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This chapter presents a novel approach to understanding urban form through the quantification of urban sections, moving beyond traditional two-dimensional analyses. By introducing urban sections as a means to express the complex spatial variations within cities, the chapter explores how these sections can be quantified using indicators such as length ratio, area ratio, and open space ratio. The study applies two different transecting methods—parallel and rotational series sections—to four districts in Nanjing, China, providing a comprehensive analysis of urban form. Through a detailed comparison of indicators derived from these methods, the chapter proposes reasonable parameters for transecting and offers insights into the morphological characteristics of urban environments. The findings highlight the potential of urban sections as a powerful tool for urban form control and relevance studies, making this chapter an essential read for those interested in advancing the scientific cognition of urban morphology.
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Abstract
A more comprehensive and in-depth understanding of the urban form has been a long-term interest of urban morphology. Compared to a plan view, urban section helps to understand the three-dimensional shape of a city from a transection. As a linear graph, the section can be quantified with some indicators easily and accurately. However, a single section cannot adequately describe the entire urban form, and a series of sections are needed to construct a representation of it. In this research, we test two different series of sections: parallel series and rotational series. In the former, all sections are distributed in parallel at a certain spacing, while in the latter, all sections are rotated around a center point. Taking four different districts of Nanjing, China, as the cases, two series of sections are applied to implement the quantitative analysis of urban form. The different parameters are also analyzed by comparison to determine reasonable values. The results show that the both series are effective in representing the urban morphological characteristics with reasonable parameters. In addition, the rotational series section method has unique advantages in expressing the urban form in different directions.
3.1 Introduction
A more comprehensive and in-depth understanding of the urban form has been a long-term interest of urban morphology. Scientific cognition of urban form can help summarize the urban patterns and explore the morphological problems (Martin 1972). Quantitative cognition turns the patterns into describable and replicable indicators, which are meaningful for relevance studies and urban form control (Oliveira and Medeiros 2016). The quantification of urban morphology at the micro-level mainly revolves around capacity and geometric attributes, including indicators such as floor area ratio (FAR), building density, open space ratio, and building height (Yoshida and Omae 2005; Pont and Haupt 2007; Steadman 2014; Çalışkan et al. 2022). By combining these indicators, different types of fabrics and characterize form can be represented. However, most of these indicators are calculated based on the plan of urban form, lacking effective expression of the complexity of urban form in three-dimensional space.
Here, the section is a potential answer to this disadvantage (Mantho 2015). Sections are commonly used in architectural drawings to express the complex spatial variations within a building. A similar concept in city is the transect, which expresses environmental change from natural-to-rural-to urban areas by categorizing built environments along a cross section (Welter 2002; Andres 2002). Transect theory has also been used in urban design and has developed into the theory of transect urbanism (Bohl and Plater-Zyberk 2006). However, the transect is an abstract and typological expression of urban form, and cannot detail specific urban form. Combining the characteristics of architectural section and urban transect, urban section focuses directly on specific city block buildings, and helps to understand the buildings’ heights and the spaces between buildings through a polyline (Tong 2019). As a linear graph, the section can be quantified with some indicators easily and accurately. Through a series of continuous vertical urban slices, city texture can be transformed into planar linear information to represent the urban form (Gu et al. 2021). However, in the series of sections, the settings of relevant parameters such as section orientation and density can affect the representation of urban form and the final indicator calculation results.
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In this research, we test two different series of sections, namely, parallel series sections and rotational series sections, and explore the reasonable values of the relevant parameters by analyzing the section indicators obtained from different sectioning methods.
The paper is organized as follows. First, it presents the calculation of quantitative indicators for urban sections and two different transect methods to obtain a series of sections. Then, it takes four districts of Nanjing City as case studies to apply the transecting methods, and calculates corresponding indices. Finally, by comparing those indicators, reasonable transecting parameters are proposed, and the urban form is analyzed.
3.2 Methodology
3.2.1 Calculation of Quantitative Indicators for Urban Sections
The urban section is a derivation of the architectural section. A sectional path is created in a certain direction in an urban area. And the spatial relationship of buildings on the section is observed. The urban section not only visually expresses the height of buildings, but also focuses on the spaces between buildings. In addition to the visual information presented by the section shape, it can be quantified to accurately represent its morphological characteristics.
Figure 3.1 presents an urban section prototype and corresponding dimensions, where L is the length of the whole section, H is the maximum height of the section, l1-ln represent the lengths of every segment of the section, A1-An represent the areas of every building section, w1-wn are the widths of every building section, ws1-wsn are the widths of the open spaces between buildings, and h1-hn are the heights of every building.
