Mapping transit‐based access: integrating GIS,routes and schedules

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam sonar mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. Multibeam acoustic data collected across a ～1000 km² area of the Carnarvon Shelf, Western Australia, were used in a predictive modelling approach to map eight seabed sediment parameters. Four machine learning models were used for the predictive modelling: boosted decision tree, random forest decision tree, support vector machine and generalised regression neural network. The results indicate overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness and Mean Grain Size. The study also demonstrates that predictive modelling using the combination of machine learning models has provided the ability to generate prediction uncertainty maps. However, the single models were shown to have overall better prediction performance than the combined models. Another important finding was that choosing an appropriate set of explanatory variables, through a manual feature selection process, was a critical step for optimising model performance. In addition, machine learning models were able to identify important explanatory variables, which are useful in identifying underlying environmental processes and checking predictions against the existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of covariance of physical and biological data for this area.     

The inclusion of differentially assessed lands in urban growth model calibration: a comparison of two approaches using SLEUTH

This research sought to understand the role that differentially assessed lands (lands in the United States given tax breaks in return for their guarantee to remain in agriculture) play in influencing urban growth. Our method was to calibrate the SLEUTH urban growth model under two different conditions. The first used an excluded layer that ignored such lands, effectively rendering them available for development. The second treated those lands as totally excluded from development. Our hypothesis was that excluding those lands would yield better metrics of fit with past data. Our results validate our hypothesis since two different metrics that evaluate goodness of fit both yielded higher values when differentially assessed lands are treated as excluded. This suggests that, at least in our study area, differential assessment, which protects farm and ranch lands for tenuous periods of time, has indeed allowed farmland to resist urban development. Including differentially assessed lands also yielded very different calibrated coefficients of growth as the model tried to account for the same growth patterns over two very different excluded areas. Excluded layer design can greatly affect model behavior. Since differentially assessed lands are quite common through the United States and are often ignored in urban growth modeling, the findings of this research can assist other urban growth modelers in designing excluded layers that result in more accurate model calibration and thus forecasting.     

Incorporating vegetation into visual exposure modelling in urban environments

Visual exposure modelling establishes the extent to which a nominated feature may be seen from a specified location. The advent of high-resolution light detection and ranging (LiDAR)-sourced elevation models has enabled visual exposure modelling to be applied in urban regions, for example, to calculate the field of view occupied by a landmark building when observed from a nearby street. Currently, visual exposure models access a single surface elevation model to establish the lines of sight (LoSs) between the observer and the landmark feature. This is a cause for concern in vegetated areas where trees are represented as solid protrusions in the surface model totally blocking the LoSs. Additionally, the observer's elevation, as read from the surface model, would be incorrectly set to the tree top height in those regions. The research presented here overcomes these issues by introducing a new visual exposure model, which accesses a bare earth terrain model, to establish the observer's true elevation even when passing through vegetated regions, a surface model for the city profile and an additional vegetation map. Where there is a difference between terrain and surface elevations, the vegetation map is consulted. In vegetated areas the LoS is permitted to continue its journey, either passing under the canopy with clear views or partially through it depending on foliage density, otherwise the LoS is terminated. This approach enables landmark visual exposure to be modelled more realistically, with consideration given to urban trees. The model's improvements are demonstrated through a number of real-world trials and compared to current visual exposure methods.     

A heuristic cellular automata approach for modelling urban land-use change based on simulated annealing

This article presents a novel cellular automata (CA) approach to simulate the spatio-temporal process of urban land-use change based on the simulated annealing (SA) algorithm. The SA algorithm enables dynamic optimisation of the CA's transition rules that would otherwise be difficult to configure using conventional mathematical methods. In this heuristic approach, an objective function is constructed based on a theoretical accumulative disagreement between the simulated land-use pattern and the actual land-use pattern derived from remotely sensed imagery. The function value that measures the mismatch between the actual and the simulated land-use patterns would be minimised randomly through the SA process. Hence, a set of attribution parameters that can be used in the CA model is achieved. An SA optimisation tool was developed using Matlab and incorporated into the cellular simulation in GIS to form an integrated SACA model. An application of the SACA model to simulate the spatio-temporal process of land-use change in Jinshan District of Shanghai Municipality, PR China, from 1992 to 2008 shows that this modelling approach is efficient and robust and can be used to reconstruct historical urban land-use patterns to assist with urban planning policy-making and actions. Comparison of the SACA model with a typical CA model based on a logistic regression method without the SA optimisation (also known as LogCA) shows that the SACA model generates better simulation results than the LogCA model, and the improvement of the SACA over the LogCA model is largely attributed to higher locational accuracy, a feature desirable in most spatially explicit simulations of geographical processes.     

A new discovery of transition rules for cellular automata by using cuckoo search algorithm

This paper presents an intelligent approach to discover transition rules for cellular automata (CA) by using cuckoo search (CS) algorithm. CS algorithm is a novel evolutionary search algorithm for solving optimization problems by simulating breeding behavior of parasitic cuckoos. Each cuckoo searches the best upper and lower thresholds for each attribute as a zone. When the zones of all attributes are connected by the operator ‘And’ and linked with a cell status value, one CS-based transition rule is formed by using the explicit expression of ‘if-then’. With two distinct advantages of efficient random walk of Lévy flights and balanced mixing, CS algorithm performs well in both local search and guaranteed global convergence. Furthermore, the CA model with transition rules derived by CS algorithm (CS-CA) has been applied to simulate the urban expansion of Nanjing City, China. The simulation produces encouraging results, in terms of numeric accuracy and spatial distribution, in agreement with the actual patterns. Preliminary results suggest that this CS approach is well suitable for discovering reliable transition rules. The model validation and comparison show that the CS-CA model gets a higher accuracy than NULL, BCO-CA, PSO-CA, and ACO-CA models. Simulation results demonstrate the feasibility and practicability of applying CS algorithm to discover transition rules of CA for simulating geographical systems.     

