Percentage Of Built-up Area Research Articles

Spatial and temporal divergence and driving mechanisms of carbon sinks in terrestrial ecosystems in the middle reaches of the Yangtze River urban agglomerations during 2008–2020

Urban cluster carbon sinks are key parts of the terrestrial carbon cycle, and play an important role in global climate change. Based on the inversion results of net ecosystem productivity (NEP) in Middle Reaches of the Yangtze River Urban Agglomeration (MRYRUA), this study considered the influence of both natural environmental and socioeconomic factors on NEP, and investigated the driving mechanism of carbon sink emphasizing spatial and temporal heterogeneity by the geographically and temporally weighted regression model (GTWR). Results demonstrated that (1) During 2008–2020, the annual average NEP was positive in MRYRUA, and the carbon sink effect of terrestrial ecosystem increased. (2) In MRYRUA, Precipitation and DEM were positively correlated with carbon sinks, opposite for temperature, percentage of water areas and population density. (3) During the study period, the influence of natural environmental factors, such as temperature and precipitation on NEP grew gradually weaker, whereas that of socioeconomic factors increased. The influence of urbanization rate, night lights index and factors of industrial structure changed from negative to positive, while percentage of built-up area had an increasing negative effect on NEP. Based on the conclusions above, this study proposed differentiated policy implications, including improving vegetation hydrothermal environment, controlling urban expansion and accelerating industrial transformation. It would provide empirical inspiration for attaining peak carbon, carbon neutrality, and sustainable development goals.

Weak effect of urbanization on bdelloid rotifers living in lichens.

Human activities have an overwhelming impact on the natural environment, leading to a deep biodiversity crisis whose effects range from genes to ecosystems. Here, we analysed the effect of such anthropogenic impacts on bdelloid rotifers (Rotifera Bdelloidea), for whom these effects are poorly understood. We targeted bdelloid rotifers living in lichen patches across urbanization gradients in Flanders and Brussels (Belgium). Urbanization was measured as the percentage of built-up area (BU) across different spatial scales, at circles from 50 to 3200 m of radius around the lichen. Urbanization effects on biodiversity were assessed on abundance, species richness and community-weighted mean body size of bdelloid rotifers, as well as on genetic diversity of a mitochondrial marker (cytochrome c oxidase subunit I) of one of the most common and widespread bdelloid species, Adineta vaga. Overall, no negative effect of urbanization was found at any diversity level and any spatial scale. Counterintuitively, the BU area quantified at the largest spatial scale had a positive effect on abundance. These results leave open the question of whether negative effects of urbanization are present for bdelloid rotifers, if they are mediated by other unexplored drivers, or if such effects are only visible at even larger spatial scales.

Mapping and modeling riverine sand and gravel mining at the sub-continental scale: A case study for India

Sand and gravel are amongst the most mined and consumed resources in the world, especially in the Global South where the demand for sand increases due to urbanization. Large parts of this extraction occur in rivers, with adverse environmental consequences. Mitigation of riverine sand and gravel mining (RSM) impacts on freshwater systems requires a robust understanding of the scale and controlling factors of RSM. However, very limited data exist on the occurrence of this process. This is especially true over larger spatial scales. Here we aim to bridge this gap and gain more insight into the occurrence of RSM at a subcontinental scale. More specifically, we (1) develop a systematic mapping procedure of RSM to collect the first large-scale dataset of RSM occurrence focusing on India as a case study. Using this dataset, we then (2) statistically analyze the factors potentially controlling spatial patterns of RSM across India. Factors were included that represent both the demand and supply of sand. Based on these results, we (3) develop a logistic regression model to estimate the probability of RSM occurrence. Overall, our work shows the enormous scale of RSM in India: of the 808 randomly selected and investigated river reaches (with lengths of ca. 10 km), 61.6 % showed clear evidence of RSM. Statistical analyses revealed that the presence of RSM is mainly linked to variables describing the demand for sand (e.g. distance to city, percentage of built-up area around the river reach), while variables relating to supply (e.g. soil texture, expected sediment discharge) showed much weaker correlations. Only rainfall variability was a clearly significant factor, which may relate to river reach accessibility. Based on these findings, we present a first model and map that predicts the susceptibility to RSM in India.

