In e na ional Jou nal o
En i onmen al Resea ch
and Public Heal h
Re iew
Sma and Regene a i e U ban G ow h: A Li e a u e
Ne wo k Analysis
Angeliki Peponi 1,2,* and Paulo Mo gado 2
1Facul y o En i onmen al Sciences, Czech Uni e si y o Li e Sciences P ague, Kamýcká129, 16500
P aha—Suchdol, Czech Republic
2Ins i u e o Geog aphy and Spa ial Planning, Cen e o Geog aphical S udies, Uni e sidade de Lisboa,
Rua B anca Edmée Ma ques, 1600-276 Lisboa, Po ugal; [email p o ec ed]
*Co espondence: [email p o ec ed]
Recei ed: 18 Feb ua y 2020; Accep ed: 30 Ma ch 2020; Published: 3 Ap il 2020


Abs ac :
“Sma ci y”, “sus ainable ci y”, “ubiqui ous ci y”, “sma sus ainable ci y”, “eco-ci y”,
“ egene a i e ci y” a e uzzy concep s; hey a e es ablished o mi iga e he nega i e impac on u ban
g ow h while achie ing economic, social, and en i onmen al sus ainabili y. This s udy p esen s he
esul o he li e a u e ne wo k analysis explo ing he s a e o he a in he concep s o sma and
egene a i e u ban g ow h unde u ban me abolism amewo k. Hea -maps o impac ci a ions,
cu ing-edge esea ch on he opic, ip- op ideas, concep s, and heo ies a e highligh ed and e ealed
h ough VOS iewe bibliome ics based on a selec ion o 1686 documen s acqui ed om Web o
Science, o a imespan be ween 2010 and 2019. This s udy discloses ha u ban g ow h is a complex
phenomenon ha co e s social, economic, and en i onmen al aspec s, and he o e laps be ween hem,
leading o a di e se ange o concep s on u ban de elopmen . In ega ds o ou concep s o in e es ,
sma , and egene a i e u ban g ow h, we see ha he e is an absence o concep ual con igui y since
bo h concep s ha e been app oached on an indi idual basis. This ac un eils he need o adop a
mo e holis ic and in e disciplina y app oach o u ban planning and design, in eg a ing hese concep s
o imp o e he quali y o li e and public heal h in u ban a eas.
Keywo ds:
bibliome ic ne wo k; dis ance maps; sma and egene a i e u ban g ow h; u ban
ecology; u ban me abolism
1. In oduc ion
Humankind al e s he ea h
´
s na u al p ocesses and shapes he landscapes causing al e a ions in
global scale phenomena such as land use/land co e change, economy, ene gy, anspo , popula ion,
and u baniza ion, among o he s [
1
]. Globally, ci ies expand, and hei popula ion is g owing; one in
i e people on ea h li es in a ci y wi h a popula ion o mo e han one million, and six y pe cen o
he global popula ion is p ojec ed o li e in u ban se lemen s by he yea 2030 [
2
]. A he Eu opean
le el, we no ice wo ex emes; a ound hund ed six y i e million ci izens li e in dynamically g owing
ci ies mainly due o mig a ion, and a ound wen y i e million ci izens li e in “dynamically sh inking”
ci ies [
3
]. App oxima ely o y pe cen o Eu opean ci ies wi h a popula ion o mo e han wo
hund ed housand a e wi nessing u ban sh inkage om economic and demog aphic pe spec i es [
4
].
U ban sh inkage is caused mainly due o changes in economic demog aphic and poli ical sys ems
as well as en i onmen al haza ds, and i leads o “unde -u iliza ion, acancy, demoli ion, eme ging
b own ield si es, and de-densi ica ion o spaces” [
3
]. The analysis o he dynamics and he spa ial
con igu a ion o he ends o u ban g ow h consis s o an essen ial opic in cu en u ban s udies [5].
U ban g ow h has a double meaning; on one hand, i signi ies he cons an ise o u ban popula ion
(u baniza ion) and, on he o he hand, he expansion o u ban li es yle and in as uc u e wi hin he
In . J. En i on. Res. Public Heal h 2020,17, 2463; doi:10.3390/ije ph17072463 www.mdpi.com/jou nal/ije ph
In . J. En i on. Res. Public Heal h 2020,17, 2463 2 o 28
se lemen sys em [
6
,
7
]. U ban g ow h o e s a a ie y o oppo uni ies (economic, social, poli ical
g ow h), bu i has a nega i e impac as well. U ban sp awl is he ype o u ban g ow h ha ing
a nega i e meaning [
5
,
8
]. Despi e he dialogue abou he de ini ion o u ban sp awl, i ep esen s
o e all a was e ul ype o u baniza ion. I is ela ed o an uncon olled expansion o u ban a eas,
sca e ed se lemen a eas (how dense o sca e ed a e he buildings and pa ches o buil -up a eas wi hin
he landscape), and low-densi y de elopmen (high a ea o land pe pe son) [
9
–
11
]. U ban sp awl
has signi ican nega i e impac s ega ding land use/land co e change and ene gy e iciency, u ban
economy, social s uc u e, physical en i onmen , public heal h, as well as he o m and spa ial
a angemen o u ban de elopmen [12–14].
Al hough he e is a g owing body o empi ical s udies ha analyses u ban g ow h and e eals i s
impac s, less a en ion has been de o ed o s udies ha e iew he e olu ion o a ious concep s on
sus ainable u ban de elopmen . This pape seeks o explo e he e olu ion o he eme ging concep s on
sus ainable u ban de elopmen (sma ci y, sus ainabili y, egene a i e ci y, and u ban me abolism)
h ough a no el ne wo k analysis o he exis ing li e a u e, using VOS iewe so wa e.
Ini ially, we a emp o disclose he main esea ch ends ound in he li e a u e unde e iew.
Then, we de ec he key schola ly sou ces conside ing i s ly, he numbe o hei ci a ions, and secondly,
hei o e all concep ual ele ance o he opic unde e iew. Looking a he way ha hese key schola ly
sou ces a e connec ed, we e eal he sub- esea ch ends. The nex s eps a e o analyze he key concep s
and heo ies coming om hese key schola ly sou ces and ind hei o igins and connec ions. The las
s ep o he li e a u e ne wo k analysis is o de ec he mos in luen ial au ho s and see how hey a e
ela ed o each o he .
VOS mapping and clus e ing echniques a e bo h p omising and use ul. They ha e been applied
o conduc bibliome ic analysis in a ious ields o s udies o ins ance co-occu ence e m analysis in
psychology [
15
], bibliog aphic analysis o he concep sa e y cul u e [
16
] o he Jou nal o In ec ion and
Public Heal h [
17
], o he mal com o and building con ol esea ch [
18
] and a bibliome ic analysis
on connec ion be ween u ban go e nance, planning, design and de elopmen [
19
] among o he s.
Thus, we adop ed he so wa e and adap ed he ne wo k analysis algo i hms o decode he deg ee o
connec i i y be ween sma and egene a i e u ban g ow h concep s.
