Effects of neighbourhood morphological characteristics on outdoor daylight and insights for sustainable urban design

Figures & data

Figure 1. The map of daylight climate zones (DCZ) and the location of Shenzhen (source: MOHURD 2012; translated and redrawn by authors).

Figure 2. A map of Shenzhen’s annual total solar radiation (source: Shenzhen Climate Centre 2011; translated by authors).

Table 1. Descriptions of examined urban design factors (UDFs) in this research (source: reviewed and summarised by authors)

Factor type	Name of UDF	Abbreviation	2D/3D	Definition and calculation method
Site-level urban design factor	Building coverage ratio	BCR (0–100%)	2D	The ratio of the building area divided by the site area (footprint)
	Floor area ratio	FAR	3D	The ratio of all buildings’ total floor area (gross floor area) to the size of the piece of the land which the buildings were built
	Mean nearest neighbour distance (nearest neighbours from centroids)	MNN (m)	2D	To indicate the development intensity of the given area and building dispersion rate
	Mean building height	MBH (m)	3D	The ratio of total heights of buildings of a given area to the number of the building in this area
	Vertical uniformity (degree of strewn at random)	DOS (m)	3D	To indicate the roughness of a given site. DOS is defined as the difference of height of the highest building and mean building height
	Tree coverage ratio	TCR (0–100%)	2D	Ground tree coverage of the given site (excluding the tree planted in the building roofs)
Point-level urban design factor	Aspect ratio	H/W	3D	The ratio of the mean height of buildings to the width of the street canyon. H/W = (H1+ H2)/2 W
	Sky view factor^a	SVF (0–100%)	3D	The percentage of visible sky. SVF is dimensionless that ranges from 0 to 100%
	Total site factor	TSF (0–100%)	3D	The integrated parameter of site geometry, sun track, solar radiation intensity, and time etc.), ranges from 0 to 100%$\mathrm{T}\mathrm{S}\mathrm{F}=\frac{\left(\mathrm{S}{\mathrm{R}}_{\mathrm{d}\mathrm{i}\mathrm{r}-\mathrm{u}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{a}\mathrm{n}\mathrm{o}\mathrm{p}\mathrm{y}}+\mathrm{S}{\mathrm{R}}_{\mathrm{d}\mathrm{i}\mathrm{f}\mathrm{f}-\mathrm{u}\mathrm{n}\mathrm{d}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{a}\mathrm{n}\mathrm{o}\mathrm{p}\mathrm{y}}\right)}{(\mathrm{S}{\mathrm{R}}_{\mathrm{d}\mathrm{i}\mathrm{r}-\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{a}\mathrm{n}\mathrm{o}\mathrm{p}\mathrm{y}}+\mathrm{S}{\mathrm{R}}_{\mathrm{d}\mathrm{i}\mathrm{f}\mathrm{f}-\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{c}\mathrm{a}\mathrm{n}\mathrm{o}\mathrm{p}\mathrm{y}})}$
	Direct site factor	DSF (0–100%)	3D	Direct site factor (DSF) is the ratio of average daily direct radiation received under canopy to the average daily direct radiation received over the canopy
	Indirect site factor	ISF (0–100%)	3D	The indirect (or diffuse) site factor (ISF) depends on the selected diffuse light distribution model in radiation.
	Canyon axis orientation	CAO	2D	North-South and East-West. Canyon orientation affects the solar admittance and ventilation
	Ground surface albedo^b	GSA (0–1)	2D	GSA (α) means the fraction of the incident sunlight that the ground surface reflects

^aFor the open spaces and the wide street canyons, each of such space’ SVF was defined as the average point-value of multiple points’ SVF, which are located in different areas of that space.

^bThe thermal properties of the ground surface materials were obtained from Code for Thermal Design of Civil Building GB 50,176–2016 (edited by MOHURD 2016), Appendix B, Table B.1 – Calculating parameters of thermophysical properties of common building materials, pp. 77–84.

Figure 3. Locations (up: the red dots) and satellite aerial views (down: yellow circles) of the 11 tested sites in the inner-city Shenzhen (source: up image: Shenzhen Municipal Planning and Natural Research Bureau, Shenzhen Master Plan 2010-2020, reproduced and re-interpreted by authors; down image: Baidu Satellite Map in 2017, and drawn by authors).

Figure 4. Morphological patterns, monitoring points, and representative sky view images of the 11 sites located in inner-city Shenzhen (source: drawn and photographed by authors).