Identification of Fire Disaster Vulnerability in Karang Rejo Sub-District, Balikpapan Central District

At least 617 cases of fire disasters were recorded in Balikpapan City from 2010 to 2020. In response, fire disaster mitigation is still a problem, especially in dense residential areas and unclean environments. One of the sub-districts with the characteristics of dense settlements and a history of fire incidents is Karang Rejo Village. This condition can be an obstacle in disaster mitigation. Therefore, it is necessary to identify appropriate mitigation efforts for this sub-district. Vulnerability assessment can be an essential first step to reducing the impact and losses of a fire disaster. The purpose of this study is to formulate fire disaster mitigation based on the level of vulnerability in Karang Rejo Village, Central Balikpapan District, using the spatial multi-criteria analysis method. The research results obtained are structural fire disaster mitigation at low, medium, and high vulnerability by mitigating aspects of building density, percentage of built-up areas, building materials, the width of access roads, availability of water reservoirs, availability of vacant land, the portion of households working in the informal sector, and the ratio of poor people.

Mapping and characterising buildings for flood exposure analysis using open-source data and artificial intelligence

The mapping and characterisation of building footprints is a challenging task due to inaccessibility and incompleteness of the required data, thus hindering the estimation of loss caused by natural and anthropogenic hazards. Major advancements have been made in the collaborative mapping of buildings with platforms like OpenStreetMap, however, many parts of the world still lack this information or the information is outdated. We created a semi-automated workflow for the development of elements-at-risk (EaR) databases of buildings by detecting building footprints using deep learning and characterising the footprints with building occupancy information using building morphological metrics and open-source auxiliary data. The deep learning model was used to detect building EaR footprints in a city in Kerala (India) with an F1 score of over 76%. The footprints were classified into 13 building occupancy types along with information such as average number of floors, total floor space area, building density, and percentage of built-up area. We analysed the transferability of the approach to a different city in Kerala and obtained an almost similar F1 score of 74%. We also examined the exposure of the buildings and the associated occupancies to floods using the 2018 flood susceptibility map of the respective cities. We notice certain shortcomings in our research particularly, the need for a local expert and good quality auxiliary data to obtain reasonable building occupancy information, however, our research contributes to developing a rapid method for generating a building EaR database in data-scarce regions with attributes of occupancy types, thus supporting regional risk assessment, disaster risk mitigation, risk reduction initiatives, and policy developments.

Remotely-Sensed Derived Built-up Area as an Alternative Indicator in the Study of Thailand’s Regional Development

Nowadays measuring national and regional development primarily relies on demographic and socio-economic indicators. An indicator in physical dimension e.g., areas of human settlements and their economic uses of lands is usually ignored due to unavailability of data in countries like Thailand. Remotely-sensed derived built-up area was used, for the first time, as a physical indicator for studying Thailand’s regional development. Remote sensing - using the decision tree classifier with the combination indices of band ratios, NDVI, MNDWI, and NDBI - and GIS techniques were utilized to estimate the regional proportion of built-up area. The relationships between the percentage of the derived built-up area and the three development indicators - urbanization rate, Gross Regional Product, and Human Achievement Index - were analyzed. Resultantly, the estimate of the 2019 derived built-up area in Thailand was 2.46% with the average accuracy of 84.5%. Regional variation in development levels existed and relationships between the percentage of built-up area and the three development indicators for the regions were strong. However, there was no relationship after excluding the region having the effect of Bangkok. Therefore, remotely-sensed derived built-up area gives new information and is suggested for use for the analysis of Thailand’s regional development.