The emainde o his s udy is o ganized as ollows. The Sec ion 2desc ibes he me hodology
applied o conduc he li e a u e ne wo k analysis. Ini ially, Sec ion 2.1 p o ides in o ma ion ega ding
he da a acquisi ion; Sec ion 2.2 p esen s he heo e ical backg ound and he echnical se ings o
he cons uc ion o he desi e bibliog aphic ne wo ks. In Sec ion 3, he key indings o he li e a u e
ne wo k analysis a e accompanied by maps and ables. The Sec ion 4discusses he me hodology,
esul s, and limi a ions o he li e a u e ne wo k analysis e iew, and Sec ion 5, he o e all con ibu ion
o his pape o he ield o u ban and en i onmen al planning.
2. Re iew Me hod
A me hodology comp ises a se o applied p ocedu es and echniques, un eiling in o ma ion
ega ding a speci ic opic o esea ch subjec , o p o ide o e all scien i ic c edibili y o he s udy.
Simila ly, he li e a u e e iew should ha e a speci ic and ailo ed me hodology, ins ead o being
opaque o e en andomly and uns uc u ed made as in mos o he pape s. Conside ing his, he
complexi y o he opic unde s udy, and i s socie al signi icance, he e is a need o a mul idisciplina y
sys ema ic li e a u e ne wo k analysis able o p o ide scien i ic e idence upon he concep ual e olu ion
o sus ainable u ban g ow h.
He e, we ha e conduc ed a li e a u e ne wo k analysis using Web o Science (WOS) as he main
bibliog aphic da a sou ce, VOS iewe so wa e o he bibliome ic ne wo k analysis and isualiza ion.
Docea so wa e was used o o ganize and manage he key indings o he li e a u e, and Mendeley
so wa e was used o gene a e he e e ences and ci a ions o scien i ically suppo he idea o sma
and egene a i e edesign o u ban a eas (Figu e 1).
In . J. En i on. Res. Public Heal h 2020,17, 2463 3 o 28
Figu e 1. Flowcha o he de eloped me hodology.
2.1. Da a Acquisi ion
To acqui e he ele an li e a u e, he Web o Science Co e Collec ion da abase was selec ed,
applying an ad anced sea ch il e by using ield ags and Booleans ope a o s as in he ollowing
exp essions; (TI=(sma * AND u ban) OR TI=(sus ainable AND u ban) OR TI=( egene a * AND
u ban) OR TI=(me abolism) AND TS=(u ban AND sp awl)), (TI=(u ban AND me abolism)), whe e
TI e e s o he i le o he documen and TS o he opic. We used imespan be ween 2010 and 2019,
English language, A icle ype o documen o he sea ch and Science Ci a ion Index Expanded
In . J. En i on. Res. Public Heal h 2020,17, 2463 4 o 28
(SCI-EXPANDED), Social Sciences Ci a ion Index (SSCI), A s & Humani ies Ci a ion Index (A&HCI)
Eme ging Sou ces Ci a ion Index (ESCI), Cu en Chemical Reac ions (CCR-EXPANDED), Index
Chemicus (IC) indexes.
These wo sea ches esul ed ini ially in 1686 ela ed a icles in o al. We educed he amoun
o li e a u e o 1091 selec ing speci ic WOS ca ego ies (En i onmen al Sciences OR En i onmen al
S udies OR U ban S udies OR G een Sus ainable Science Technology OR Regional U ban Planning OR
Geog aphy OR Ecology OR De elopmen S udies OR Biodi e si y Conse a ion). F om his sea ch
se , we c ea ed a ma ked lis selec ing inally 243 a icles conside ing hei ele ance o he opic
and he imes ci ed by eading hei i le, abs ac and keywo ds. These 243 eco ds we e sa ed in
Tab-delimi ed (Win) o ma conside ing hei ull eco ds and ci ed e e ences.
2.2. Bibliome ic Analysis
To cons uc and analyze ou bibliome ic ne wo k o he 243 a icles, we used VOS iewe so wa e.
VOS mapping echnique is applied o c ea e dis ance maps. In dis ance maps, he dis ance be ween wo
i ems o he ne wo k shows he s eng h o hei ela edness; sho e dis ance means highe ela edness.
This me hod comes as an al e na i e o he mul idimensional scaling echnique adi ionally used o
he isualiza ion o hese ypes o maps [
20
–
22
]. The VOS mapping echnique consis s o h ee pa s; a)
he no maliza ion, b) he mapping, and c) he clus e ing o he ne wo k nodes. In he i s pa , he
associa ion s eng h no maliza ion is pe o med by de aul , no malizing he s eng h/weigh o he
links be ween he i ems o he nodes. The second pa is he wo-dimensional mapping o he nodes o
he bibliome ic ne wo k placing he nodes wi h s ong ela ion close o each o he and he nodes wi h
weak ela ion in longe dis ance o each o he . In he hi d pa , he clus e ing echnique is applied,
which assigns each node o he ne wo k o clus e s conside ing hei ela edness. Mo e in o ma ion
ega ding he exp essions applied om he VOS mapping echnique can be ound in [23–25].
Depending on he ype o analysis we wan o conduc , he i ems o ou in e es can be connec ed
by co-au ho ship, co-occu ence, ci a ion, bibliog aphic coupling, o co-ci a ion links calcula ed in one
o wo ways. The ull coun ing e sus he ac ional coun ing me hod is used o calcula e bibliog aphic
coupling, co-ci a ion, o co-au ho ship links and he bina y e sus he ull coun ing me hod is used o
calcula e co-occu ence links in ne wo ks/maps c ea ed based on ex da a.
Ini ially, we c ea ed a co-occu ence map based on ex da a o see which keywo ds/ e ms a e
ela ed o each o he in ou bibliog aphic da a se , e ealing he esea ch ends in ou da a se .
The e ms we e ex ac ed om bo h he i le and abs ac ields o he documen s. Fo he cons uc ion
o his map/ne wo k, we used bina y coun ing me hod ins ead o ull coun ing (Table 1, Figu e 2).
In his way, he co-occu ence links be ween he keywo ds a e based on he numbe o documen s
ha hey occu oge he a leas once. Looking a Table 1, we see he numbe o occu ences o
h ee keywo ds in i e documen s. Figu e 3, demons a es he numbe o occu ences (No Oc.)
and he s eng h o he links (l. s.) be ween he keywo ds using bina y and ull coun ing me hod.
Applying he ull coun ing me hod signi ies ha all occu ences o a e m in all documen s a e coun ed.
On he con a y, using bina y coun ing me hod, he numbe o occu ences o a e m is no aken
in o conside a ion; only he p esence o he absence o a e m in a documen coun s. De ining a
minimum numbe o occu ences o a e m equaling en, om 6640 e ms 130 mee he h eshold,
and 57 we e selec ed as he mos ele an e ms based on ou in e p e a ion and hei ele ance sco e.
