Information For Urban Planning Research Articles

An Extended Minimum Spanning Tree method for characterizing local urban patterns

ABSTRACTDetailed and precise information on urban building patterns is essential for urban design, landscape evaluation, social analyses and urban environmental studies. Although a broad range of studies on the extraction of urban building patterns has been conducted, few studies simultaneously considered the spatial proximity relations and morphological properties at a building-unit level. In this study, we present a simple and novel graph-theoretic approach, Extended Minimum Spanning Tree (EMST), to describe and characterize local building patterns at building-unit level for large urban areas. Building objects with abundant two-dimensional and three-dimensional building characteristics are first delineated and derived from building footprint data and high-resolution Light Detection and Ranging data. Then, we propose the EMST approach to represent and describe both the spatial proximity relations and building characteristics. Furthermore, the EMST groups the building objects into different locally connected subsets by applying the Gestalt theory-based graph partition method. Based on the graph partition results, our EMST method then assesses the characteristics of each building to discover local patterns by employing the spatial autocorrelation analysis and homogeneity index. We apply the proposed method to the Staten Island in New York City and successfully extracted and differentiated various local building patterns in the study area. The results demonstrate that the EMST is an effective data structure for understanding local building patterns from both geographic and perceptual perspectives. Our method holds great potential for identifying local urban patterns and provides comprehensive and essential information for urban planning and management.

Improving Urban Planning Information, Transparency and Participation in Public Administrations

In recent years, there has been a renewed interest in the involvement of citizens in all public affairs that is also extended to urban planning. Spanish Public Administrations have made important changes and progress trying to get urban and spatial planning closer to the citizen. Firstly, a significant effort has been made to generate knowledge services providing citizen access to urban planning information. Secondly, administrations try to involve citizens in urban planning through participation programmes by using the new channels that information and communication technology offers. This paper analyses different instruments and web-based participation systems implemented in Spain in order to check the result of these developments concluding that there is still a long considerable way to go since information and communications technologies offers a lot of options and tools to improve these processes.

Urban vehicle detection in high-resolution aerial images via superpixel segmentation and correlation-based sequential dictionary learning

Vehicle detection in high-resolution aerial images has received widespread interests when it comes to providing the required information for traffic management and urban planning. It is challenging due to the relatively small size of the vehicles and the complex background. Furthermore, it is particularly challenging if the higher detection efficiency is required. Therefore, an urban vehicle detection algorithm is proposed via improved entropy rate clustering (IERC) and correlation-based sequential dictionary learning (CSDL). First, to enhance the detection accuracy, IERC is designed to generate more regular superpixels. It aims to avoid the situation that one superpixel sometimes straddles multiple vehicles. The generated superpixels are then treated as the seeds for the training sample selection. Then, CSDL is constructed to achieve a fast sequential training and updating of the dictionary. In CSDL, only the atoms correlated with the sparse representation of the new training data are inferred. Finally, comprehensive analyses and comparisons on two data sets demonstrate that the proposed method generates satisfactory and competitive results.

Detección del crecimiento urbano en el estado de Hidalgo mediante imágenes Landsat

