**2. Developing conceptual approaches of urban growth modeling toward 3D**

There are two major conceptual approaches at metropolitan scale for the analysis of spatial and temporal urban patterns, namely, traditional and modern perspectives. These approaches are illustrated in **Figure 1** adapted from Herold [9]. Herold explains that processes produce structures in the traditional top-down view (i.e. from process to structure), whereas two-dimensional spatial arrangements of urban elements such as open and public spaces (i.e. structures) are representative of socioeconomic activities or policies and strategic plans to achieve a certain type of urban pattern (i.e. process) in the modern bottom-up view (i.e. from structure to process). Demand for land, master plans and economic forces are major drivers

*Sustainability in Urban Planning and Design*

ered for future cities.1

urban microclimate.

(i.e. neighborhood, city and metropolitan area).

the levels of urban form analysis into neighborhood, city and metropolitan area together with three variables of density, diversity and spatial structure. These variables for different scales of analysis may carry different meanings. Therefore, firstly, the scale of analysis needs to be determined, and then the meaning of the variable for that scale needs to be found. While plot and urban block are the terms implying local scale, urban form is used for a range of scales from local to regional

Sustainability of urban form is a crucial topic that needs to be carefully consid-

Nations (UN) in setting up the UN Sustainable Development Goals [6], in which the 11th goal aims to "Make cities and human settlements inclusive, safe, resilient and sustainable". According to the UN, city populations are growing with about 54% of the global population,or about 3.9 billion people, now living in cities [6]. One of the issues facing future cities centers around climate change. Land use has been known as one of the major factors affecting the level of heat in urban areas at a large scale. If we think about cities in three dimensions, we see that the height and bulk of buildings are also important factors in local climate phenomena, in particular the urban heat island (UHI) effect defined by the temperature difference between urban areas and their surrounding rural areas. Building height and geometry affect the distribution patterns of shade, wind speed and wind direction. Urban canyon geometry (orientation plus aspect ratio, the ratio of average building height to street width) affects street ventilation and the dispersion of air pollution. In turn, these factors interact with the urban heat islands effect to create a unique

Knowledge of three-dimensional (3D) urban growth including changes in human formed and natural objects requires accurate monitoring systems that are able to identify areas with greater changes that are unsustainable and therefore can be prioritized areas for greater attention for intervention policies and activities. In this way, the monitoring system helps to build a more resilient urban form that should maintain adequate levels of the natural environment in built-up areas.

In addition, urban vegetation cover has positive effects on microclimate since it helps to reduce carbon emissions though absorbing CO2 as well as mitigating other gaseous and particulate air pollution. Additionally, it helps to minimize soil erosion,

Current urban change studies focus on land use change detection occurring in decades or annually at large scales and ignore short-term changes of vegetation within built-up areas. Also, detected urban changes are generally two-dimensional; for example, rarely changes within an area of lawn or area of trees have been noticed. The differential effects of trees and grass areas on microclimate can be easily understood in terms of shading and evapotranspiration. Also in Shanahan et al. [7], the benefits of tree cover in a city in the UK one in Australia, were estimated by 'Nature Relatedness', in which tree cover varied from less than 10% to more than 60%. The Natural Relatedness scale correlates well with attitudes toward nature and distinguishes between those who are enthusiastic about nature and those who are not. The chapter demonstrates the benefits of tree cover including reduced stress and asthma and 'psychological restoration'. 'Nature dose intensity' in the form of trees taller than 2 m was assessed using airborne lidar and NDVI from Landsat 8

This raises a critical question about how vegetation cover changes compared to 3D changes in built form in urban areas. Through exploring fine resolution 3D

<sup>1</sup> In this chapter more or less 'sustainable' refers to the dynamic relationship between vegetation and

retain soil moisture and reduce the generation of dust.

The need of sustainable cities was recognized by the United

**54**

images [8].

built form in the city

and factors that affect urban change over time. Indeed, the question is how a type of pattern for change in urban structures results from these processes. As shown in **Figure 1**, urban metrics are applied to remote sensing data to derive spatial and temporal patterns of urban structure and development in the bottom-up view known as modern perspective. Then the derived structure becomes the subject for analysis and investigation of the underlying processes. In contrast, it can be argued that the processes are the major drivers of the existing patterns of urban form and structure [9] in the traditional perspective.