Te ms wi h highe ele ance sco es end o ep esen speci ic concep s unde s udy, while e ms wi h
lowe ele ance sco e appea o ep esen mo e gene al opics. The ne wo k was no malized wi h he
associa ion s eng h me hod and clus e ed wi h esolu ion pa ame e
γ
equals one and he minimum
clus e size equals i e. The co-occu ence links we e weigh ed conside ing he occu ence o he e ms.
The a e age o ci a ions was used as he sco e a ibu e.
In . J. En i on. Res. Public Heal h 2020,17, 2463 5 o 28
Table 1. Numbe o occu ences o keywo ds ( K1-3) in documen s (D1-5).
Documen s
Keywo ds/Te ms D1 D2 D3 D4 D5
K1 12345
K2 12312
K3 1 1 2
Figu e 2.
Co-occu ence ne wo k o keywo ds, (
a
) bina y coun ing me hod, (
b
) ull coun ing me hod.
Then, we cons uc ed a bibliog aphic coupling ne wo k o documen s in ending o see which
a e mo e ela ed o each o he and mo e ci ed. In his map, he ela edness o he documen s is
based on he deg ee ha hey ci e he same documen . Conside ing ha all he documen s o ou
bibliome ic ne wo k a e ela ed o he main opic, we used he ull coun ing me hod o highligh
he in luence o high ci ed documen s o he ne wo k. F om he o al 243 documen s, he 228 we e
connec ed. We mapped and isualized he ne wo k in o six clus e s using associa ion s eng h as a
no maliza ion me hod wi h esolu ion pa ame e equaling one and minimum clus e size equaling
i e. The bibliog aphic coupling links we e weigh ed using he o al link s eng h, and he numbe o
ci a ions was used as he sco e a ibu e.
A e wa ds, we cons uc ed he bibliog aphic coupling ne wo k o au ho s using he ac ional
coun ing me hod o examine which au ho s sha e a common ield o s udies. Gi ing he minimum
numbe wo o documen s pe au ho , o he 748 au ho s, only 49 mee his h eshold. In his ne wo k,
he ela edness o he au ho s is based on he deg ee ha hey ci e he same documen . In his way, he
bibliog aphic coupling links be ween he au ho s a e based on he numbe o documen s ha hey
commonly ci e, no including he o al numbe o au ho s o each o he same documen s ha hey
ci e. Fo example, i an au ho A2 ci es he same documen D1 wi h he au ho s A1 and A3, he links
be ween he au ho A2 and A1 and A2 and A3 will ha e s eng h o 1 /2=0.5, and a he same ime i
he au ho s A1 and A3 ha e ci ed ano he documen D2, he s eng h o he link be ween A1 and A3
will be 1.5 (1/2=0.5 o he D1, plus 1 o he D2) (Figu e 3). We mapped he ne wo k in o ou clus e s
using associa ion s eng h as a no maliza ion me hod. The minimum clus e size was equal o i e. We
ga e he o al link s eng h he same sco e as he weigh and he a e age o ci a ions as he a ibu e o
he i ems.
Figu e 3.
Bibliog aphic coupling ne wo k o au ho s, (
a
) ac ional coun ing me hod, (
b
) ull
coun ing me hod.

In . J. En i on. Res. Public Heal h 2020,17, 2463 6 o 28
The ea e , we in ended o see he ela edness o he ci ed e e ences based on he deg ee ha hey
ha e been ci ed oge he by ano he documen . Fo his ype o analysis, we cons uc ed a co-ci a ion
map o ci ed e e ences using he ac ional coun ing me hod o a oid he in luence o documen s wi h
a long lis o e e ences, as men ioned p e iously. Gi ing a minimum numbe o ci a ions o a ci ed
e e ence equals o i e om 13133 ci ed e e ences 117 mee his h eshold.
3. Resul s
The i s map p oduced p esen s a bibliog aphic ne wo k o 57 nodes/keywo ds connec ed wi h
co-occu ence links and g ouped in o h ee clus e s (Figu e 4a, Table 2). This i s pa o his analysis
shows he keywo ds ha appea oge he and hei equency in he da a se . Thei p oximi y o
ano he e eals he ela edness o each pai o e ms. The colo o each node indica es he clus e
in which i belongs. These keywo ds clus e s can be in e p e ed as he esea ch ends o he opic
unde e iew.
Looking a he links be ween he keywo ds we iden i y ha he op i e pai s o keywo ds wi h
he g ea es co-occu ence a e ci y and p ocess wi h link s eng h equaling o 44, ci y and sys em wi h
link s eng h o 43, ci y and s a egy wi h link s eng h o 30, ci y and sma ci y wi h link s eng h o
28, ci y and managemen wi h s eng h o 26. Ou gene al unde s anding om hese links is ha he
mos connec ed/ ela ed pa o he li e a u e ea s ci ies as sys ems, and unde sys em analysis he
li e a u e s udies he associa ed p ocesses seeking o s a egies o ensu e a sma and mo e e icien
u ban managemen .
Figu e 4. Con .
In . J. En i on. Res. Public Heal h 2020,17, 2463 7 o 28
Figu e 4.
(
a
). Map o co-occu ence analysis based on keywo ds. (
b
). Map o co-occu ence analysis
based on keywo ds indica ing he a e age o ci a ion.
Table 2. Numbe o co-occu ences o he selec ed keywo ds pe clus e .
CLUSTER 1 (23 I ems) CLUSTER 2 (19 I ems) CLUSTER 3 (15 I ems)
Keywo ds No.
Occu ences Keywo ds No.
Occu ences Keywo ds No.
Occu ences
Challenge 32 Assessmen 27 Bene i 16
Ci y 143 Clima e change 14 Ci izen 17
Cul u e 12 E ec 32 In o ma ion 25
Go e nance 22 Ene gy 30 In as uc u e 30
Knowledge 19 En i onmen 38 In eg a ion 18
Oppo uni y 20 Flow 30 In e en ion 18
Policy 50 F amewo k 48 Li e 19
Popula ion 18 Impac 39 Managemen 53
P oblem 24 Model 47 Planning 35
P ocess 72 Region 21 Quali y 25
Regene a ion 27 Resou ce 35 Scale 36
S akeholde 19 Sys em 71 Se ice 36
S a egy 50 T anspo a ion 16 Sma ci y 38
Sus ainabili y 49 U ban a ea 34 Solu ion 33
Sus ainable ci y 15 U ban me abolism 36 Technology 32
Sus ainable
de elopmen 23 U ban planning 31
Sus ainable u ban
de elopmen 22 U baniza ion 15
T ans o ma ion 21 Was e 15
U ban de elopmen 27 Wa e 17
U ban en i onmen 14
U ban policy 14
U ban egene a ion 52
U ban sus ainabili y 17
In . J. En i on. Res. Public Heal h 2020,17, 2463 8 o 28
In Table 2, we can see all he keywo ds pe clus e and how many imes hey appea in he da a
se (numbe o occu ences). In he i s clus e ( ed colo ), which con ains 23 keywo ds, he op i e
keywo ds wi h he g ea es numbe o occu ences a e ci y which appea s 143 imes; u ban egene a ion
52 imes; policy 51; s a egy 50 imes; and sus ainabili y 49 imes. The second clus e (g een colo ),
which con ains 19 keywo ds, deno es a mo e enginee ing app oach as he i e e ms wi h he highe
occu ence, a e sys em 71 imes; amewo k 48 imes; model 47 imes; impac 39 imes; and en i onmen
38 imes. The hi d clus e (blue colo ) o 15 keywo ds p esen s mixed e ms om di e en scien i ic
ields since he op i e e ms a e managemen 53 imes; sma ci y 38 imes; scale and se ice 36 imes
each; and planning 35 imes.