Detection of urban growth through digital processing of satellite images provides valuable information for understanding the dynamics of change of land use and its spatial relationship with environmental factors. To apply or create effective policies for land use planning is essential to have a historical record of the regional distribution of human centers and in our country this kind of geographical database is practically null. Although Mexico has an update and complete mapping of land use, this poses great challenges. Within this issue, the Hidalgo state destines half of its territory to agricultural use, nonetheless, ranks fifth nationally in road infrastructure density. In the last decade, the current highway “Arco Norte” that crosses the southern state has promoted economic development in several neighboring municipalities and many of them were integrated into the Management Programme of the Metropolitan Area of the Valley of Mexico 2012.Given this background, this paper is focused on the generation of geographic information for regional urban planning and the overall aim is to examine urban growth rate during the period 2000-2014 in the state of Hidalgo, Mexico and identify potential areas of expansion from Landsat images. The methodology was based on techniques of remote sensing and Geographical Information System (GIS). The inputs used were six Landsat scenes: three for 2000 year and three for 2014. Image processing was performed on ERDAS Imagine® 9.1 and the spatial analysis of urban coverage statewide on ArcGIS 10.0 by ESRI®. First, the radiometric correction was made and we obtained the urban polygons of the 2000 year through of supervised classification. The 2014 urban layer was digitized manually due to the spectral incompatibility between the bands of the Landsat sensor 5 and 7, and the Landsat sensor 8. Then, we build a road density map and the spatial relationship of the urban centers with the road influence area was evaluated. For the year 2000, 103 urban polygons were mapped, whilst for 2014 were identified ten polygons more with a mapped minimum area of 24 ha. The main results indicated that in the state has increased 72.3 km2 urban area from 2000 to 2014. This represents an average growth rate of 1.8% per year. The most widespread municipalities are located in the region of Valle del Mezquital, however, Mineral de la Reforma, Tetepango, Tizayuca and Pachuca showed growth rates of 183.44%, 102% 94% and 68.5% in fourteen years, respectively. According to the road map density, these municipalities are located in areas of greatest influence of infrastructure as the Arco Norte highway in the state. The above findings, lead us to conclude that the Mezquital Valley and the Basin of Mexico are potential areas of urban spreading and it is associated with road development in the Central Mexico.

Estimation of Carbon Stocks from Land-use Change due to Tourism in Phuket Island, Thailand

According to the National Statistical Office (NSO) and the Phuket Provincial Statistical Office (PPSO), Phuket Island records a high growth rate for tourism, indicating the importance in local and national economic development. The tourism industry created noticeable effect on economic, social and also on the environmental systems. The growth of the tourism industry in Phuket has resulted in significant changes to the island, especially in the urban structure, causing problems for local citizen such as serious traffic congestion, cost-of-living increases, and loss of original forest area. The tourism industry is also a major contributor to the generation of greenhouse gases whilst it is accepted that global warming may bring tsunami. Phuket is a high- risk area for tsunami events. This has become more evident since the 2004 Indian Ocean tsunami devastated many coastal areas on the island and this is now a major concern to many citizens. Deforestation is an obvious cause of global warming due to the release of carbon from this pool. As a starting point to find the solution for these stated problems, the study aims to explore the consequence of land-use change on soil carbon stocks in Phuket province from 2000 to 2009, applying geographical information system (GIS). This exploration can help to provide information for Phuket urban planning and initiation of the forest landscape restoration so as to be a part in assisting Phuket’s tourism industry to develop sustainably.

Fractal characteristics of urban surface transit and road networks: Case study of Strasbourg, France

The fractal characteristics of urban forms and road networks can provide extremely useful information for urban planning. Previous research, however, has hardly acknowledged the fractal nature of transit networks, although this topic is of vital importance given the significance of public transit to city operations. In this study, the fractal characteristics of urban surface transit and road networks were analyzed based on the case study of Strasbourg, France. Two fractal dimensions that are most widely used, the length dimension and branch dimension, were calculated and analyzed using regression and correlation analysis. The results show that surface transit networks are fractal in seven sub-districts of Strasbourg. Furthermore, a relationship was found between the length dimension and branch dimension of road network. The branch dimension of transit network was related not only to the length dimension of transit network but also to the branch dimension of road network. Based on the fractal information, the results suggest possible methods for designing good road and surface transit networks that are well-coupled in urban traffic planning. The implications for urban development are that some potential problems with regard to traffic network structure may exist if current situations are not coincident with some findings in this article.

Opening up the subsurface for the cities of tomorrow The subsurface in the planning process

Abstract COST (European Cooperation in Science and Technology) Action TU1206 Sub-Urban has explored sustainable use and management of the urban subsurface, and the use of subsurface information in urban planning and development. A part of the Action (Working Group 1) has assessed the ‘state-of-art’ in cities; another part (Working Group 2) has evaluated practices and techniques. Both have considered access to subsurface knowledge in cities. A network was established by the Action with more than 100 participants in total; and in Working Group 2, there were more than 50 participants. Working Group 2 has resulted in 6 full reports and a summary report. The Action’s Working Group 1 undertook comprehensive city studies. These established that the subsurface was in effect virtually ‘Out of mind, out of sight’ with respect to planning and management and there was a significant knowledge gap to fill. The task for Working Group 2 was to improve this situation. This paper is based on the work drawn together in the Working Group 2 Summary report ‘Opening up the subsurface for the cities of tomorrow’. This deals with good practices in urban subsurface planning and management; and how the urban subsurface planning and management processes can be improved in the future.