Fig. 3.1
An urban section prototype and corresponding dimensions
Based on the prototype, several indices are proposed to represent the morphological characteristics. The length ratio (LR) is the ratio of the sum of l to L, representing the tortuosity of the urban section line. The area ratio (AR) is the ratio of the sum of A to L, which could be regarded as the average buildings volume of the entire section extent, or the FAR. The average height (AH) is the average height of all buildings. The width ratio (WR) is the ratio of the sum of w to L, which can be regarded as the building density. In addition, the open space ratio (OSR) is the ratio of the sum of the width between buildings to L, which could be used to present the open spaces of the section. The formulas for calculating these indicators are as follows:
$$\text{LR}= \sum {l}_{n}/L$$
(3.1)
$$\text{AR}= \sum {A}_{n}/L$$
(3.2)
$$\text{AH}= \sum {h}_{n}/n$$
(3.3)
$$\text{WR}= \sum {w}_{n}/L$$
(3.4)
$$\text{OSR}= \sum {ws}_{n}/L$$
(3.5)
To make OSR more capable of expressing the advantages of open space in terms of environmental performance, we also set a special rule for the calculation. In the study of isolated roughness flow in street canyon, Oke found that when the height-to-width ratio of the street section is <0.33, buildings on both sides do not significantly affect each other’s wind fields, and the wind flow remains relatively smooth without the appearance of large turbulence and vortexes (Oke 1988). Ashihara also found that space with a height-to-width ratio of <0.33 was open and discrete, with a poor sense of enclosure (Ashihara 1984). Therefore, we define that only open spaces with a height-to-width ratios less than 0.33 will have its ws included in the calculation of OSR.
Considering that much of the urban form data is planar, it is not easy to draw the sections and calculate the indicators manually. It is even more time-consuming when series of sections are required. Therefore, we have developed a program based on Processing (https://www.processing.org). By importing building plans with height information and setting the direction and density of the cutting, the program can automatically generate all the sections and calculate all the indicators.
3.2.2 Two Types of Cutting Methods
A section is just a cutting of an object and can only reflect its local features. Even in architectural drawings, multiple sections are required to represent the interior spaces of the building. Due to the complexity of urban form, a single section cannot fully depict its morphological characteristics. To create a comprehensive representation, a series of sections can be generated by cutting the urban area at a certain density. There are two types of cutting methods: parallel series cutting (Gu et al. 2021) and rotational series cutting (Kaya and Mutlu 2017; Tong et al. 2020).
Parallel series cutting involves drawing a series of evenly spaced parallel transect lines across an urban area to create a set of parallel sections (Fig. 3.2). This method is similar to a CT (Computed Tomography) scan, where each section corresponds to a scanned image of a CT. By associating all slices, a relatively complete reconstruction of the 3D object is possible. By adjusting the density of the sections, a more detailed representation of the urban form can be achieved. In China, due to the demand for sunlight, most buildings face south to get the maximum amount of sunlight (Li et al. 2018). Therefore, the parallel transect line is set to be east–west, which runs through the long side of the buildings and presents the degree of curvature of the building contour line.
In the case of a rotational section, a fixed point is selected within a certain urban area, and a series of sections are obtained by rotating transect lines around this fixed point at a set angle (Fig. 3.3). In comparison to parallel series cutting, rotational cutting does not need to consider the direction of the transect line. However, to ensure consistent L-values when calculating the indicators, the study range is circular. Moreover, the transect lines have a distinct ray character, their distribution is dense at the center and sparse at the periphery, and the representation of the morphological characteristics of the city is closely related to the position of the center.
Both cutting methods result in a series of sections, which in turn allow the calculation of the corresponding indicators. Figure 3.4 shows the series of sections for the parallel cutting method and the five indicators for each section. Figure 3.5 shows the series of sections for the rotational cutting method and the five indicators for each section. Despite targeting the same area, there are significant differences in the results obtained by the two methods, both in terms of section images and the quantitative indicators.
Fig. 3.4
The series of sections for the parallel cutting method and the five indicators for each section (Source Created by the authors)
Two cutting methods involve the setting of some parameters. Both methods need to set the section range. In addition, the parallel cutting method needs to determine the density of the transect lines, and the rotational cutting method needs to set the rotational angle of the transect lines.