Figu e 4b and Table 3p esen he esul s o he second pa o his analysis. We can see he
co-occu ence ne wo k o keywo ds weigh ed by he numbe o occu ences o each keywo d and
colo ed conside ing he a e age numbe o ci a ions o he documen s ha hese keywo ds ha e.
Looking a Table 3, we see he exac numbe o a e age ci a ions ha co esponds indi ec ly o each
keywo d pe clus e . In he i s clus e , he i e i s keywo ds wi h he g ea es numbe o a e age
ci a ions a e knowledge (100.11), sus ainable de elopmen (54.70), p oblem (54.46), popula ion (50.44), and
go e nance (50.05). In he second clus e , he keywo ds amewo k (50.58), model (48.45), sys em (45.38),
anspo a ion (44.88), and wa e (41.71) a e he i e keywo ds ha occu ed in documen s wi h g ea es
a e age ci a ions. In he hi d clus e , hese keywo ds a e sma ci y (91.68), ci izen (89.65), echnology
(88.41), se ice (74.25) and quali y (64.76).
Table 3. A e age ci a ions o he selec ed keywo ds pe clus e s in co-occu ence analysis.
CLUSTER 1 (23 I ems) CLUSTER 2 (19 I ems) CLUSTER 3 (15 I ems)
Keywo ds A g.
Ci a ions Keywo ds A g.
Ci a ions Keywo ds A g.
Ci a ions
Challenge 44.22 Assessmen 32.37 Bene i 26.88
Ci y 46.08 Clima e change 39.07 Ci izen 89.65
Cul u e 26.17 E ec 35.66 In o ma ion 57.72
Go e nance 50.05 Ene gy 40.57 In as uc u e 54.53
Knowledge 100.11 En i onmen 39.16 In eg a ion 31.89
Oppo uni y 48.35 Flow 43.23 In e en ion 15.78
Policy 31.31 F amewo k 50.58 Li e 45.42
Popula ion 50.44 Impac 37.10 Managemen 46.09
P oblem 54.46 Model 48.45 Planning 43.77
P ocess 38.00 Region 34.24 Quali y 64.76
Regene a ion 21.15 Resou ce 23.36 Scale 39.42
S akeholde 42.84 Sys em 45.38 Se ice 74.25
S a egy 26.54 T anspo a ion 44.88 Sma ci y 91.68
Sus ainabili y 40.37 U ban a ea 25.09 Solu ion 59.06
Sus ainable ci y 32.40 U ban me abolism 34.92 Technology 88.41
Sus ainable
de elopmen 54.70 U ban planning 33.03
Sus ainable u ban
de elopmen 48.77 U baniza ion 30.13
T ans o ma ion 25.81 Was e 31.93
U ban de elopmen 37.44 Wa e 41.71
U ban en i onmen 72.71
U ban policy 46.79
U ban egene a ion 15.17
U ban sus ainabili y 19.76
In . J. En i on. Res. Public Heal h 2020,17, 2463 9 o 28
Based on his analysis and looking a he numbe o occu ence and a e age ci a ions, we
unde s and ha he li e a u e is di ided in o h ee main esea ch ends (clus e s) o u ban g ow h.
The i s esea ch end ies o unde s and he u ban p ocesses and o apply his knowledge in o de
o ackle ela ed u ban challenges and p oblems. This pa o he li e a u e is seeking policies and
s a egies ha suppo sus ainable u ban de elopmen , o e ing oppo uni ies o u ban egene a ion
in ol ing di e en s akeholde s. The second esea ch end s udies u ban sys ems, on a egional scale
using an u ban me abolism amewo k o ackle he nega i e en i onmen al impac s o hese u ban
sys ems. In his way, we model he consump ion o esou ces, he lows o ene gy and ma e ial wi hin
u ban sys ems (i.e., wa e , anspo a ion), and he esul ing ou comes o o he sys ems in he o m o
pollu ion, was e o expo p oduc . The hi d esea ch end e e s, o he in eg a ion o he concep
“sma ci y” in u ban planning and managemen a di e en scales o analysis. Sma ci y concep
bene i s he ci izens by inc easing he o e all quali y o li e o e ing solu ions, using echnological
in as uc u es o ha e access o se ices and in o ma ion.
Figu e 5a,b p esen he bibliog aphic coupling ne wo k o he documen s, ou second analysis.
As shown in Figu e 5a, he ne wo k o 228 nodes ep esen s he connec ed documen s o ou da a
se unde his analysis, and i is g ouped in o six clus e s. The size o he labels o he documen s
ep esen ed by ci cles a ies depending on he numbe o ci a ions e e ing o he documen s (weigh )
(Table A1, and Table A3). The op i e ci ed documen s in he i s clus e o 60 i ems ( ed colo )
a e Dempsey e al. (2011) 275 imes ci ed, While e al. (2010) 172 imes ci ed, Gonz
á
lez e al. (2013)
166 imes ci ed, Cu hill (2010) 91 imes ci ed, and Degen & Ga cia (2012) 79 imes ci ed. In he second
clus e o 47 i ems (g een colo ), he op i e documen s wi h mo e ci a ions a e Ne ens e al. (2013)
wi h 191 ci a ions, McCo mick e al. (2013) wi h 144 ci a ions, Ba bosa e al. (2012) wi h 135 ci a ions,
Ma low e al. (2013) wi h 126 ci a ions, and Zhao (2010) wi h 121 ci a ions. Fo he clus e h ee (blue
colo ) o 40 i ems Kennedy e al. (2011) 258 imes ci ed, Chen & Chen (2019) 127 imes ci ed, Pince l e al.
(2012) 98 imes ci ed, Ba les 2010) 86 imes ci ed and Pea son e al. (2010) 74 imes ci ed a e he op
highly ci ed documen s. The mos ci ed documen s o he ou h clus e o 40 i ems (yellow colo )
a e Zanella e al. (2014) wi h 1065 ci a ions, Ca agliu e al. (2011) wi h 576 ci a ions, Ba y e al. (2012)
wi h 372 ci a ions, Albino e al. (2015) wi h 260 ci a ions and Lomba di e al. (2012) wi h 158 ci a ions.