中国特大城市空间形态演变研究

以2008年全国52个百万人口以上的特大城市为样本,分析了1990-2008年中国特大城市空间形态在形状指数、空间紧凑度和空间破碎度方面的演变特征。研究表明:1)中国特大城市空间形态趋向带状特征,形状率和圆形率指数均呈下降趋势,下降幅度最大的是西北部、西部和东部地区的城市;2)空间紧凑度下降,面积-周长紧凑度和面积-轴线紧凑度指数均呈下降趋势,下降幅度最大的是西部地区的城市;3)空间破碎度趋于增强,分形维数呈上升趋势,上升幅度最大的是西南和东南部地区的城市;4)影响中国特大城市空间形态特征变化的因素主要有城市规模的扩大、新型城市空间要素的出现和城市空间结构的多中心化。     

Sea-level rise and flooding in coastal riverine flood plains

Abstract

This work presents a method for calculating the contributions of sea-level rise and urban growth to flood risk in coastal flood plains. The method consists of hydraulic/hydrological, urban growth and flood-damage quantification modules. The hydraulic/hydrological module estimates peak annual flows to generate flood stages impacted by sea-level rise within flood plains. A model for urban growth predicts patterns of urbanization within flood plains over the period 2010–2050. The flood-damage quantification module merges flood maps and urbanization predictions to calculate the expected annual flood damage (EAFD) for given scenarios of sea-level rise. The method is illustrated with an application to the Tijuana River of southern California, USA, and northwestern Mexico, where the EAFD is predicted to increase by over US$100 million because of sea-level rise of 0.25–1.0 m and urban growth by the year 2050. It is shown that urbanization plays a principal role in increasing the EAFD in the study area for the range of sea-level rise considered.

Editor Z.W. Kundzewicz

Citation Garcia, E.S. and Loáiciga, H.A., 2013. Sea-level rise and flooding in coastal riverine flood plains. Hydrological Sciences Journal, 59 (1), 204–220.     

Hydrological study of the potential effects of the melting of Nevado del Ruiz glacier on urban growth zones in Manizales,Colombia

ABSTRACT

This paper presents the results of a hydrological study aimed at characterizing flood-prone areas in the urban growth zone in the city of Manizales based on the potential effects of melting of the Nevado del Ruiz glacier, in Caldas, Colombia. These results constitute a basis for decision making regarding possible urban growth zones in Andean areas that face risks from volcanic eruptions producing lahars and floods caused by glacier melt. Conservative estimates of extreme flows in the Chinchiná River in the urban growth area of El Rosario can be obtained by considering the effects of rain triggered by airborne particulate material following a volcanic explosion combined with the effects of glacier melt. The effects of global warming on tropical glaciers contribute to their retreat, leading to their disappearance. Therefore, the worst scenario would take place if these events occurred in the short term as glacier volume decreases with time.

Editor Z.W. Kundzewicz; Associate editor not assigned     

Impacts of urbanisation on hydrological and water quality dynamics,and urban water management: a review

ABSTRACT

As urban space continues to expand to accommodate a growing global population, there remains a real need to quantify and qualify the impacts of urban space on natural processes. The expansion of global urban areas has resulted in marked alterations to natural processes, environmental quality and natural resource consumption. The urban landscape influences infiltration and evapotranspiration, complicating our capacity to quantify their dynamics across a heterogeneous landscape at contrasting scales. Impervious surfaces exacerbate runoff processes, whereas runoff from pervious areas remains uncertain owing to variable infiltration dynamics. Increasingly, the link between the natural hydrological cycle and engineered water cycle has been made, realising the contributions from leaky infrastructure to recharge and runoff rates. Urban landscapes are host to a suite of contaminants that impact on water quality, where novel contaminants continue to pose new challenges to monitoring and treatment regimes. This review seeks to assess the major advances and remaining challenges that remain within the growing field of urban hydrology.

Editor M.C. Acreman; Associate editor E. Rozos     

Field investigation of a dry detention pond with underground detention storage

Abstract

A dry pond is an urban drainage component designed to temporarily store stormwater runoff and to encourage infiltration of surface water to the subsurface layer. This paper investigates field measurement of a dry pond at Taiping Health Clinic, Perak, Malaysia that has been functioning well for five years. The pond has a surface area of 195 m², maximum depth of 32 cm, and a storage capacity of 31.88 m³. The study focused on the infiltration functionality of the constructed dry pond and the results show that it has an average infiltration rate of 125 mm/h and dries up in 330 min after being filled to a depth of 31 mm. A public-domain hydrological model was then employed to simulate hydrographs of ponding and draining, the results of which matched observations with 86–98% accuracy. These results can lead to better understanding of the system and allow duplication of such a drainage design elsewhere.

Editor D. Koutsoyiannis

Citation Lai, S.H. and Mah, D.Y.S., 2012. Field investigation of a dry detention pond with underground detention storage. Hydrological Sciences Journal, 57 (6), 1249–1255.