ANALYSIS ON RESIDENTIAL LOCATION CHOICE AND ITS EVALUATION INDEXES BASED ON MODAL THEORY

On visiting real-estate agents or real-estate information websites, we can easily get information on houses or rooms, but it is difficult to know more about the city or area in which the houses or rooms are located. Particularly, it is difficult to determine the atmosphere and comfortability of the area. On the other hand, cities and areas are to be strictly chosen as population decreases. It is necessary to understand how cities and areas are evaluated and how they change in the future for planning them. This paper aims to determine the tendency of residential location choice and evaluation indexes of the choice including atmosphere and comfortability using a questionnaire survey. This paper applied modal theory for the analysis. We defined the concept of "modality" as "total mode of being." This theory enables us to analyze residential location choice from comprehensive viewpoints, treating both quantitative information like transportation or facility location and vague information like atmosphere or comfortability as equal evaluation indexes. Moreover, we assumed a process model of residential location choice based on the modal theory: a person grasps modality in his/her daily life, and takes background into consideration like his/her own property, memory, conditions of seeking houses or rooms, preference and so on, then chooses a concrete residential location. The survey items included "property" of the residents, "housing conditions" like family structure and transportation, "residential location" shown as urban scale and area type, and "evaluation indexes" for the location. The housing conditions and residential location were asked for both the present and future expected residence in order to analyze the process of making choices and the future trend. As for evaluation indexes, we selected 53 indexes that involved both convenience and facility location, and atmosphere and comfortability. The survey was conducted in June 2016, and 1,244 samples were collected through the survey. Chapter 3 analyzed "evaluation indexes." We found that not only existing indexes like convenience and facility location but also those like atmosphere and comfortability were highly valued in choosing a residential location. Additionally, we made clear that some indexes are important because most residents put weight on them but other indexes are also important as they make significant differences between residents. In Chapter 4, we added "property" and "housing conditions" into our analysis. The main analysis methods included extracting highly evaluated indexes based on property and residential conditions, and visualizing the change of residential conditions from the present to future. The analysis made clear that males tend to prefer urbanized areas with good public image and females like safe and convenient areas. Families with children preferred to live in detached houses in suburban areas that have good education level. Single households had an opposite tendency toward child-raising families. Chapter 5 analyzed "residential location" using the same methods as in the previous chapter. We found that the population tends to move to bigger cities in the future, but cities with 0.5-1 million people can be a good size with a fascination for both urban and suburban areas. As for area type, urban cores, small shopping districts, and areas with middle-size apartment buildings will become more popular. On the other hand, residential areas without gardens and mixed areas of houses and factories are lowly evaluated as a living environment. These results are valid as information for house hunters and future urban planning. We plan to develop this study by introducing financial conditions and actual area for concrete analysis.

Surface urban heat island effect and its relationship with urban expansion in Nanjing, China

Nanjing, a typical megacity in eastern China, has undergone dramatic expansion during the past decade. The surface urban heat island (SUHI) effect is an important indicator of the environmental consequences of urbanization and has rapidly changed the dynamics of Nanjing. Accurate measurements of the effects and changes resulting from the SUHI effect may provide useful information for urban planning. Index, centroid transfer, and correlation analyses were conducted to measure the dynamics of the SUHI and elucidate the relationship between the SUHI and urban expansion in Nanjing over the past decade. Overall, the results indicated that (1) the region affected by the SUHI effect gradually expanded southward and eastward from 2000 to 2012; (2) the centroid of the SUHI moved gradually southeastward and then southward and southwestward, which is consistent with the movement of the urban centroid; (3) the trajectory of the level-3 SUHI centroid did not correspond with the urban mass or SUHI centroids during the study period and (4) the SUHI intensity and urban fractal characteristics were negatively correlated. In addition, we presented insights regarding the minimization of the SUHI effect in cities such as Nanjing, China.