Fo he i h clus e (pu ple colo ) o 31 i ems he op i e ci ed documen s a e Haapio (2012) 88 imes
ci ed, Yigi canla & Lee (2014) and Jansson (2013) wi h 60 imes ci ed each, Zi i e al. (2015) wi h
58 imes ci ed and Pili e al. (2017) wi h 51 imes ci ed. Fo he six h clus e o 10 i ems (ligh blue colo ),
Haghshenas & Vazi i (2012) wi h 80 ci a ions, Moo e e al. (2013) wi h 56 ci a ions, Pojani & S ead
(2015) wi h 40 ci a ions, Liu (2012) wi h 30 ci a ions, and New on & Glackin (2014) wi h 19 ci a ions a e
he op i e ci ed documen s. The esul s o his analysis show he schola ly sou ces wi h a highe
impac in he gene al ield o u ban and en i onmen al planning. These sou ces cons i u e publica ions
wi h a g ea e numbe o ci a ions.
In . J. En i on. Res. Public Heal h 2020,17, 2463 16 o 28
wi h he g ea es numbe o a e age ci a ions, in he hi d clus e , hese au ho s a e Pince l S ephanie
(51.67), Ch usoulakis Nek a ios (50.00), Lopes My iam (50.00), Rosado Leona do (33.00), and Spano Dona ella
(31.50), and in he ou clus e he au ho s Moglia Mangus (68.50), New on Pe e (15.00), Da oudi Simin
(7.00), Newman Pe e (15.00), and Thomson Giles (6.33).
In ou las analysis, we cons uc ed he co-ci a ion map o he 117 connec ed ci ed e e ences o
ou da a se , g ouped in ou clus e s (Figu e 7). On his map, we can iden i y he connec ions-links o
he ci ed e e ences ha ha e been ci ed join ly by ano he documen , which allow us o in e abou
he ela i eness impo ance o he documen , i.e., he mo e ci ed, he highe he impo ance o he
documen . In his analysis he s eng h o he links (weigh s) ep esen s he numbe o ci a ions made
o he ci ed e e ence o each node. In Table 6, we can see he op i e ci ed e e ences pe clus e , hei
links wi h o he ci ed e e ences o ou da a se , and hei numbe o ci a ions. Knowing he mos
in luen ial ci ed e e ences o he documen s unde e iew pe in ome ic clus e , we can de ec which
au ho s ha e been in luenced by whom and how speci ic concep s ha e been o med and e ol ed o e
he yea s. We can also go back o s udy he o iginal ideas and d aw a concep e olu ion imeline.
Figu e 7. Map o co-ci a ion analysis based on ci ed e e ences.
Table 6. Impo an ci ed e e ences unde co-ci a ion links pe in ome ic clus e .
No.
Ci .
No.
Links Impo an Ci ed Re e ences
CLUSTER 1
(43 I ems)
29 63 Kennedy, C.A., Cuddihy, J., Engel Yan, J., 2007. The changing
me abolism o ci ies. Jou nal o Indus ial Ecology 2007 (11), 43–59
26 53 Wolman, A., 1965. The me abolism o ci ies. Scien i ic Ame ican 213
(3), 179–190
20 55
Newman, P.W.G., Bi ell, R., Holmes, D., Ma he s, C., New on, P.,
Oakley, G., O’Conno , A., Walke , B., Spessa, A., Tai , D., 1996. Human
se lemen s. In: Aus alian S a e o he En i onmen Repo .
Depa men o En i onmen , Spo and Te i o ies, Canbe a, Aus alia.
18 51 Kennedy, C., P. Pince l, and P. Bunje. 2011. The s udy o u ban
me abolism and i s applica ions o u ban planning and design.
En i onmen al Pollu ion 159(8–9): 1965–1973.
12 46 Niza, S., L. Rosado, and P. Fe ao. 2009. U ban me abolism:
Me hodological ad ances in u ban ma e ial low accoun ing based on
he Lisbon case. Jou nal o Indus ial Ecology 13(3): 384–405.
CLUSTER 2
(34 I ems)
15 58
Hollands, R.G., 2008. “Will he Real Sma Ci y Please S and Up?” Ci y:
Analysis o U ban T ends, Cul u e, Theo y, Policy, Ac ion 12: 3, 303–320.
15 57 Ca agliu, A., Del Bo, C., & Nijkamp, P. (2009). Sma ci ies in eu ope,
se ie esea chmemo anda 0048. VU Uni e si y Ams e dam, Facul y o
Economics, BusinessAdminis a ion and Econome ics.
14 51
Gi inge , R., Fe ne , Ch, K ama , H., Kalasek, R., Pichle -Milano ic, N.,
e al. (2007). Sma ci ies- anking o Eu opean medium-sized ci ies.
Cen e o RegionalScience (SRF), Vienna Uni e si y o Technology.
13 49 Vanolo, A. (2014). Sma men ali y: The sma ci y as a disciplina y
s a egy. U ban S udies, 51, 883–898.
11 46 Nei o i, P., De Ma co, A., Cagliano, A. C., Mangano, G., & Sco ano, F.
(2014). Cu en ends in sma ci y ini ia i es: Some s ylised ac s.
Ci ies, 38, 25–36.

In . J. En i on. Res. Public Heal h 2020,17, 2463 17 o 28
Table 6. Con .
No.
Ci .
No.
Links Impo an Ci ed Re e ences
CLUSTER 3
(24 I ems)
17 33
Flo ida, R. (2002) The ise o he c ea i e class. Basic Books, New Yo k.
12 26 Ha ey D (1989) F om manage ialism o en ep eneu ialism: The
ans o ma ion in u ban go e nance in la e capi alism. Geog a iska
Annale : Se ies B, Human Geog aphy 71(1): 3–17.
10 13 Smi h, Neil (1996). The new u ban on ie . Gen i ica ion and he
e anchis ci y. London: Rou ledge.
9 35 Flo ida, R (2005). Ci ies and he C ea i e Class. Rou ledge, New Yo k.
7 17
Peck, J (2005) S uggling wi h he c ea i e class. In e na ional Jou nal o
Regional Resea ch 29(4), 740–770.
CLUSTER 4
(16 I ems)
13 35 G imm, N. B., Fae h, S. H., Golubiewski, N. E., Redman, C. L., Wu, J.,
Bai, X., e al. (2008). Global change and he ecology o ci ies. Science,
756–760.
7 16
Tzoulas, K., Ko pela, K., Venn, S., Yli-Pelkonen, V., Ka´zmie czak, A.,
Niemela, J., & James, P. (2007). P omo ing ecosys em and human heal h
in u ban a eas using G een In as uc u e: A li e a u e e iew.
Landscape and U ban Planning, 81(3), 167–178.
6 37 Campbell, S. (1996). G een ci ies, g owing ci ies, jus ci ies? U ban
planning and he con adic ion o sus ainable de elopmen . Jou nal o
he Ame ican Planning Associa ion, 62, 296–312.
4. Discussion
4.1. Discussion and Limi a ions o Me hodology
The no el y o he p oposed me hodology o li e a u e ne wo k analysis in compa ison wi h
he adi ional way o conduc ing a li e a u e e iew is he ac ha i is using bibliog aphic me ics.