Plant Dispersal Mode at Different Urbanization Levels in Ipoh City Council, Perak

Urbanization is rapidly expanding, and many forests are being cleared. The loss of crucial ecological functions, including dispersal and pollination, in urban settings can have detrimental effects on individual species and the sustainability of entire ecosystems. Nevertheless, how urbanization affects seed dispersal is still largely unexplored. Hence, this study aimed to investigate the association between plant dispersal mode and urbanization intensity in Ipoh City Council, Perak. The percentage of built-up area within a 1km2 area was measured using ArcGIS software to establish the urbanization gradient. To reflect distinct urbanization, a total of 12 sampling plots, with the sized of 1km2 for each plot were designed. 40 subplots were randomly selected in each plot to create a complete sampling site of 0.1 hectare, and any plants discovered in the subplots were identified at the species level. To characterize the mode of dispersion for each plant species recorded, a few reports from literature have been used as a guideline. Endo-zoochory and hemerochory were more prevalent in urban settings than in other study areas. Significant abundance of zoochory-dependent plants in this study area, it shows urbanization does not always reduce the nature conservation value of places in Ipoh. In the future, policymakers, and town planners could use the findings of this study to help them continuously improve urban development and generate more sustainable urban expansion.

Changes in Reticular River Network under Rapid Urbanization: A Case of Pudong New Area, Shanghai

Large quantity of rivers have disappeared during rapid urbanization in China’s Yangtze River Delta, and it is difficult to define the changes in the river network owing to its high dense and complex reticular structure. Shanghai’s Pudong New Area (SPNA) is a typical area of rapid urbanization in the delta. A Comprehensive River-network Indicator System (CRIS), including quantity and area, geomorphologic structure, and landscape connectivity indicators, was established to characterize the changes in the dense reticular river network in SPNA from 1965 to 2010. The percentage of urban area rapidly increased from 22.52% to 59.49% in SPNA, whereas that of water surface (Wp) decreased from 10.57% to 7.23% during the same period. The changes in river network displayed a clear spatial gradient, and the closer the functional area is to the city center, the earlier and faster the changes in the rivers. CRIS obviously changed when the percentage of built-up area increased from 10% to 30%; however, the CRIS changed more gently when the percentage exceeded 30%. Among the three sub-indicators of CRIS, quantity and area strongly corresponded to urbanization stages, geomorphologic structure was most sensitive to urbanization, and landscape connectivity accurately captured the threshold phenomena in the change in reticular river network.

Land use and land cover changes in the Lower Neretva Region from 1990 to 2020

Changes in land use and land cover are the result of complex interactions between humans and their environment. This study examines land use and land cover changes in the Lower Neretva Region between 1990 and 2020. Political and economic changes in the early 1990s resulted in changes in the landscape, both directly and indirectly. Multispectral image processing was used to create thematic maps of land use and land cover for 1990, 2005, and 2020. Satellite images from Landsat 5, Landsat 7 and Landsat 8 were the main source of data. Land use and land cover structure was assessed using a hybrid approach, combining unsupervised and manual (visual) classification methods. An assessment of classification accuracy was carried out using a confusion matrix and kappa coefficient. According to the results of the study, the percentage of built-up areas increased by almost 33%. Agricultural land and forests and grasslands also increased, while the proportion of swamps and sparse vegetation areas decreased.

Main macroinvertebrate community drivers and niche properties for characteristic species in urban/rural and lotic/lentic systems