Mass balance-based regression modeling of Cd and Zn accumulation in urban soils of Beijing

Accumulation of heavy metals in urban soil can pose adverse impacts on public health and terrestrial ecosystems. We developed a mass balance-based regression model to simulate the heavy metal accumulation in urban soils as a function of time and to explore connections between metal concentration and urbanization processes. Concentrations of Cd and Zn in 68 residential soil samples in the urban area of Beijing were used. The background concentrations, the loss rates and the input fluxes of Cd and Zn in urban soils of Beijing during the last three decades were estimated using a regression of the time series of accumulations of the metals. Based on the regression estimates, we simulated the general trends of Cd and Zn accumulation in the soils from 1978 to 2078. The concentrations of Cd and Zn in urban soil generally increased with the population growth, vehicle use and coal consumption. The mean concentrations of Cd and Zn in urban soil of Beijing would increase by 3 fold over the next 70years for the current development scenario. The mass balance-based regression approach, which is able to reconstruct the history data of urban soil pollution, provides fundamental information for urban planning and environmental management.

Determining the Relationship Between Census Data and Spatial Features Derived From High-Resolution Imagery in Accra, Ghana

Remotely sensed-based estimates of dwelling and population characteristics can provide timely and spatially explicit information for urban planning and development in emerging cities. This exploratory analysis quantifies spatial features of built-up areas derived from high-resolution satellite imagery and directly relates them to census-derived variables in Accra, Ghana. Spatial features are image metrics that analyze pixel groups in order to describe the geometry, orientation, and patterns of objects in an image. By using spatial features in an urban setting, city infrastructure variations, such as roads and buildings, can be quantified and related to census variables, such as living standards and housing conditions. To test the associations between spatial patterns and demographic variables, five spatial features (line support regions, PanTex, histograms of oriented gradients, local binary patterns, and Fourier transform) were quantified and extracted from the imagery, and then correlated to the census variables. Findings indicate both spatial features and spectral information (such as NDVI) correlate strongly with standards of living such as population and housing density. Results from this study suggest that spatial features derived from satellite imagery can be used to help map socioeconomic characteristics within the city of Accra, Ghana, and that this methodology may be transferable to other developing cities.

Intra‐urban nocturnal cooling rates: development and evaluation of the NOCRA model

ABSTRACTA nocturnal cooling rate model (NOCRAM) to simulate nocturnal air temperature at urban sites is presented. The model is designed for urban planners, practitioners and researchers who demand meteorological information for urban planning and research applications. The model is based on the concept of nocturnal cooling, progressing in two distinct phases, i.e. site‐dependent cooling around sunset and site‐independent cooling from about 1 or 2 h after sunset until sunrise. Cooling rates are usually determined predominantly by prevailing weather conditions (i.e. clearness of the sky and wind speed), followed by maximum daily air temperature and by sky view factors. Second phase cooling is chiefly determined by sky clearness and wind speed. The findings and statistical results from the analysis of observational data during warm months (May–September) from Gothenburg, Sweden, as well as from past studies, were used. The model requires standard meteorological variables (i.e. wind speed, incoming short‐wave radiation, air temperature, relative air humidity, air pressure) at a reference station as well as geometrical information (i.e. the sky view factor of the site and the geographical co‐ordinates of the reference meteorological station). The model simulates the characteristic development of cooling rates in the two phases at open sites and built‐up sites with different sky view factors under a wide range of weather conditions in warm months. Using the modelled cooling rates, nocturnal air temperature is estimated easily with the accuracy of root mean square error (RMSE) ≤1.54 °C and R2 ≥0.78.