The e o e, we can dis inguish ha his analysis has a h ee old objec i e. Fi s ly, i is pedagogical.
Secondly, i elimina es he unce ain y o a andomly casual li e a u e e iew and educes complexi y
by mi iga ing all he noise o he big olume o da a accessible h ough he in e ne . Thi dly, i
is me hodological, hus i p o ides a li e a u e e iew wi h cohe ence and a scien i ic p o ocol o
acqui e o ien ed-knowledge. The unde aken li e a u e ne wo k analysis is de ailed and desc ip i e,
discussing he planning s ages and explaining he ope a ional s eps o he li e a u e e iew. Finally,
he ob ained esul s a e illus a ed h ough ables and dis ance maps, p o iding insigh s o schola s
who a e beginning hei esea ch on he opic a oiding an ini ial andom sea ch.
I is essen ial o cla i y ha hese bibliog aphic ne wo ks show he ela edness o he i ems unde
s udy based on how s ong he links ha hey sha e a e. In bibliog aphic coupling ne wo ks, links exis
be ween i ems ha ci e he same documen , in co-ci a ion be ween i ems ha hey ha e been ci ed by
he same documen , in co-occu ence ne wo ks ega ding he numbe o documen s in which hey occu
oge he . Thus, om a echnical poin o iew, his me hod demons a es e ec i eness. Ne e heless,
limi a ions a e s emming om he in e p e a ion o hese ne wo ks in he clus e analysis s age.
Fo ins ance, in case o co-occu ence ne wo ks, keywo ds can occu oge he in mo e ha one pape
ha ing di e en meanings and hus gene a ing misleading bibliog aphic ne wo ks. In bibliog aphic
coupling ne wo ks, wo i ems can ci e he same documen bu exp essing disag eemen abou he
opic unde s udy. In o de o diminish hese issues in he ne wo k analysis, we ca e ully selec ed
he ini ial li e a u e da ase based on mul iple g oup discussions by expe s. O he limi a ions a ise
om he me hods applied o conduc ne wo k analysis. As men ioned in a p e ious sec ion, he e
a e wo coun ing me hods, he ull and ac ional coun ing me hods. A esea che has o be awa e o
he limi a ions a ising om he di e en me hods applied in a ious ne wo ks. Fo ins ance, using
ac ional coun ing me hod, highly ci ed a icles ha ha e a smalle in luence on he cons uc ion o
bibliog aphic coupling ne wo ks and a icles wi h many e e ences like e iew a icles, ha e a less
impo an ole in he cons uc ion o co-ci a ion ne wo ks. A icles wi h many au ho s ha e he same
weigh wi h a icles wi h less au ho s in he cons uc ion o co-au ho ship ne wo ks [
25
,
26
]. We used
In . J. En i on. Res. Public Heal h 2020,17, 2463 18 o 28
ac ional coun ing me hod when we wan ed o gi e equal impo ance o he i ems unde ne wo k
analysis. Despi e he iden i ied limi a ions, i is ou unde s anding ha li e a u e ne wo k analysis
p o ides a as e a e o disco e y, mo e accu a e and mo e in-dep h insigh s han o he li e a u e
e iew me hods we ha e known, and expe imen ed wi h un il now.
4.2. Discussion o Resul s
A gene al obse a ion om all he di e en ypes o bibliome ic analysis we conduc ed he e is ha
he numbe o ci a ions canno be aken as he main d i e o show he impo ance o an i em wi hou
aking in o conside a ion he o al link s eng h o he i em; meaning he deg ee o connec ion wi h he
es o he i ems in he da ase unde analysis. Fo ins ance, compa ing he wo maps (Figu e 5a,b), we
see ha documen s wi h an ex emely high numbe o ci a ions a e no he bes connec ed o he es
o he documen s o he da a se , and he e o e hey a e no he mos ela ed o he opic o analysis.
Looking a he links o he i ems o all ou bibliome ic analysis, we obse e ha he links be ween he
concep s o sma and egene a i e me abolic u ban g ow h do no appea o be s ong, o appea o be
absen . As an example, shown in Figu e 8, we ha e made a selec ion o he keywo ds o ou in e es
sma ci y,u ban me abolism, and u ban egene a ion, and can clea ly see ha hey a e no connec ed.
Figu e 8. Links be ween main keywo ds unde co-occu ence analysis.
We ob ain he same image when looking closely a he links in ou second analysis o he
bibliog aphic coupling o documen s (Figu e 5a). In Figu e 9, we ha e selec ed one ep esen a i e
documen o each concep sma ci y; Ah enniemi e al. (2017), u ban me abolism; Dempsey e al.
(2012), u ban egene a ion; Kennedy e al. (2011) o make his s a emen be e unde s ood.
In . J. En i on. Res. Public Heal h 2020,17, 2463 19 o 28
Figu e 9. Links be ween main concep s unde bibliog aphic coupling analysis based on documen s.
5. Conclusions
In his s udy, we conduc ed a li e a u e ne wo k analysis o e iew he concep o u ban g ow h
unde me abolic amewo k ocusing on sma and egene a i e u ban design wi hin he las en
yea s. Using VOS iewe we cons uc ed ne wo k maps ha helped us de ec ela edness o concep s,
documen s, main e e enced wo ks, and op in luence s au ho s along wi h ip- op cu ing-edge
esea ch upon he opic. Ini ially, we indica ed h ee main esea ch ends ela ed o u ban g ow h
(see esul s o analysis 1) and going one s ep u he , we we e able o iden i y six key sub- esea ch
ends (see esul s o analysis 2) and hei ela edness. We de ec ed he mos in luence au ho s
wi hin ou da ase pe sub-concep (see esul s o analysis 3) (Figu e 10), and inally, we acked
he o igins o hese key sub- esea ch ends ela ed o he u ban g ow h concep unde analysis
(see esul s analysis 4). The o e all indings showed ha u ban g ow h esea ch is simul aneously
mul idisciplina y and in e disciplina y in eg a ing social, ecological, poli ic, economic sciences, cul u e
and a s, en i onmen al, and compu e sciences. We iden i ied a lack o connec edness be ween
sma and egene a i e concep s o u ban g ow h. The e o e, his p o ides scien i ic e idence ha in
o de o adop a holis ic app oach allowing u u e ci ies o ackle challenges ela ed o unbalanced
u baniza ion-economy-en i onmen dynamics, and o p o ide a be e li e quali y and wellbeing, we
need o u n he esea ch ocus on building his link be ween he ields o sma and egene a i e u ban
s udies. We ha e al eady s a ed o concep ualize he amewo k o sma and egene a i e u ban
g ow h in pos an h opocen ic u banism.
In . J. En i on. Res. Public Heal h 2020,17, 2463 20 o 28
Figu e 10. Map o cascade ela ions among he bibliome ic clus e s.
Au ho Con ibu ions:
All au ho s ha e ead and ag ee o he published e sion o he manusc ip .
