% between the periods. This implies the measure and spate of land conversion in Owerri between the periods showed upward swing. The mean percentage change from 1986 to 2016 revealed increases from 31.2% to 47.31% and to 49.61% for 1986, 2000 and 2016, respectively. Digital Elevation Model was developed with ArcGIS to identify flood prone areas within the study area. A flow accumulation model was created using the DEM before re-classification into high risk, moderate risk and low risk zones using contours and based on elevation. This was overlaid on the impervious layer of the area, to produce a vulnerability map showing locations at a particular level of risk, according to their proximity and extent of paved surface area. This confirms that changes in impervious surfaces, significantly, produce corresponding effect in flood vulnerability. This study recommended that adequate land use planning be enforced.

Assessing the Impacts of Chinese Sustainable Ground Transportation on the Dynamics of Urban Growth: A Case Study of the Hangzhou Bay Bridge

Although China has promoted the construction of Chinese Sustainable Ground Transportation (CSGT) to guide sustainable development, it may create substantial challenges, such as rapid urban growth and land limitations. This research assessed the effects of the Hangzhou Bay Bridge on impervious surface growth in Cixi County, Ningbo, Zhejiang Province, China. Changes in impervious surfaces were mapped based on Landsat images from 1995, 2002, and 2009 using a combination of multiple endmember spectral mixture analysis (MESMA) and landscape metrics. The results indicated that the area and density of impervious surfaces increased significantly during construction of the Hangzhou Bay Bridge (2002–2009). Additionally, the bridge and connected road networks promoted urban development along major roads, resulting in compact growth patterns of impervious surfaces in urbanized regions. Moreover, the Hangzhou Bay Bridge promoted the expansion and densification of impervious surfaces in Hangzhou Bay District, which surrounds the bridge. The bridge also accelerated socioeconomic growth in the area, promoting rapid urban growth in Cixi County between 2002 and 2009. Overall, the Hangzhou Bay Bridge is an important driver of urban growth in Cixi County, and policy suggestions for sustainable urban growth should be adopted in the future.

Annual dynamics of impervious surface in the Pearl River Delta, China, from 1988 to 2013, using time series Landsat imagery

Information on impervious surface distribution and dynamics is useful for understanding urbanization and its impacts on hydrological cycle, water management, surface energy balances, urban heat island, and biodiversity. Numerous methods have been developed and successfully applied to estimate impervious surfaces. Previous methods of impervious surface estimation mainly focused on the spectral differences between impervious surfaces and other land covers. Moreover, the accuracy of estimation from single or multi-temporal images was often limited by the mixed pixel problem in coarse- or medium-resolution imagery or by the intra-class spectral variability problem in high resolution imagery. Time series satellite imagery provides potential to resolve the above problems as well as the spectral confusion with similar surface characteristics due to phenological change, inter-annual climatic variability, and long-term changes of vegetation. Since Landsat time series has a long record with an effective spatial resolution, this study aimed at estimating and mapping impervious surfaces by analyzing temporal spectral differences between impervious and pervious surfaces that were extracted from dense time series Landsat imagery. Specifically, this study developed an efficient method to extract annual impervious surfaces from time series Landsat data and applied it to the Pearl River Delta, southern China, from 1988 to 2013. The annual classification accuracy yielded from 71% to 91% for all classes, while the mapping accuracy of impervious surfaces ranged from 80.5% to 94.5%. Furthermore, it is found that the use of more than 50% of Scan Line Corrector (SLC)-off images after 2003 did not substantially reduced annual classification accuracy, which ranged from 78% to 91%. It is also worthy to note that more than 80% of classification accuracies were achieved in both 2002 and 2010 despite of more than 40% of cloud cover detected in these two years. These results suggested that the proposed method was effective and efficient in mapping impervious surfaces and detecting impervious surface changes by using temporal spectral differences from dense time series Landsat imagery. The value of full sampling was revealed for enhancing temporal resolution and identifying temporal differences between impervious and pervious surfaces in time series analysis.

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hotspot regions in the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re-densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms.