Figure 5. Comparison of the 11 sample sites’ morphological characteristics. Urban density factors: (a) (b) (c); Urban geometry factors: (d) (e) (f) (g); Site factors: (h) (i) (j); Greenery factor: (k); Ground surface material factor: (l) (surveyed and drawn by authors). Notes: 1) Here, TCR means the tree coverage ratios at the ground level, while the trees planted on the roofs were not taken into account for the investigation of performances of daylight and solar radiation at the pedestrian level in this research. 2) Each site’s GSA was weighted average value and calculated based on the ratios of different land cover types (except for the buildings) and ground surface materials within the site, not the average value of the tested spaces in each site.

Table 2. Plot size, morphological characteristics, and building information of the selected 11 sites (surveyed by authors)

Site Code	Site Full Name and Functions	Built Year	Plot size (ha)	No. of buildings (N)	Average plot area per building (m^2)	No. of building per unit of area (N/ha)	Morphological Patterns
A	Hubei Old Village (mixed functions)	1980s	5.07	264	192.2	52	High-density Mid-rise (random layout)
B	Xinlong Fang (residential area)	1980s	0.92	10	918.3	11	Mid-density Mid-rise (strip form)
C	Modern Block (offices + hotels)	2000s	6.22	30	2074.7	5	Low-density Mid- to High-rise (large-scale)
D	Hubei New Village (mixed functions)	1986	5.79	268	216.2	46	High-density Mid-rise (uniform layout)
E	Hubei Central Seafood Square	1990s	1.06	1	10569.1	1	Public Open Space
F	Luohu Cultural Park (urban park)	1986	2.38	14	1698.8	6	Urban Park (highly vegetated)
G	Modern Block (offices + housing)	1990s-2000s	3.31	11	3009.0	3	Low-density High-rise (mixed form)
H	Hubei Ancient Village (mixed functions)	1800s	3.14	90	349.4	29	High-density Low-rise (strip form)
YN	Yunong Village (reconstructed, city complex)	2005–2008	4.92	17	2893.6	4	Large-scale High-rise (courtyard)
CWW	Caiwuwei (reconstructed, city complex)	2006–2011	7.65	9	8496.9	1	Large-scale High-rise (no courtyard)
JB	Jiabei Community (mixed functions)	1990s	15.73	43	3658.8	3	Low-density High-rise (mixed forms)

Table 3. Data collection instruments and analytical tools in this research (made by authors)

Instrumentation	Parameters	Monitoring Range, Accuracy, and Resolution	Record Interval
Nikon Coolpix 4500 with a fisheye lens	Spatial geometry and degree of openness	Nikon FC-E8 fisheye lens (28 mm f/2.0–8.0 lens)	Take the photos (sky view images) at a pedestrian level under the cloudless condition
Canopy structure and solar radiation analysis system WinSCANOPY® 2016a	Sky view factor (SVF), Direct site factor (DSF), Indirect site factor (ISF), and Total site factor (TSF)	To calculate the value of SVF and site factors; to visualize SVF and TSF in each measuring space (5 million pixels)	Calculation through computer
Digital Illuminometer TES-1332A	Horizontal illuminance level (HIL)	Monitor range is 0 lux~200,000 lx, with the accuracy of ±3% rdg ±0.5% f.s. (<10,000 lx) and ±4% rdg ±10 dgt (>10,000 lx), and resolution of 0.1 lx	Record the value of horizontal illuminance level when the readings tend to stabilize

Figure 6. Processes of monitoring the outdoor daylight parameters on site (source: photographed by authors).

Figure 7. Hourly changes of daytime average horizontal illuminance level of the 11 sites.⁷

Figure 8. Peak hours horizontal illuminance level (11:00 am-16:00 pm average) and daytime average illuminance level (D-HIL) of the 11 sites.

Figure 9. Boxplot of daytime horizontal illuminance level of all tested points in the 11 sites.

Figure 10. Hourly changes of site illuminance uniformity (SUo) of the 11 sites during the daytime (the minimum requirement of Uo in Japan is 0.20).

Table 4. Pearson’s correlation between UDFs and examined environmental parameters

	UDF	D-HIL	M-HIL	EA-HIL	LA-HIL	D-SUo
Site-level	BCR	−0.138	−0.177	−0.057	−0.246*	−0.280**
	FAR	0.022	0.120	−0.069	−0.134	−0.397**
	MNN	0.189	0.196	0.117	0.195	−0.055
	MBH	0.075	0.135	0.000	−0.022	−0.321**
	DOS	0.053	0.062	0.029	0.017	−0.296**
	TCR	−0.155	−0.130	−0.143	−0.057	0.002
Point-level	H/W	−0.507***	−0.344**	−0.458***	−0.392***	−0.263*
	SVF	0.858***	0.725***	0.751***	0.657***	0.307**
	DSF	0.616***	0.415***	0.680***	0.512***	0.203
	ISF	0.558***	0.454***	0.542***	0.419***	0.075
	TSF	0.729***	0.516***	0.745***	0.618***	0.385***
	GSA	−0.370**	−0.230*	−0.151	−0.138	0.355***