Artificial ultra-fine aerosol tracers for highway transect studies

The persistent evidence of health impacts of roadway aerosols requires extensive information for urban planning to avoid putting populations at risk, especially in-fill projects. The required information must cover both highway aerosol sources as well as transport into residential areas under a variety of roadway configurations, traffic conditions, downwind vegetation, and meteorology. Such studies are difficult and expensive to do, but were easier in the past when there was a robust fine aerosol tracer uniquely tied to traffic – lead. In this report we propose and test a modern alternative, highway safety flare aerosols. Roadway safety flares on vehicles in traffic can provide very fine and ultra-fine aerosols of unique composition that can be detected quantitatively far downwind of roadways due to a lack of upwind interferences. The collection method uses inexpensive portable aerosol collection hardware and x-ray analysis protocols. The time required for each transect is typically 1 h. Side by side tests showed precision at ± 4%. We have evaluated this technique both by aerosol removal in vegetation in a wind tunnel and by tracking aerosols downwind of freeways as a function of season, highway configuration and vegetation coverage. The results show that sound walls for at-grade freeways cause freeway pollution to extend much farther downwind than standard models predict. The elevated or fill section freeway on a berm projected essentially undiluted roadway aerosols at distances well beyond 325 m, deep into residential neighborhoods. Canopy vegetation with roughly 70% cover reduced very fine and ultra-fine aerosols by up to a factor of 2 at distances up to 200 m downwind.

Modeling and visualizing uncertainties of flood boundary delineation: algorithm for slope and DEM resolution dependencies of 1D hydraulic models

As flood inundation risk maps have become a central piece of information for both urban and risk management planning, also a need to assess the accuracies and uncertainties of these maps has emerged. Most maps show the inundation boundaries as crisp lines on visually appealing maps, whereby many planners and decision makers, among others, automatically believe the boundaries are both accurate and reliable. However, as this study shows, probably all such maps, even those that are based on high-resolution digital elevation models (DEMs), have immanent uncertainties which can be directly related to both DEM resolution and the steepness of terrain slopes perpendicular to the river flow direction. Based on a number of degenerated DEMs, covering areas along the Eskilstuna River, Sweden, these uncertainties have been quantified into an empirically-derived disparity distance equation, yielding values of distance between true and modeled inundation boundary location. Using the inundation polygon, the DEM, a value representing the DEM resolution, and the desired level of confidence as inputs in a new-developed algorithm that utilizes the disparity distance equation, the slope and DEM dependent uncertainties can be directly visualized on a map. The implications of this strategy should benefit planning and help reduce high costs of floods where infrastructure, etc., have been placed in flood-prone areas without enough consideration of map uncertainties.

Measuring and mapping the spatial distribution of the quality of life in a city: a case study in Nanjing

ABSTRACTPopulation agglomeration in urban areas makes it easy to share valid urban facilities and services that make up a high Quality of Life (QoL). However, most cities in a developing stage face the problem of under-service; this means the supply of service facilities cannot catch up with the agglomeration of the population. Additionally, insufficient transport infrastructure also does not meet the swift growth of transport demand. Urban QoL inevitably decreases under the conditions of insufficient service facilities and transport infrastructure. This paper investigates an integrated methodology to evaluate QoL by measuring the aggregated values of urban services: education services, shopping services, and medical care services. All the values of urban services are evaluated in three stages: existing values, accessible values, and perceived values, in which existing values are examined by the scale of service facilities; accessible values are effected by travel costs and obtained by applying spatial analysis in GIS and using the road and subway network in the city; and perceived values are affected by people's preferences to each service and obtained by a questionnaire that was conducted in Nanjing. As a result, this paper integrates both the objective and subjective approaches of QoL calculation and illustrates that QoL distribution in Nanjing is spatially unbalanced and unequal among different population groups; which is highlighted in that QoL distribution is visualized in 1000 m × 1000 m grids in Nanjing city. Moreover, this method can aggregate for any size of space and combination of people's attributes, which allows it to provide overall information for urban planning and policy making.

Automatic Extraction of Urban Road Centerlines from High-Resolution Satellite Imagery Using Automatic Thresholding and Morphological Operation Method

The commercial high-resolution imaging satellite with 1 m spatial resolution IKONOS is an important data source of information for urban planning and geographical information system (GIS) applications. In this paper, a morphological method is proposed. The proposed method combines the automatic thresholding and morphological operation techniques to extract the road centerline of the urban environment. This method intends to solve urban road centerline problems, vehicle, vegetation, building etc. Based on this morphological method, an object extractor is designed to extract road networks from highly remote sensing images. Some filters are applied in this experiment such as line reconstruction and region filling techniques to connect the disconnected road segments and remove the small redundant. Finally, the thinning algorithm is used to extract the road centerline. Experiments have been conducted on a high-resolution IKONOS and QuickBird images showing the efficiency of the proposed method.