The effect of urbanization is often reflected both in lotic and lentic habitats, through changes in diversity and structural and compositional changes in macroinvertebrate communities. In this study, we focused on macroinvertebrate assemblage in lotic and lentic ecosystems of the Krąpiel River catchment area (NW Poland) with the following aims: (1) to determine the main driver in structuring lotic and lentic macroinvertebrate communities and the factors that influence them in urban versus rural landscapes; (2) to test whether the diversity of macroinvertebrate assemblages in urban lotic/lentic ecosystems is lower than that in rural landscapes; (3) to identify characteristic macroinvertebrate species for urban and rural lotic/lentic ecosystems; to (4) determine species tolerance ranges and species optimums, with special emphasis on characteristic “urban” and “rural” species. Distance from study sites to built-up areas and conductivity were the main factors contributing to the separation of urban vs. rural habitats. For lotic sites, temperature, the percentage of built-up area, insolation, and oxygen concentration were the main factors significantly associated with changes in community composition. For lentic sites, insolation, temperature, and BOD5 were recognized as the main factors which are significantly associated with changes in community composition. The results for lentic habitats were as expected: average species richness was higher in rural than in urban habitats. The characteristic species for each of the four habitat groups included Mideopsis orbicularis for Lentic rural habitats; Hygrobates longipalpis for Lotic rural habitats; Piona sp. for Lentic urban habitats; Mideopsis crassipes for Lotic urban habitats. Hygrobates longipalpis and Piona sp. were at the opposite sides with respect to the degree of urbanization. Result of this investigation has shown that the impact of urbanization and consequently the implementation of conservation measures should be viewed separately within the lentic and lotic gradient.

Land reclamation pattern and environmental regulation guidelines for port clusters in the Bohai Sea, China.

Coastal land reclamation (CLR), particularly port reclamation, is a common approach to alleviating land shortages. However, the spatial extent, percentages, and processes of these newly reclaimed ports are largely unknown. The Bohai Sea is the most concentrated area of port reclamation worldwide. Thus, this study addresses the changes in the different coastline types and port reclamation process in the area. The reclamation area of the 13 ports in the Bohai Sea in 2002-2018 was 2,300 km2, which decreased the area of the sea by 3%. The natural coastline length in Tianjin decreased by 47.5 km, whereas the artificial coastline length increased by 46.6 km. Based on the port boundary, however, only 26.3% of the reclaimed areas have been used for port construction, which concentrates in the Tianjin and Tangshan ports. The ratio of built-up area within the ports is only 32.5%, and approximately 48.3% of the reclaimed areas have no construction projects. The port land reclamation in the Bohai Sea has been undergoing periods of acceleration, peak, deceleration, and stagnation since 2002. Hence, future port reclamation should not be totally prohibited, and fine management should be conducted based on the optimization of the reclaimed port area. The innovation of this research is its analysis of the port internal land use pattern, the percentage of built-up area in the ports, and the sustainability of port reclamation policies. The findings have vital implications for scientifically regulating the spatial pattern and exploring the utility of port reclamation.

Fractal dimension of European Cities: A comparison of the patterns of built-up areas in the urban core and the peri-urban ring

This study compares the urban form of large European cities using fractal dimensions. Fractal dimensions are computed for built-up areas using data available in the Imperviousness High Resolution Layer dataset (EEA, 2012), and are estimated following two different methodologies; the binary approach which considers only two classes, developed land and non-developed land and the grayscale approach in which the built-up intensity, as expressed by the soil sealing degree is explicitly taken into account. Fractal dimensions are estimated for the 60 European cities with population exceeding one million. Using the boundaries defined in Urban Atlas the functional urban Area (FUA) is divided in two parts, the core of the urban area and the peri-urban ring area. Fractal dimensions are computed for each of these three spatial entities. Results show that the grayscale fractal dimension values at the FUA level are 1.18-1.55 and that the equivalent binary ones are always higher with values between 1.34 and 1.83. There is a high correlation between the two sets of fractal dimensions, as well as between the fractal dimension and the overall percentage of built-up area. Cities are also compared across regions (UK-Ireland, Scandinavia, Central, South, East). Significantly higher fractal values at the FUA level are reported in the cities located on the highly urbanized European corridor spanning from South UK to the Netherlands, Belgium, the Ruhr region and Northern Italy, while East European and Scandinavian cities form a distinct group with lower fractal dimension values. Another group of cities with high FUA fractal dimensions includes the coastal South European cities Porto, Lisbon, Naples and Barcelona. At the CΟRE urban areas, the highest fractal values are observed in the largest cities (London, Paris, Berlin) which are compactly built-up.