Influence of urban land cover changes and climate change for the exposure of European cities to flooding during high-intensity precipitation

Abstract. The extent and location of impervious surfaces within urban areas due to past and present city development strongly affects the amount and velocity of run-off during high-intensity rainfall and consequently influences the exposure of cities towards flooding. The frequency and intensity of extreme rainfall are expected to increase in many places due to climate change and thus further exacerbate the risk of pluvial flooding. This paper presents a combined hydrological-hydrodynamic modelling and remote sensing approach suitable for examining the susceptibility of European cities to pluvial flooding owing to recent changes in urban land cover, under present and future climatic conditions. Estimated changes in impervious urban surfaces based on Landsat satellite imagery covering the period 1984–2014 are combined with regionally downscaled estimates of current and expected future rainfall extremes to enable 2-D overland flow simulations and flood hazard assessments. The methodology is evaluated for the Danish city of Odense. Results suggest that the past 30 years of urban development alone has increased the city's exposure to pluvial flooding by 6% for 10-year rainfall up to 26% for 100-year rainfall. Corresponding estimates for RCP4.5 and RCP8.5 climate change scenarios (2071–2100) are in the order of 40 and 100%, indicating that land cover changes within cities can play a central role for the cities' exposure to flooding and conversely also for their adaptation to a changed climate.

Implications of land use policy on impervious surface cover change in Cixi County, Zhejiang Province, China

There is a growing need to understand interactions between land use policies and the development of impervious surfaces. This paper (1) develops an approach to quantify impervious surface change in urban areas using multi-temporal remotely-sensed data sets; and (2) links observed change to change in land use policies. Cixi County in Zhejiang Province, China was used as a representative case study. Landsat imagery from 1987, 1995, 2002, and 2009 was used to detect impervious surface change. First, impervious surfaces for each image were estimated at the sub-pixel level via multiple endmember spectral mixture analysis (MESMA). Second, a high pass change filter (HPCF) was proposed to identify impervious surface change over time. Third, the Getis–Ord (Gi∗) metric was applied to the HPCF results to determine areas of substantial change (hot spots). In terms of the first objective, results suggested that the HPCF-Gi∗ metric could successfully reveal the location, intensity, and geographic extent of significant change in impervious surface coverage. With respect to the second objective, two major mechanisms of impervious surface change were identified: new land development and redevelopment of existing impervious surfaces. The nature and spatial pattern of these mechanisms can be explained through two classical urban growth models. We found that since 1994 the annual rate of impervious surface growth decreased considerably, suggesting that national land protection policies implemented in that year may have had some effect. However, the total area of impervious surface cover continued to increase, particularly in and around urban areas due to the above mechanisms. Both new land development and redevelopment could be linked to land use regulations and their implementation at the local level through local economic development pressure, the construction of transportation corridors, and the incentive structure for local government.

Quantifying impervious surface changes using time series planimetric data from 1940 to 2011 in four central Iowa cities, U.S.A

Rapid expansion of urban areas has been identified as a significant challenge for management of natural systems in and around cities and for their residents. As a starting point, urban expansion must be quantified before it can be associated with other natural or social processes. Although spatial metrics have been used previously to quantify urban expansion, they have only rarely been applied to planimetric data. Using multi-year high-resolution planimetric data, a percent impervious surface-based zoning strategy, and six spatial metrics, we quantified impervious surface (IS) changes in four rapidly growing cities in central Iowa, U.S.A. from 1940 to 2011. We documented increases in IS area over time, primarily due to increases in buildings and parking lot areas in the most recent 20 years. Application of a new spatial metric, percent connected impervious surface area, indicated increasingly connected IS area throughout the period of study. Application of a second new metric, road equivalent width, indicated gradual increases in road width over time. Distinct spatial patterns of change for IS classes occurred in the three different percent IS zones, with roads dominating low percent IS zones, buildings dominating medium percent IS zones, and parking lots dominating high percent IS zones. Use of low impact practices (pervious pavement, bioswales, sand filters) is recommended to minimize impact from expanding and increasingly connected IS areas. Further, land use policies and planning tools could be strategically implemented by targeting specific IS classes that dominate different city zones.

Accuracy assessment of NLCD 2006 land cover and impervious surface

Release of NLCD 2006 provides the first wall-to-wall land-cover change database for the conterminous United States from Landsat Thematic Mapper (TM) data. Accuracy assessment of NLCD 2006 focused on four primary products: 2001 land cover, 2006 land cover, land-cover change between 2001 and 2006, and impervious surface change between 2001 and 2006. The accuracy assessment was conducted by selecting a stratified random sample of pixels with the reference classification interpreted from multi-temporal high resolution digital imagery. The NLCD Level II (16 classes) overall accuracies for the 2001 and 2006 land cover were 79% and 78%, respectively, with Level II user's accuracies exceeding 80% for water, high density urban, all upland forest classes, shrubland, and cropland for both dates. Level I (8 classes) accuracies were 85% for NLCD 2001 and 84% for NLCD 2006. The high overall and user's accuracies for the individual dates translated into high user's accuracies for the 2001–2006 change reporting themes water gain and loss, forest loss, urban gain, and the no-change reporting themes for water, urban, forest, and agriculture. The main factor limiting higher accuracies for the change reporting themes appeared to be difficulty in distinguishing the context of grass. We discuss the need for more research on land-cover change accuracy assessment.