3.3 Case Study
Nanjing is a representative city in China with an urban fabric of different periods. This study selected four morphologically diverse areas in Nanjing: Xinjiekou, the traditional central business district; Hexi, the new central business district; Chengnan, which retains the traditional historical pattern; and Jiangning, a suburban area with a large number of new modern residences and inadequate public facilities (Fig. 3.6).
Xinjiekou has a high concentration of high-rise buildings, commercial offices, and a high degree of mixed building functions. Hexi is full of large public buildings, with a large building scale, low building density, sparse distribution, wide roads, more open external space, and a higher average building height. As a representative of the old city, Chengnan has a smaller building scale, lower average building height, higher building density, more varied building forms, and high building coverage. Jiangning is located in the suburban area of Nanjing, where the plots are not regular, the buildings are residential, the average height is high, the coverage rate is more balanced, and the plan is more regular. Table 3.1 shows the satellite images and building plans. The form of each districts is distinct, which provides a good research sample for the study of urban sections.
To investigate the best scale at which the series of urban sections could reflect the morphological characteristics of the area, the center points of the four study areas were selected as reference points, and based on these points, square areas with side lengths of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 km were selected as our study areas (Table 3.2).
Table 3.2
Study scopes of the four districts with different side lengths
Image Source Created by the authors
The density of the transect lines also affects the section shape and indicator calculation. In this study, the section spacing is set as the parameter to adjust the section density. We apply 2, 5, 8, 10, 12, 15, and 18 as the values of section spacing. The smaller the spacing, the greater the density of the sections. Parallel cuttings of different densities were performed separately for each scope in each district, yielding seven separate sets of data, each with five indicator data, LR, AR, AH, WR, and OSR. As shown in Table 3.3, taking the 3.0 km range of Xinjiekou as an example, the sections were obtained from seven density cuttings.
Table 3.3
The parallel sections were obtained from seven density cuttings
Study scope
Section spacing 2
Section spacing 5
Section spacing 8
Section spacing 10
Section spacing 12
Section spacing 15
Section spacing 18
Image Source Created by the authors
3.3.2 Rotational Cutting with Different Parameters
Similar to parallel cutting, the size of the section range is the first parameter to be considered. Circles with diameters of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0 km were used as the scope of the study (Table 3.4).
Table 3.4
Study scopes of the four districts with different diameters
Image Source Created by the authors
In rotational cutting, the section angular spacing affects the section density. Values of 5°, 10°, and 15° are used for the section angular spacing. As shown in Table 3.5, taking the 3.0 km range of Xinjiekou as an example, the sections were obtained from three density rotational cuttings.
Table 3.5
Sections and indicators at different angular spacings (image source: created by the authors)
Section angular spacing
Rotational series sections and indicators
5°
10°
15°
To conveniently analyze the variation in the magnitude of the section indicators in each direction, radar plots were selected for data analysis. As shown in the first graph in Fig. 3.7, there is only one value on each section. All data are mirrored center-symmetrically around the center of the circle to obtain the second graph in Fig. 3.7, which makes it easy to observe the values and changes in the direction. In the third graph, the orange circle represents the average value of all data.
Fig. 3.7
Method of drawing the radar plot of indicator values of rotational sections (Source Created by the authors)
For the same area, we take the average of the indicator value obtained under seven different density sections and put them in the same coordinate system for statistics. In the following figures, the horizontal coordinates represent the scale range 0.5–4.0 km, the vertical coordinates represent the size of the indicator value, and the line of the seven sets of data represents the change in each indicator as the range increases.
Taking Xinjiekou as an example, which is shown in Fig. 3.8, LR is distributed between 1.6 and 2.2, AR is distributed between 6 and 12, AH is between 20 and 50 m, WR is between 0.25 and 0.3, and OSR is concentrated between 0.4 and 0.5. From the changing trend, the LR, AR, and AH of Xinjiekou gradually descend, and the AR and AH descend in a consistent trend. The WR rises first, then descends rapidly at 2.5–3.0 km, and then falls back after a basic stabilization at 3.0–3.5 km. The OSR descends rapidly at 0.5–1.0 km, and rises to 4.0 km after falling back to 2.5 km.
Fig. 3.8
The plot of indicator values of parallel sections of Xinjiekou (Source Created by the authors)
There is a certain commonality in the interpretation of the indicator values and trends of the four districts. There is a large positive correlation between the indicators LR, AR, and AH, and the change trends are similar, while there is an opposite change trend between WR and OSR. When the range is less than 2.5 km, the value of each indicator changes considerably, and at 2.5–4.0 km, the value tends to stabilize. This characteristic is more evident in the trends of LR, AR, and AH. In order to better compare the similarity between each district, seven sets of data for each indicator value of the above four districts were averaged at different scales (Fig. 3.9).