Concep ualiza ion, P.M. and A.P.; me hodology, A.P.; so wa e, A.P.; alida ion, A.P., and P.M.; o mal analysis,
A.P.; in es iga ion, A.P.; esou ces, P.M and A.P.; da a cu a ion, A.P.; w i ing—o iginal d a p epa a ion, A.P.;
w i ing— e iew and edi ing, P.M and A.P.; isualiza ion, A.P.; supe ision, P.M.; p ojec adminis a ion, A.P and
P.M..; unding acquisi ion, P.M. and A.P.
Funding: The APC was unded by CEG and also FCT (UIDB/00295/2020 e UIDP/00295/2020).
Acknowledgmen s:
We acknowledge he GEOMODLAB - Labo a o y o Remo e Sensing, Geog aphical Analysis
and Modelling-o he Cen e o Geog aphical S udies/IGOT o p o iding he equi ed equipmen and acili ies
o his s udy. We app ecia e he aluable eedback om he edi o and he anonymous e iewe s.
Con lic s o In e es : The au ho s decla e no con lic o in e es .
In . J. En i on. Res. Public Heal h 2020,17, 2463 21 o 28
Appendix A
Table A1. Numbe o ci a ions o documen s pe clus e based on he bibliog aphic coupling analysis.
CLUSTER 1
(60 I ems)
CLUSTER 2
(47 I ems)
CLUSTER 3
(40 I ems)
CLUSTER 4
(40 I ems)
CLUSTER 5
(31 I ems)
CLUSTER 6
(10 I ems)
Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions
A baci (2012) 31 Alexand escu e
al. (2018) 6 Ba les (2010) 86 Ah enniemi e
al. (2017) 77 Capu o e al.
(2012) 13 Da oudia and
S u zake b
(2017) 10
Baba (2017) 2 A mann (2014) 20 Basi i e al.
(2017) 3Al Nuaimi e al.
(2015) 78 Dell‘ollo e al.
(2014) 10 Haghshenas and
Vazi i (2012) 80
Bailey (2012) 30
A mann (2014b)
28 Blecic e al.
(2014) 10 Albino e al.
(2015) 260 Fa mani e al.
(2012) 10 Li e al. (2017) 0
Ba bou e al.
(2016) 1Ba bosa e al.
(2012) 135 B o o e al.
(2012) 70
Angelidou (2014)
125 G ekousis e al.
(2019) 0 Liu (2012) 30
Belanche e al.
(2016) 34 Beck e al. (2013) 7 Chen and Chen
(2019) 127
Ba y e al. (2012)
372 Haapio (2012) 88 Moo e e al.
(2013) 56
Biddulph (2011) 29
Be a e al. (2016)
5Ches e e al.
(2012) 33 Be z e al. (2016) 6 Hale and Sadle
(2012) 12 New on and
Glackin (2014) 19
Blessi e al.
(2012) 17 Bona oni e al.
(2017) 10 Ch ysoulakis e
al. (2013) 53 Bib i and
K ogs ie (2017) 58 He schel (2013) 26 Pojani and S ead
(2015) 40
Bulkeley e al.
(2016) 14 B eus e e al.
(2013) 15 Conke and
Fe ei a (2015) 23 Ca agliu e al.
(2011) 576 Jansson (2013) 60 Thomson and
Newman (2018) 4
Codecasa and
Ponzini (2011) 16 B idges (2016) 2 Cui e al. (2019) 0 C i ello (2014) 17 Jim (2013) 43
Van Timme en e
al. (2012) 6
Couch e al.
(2011) 67 Chelle i e al.
(2016) 2 Dijs e al. (2018) 4 Falco e al.
(2018) 0Kau and Ga g
(2019) 1Webb e al.
(2018) 11
Cu hill (2010) 91 D’Al.isa e al.
(2012) 32 Ga cía-Guai a e
al. (2018) 1Falco e al.
(2019) 0 Rosa (2014) 43
Deakin (2012) 11 Die kes e al.
(2015) 19 Golds ein e al.
(2013) 42 Ejaz e al. (2017) 54
Rosa e al. (2017)
9
Degen and
Ga cia (2012) 79
F ancesch-Huidob o
(2015) 8Gonzalez e al.
(2013) 47 Ga au and
Pa an (2018) 28 Leigh and
Hoelzel (2012) 21
Dempsey e al.
(2011) 275 Gai ani e al.
(2014) 14 Huang e al.
(2018) 0Ga au e al.
(2016) 7Lomba di e al.
(2011) 40
Dempsey e al.
(2012) 76 Gi a d (2013) 26 Inos oza (2014) 24 Gazzola e al.
(2019) 0 MacLeo d (2013) 37

In . J. En i on. Res. Public Heal h 2020,17, 2463 22 o 28
Table A1. Con .
CLUSTER 1
(60 I ems)
CLUSTER 2
(47 I ems)
CLUSTER 3
(40 I ems)
CLUSTER 4
(40 I ems)
CLUSTER 5
(31 I ems)
CLUSTER 6
(10 I ems)
Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions
Dixon e al.
(2011) 22 G ê -Regamey e
al. (2013) 48 Kennedy e al.
(2011) 258 Gha aibeh e al.
(2017) 32
Ma sal-Llacuna
and
López-Ibáñez
(2014)
8
E gas (2010) 34 Guzmán e al.
(2017) 20 Kılkı¸s (2017) 0 Goodspeed
(2014) 39 Ma eo and
Cuna (2016) 3
E iksson (2010) 28 Kaika (2017) 32 Lehmann (2011) 28 Ib ahim e al.
(2018) 6Ma akis e al.
(2015) 11
F an ál e al.
(2015) 28 Klopp and
Pe e a (2017) 22
Liang and Zhang
(2012) 38 Lomba di e al.
(2012) 158 Mo imo o (2011) 10
González e al.
(2013) 166 Lapenna and
Tocca ondi
(2017) 0 Lin e al. (2014) 27 Macke e al.
(2018) 8Mö be g e al.
(2013) 17
G ay and Po e
(2015) 19 Li e al. (2017) 17 Lund e al.
(2015) 45 Mani iu and
Ped ini (2016) 2 Oh e al. (2011) 5
Guima ães
(2017) 2 Lu e al. (2016) 14 Meije (2011) 18 Ma ch and
Ribe a-Fumaz
(2016) 32
Peng e al. (2015)
32
Güzey (2016) 11 Ma low e al.
(2013) 126 Mos a a i e al.
(2014) 10 Ma sal-Llacuna
e al. (2015) 61 Pili e al. (2017) 51
Haas and Locke
(2012) 0McCo mick e al.
(2013) 144 Mos a a i e al.
(2014a) 7Ma in e al.
(2018) 11 Roge s e al.
(2012) 34
Hodkinson
(2011) 23 Med ed (2016) 9 Niemi e al.
(2012) 54 Ma in e al.
(2019) 0 Sco (2007) 31
Howley e al.
(2009) 73 Ne ens e al.
(2013) 191 Pea son e al.