While two-dimensional information on urban development patterns is typically derived from the modern approaches, they have not been applied to investigate 3D knowledge of urban patterns. This gap is noted in **Figure 1**, and the aim of this research is to fill the gap of vertical urban development pattern analysis by proposing new 3D metrics and employing 3D remote sensing data (i.e. airborne lidar).

The motivation for proposing new 3D compactness metrics in this study is the current lack of appropriate metrics. Two commonly used metrics in urban planning are building coverage ratio (BCR) and floor area ratio (FAR). BCR is defined as the building coverage area divided by the area of the land lot (plot). This metric is also known as the building–to-land ratio (BTL). FAR refers to the ratio of the combined area of building floors to the total area of the land lot. As seen, BCR and FAR are 2D and 3D, respectively. While FAR has been calculated using remote sensing data such as airborne lidar, it suffers from the problem of uncertainty, because FAR is calculated based on assumptions about each floor height. This metric is subject to uncertainty because floor height is definitely higher for a retail land use in a large shopping center than for low-density residential land use (Yu et al. [10]). Also, the threshold of floor height differs from city to city.

Past and current practices in urban form studies focus on themes such as the two-dimensional growth of urban form or horizontal development in space and time [11, 12] as shown by the following:


There are also studies on the effect of urban form on energy consumption for a sustainable city [22].

**57**

*New Metrics for Spatial and Temporal 3D Urban Form Sustainability Assessment Using Time…*

Nowadays the use of 3D building models focuses on visualization, which also have high "potential for supporting the 'smart city' concept" [23]. 3D city models are often managed by using CityGML that is an information model for storing, representing and exchanging of virtual 3D city models. While there are methods in CityGML that demonstrate the 3D changes to buildings [24] in urban areas, there

• Such studies usually only consider cities as places of buildings, whereas cities consist of buildings, infrastructure, trees and other vegetation cover established on terrain with various topographical characteristics across different locations.

• This kind of change detection using existing 3D city models is not appropriate for applications of disaster monitoring, as the 3D models are not representative

Indeed, the as-built city models derived from airborne lidar data are closer to reality than those 3D models created from cadastral layers and building height information which usually ignores detailed height information of the different parts of a building. Also, advanced remote sensing airborne lidar data captured over urban areas is an accurate source of 3D data from which to derive 3D city models. Change detection from time series airborne lidar data is a preferred approach as it does not include the above-mentioned problems. As well, advanced data collection methods such as using remote piloted aerial system (RPAS) can be used for collection of data immediately after rapid changes consequent on disaster events such as floods or earthquakes. There are several algorithms for detection of these changes from time series airborne lidar data. One of the major problems in urban change detection studies of airborne lidar data is that the pixel-based algorithms that are more appropriate for calculation of volumetric changes suffer from either lack of

There are other problems relevant to 3D metrics for assessment of the sustainability of urban form. While there are 3D metrics for comparison of different urban forms or to characterize 3D cities, there is a lack of appropriate metrics for application into the assessment of the sustainability of urban form over time, as defined in the Introduction. Koziatek and Dragicevic (2019) proposed 3D indices for spatial and temporal urban analysis of 3D urban expansion, but one of the major problems of their studies is that they do not use time series 3D remote sensing data for exploration of the real changes of the buildings over time. There is a problem of uncertainty in their 3D models because various sources of building height data are used to create time series 3D city models. For example, the number of floors is one source of building height data, but as discussed before, heights between floors for buildings with different functionalities vary; therefore, estimation of building heights for an urban

area with various building uses based on number of floors is very inaccurate.

All in all, a thorough review of the urban form literature and metrics [25] shows that even though urban form analysis has a long history in the literature, there are deficiencies in metrics development including (a) a lack of 3D studies using remote sensing for sustainability assessment of urban form and (b) a lack of studies on 3D

of real situations and as well they require a lot of time to produce.

**3. Problems of 3D urban development studies in literature**

are some problems with these methods that are listed below:

height change information or a high level of noise.

urban growth assessment for sustainability.

• Studying time series 3D models is a very time-consuming task.

*DOI: http://dx.doi.org/10.5772/intechopen.89617*

*New Metrics for Spatial and Temporal 3D Urban Form Sustainability Assessment Using Time… DOI: http://dx.doi.org/10.5772/intechopen.89617*