Fig. 3.9
Comparison of parallel section indicator values across the four districts (Source Created by the authors)
As Fig. 3.9 illustrates, the values of Xinjiekou are higher than those of the other three districts in LR, AR, and AH, and the OSR values of Xinjiekou are the lowest. The LR and AR values of Chengnan, Hexi, and Jiangning are closer, and the three variables tend to be consistent after 2.0 km. The WR values of Xinjiekou and Chengnan are closer, and the overall OSR values of Jiangning and Chengnan are closer. The AH values of Xinjiekou and Hexi are higher than those of Chengnan and Jiangning, but all four districts tend to be consistent with the increase in the section scope range. From the perspective of change trends in general, Jiangning and Chengnan are closer in change trends, while Xinjiekou and Hexi are more similar.
3.4.2 Evaluation of the Parameters of the Parallel Series Cutting
Both the scope and density of the parallel series cutting affect the indicator values. Reasonable parameter thresholds are key to conducting urban section studies. In this research, we introduce relevant urban planning indicators as reference values. By comparing these section indicator values and the urban planning indicator values of the same scope, we can evaluate the reasonableness of the parameters for parallel series cutting.
The indicators directly linked to specific forms in urban planning are mainly the FAR, building density, and building height. The FAR is the ratio of the total building area to the block area. When the buildings tend to be homogeneous and reach a state of uniform distribution, the series sections are basically the same. If the buildings are horizontally compressed to the two-dimensional state, each floor area is the width of each building, and the land area is equivalent to L in Fig. 3.1. The difference between the AR and FAR is the average floor height, so the AR can be compared with the FAR to judge the urban morphological characteristics reflected by the AR value. In the two-dimensional vertical state, the building density is equal to the ratio of the sum of the widths of the buildings to the range L. The calculation method is the same as that of WR in the section, so we can equate the building density to WR. The average building height in this paper is the ratio of the height of all buildings to the number of buildings in a certain range. The average building height is calculated in the same way as AH, so we can equate it to AH directly. When the urban buildings are in the two-dimensional vertical state, i.e., the same state as the urban building section, we consider the FAR, density, and average building height in the three-dimensional state to be equivalent to the section indicators AR, WR, and AH. The higher the degree of matching of the indicator values, the better the section parameters express the characteristics of the urban form of the area. Even when buildings are non-homogeneous, the average values of the series of sections will converge to the corresponding planning indicators.
Therefore, we can use the above-obtained section indicators AR, WR, and AH in Xinjiekou, Hexi, Chengnan, and Jiangning with different scopes and transect densities, and compare them with the FAR, density, and average height in the same areas for fitting analysis, as shown in Table 3.6.
Table 3.6
Comparison of section indicators and planning indicators in different parameters
Images Source Created by the authors
Graphically, with the increase in transect spacing, AH and WR seem to be closer to the corresponding urban planning indicators and fit better, but it is hard to see the specific degree of data fit from the graph. To better compare the deviation of the section index data with the actual situation at different scales, according to the previous discussion, we compare the sum of the deviation of the section indicators and the urban planning indicators in each area. For a more accurate analysis, we measure the deviation of the section indicators from the urban planning indicators by the degree of deviation.
Since FAR and AR, density and WR, and average height and AH are not at the same scale level or order of magnitude, direct comparisons cannot be made. The deviation values were first standardized, and then the deviation values of AR, WR, and AH values were summed and compared to obtain the smallest sum of deviation values, which best reflected the real urban morphological characteristics.
Figure 3.10 presents the sum of the degrees of deviation of the three indicators AR, WR, and AH for each district at different section densities and scopes. The sum of deviations is relatively close, and all show some idiosyncrasies at a different scope, but do not affect the overall trend. The sum of deviations in Chengnan and Jiangning decreases after rising to the scope of 1.5 km, and the value fluctuation gradually decreases. The overall deviation values are close together in Hexi, with an overall decrease followed by an increase, but do not show significant specificity. The value of Xinjiekou drops sharply after 1.0 km, and fluctuates slightly as the scope becomes larger, with a slightly stronger degree of fluctuation than that of Hexi. The last graph in Fig. 3.10 represents the sum of the deviations of all indicators. On the whole, the sum of deviation is the largest in Chengnan and Jiangning at 1.5 km, and the trend of deviation is very close as the scope becomes larger. The trend lines of Xinjiekou and Hexi are very similar, both continue to fall to 1.5 and 2.0 km, and there is a clear trend of rising and falling at the 2.0–3.0, 2.0–3.5 km ranges.