***. Correlation is significant at the 0.001 level (2-tailed)

**. Correlation is significant at the 0.01 level (2-tailed)

*. Correlation is significant at the 0.05 level (2-tailed)

Table 5. Pearson correlation test among the 12 UDFs (except for the canyon axis orientation CAO)

	BCR	FAR	MNN	MBH	DOS	TCR	H/W	SVF	DSF	ISF	TSF	GSA
BCR	1.000	0.011	−0.609***	−0.144	−0.085	−0.721***	0.366**	−0.239*	−0.142	−0.239*	−0.104	−0.006
FAR		1.000	0.541***	0.929***	0.752***	−0.284**	0.226	0.104	0.084	0.417***	−0.266*	−0.416***
MNN			1.000	0.772***	0.790***	0.470***	−0.294*	0.325**	0.203	0.443***	0.027	−0.309**
MBH				1.000	0.928***	−0.052	0.060	0.176	0.131	0.450***	−0.180	−0.456***
DOS					1.000	0.076	−0.017	0.126	0.087	0.328**	−0.127	−0.399***
TCR						1.000	−0.356**	−0.063	−0.081	−0.097	−0.007	0.152
H/W							1.000	−0.524***	−0.410***	−0.248*	−0.542***	0.059
SVF								1.000	0.670***	0.692***	0.742***	−0.250*
DSF									1.000	0.812***	0.767***	−0.223*
ISF										1.000	0.392***	−0.375***
TSF											1.000	−0.062
GSA												1.000

***. Correlation is significant at the 0.001 level (2-tailed); **. Correlation is significant at the 0.01 level (2-tailed);

*. Correlation is significant at the 0.05 level (2-tailed).

Figure 11. Scatter plots for Site-level UDFs and Point-level UDFs against the daytime average horizontal illuminance level (D-HIL) and the daytime site illuminance uniformity (D-SUo): a) between BCR and site avg. D-HIL, (b) between MNN and site avg. D-HIL, (c) between BCR and D-SUo; (d) between FAR and D-Suo, (e) between SVF and D-HIL; (f) between TSF and D-HIL; (g) between H/W and D-HIL, and (h) between GSA and D-HIL.

Table 6. Summary of the multivariable linear regression models of the examined environmental parameters

Eq.	Multivariate Linear Fitting Equation	Adjust R^2	SE	F	Sig.
(6-a)	D-HIL = – 5910.030 + 1486.443SVF	0.716	10883.014	164.915	<0.001
(6-b)	M-HIL = – 4080.546 + 1869.076SVF	0.464	23199.764	57.379	<0.001
(6-c)	EA-HIL = – 14802.793 + 1211.116SVF + 493.154TSF	0.640	17365.998	58.681	<0.001
(6-d)	LA-HIL = – 1189.224 + 340.25SVF – 23.185MBH	0.596	3249.143	49.008	<0.001
(6-e)	D-SUo = – 0.045 + 0.01SVF + 0.498GSA – 0.00036DOS	0.446	0.136	18.452	<0.05

Table 6a. Regression analysis for average D-HIL of the 11 tested sites

Model	Model a1
Variable	B	SE	Beta
SVF (%)	1486.443***	115.749	0.849
Constant			−5910.030*
R^2			0.720
Adjust R^2			0.716***
F static			164.915
n			84

* P < 0.05; ** P < 0.01; *** P < 0.0001 (2-tailed tests).

Table 6b. Regression analysis for average M-HIL of the 11 tested sites

Model	Model b1
Variable	B	SE	Beta
SVF (%)	1869.076***	246.747	0.688
Constant			−4080.546
R^2			0.473
Adjust R^2			0.464***
F static			57.379
n			84

*P < 0.05; ** P < 0.01; *** P < 0.0001 (2-tailed tests).

Table 6c. Regression analysis for average EA-HIL of the 11 tested sites

Models	Model c1			Model c2
Variables	B	SE	Beta	B	SE	Beta
SVF (%)	1905.582***	198.497	0.768	1211.116***	279.798	0.488
TSF (%)	–	–	–	493.154*	149.248	0.373
Constant			−9833.248*			−14802.793***
R^2			0.590			0.651
Adjust R^2			0.584***			0.640***
F static			92.161			58.681
n			84			84

* P < 0.05; ** P < 0.01; *** P < 0.0001 (2-tailed tests).