Spatiotemporal analysis of the coordination of economic development, resource utilization, and environmental quality in the Beijing-Tianjin-Hebei urban agglomeration

Rapid urbanization has produced a series of environmental and resource issues in the Beijing-Tianjin-Hebei urban agglomeration (BTHUA). It is necessary to identify pathways toward sustainable urban development. This study explores the coordination relationship within the economy-resources-environment (ERE) system in the BTHUA during 2008–2017. First, a comprehensive indicator system and a coupling coordination index (CCI) were established to measure the coordination relationship in the ERE system. Second, an obstacle degree model was applied to identify the leading indicators affecting the coordinated development of the ERE system. Our results suggested that: (1) the coupling coordination state of the ERE system in the BTHUA has improved from a low coordination stage to a good coordination stage during the study period; (2) the spatial distribution of the coupling coordination state showed a pattern of better performance in the south and east and worse in the north and west; (3) the percentage of secondary industry in the GDP, percentage of built-up areas in the total land area, and sewage treatment rate were the primary factors that affected the ERE system’s coordination state. This study provides the basis for future work on the environment and resource protection in the capital region of China and other similar areas undergoing urban sprawl around the world.

Assessing the Impact of Urbanization on Outdoor Thermal Comfort in Selected Local Government Areas in Ogun State, Nigeria

This study seeks to assess the land use land cover (LULC) and spatial-temporal trends of six outdoor thermal comfort indices in four Local Government Areas (LGAs) of Ogun state, Southwestern, Nigeria. Data used for this study are air temperature, relative humidity, cloud cover and wind speed which span from 1982 to 2018. These data were obtained from ERA-INTERIM archive. The 1986, 2000 and 2018 used for the analysis of the LULC were from the satellite imagery hosted by the United States Geological Survey (USGS). Landsat Thematic Mapper, Landsat 7 and Landsat 8 Operational Land Imager data of 1986, 2000 and 2018 to assess the changes that have taken place between these periods. Thermal comfort indices such as Effective Temperature (ET), Temperature Humidity Index (THI), Mean radiant temperature (MRT) and Relative Strain Index (RSI) were used. Rayman model was used for the computation of the three thermal comfort indices (MRT, PET, PMV). The results show decrease in vegetation, forest, and an increase in percentage of built-up areas between 1986–2000, and 2000–2018. A rapid increase in built-up areas in the three (Abeokuta South, Ifo, Shagamu,) of the four LGAs, while one (Ijebu East) has a slow increase in the built-up areas. The trend in the thermal comfort indices also shows that thermal discomfort had been on increase for the past 37 years and it was observed that the level of comfort has deteriorated more in the last decade compared to the previous decade especially in the built-up areas. This work suggests a framework for evaluating the relationship between the quantitative and qualitative parameters linking the microclimatic environment with subjective thermal assessment. This will contribute to the development of thermal comfort standards for outdoor urban settings. Also, the study will help urban planners in their decision making, and in heat forecast.

Measuring Urban Land Use Change and Sprawl Using Geospatial Techniques: A Study on Purulia Municipality, West Bengal, India