Fig. 3.10
Deviation of the standardized indicators in the four districts with different cutting densities and scopes (Source Created by the authors)
With the comparison result shown in Fig. 3.10, we believe that scope 2.0–3.5 km best reflects the urban morphological characteristics of each district. When the scope is set to 2.0 km, the sum of the deviations of the four districts is the smallest, and the deviations of each district are also small.
Furthermore, with a scope of 2.0 km, the deviations at different cutting densities are statistically analyzed. Figure 3.11 presents the result. The left graph shows the deviations of the eight densities from 2 to 18 in different districts at a scope of 2.0 km, and the right graph shows the sum of the deviations of all four districts.
Fig. 3.11
Deviation of the standardized indicators with different cutting densities at scope 2.0 km. The left shows the separate statistical chart for each district, and the right shows the statistical chart for the sum of all districts (Source Created by the authors)
As shown in Fig. 3.11, when the cutting density is 2, the sum of the deviation of all districts is the smallest, the deviation of each district is between 1 and 2, and the data distribution is more concentrated. Therefore, the cutting scope is 2 km and the cutting density is 2 (spacing of transect line is 12 m), which are the more reasonable parameter thresholds for parallel series cutting, and the sections obtained better reflect the morphological characteristics of the city.
3.4.3 Analysis of the Rotational Series Sections
Previously, we determined the cutting scope and cutting angular spacing for rotational series cutting. The cutting scopes are from 0.5 to 4.0 km, and the cutting angular spacing is 15°. The indicators at different angular spacings at the same scope are represented in the form of radar plots. Each district obtains five sets of radar maps, namely, LR, AR, AH, WR, and OSR, and each indicator has a total of 8 radar plots under different cutting scopes.
Taking Xinjiekou as an example, Table 3.7 shows some radar plots of the rotational series sections. In the table, A represents the mean value of the corresponding section indicators, and S represents the standard variance. A larger value of S represents greater volatility of the radar plot values.
Table 3.7
Radar plots of indicator values of rotational sections of Xinjiekou
Indicator
1.0 km
2.0 km
3.0 km
4.0 km
LR
AR
AH
WR
OSR
Image Source Created by the authors
Comparing the radar plots of the rotational sections of Xinjiekou in Table 3.7, the differences in the directions of the AR and AH are relatively similar, both change from the specificity presented in the east–west and southwest 60° section directions to the specificity in the north–south direction, and the average values gradually decrease with increasing scope. The WR presents the difference in the north–south direction, and the OSR mainly presents the difference in the southeast 30° section direction. The values of WR gradually increased with increasing scope, and the mean values of OSR did not change much.
3.4.4 Evaluation of the Parameters of the Rotational Series Cutting
As in the case of parallel series cutting, the degree of deviation between the rotational section indicators of each district and the urban planning indicators is used to evaluate the reasonableness of the cutting parameters. Table 3.8 shows the comparison of section indicators and planning indicators in different parameters of rotational cuttings.
Table 3.8
Comparison of section indicators and planning indicators for different parameters of rotational cuttings
Images Source Created by the authors
Similarly, the deviation values were standardized and then summed, and the three indicators were combined to evaluate the fit with the urban planning indicators at each scope. The standardized deviation values of the three indicators in the same scope of each district are summed together, and the result is graphically represented as shown in Fig. 3.12 on the left. The smaller the value is, the better the fit of the data, and the more it reflects the specificity of the morphological characteristics of the city. The deviations in all four districts show an upward trend at the 0.5–1.5 km scope after a rapid decrease in deviation and a more moderate increase at 3.0 km. The deviations of indicators in the range of 1.5–3.0 km are all low. The sums of the deviation of indicators of all districts are shown in Fig. 3.12 on the right. When the scope is set as 2.0 km, the sum of the deviations of the four districts is the smallest, and the deviations of each district are very close. Therefore, we conclude that the most suitable scope for the rotational section is 2.0 km, which is the same as the optimum value taken for the parallel section.
Fig. 3.12
Deviation of the standardized indicators with different cutting scopes. The left shows the separate statistical chart for each district, the right shows the statistical chart for the sum of all districts (Source Created by the authors)
3.5 Application of Reasonable Cutting Parameters and Urban Form Analysis
After obtaining adequate cutting parameters, we performed parallel and rotational cutting for each of the four cases and calculated the indicators for the sections, which are then compared to analyze the differences in their morphological characteristics.