Mapping impervious surface change from remote sensing for hydrological modeling

This paper describes a method to estimate changes in impervious surface fraction from widely available medium resolution remote sensing data. The potential of the impervious surface fraction data for hydrological modeling is illustrated by a case study for the Kleine Nete catchment, Belgium. Impervious surface fraction data for the Kleine Nete were simulated based on a Landsat TM image acquired in 1986 and a Landsat ETM+ of 2003. The paper assesses the impact of change in impervious surface cover between 1986 and 2003 on the vertical water balance and groundwater system. The results show that impervious surface fractions can be obtained from medium resolution remote sensing data with reasonable accuracy, the mean average error is around 18% and the bias close to zero for both the recent and historical image. Comparing the impervious surface fractions of 1986 and 2003 indicates that most urbanization occurred by densification of existing urban areas. The average impervious fraction of the urban cells increases from 25.4% to 29.2% between 1986 and 2003. Urban runoff increases by 9.5% between 1986 and 2003 due to the increase in impervious surfaces, while the evapotranspiration and recharge in urban areas decrease by 1.5% and 1.6% respectively. For the study area a land-use class based parameterization method underestimates groundwater recharge and head decreases in the most dense urban area and overestimates those in some of the smaller urban centers.

Extraction and Analysis of Impervious Surfaces Based on a Spectral Un-Mixing Method Using Pearl River Delta of China Landsat TM/ETM+ Imagery from 1998 to 2008

Impervious surface area (ISA) is considered as an indicator of environment change and is regarded as an important input parameter for hydrological cycle simulation, water management and area pollution assessment. The Pearl River Delta (PRD), the 3rd most important economic district of China, is chosen in this paper to extract the ISA information based on Landsat images of 1998, 2003 and 2008 by using a linear spectral un-mixing method and to monitor impervious surface change by analyzing the multi-temporal Landsat-derived fractional impervious surface. Results of this study were as follows: (1) the area of ISA in the PRD increased 79.09% from 1998 to 2003 and 26.88% from 2003 to 2008 separately; (2) the spatial distribution of ISA was described according to the 1998/2003 percentage respectively. Most of middle and high percentage ISA was located in northwestern and southeastern of the whole delta, and middle percentage ISA was mainly located in the city interior, high percentage ISA was mainly located in the suburban around the city accordingly; (3) the expanding direction and trend of high percentage ISA was discussed in order to understand the change of urban in this delta; High percentage ISA moved from inner city to edge of urban area during 1998–2003 and moved to the suburban area that far from the urban area mixed with jumpily and gradually during 2003–2008. According to the discussion of high percentage ISA spatial expanded direction, it could be found out that high percentage ISA moved outward from the centre line of Pearl River of the whole delta while a high ISA percentage in both shores of the Pearl River Estuary moved toward the Pearl River; (4) combining the change of ISA with social conditions, the driving relationship was analyzed in detail. It was evident that ISA percentage change had a deep relationship with the economic development of this region in the past ten years. Contemporaneous major sport events (16th Asia Games of Guangzhou, 26th Summer Universidad of Shenzhen) and the government policies also promoted the development of the ISA. Meanwhile, topographical features like the National Nature Reserve of China restricted and affected the expansion of the ISA. Above all, this paper attempted to extract ISA in a major region of the PRD; the temporal and spatial analyses to PRD ISA demonstrated the drastic changes in developed areas of China. These results were important and valuable for land use management, ecological protection and policy establishment.

Monitoring rapid urban expansion using a multi-temporal RGB-impervious surface model

In this paper, we developed a novel method of combining remote sensing tools at the sub-pixel level for accurate identification of impervious surface time series changes. We examined the use of the red-green-blue impervious surface model (RGB-IS) in detecting time series internal modification of urban regions by integrating Landsat data collected over four different periods between 1987 and 2009 (i.e., 1987, 2000, 2002, and 2009). The performance of this approach was compared with two conventional methods, namely standard RGB-normalized difference vegetation index (NDVI) and post-classification technique. In contrast to conventional techniques, RGB-IS could monitor between-class changes, within-class changes, and location of these modifications. The proposed method was independent of seasonal changes and was also able to serve as a useful alternative for quick mapping growth hotspots and updating transportation corridor map. The results also showed that Cixi County, Zhejiang Province, China experienced tremendous impervious surface changes, especially along the corridors of newly constructed highways and around urban areas over the past 22 years.