Population growth, desire for more income, transportation facilities and rural to urban migration have increased the rate of urbanisation and complicated its pattern over Purulia district, West Bengal, India. This situation obstructs the organised and planned urban development provoking the sprawl like phenomenon within the urban locality. As the district belongs to a socio-economic deprived region, most of the researchers mainly concentrate on the physical and socio-economic problems of the district neglecting the scenario of urbanisation over the district. So, the present study is an attempt to assess the urban growth modelling over the Purulia Municipality which is a dominating city in terms of population and urban functions in the district. Images from Landsat-5 Thematic mapper (TM) and Landsat-8 Operational Land Imager (OLI) were used to prepare land use land cover (LULC) maps of 1998, 2008 and 2018. Supervised classification with maximum likelihood classifier was applied. Direction-based relative Shannon’s entropy model has been used for quantification of urban expansion in the last 20 years. The LULC changing condition shows that 65.41% vegetation coverage, 47.63% water body, 31.55% bare land and 10.79% agricultural land have been diminished within this time due to increasing demand for artificial man-made land. Besides, the built-up area has grown by 122% within the 20 years which proved that urban physical expansion is going on over the municipality. The results show that the pattern of urban growth of this municipality is a compact one, and the built-up areas are mostly oriented towards North, North-east, East, South-east and South directions than the other quadrants. Besides, the percentage of built-up area has been rapidly decreasing from CBD to periphery area due to increasing distance. For the planning purpose of balance development in a socio-economic deprived region like Purulia district, the outcomes of this study can best be utilised by the local planners and administrators.

Geographical and Economic Factors Affecting the Spatial Distribution of Micro, Small, and Medium Enterprises: An Empirical Study of The Kujawsko-Pomorskie Region in Poland

Micro, small, and medium-sized enterprises (MSMEs) are an essential part of economies at the national, regional, and local levels. Understanding the determinants of the development of this sector is interesting not only for researchers but also for local governments to support the development of this sector. This paper analyses micro, small, and medium enterprises at the gmina (local) level in one region, the Kujawsko-Pomorskie voivodship (NUTS2) in Poland. The authors use multivariate linear regression, spatial econometrics, and classification trees to model the influence of different factors on the number of enterprises relative to population size. The authors found that the most crucial factor in all cases, independently of the method used, is the local government’s revenue from personal income tax per capita. This finding, together with the lack of significance of variables related to the distance to technological parks or economic zones, indicates that the enterprises in the region produce mainly for local consumption and lack innovativeness. The authors also examined the influence of spatial context on the number of enterprises. The most important factor seems to be the percentage of built-up areas, but there are also others, depending on the model type; again, this confirms the local character of the activity of micro, small, and medium enterprises in the region. Variables representing the spatial context can explain the relative number of enterprises with coefficient of determination (R2) between 0.30 and 0.45, which shows that this context played a relatively significant role in the development of the MSME sector in the region. On the other hand, the econometric models (that include the neighborhood) are only significant (improving R2) for medium enterprises, which means that medium enterprises expand their activity beyond the local range.

EKSTRAKSI TERHADAP TUTUPAN LAHAN TERBANGUN MENGGUNAKAN CITRA PENGINDERAAN JAUH RESOLUSI MENENGAH DI KEPESISIRAN KOTA TERNATE

The spatial pattern of Ternate City has experienced a significant development mainly on the physical expression of urban areas which is driven by the growth of built-up areas in a relatively fast time. The built-up area is an important element of the phenomenon of urban development that is inseparable from the history of city growth, current conditions, and future city growth. Analysis of urban land cover using remote sensing data with data extraction related to built-up areas in 27 coastal villages of Ternate City. Image data used are Landsat 8 OLI multispectral imagery for the 2016 year recording with using channels 2 to 8. The results of the built-up area extraction using a maximum likelihood classified indicate that the growth of the built-up area is very massive, especially for the four villages which are including region the Ternate City Service Center. The percentage of built-up area is a relative representation of the density of land cover is very high, especially some villages areas bordering sea waters within the City of Ternate.