3.5.1 Parallel Series Sections
Through the above study, the adequate parameters for parallel series cutting are a scope of 2.0 km and a density of 2. Figure 3.13 presents the comparative analysis of the indicators in four districts. It can be seen that LR, AR, AH, and WR are the largest in Xinjiekou, which represents the highest building form, complexity, and functional mix in this district. As a new CBD, Hexi has the largest OSR, as well as a larger AR and AH, which is different from the crowdedness of Xinjiekou and pays more attention to spatial quality. The overall building coverage in Chengnan is high, the OSR is low, and the complexity of building functions is high; however, because it is an old city, the AR and AH are the smallest. Jiangning has more residential houses and is an area to be developed, and the public building facilities are insufficient. The indicators in all aspects of Jiangning are close to Chengnan.
Fig. 3.13
Comparative analysis of indicators of parallel series sections in four districts (Source Created by the authors)
The above study indicates that the adequate scope for the rotational series cutting is 2.0 km. Table 3.9 presents the comparative analysis of the indicators in four districts. In a comprehensive view, the radar plots of each district show certain similarities and specificities in some places. The values on the radar plots of the LR indicators of each district in all directions are relatively balanced, all tend to be circular, and do not exhibit obvious directional specificity. The directions showing variability in AR and AH for Xinjiekou, Hexi, and Chengnan are very similar. This indicates that the building capacity size of these three districts in the same direction is closely related to the average building height in that direction, and the building capacity size of Jiangning is closely related to the building coverage in that direction. The AR and AH of Chengnan show variability in the direction of the north–south section, the AR and AH of Hexi show variability in the direction of the southwest and east–west sections, and the AR and AH of Xinjiekou show variability in the direction of the north–south sections. The AR and WR of Jiangning are more balanced, showing variability in the direction of the sections 30° southeast and 75° southwest. The OSR of Chengnan and Jiangning both show directional specificity of values in the southwest section.
Table 3.9
Comparative analysis of indicators of rotational series sections in four districts
Indicator
Xinjiekou
Hexi
Chengnan
Jiangning
LR
AR
AH
WR
OSR
Images Source Created by the authors
3.6 Conclusion
For the study of urban form, the urban section helps to understand the characteristics of building heights and the spaces between buildings compared to the traditional plan view. Moreover, as a two-dimensional polyline, the urban section is easy to use indicators for quantitative analysis. Parallel and rotational series cutting methods further provide different approaches to creating sections, offering more space for imagining the potential value of urban sections.
In the case study of the four districts of Nanjing, it is also clear that the relevant parameters of the cutting method have a direct impact on the results of the sections. Using traditional urban planning indicators as a reference, we compared the results obtained from different cutting parameters with the planning indicators to find the group with the smallest deviation, thus providing a benchmark for setting a reasonable threshold for the parameters. After many comparisons, we finally determined that a cutting scope of 2.0 km was the most reasonable. On this basis, a density of 12 m was adopted for parallel series sections.
Applying reasonable cutting parameters, four districts in Nanjing were analyzed for their respective quantitative indicators. By comparison, we can see that the urban section indicators reflect the different morphological characteristics of these cases well. In particular, the use of radar maps with rotational series sections provides an intuitive visualization of the morphological differences in different directions.
Certainly, despite the advantages of urban sections for the representation of urban form, a single section can only reflect local urban form and cannot express the entire morphological characteristics of the city. The parallel series cutting method can visually show the three-dimensional form of the city, but the results are directly influenced by parameters such as the direction and density of the cut. The rotational series cutting method avoids the interference of the cutting parameters, but the results depend on the choice of the center point and cannot intuitively express the urban form. In contrast, Gu et al. (2021) provided a new idea by using two perpendicular directions to perform parallel series cutting. However, the difference in calculated indicator values between the two directions is too great, and how to interpret the difference remains to be studied.
In this study, although multiple cases and parameters were tested, the scope was limited to square or circle. In practical applications, the shape of the block or neighborhood is not like this, and even irregular. At this point, no matter which series of cutting method is used, the length of each section may be different. Using the average value as the quantitative result of the urban form actually obscures the complexity of the boundary shape. Therefore, the application of cutting methods needs to be approached with caution and careful consideration of the limitations.
While the study of the urban section is still relatively preliminary, its quantitative representation of urban form can assist in a better understanding of urban morphology. The urban section has good potential for applications in urban design and urban construction control.
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