(2010) 74 Mosannenzadeh
e al. (2017b) 15 Shi e al. (2012) 43
Hus on e al.
(2015) 16 Newell e al.
(2013) 41 Pince l e al.
(2012) 98 Palma Lamp eia
dos San os (2016)
11 Song (2005) 55
Jung e al. (2015) 16
Pe ales-Mompa le
e al. (2015) 13 Rosado e al.
(2014) 54 Pinna e al.
(2017) 10 S azze a (2010) 13
Ke esz ely and
Sco (2012) 11 Pupphachai and
Zuidema (2017) 13 Rosado e al.
(2016) 12 Roche (2014) 36
Tyle e al. (2013)
25
Ko and Klijn
(2013) 12 Radulescu e al.
(2016) 8Shah okni e al.
(2015a) 7Shah okni e al.
(2015) 14 Yigi canla and
Lee (2014) 60
In . J. En i on. Res. Public Heal h 2020,17, 2463 23 o 28
Table A1. Con .
CLUSTER 1
(60 I ems)
CLUSTER 2
(47 I ems)
CLUSTER 3
(40 I ems)
CLUSTER 4
(40 I ems)
CLUSTER 5
(31 I ems)
CLUSTER 6
(10 I ems)
Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions
K iznik (2018) 2 Rome o-Lankao
e al. (2014) 24 Singh e al.
(2011) 54 Shen e al. (2018 1 Zi i e al. (2015) 58
La co (2016) 20 Sha ma e al.
(2010) 26 Voskamp e al.
(2018) 8 Shin e al. (2015) 19
Lee e al. (2014) 12 Simon e al.
(2015) 19 Wachsmu h
(2012) 46 Soyinka e al.
(2016) 3
Lees and
Melhuish (2012) 12 S edo a e al.
(2015) 7Walke and Beck
(2012) 14 S eenb uggen e
al. (2015) 42
Lim e al. (2013) 16 T an (2016) 12 Xia e al. (2018) 3 T anos and
Ge ne (2012) 48
Lugosi, e al.
(2010) 17 Uya a and Gee
(2013) 27
Yang e al. (2012)
19 Win e s (2011) 97
Malleson and
Heppens all
(2013) 12 Van de Meene e
al. (2011) 71
Yang e al. (2014)
24 Yigi canla
(2015) 21
Ma í-Cos a and
Miquel (2011) 23 Wei e al. (2015) 36 Zhang e al.
(2011) 56 Yigi canla e al.
(2019) 0
McGui k e al.
(2016) 13 Willuwei and
OSulli an (2013) 39 Zhang e al.
(2014) 22 Zanella e al.
(2014) 1065
Mee ke k (2013) 25 Yang and Wang
(2017) 7Zhang e al.
(2018) 1Zhang e al.
(2019) 0
Mosannenzadeh
e al. (2017) 9Yigi canla and
Te iman (2015) 46
Obeng-Odoom
(2014) 14 Yim e al. (2015) 3
Pa es e al.
(2014) 12 Yin e al. (2014) 56
Pa és e al.
(2012) 20 Yue e al. (2014) 26
Pa k (2014) 2 Zhang e al.
(2016) 3
Rhodes and
Russo (2013) 20 Zhao (2010) 121
Sasaki (2010) 42 Zie ogel e al.
(2016) 18
In . J. En i on. Res. Public Heal h 2020,17, 2463 24 o 28
Table A1. Con .
CLUSTER 1
(60 I ems)
CLUSTER 2
(47 I ems)
CLUSTER 3
(40 I ems)
CLUSTER 4
(40 I ems)
CLUSTER 5
(31 I ems)
CLUSTER 6
(10 I ems)
Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions Documen s Ci a ions
Schue ze and
Chelle i (2016) 13
Shao and Liu
(2018) 1
Susilo e al.
(2012) 39
Tasan-Kok (2010)
25
Tulumello (2016) 10
Ulldemolins
(2014) 22
Uysal (2012) 23
Van den Be g
(2013) 22
Ven o (2017) 8
While e al.
(2010) 172
Wins on (2010) 43
Zeb acki and
Smulde s (2012) 1
Zhong (2016) 10
In . J. En i on. Res. Public Heal h 2020,17, 2463 25 o 28
Table A2. A e age ci a ions and o al link s eng h o au ho s pe clus e based on bibliog aphic coupling analysis.
CLUSTER 1 (17 i ems) CLUSTER 2 (14 i ems) CLUSTER 3 (13 i ems) CLUSTER 4 (5 i ems)
Au ho s To al Link
S eng h
A g.
Ci a ions Au ho s To al Link
S eng h
A g.
Ci a ions Au ho s To al Link
S eng h
A g.
Ci a ions Au ho s To al Link
S eng h
A g.
Ci a ions
Angelidou
Ma ga i a 125.38 62.50 A mann
Ma ina 10.00 24.00 Ches e
Mikhail 129.80 28.50
Da oudi Simin
89.33 7.00
Bisello
Ad iano 142.55 12.00 Ca lucci
Ma ghe i a 121.00 54.50 Ch usoulakis
Nek a ios 167.62 50.00 Moglia
Mangus 142.00 68.50
B and Nils 103.81 10.5 Chelle i
Lo enzo 21.75 7.50
Fa zinmoghadam
Mohamad 133.47 8.50 Newman Pe e 292.25 6.33
De Fac o
S e ano 123.38 0.00 La Rosa
Daniele 10.00 26.00 Gonzalez
Ainhoa 167.62 50.00 New on Pe e 142.17 15.00
E ans James 147.39 5.50 Li Feng 57.00 10.00 Liu Gengyuan 98.75 29.50 Thomson Giles 292.25 6.33
Ga au Chia a 93.90 15.00 Lomba di D.
Rachel 136.50 37.00 Lopes My iam 167.62 50.00
Ka onen
And ew 147.39 5.50 Ma i-Cos a
Ma c 93.50 18.33 Lu Weisheng 43.00 2.00
Laza e ic
Da id 103.81 10.50 Mcgui k
Pauline M. 6.00 13.50 Mos a a i
Na iman 133.47 8.50
Ma sal-Llacuna
Ma ia Luis 3.00 34.50 Pa es Ma c 90.50 16.00 Pince l
S ephanie 149.17 51.67
Masala
F ancesca 84.12 19.00 Po e Libby 87.60 29.50 Rosado
Leona do 16.63 33.00
Mosannenzadeh
Fa naz 142.25 12.00 Roge s Ch is
D.F. 137.17 28.00 Spano
Dona ella 107.13 31.50
Nijkamp Pe e 162.33 309.0 Sal a i Luca 121.00 54.50 Yang Dewei 39.10 21.50
Pinna
F ancesco 84.12 19.00 Wang Rusong 45.00 36.50 Zhang Yan 105.35 27.00
Shah okni
Hossein 103.81 10.50 Zhang
Xiaoling 64.00 17.33
T anos
Emmanuil 166.71 45.00
Ve o a o
Daniele 142.55 12.00
Yigi canla Tan 45.11 27.00