Phenotypic signatures of urbanization are scale-dependent: A multi-trait study on a classic urban exploiter

Understanding at which spatial scales anthropogenic selection pressures operate most strongly is a prerequisite for efficient conservation and management of urban biodiversity. Heterogeneity in findings on the strength and direction of urbanization effects may result from a lack of consensus on which spatial scales are most adequate when studying biotic effects of urbanization. Therefore, here, using the house sparrow (Passer domesticus) as model, we test the hypothesis that more than one spatial scale will explain variation among phenotypic stress markers. By applying a unique hierarchical sampling design enabling us to differentiate between local and regional effects of urbanization, we here show that the strength and direction of relationships with the percentage of built-up area – a simple structural measure of urbanization - vary among phenotypic stress markers and across the spatial range over which urbanization is measured. While inverse relationships with scaled body mass and bill height of adult house sparrows (Passer domesticus) were strongest when the degree of urbanization was quantified at city-level, similar relationships with corticosterone concentrations in feathers were only detected at the scale of individual home ranges. In contrast, tarsus length, wing length, and two measures of feather development were not significantly related to urbanization at any spatial scale. As the suite of phenotypic stress markers applied in this study revealed signatures of urbanization over a broad spatial range, we conclude that measures aimed at mitigating impacts of urbanization on free-ranging populations should best be implemented at multiple spatial scales too.

Improving estimates of built-up area from night time light across globally distributed cities through hierarchical modeling

Built-up area has become an important indicator for studying urban environments, but mapping built-up area at the regional/global scale remains challenging due to the complexity of impervious surface features. Nighttime light data (NTL) is one of the major remote sensing data sources for regional/global built-up or impervious surface mapping. A single regression relationship between fractional built-up/impervious area and NTL or various indices derived based on NTL and vegetation index (e.g., NDVI) data had been established in many previous studies. However, due to the varying geographical, climatic, and socio-economic characteristics of cities, the same regression relationship may vary significantly across cities. In this study, we examined the regression relationship between percentage of built-up area (pBUA) and vegetation adjusted nighttime light urban index (VANUI) for 120 randomly selected cities around the world with a hierarchical hockey-stick regression model. We found that there is a substantial variability in the slope (0.658 ± 0.318), the threshold VANUI (−1.92 ± 0.769, log scale) after which the linear relationship holds, and the coefficient of determination R2 (0.71 ± 0.14) among globally distributed cities. A small proportion of this substantial variability can be attributed to socio-economic status (e.g., total population, GDP per capita) and landscape structures (e.g., compactness and fragmentation). Due to these variations, our hierarchical model or no-pooling model (i.e., fit each city individually) can significantly improve model prediction accuracy (17% in terms of root mean squared error) over a complete-pooling model. We, however, recommend hierarchical models as they can provide meaningful priors for future modeling under a Bayesian framework, and achieve higher prediction accuracy than no-pooling models when sample size is small.

Developing a cellular automata model of urban growth to inform spatial policy for flood mitigation: A case study in Kampala, Uganda

Urban growth may intensify local flooding problems. Understanding the spatially explicit flood consequences of possible future land cover patterns contributes to inform policy for mitigating these impacts. A cellular automata model has been coupled with the openLISEM integrated flood modeling tool to simulate scenarios of urban growth and their consequent flood; the urban growth model makes use of a continuous response variable (the percentage of built-up area) and a spatially explicit simulation of supply for urban development. The models were calibrated for Upper Lubigi (Kampala, Uganda), a sub-catchment that experienced rapid urban growth during 2004–2010; this data scarce environment was chosen in part to test the model's performance with data inputs that introduced important uncertainty. The cellular automata model was validated in Nalukolongo (Kampala, Uganda). The calibrated modeling ensemble was then used to simulate urban growth scenarios of Upper Lubigi for 2020. Two scenarios, trend conditions and a policy of strict protection of existing wetlands, were simulated. The results of simulated scenarios for Upper Lubigi show how a policy of only protecting wetlands is ineffective; further, a substantial increase of flood impacts, attributable to urban growth, should be expected by 2020. The coupled models are operational with regard to the simulation of dynamic feedbacks between flood and suitability for urban growth. The tool proved useful in generating meaningful scenarios of land cover change and comparing their policy drivers as flood mitigation measures in a data scarce environment.