Detection of impervious surface change with multitemporal Landsat images in an urban–rural frontier

Mapping and monitoring impervious surface dynamic change in a complex urban–rural frontier with medium or coarse spatial resolution images is a challenge due to the mixed pixel problem and the spectral confusion between impervious surfaces and other non-vegetation land covers. This research selected Lucas do Rio Verde County in Mato Grosso State, Brazil as a case study to improve impervious surface estimation performance by the integrated use of Landsat and QuickBird images and to monitor impervious surface change by analyzing the normalized multitemporal Landsat-derived fractional impervious surfaces. This research demonstrates the importance of two-step calibrations. The first step is to calibrate the Landsat-derived fraction impervious surface values through the established regression model based on the QuickBird-derived impervious surface image in 2008. The second step is to conduct the normalization between the calibrated 2008 impervious surface image with other dates of impervious surface images. This research indicates that the per-pixel based method overestimates the impervious surface area in the urban–rural frontier by 50%–60%. In order to accurately estimate impervious surface area, it is necessary to map the fractional impervious surface image and further calibrate the estimates with high spatial resolution images. Also normalization of the multitemporal fractional impervious surface images is needed to reduce the impacts from different environmental conditions, in order to effectively detect the impervious surface dynamic change in a complex urban–rural frontier. The procedure developed in this paper for mapping and monitoring impervious surface area is especially valuable in urban–rural frontiers where multitemporal Landsat images are difficult to be used for accurately extracting impervious surface features based on traditional per-pixel based classification methods as they cannot effectively handle the mixed pixel problem.

Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods

A prototype method was developed to update the U.S. Geological Survey (USGS) National Land Cover Database (NLCD) 2001 to a nominal date of 2006. NLCD 2001 is widely used as a baseline for national land cover and impervious cover conditions. To enable the updating of this database in an optimal manner, methods are designed to be accomplished by individual Landsat scene. Using conservative change thresholds based on land cover classes, areas of change and no-change were segregated from change vectors calculated from normalized Landsat scenes from 2001 and 2006. By sampling from NLCD 2001 impervious surface in unchanged areas, impervious surface predictions were estimated for changed areas within an urban extent defined by a companion land cover classification. Methods were developed and tested for national application across six study sites containing a variety of urban impervious surface. Results show the vast majority of impervious surface change associated with urban development was captured, with overall RMSE from 6.86 to 13.12% for these areas. Changes of urban development density were also evaluated by characterizing the categories of change by percentile for impervious surface. This prototype method provides a relatively low cost, flexible approach to generate updated impervious surface using NLCD 2001 as the baseline.

농경지 불투수면 변화에 따른 유역 수문 영향 분석

The Soil and Water Assessment Tool (SWAT) model was used in this study to evaluate the hydrologic impacts by the impervious surface change in the farm region. The model was calibrated and validated by using four years (1999-2002) of measured data for the Gyeongancheon watershed in Korea. The simulation results agreed well with observed values during the calibration and validation periods. Land use scenarios including various changes of the plastic film house area in the farm region were applied to assess their effects on watershed hydrology. The results indicated that the surface direct (5.6%~14.0%) and total runoff (0.8%~1.5%) increased, but the groundwater discharge (10.7%~27.7%) and evapotranspiration (1.5%~3.3%) decreased as the plastic film house area (5.7%~12.4%) increased.

On Climate Impacts of a Potential Expansion of Urban Land in Europe

Abstract Over the last two decades, a disproportional increase of urban land area in comparison with the population growth has been observed in many countries of Europe, and this trend is predicted to continue. The conversion of vegetated land into urban land leads to a higher proportion of impervious surface area, to decline and change of vegetation cover, to artificial heat sources, and therefore to changes in climate. This study focuses on the implications of the expansion of urban land for the European climate at the local and regional scales. Regional climate simulations with the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) coupled to the Town Energy Budget model are used to isolate effects of urban land expansion on temperature and precipitation. The study suggests that the expansion of current urban land by 40% would lead to an enlargement of regions affected by thermal stress by a factor of 2, whereas the intensity of the thermal stress does not change significantly. Precipitation in urban areas would be reduced by 0.2 mm day−1 in summer as a result of disturbances of the water cycle caused by urban surfaces. The area in which precipitation was altered increased nearly linearly with the urban land increment.