Effects of Urban Landscape Pattern on PM2.5 Pollution--A Beijing Case Study.

PM2.5 refers to particulate matter (PM) in air that is less than 2.5μm in aerodynamic diameter, which has negative effects on air quality and human health. PM2.5 is the main pollutant source in haze occurring in Beijing, and it also has caused many problems in other cities. Previous studies have focused mostly on the relationship between land use and air quality, but less research has specifically explored the effects of urban landscape patterns on PM2.5. This study considered the rapidly growing and heavily polluted Beijing, China. To better understand the impact of urban landscape pattern on PM2.5 pollution, five landscape metrics including PLAND, PD, ED, SHEI, and CONTAG were applied in the study. Further, other data, such as street networks, population density, and elevation considered as factors influencing PM2.5, were obtained through RS and GIS. By means of correlation analysis and stepwise multiple regression, the effects of landscape pattern on PM2.5 concentration was explored. The results showed that (1) at class-level, vegetation and water were significant landscape components in reducing PM2.5 concentration, while cropland played a special role in PM2.5 concentration; (2) landscape configuration (ED and PD) features at class-level had obvious effects on particulate matter; and (3) at the landscape-level, the evenness (SHEI) and fragmentation (CONTAG) of the whole landscape related closely with PM2.5 concentration. Results of this study could expand our understanding of the role of urban landscape pattern on PM2.5 and provide useful information for urban planning.

Fast Multiclass Vehicle Detection on Aerial Images

Detecting vehicles in aerial images provides important information for traffic management and urban planning. Detecting the cars in the images is challenging due to the relatively small size of the target objects and the complex background in man-made areas. It is particularly challenging if the goal is near-real-time detection, i.e., within few seconds, on large images without any additional information, e.g., road database and accurate target size. We present a method that can detect the vehicles on a 21-MPixel original frame image without accurate scale information within seconds on a laptop single threaded. In addition to the bounding box of the vehicles, we extract also orientation and type (car/truck) information. First, we apply a fast binary detector using integral channel features in a soft-cascade structure. In the next step, we apply a multiclass classifier on the output of the binary detector, which gives the orientation and type of the vehicles. We evaluate our method on a challenging data set of original aerial images over Munich and a data set captured from an unmanned aerial vehicle (UAV).

Analysis of the pattern and intensity of urban activities through aggregate cellphone usage

This study applies passive mobile positioning data such as Call Volume, Handover, and Erlang to detect the spatiotemporal distributions of urban activities. We obtained hourly aggregated cellphone data from a dataset of communications in Lisbon, Portugal. Fuzzy c-mean clustering algorithm was applied to the cellphone data to create clusters of locations with similar features in two aspects of activities: the pattern and intensity of urban activities along the hours of a day. In order to validate those clusters as actual predictors of human activity, we compared them with clusters formed using ground truth variables namely presence of people, buildings, points of interest, and bus and taxi movement. To identify the patterns of urban activities, the Erlang data provided a better match, with the ground truth giving 69% of overall accurate predictions. In the case of the intensity of activities, Handover data provided the highest match, with the ground truth yielding 80% of overall accuracy of predictions. Hence, the results demonstrate the potential of passive mobile positioning data in detecting intensity of activities that are superimposed on the different activity patterns, which is a fundamental piece of information for transportation and urban planning.

Mapping the land use history for protection of soils in urban planning: what reliable scales in time and space?

Purpose Mainstreaming land use history into urban maps is of interest for many applications. In this study, it was seen as a way for introducing soil quality information in urban planning. The quality of urban soils is indeed assumed to be driven not only by the current land cover but also by the land use history. The purpose is to investigate this assumption by proposing two mapping processes of the land use history.