Table 6d. Regression analysis for average LA-HIL of the 11 tested sites

Models	Model d1			Model d2
Variables	B	SE	Beta	B	SE	Beta
SVF (%)	334.205***	35.486	0.762	340.250***	34.675	0.776
MBH (m)	–	–	–	−23.185*	10.946	−0.167
Constant			−2203.176**			−1189.224
R^2			0.581			0.609
Adjust R^2			0.574***			0.596***
F static			88.699			49.008
n			84			84

* P < 0.05; ** P < 0.01; *** P < 0.0001 (2-tailed tests).

Table 6e. Regression analysis for D-SUo of the 11 tested sites

Models	Model e1			Model e2			Model e3			Model e4			Model e5
Variables	B	SE	Beta	B	SE	Beta	B	SE	Beta	B	SE	Beta	B	SE	Beta
TSF (%)	0.004***	0.001	0.503	0.004***	0.001	0.506	0.001	0.001	0.140	–	–	–	–	–	–
GSA	–	–	–	0.433**	0.145	0.305	0.583***	0.143	0.410	0.617***	0.139	0.433	0.498***	0.145	0.350
SVF (%)	–	–	–	–	–	–	0.008**	0.002	0.488	0.009***	0.002	0.599	0.010***	0.001	0.604
DOS (m)	–	–	–	–	–	–	–	–	–	–	–	–	−0.00036*	0.000	−0.220
Constant			0.062			−0.037			−0.104*			−0.101*			−0.045
R^2			0.253			0.346			0.438			0.430			0.472
Adjust R^2			0.241***			0.325**			0.411**			0.412			0.446*
F static			21.667			16.640			16.136			23.799			18.452
n			84			84			84			84			84

* P < 0.05; ** P < 0.01; *** P < 0.0001 (2-tailed tests).

Figure 12. Different types of light reflection changed by the ground surfaces (source: Miguet and Groleau 2002, redrawn by authors).

Figure 13. Example of effects of sunlight interception and penetration during the daytime: (a) Site YN-Space NY5; (b) Site JB-Space M12; (c) Site A-Space A2; (d) Site A-Space A3; (e) Site D-Space D1, D2 and D3; (f) Site F-Space F2 (source: photographed by authors).

Figure 14. Mechanisms of outdoor illumination in cities: daylight and solar radiation patterns within urban canyons (source: drawn by authors, based on field observation and literature review of Miguet and Groleau 2002; Kotzen 2003; Tregenza and Wilson 2011; Douglas and James 2015; Giridharan 2016).

Figure 15. Examples of daytime occupant use of outdoor spaces in different types of urban (sub)neighbourhoods: (a) Site A – A1 and A2 (urban village); (b) Site F – F3 (urban park); (c) Site C – C1 (modern urban block); and (d) Site JB – M6 (urban open space) (source: photographed by authors).

Table

Table

Tested Sites	Tested Date	Sunrise Sunset	Background Weather Conditions	Morning (M) (09:00–12:00)			Early Afternoon (EA) (13:00–16:00)			Late Afternoon (LA) (16:00–18:00)
				09:00–10:00	10:00–11:00	11:00–12:00	13:00–14:00	14:00–15:00	15:00–16:00	16:00–17:00	17:00–18:00
A, B	02/10/2017	06:15:33 18:10:37	32 ~ 27°C Weak wind	Overcast	Cloudy	Sunny	Sunny	Sunny	Sunny	Sunny	Sunny
C, D	03/10/2017	06:15:53 18:09:39	33 ~ 26°C Weak wind	Sunny	Cloudy	Cloudy	Sunny	Sunny	Sunny	Sunny	Sunny
E, F	06/10/2017	06:16:54 18:06:49	32 ~ 27°C Weak wind	Partly cloudy	Partly cloudy	Sunny	Sunny	Sunny	Sunny	Sunny	Sunny
G, H	11/10/2017	06:18:42 18:02:16	33 ~ 28°C Weak wind	Cloudy	Cloudy	Sunny	Sunny	Sunny	Sunny	Sunny	Sunny
YN	07/10/2017	06:17:15 18:05:54	33 ~ 27°C Weak wind	Partly cloudy	Partly cloudy	Partly cloudy	Partly cloudy	Sunny	Sunny	Sunny	Sunny
CWW	08/10/2017	06:17:36 18:04:58	32 ~ 27°C Weak wind	Cloudy	Sunny	Sunny	Sunny	Partly cloudy	Partly cloudy	Cloudy	Cloudy
JB	10/10/2017	06:18:19 18:03:10	34 ~ 27°C Weak wind	Cloudy	Partly cloudy	Sunny	Partly cloudy	Partly cloudy	Sunny	Sunny	Cloudy

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