Academic Edi o : Jane Nichol
Recei ed: 30 Oc obe 2024
Re ised: 2 Janua y 2025
Accep ed: 8 Janua y 2025
Published: 10 Janua y 2025
Ci a ion: Sola-Ca aballo, J.;
Se ano-Jiménez, A.; Ri e a-Gomez,
C.; Galan-Ma in, C. Mul i-C i e ia
Assessmen o U ban The mal
Ho spo s: A GIS-Based Remo e
Sensing App oach in a Medi e anean
Clima e Ci y. Remo e Sens. 2025,17,
231. h ps://doi.o g/10.3390/
s17020231
Copy igh : © 2025 by he au ho s.
Licensee MDPI, Basel, Swi ze land.
This a icle is an open access a icle
dis ibu ed unde he e ms and
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A ibu ion (CC BY) license
(h ps://c ea i ecommons.o g/
licenses/by/4.0/).
A icle
Mul i-C i e ia Assessmen o U ban The mal Ho spo s:
A GIS-Based Remo e Sensing App oach in a Medi e anean
Clima e Ci y
Ja ie Sola-Ca aballo 1,* , An onio Se ano-Jiménez 2, Ca los Ri e a-Gomez 1and Ca men Galan-Ma in 1
1Depa amen o de Cons ucciones A qui ec ónicas I, Escuela Técnica Supe io de A qui ec u a, Uni e sidad
de Se illa, A da. Reina Me cedes, 2, 41012 Se ille, Spain; [email p o ec ed] (C.R.-G.); [email p o ec ed] (C.G.-M.)
2
Depa amen o de Cons ucciones A qui ec ónicas, Escuela Técnica Supe io de A qui ec u a, Uni e sidad de
G anada, Campo del P incipe, sn, 18071 G anada, Spain; se anojimenez@ug .es
*Co espondence: [email p o ec ed]; Tel.: +34-954-556-59
Abs ac : One o he mos signi ican u ban challenges ocuses on add essing he e ec s
o u ban o e hea ing as a consequence o clima e change. Se e al me hods ha e been
de eloped o cha ac e ize u ban hea islands (UHIs); howe e , he mos widely used
in ol e complex planning, huge ime consump ion, and subs an ial human and echnical
esou ces on ield moni o ing campaigns. The e o e, his s udy aims o p o ide an easily
accessible and a o dable emo e sensing me hod o loca ing u ban ho spo s and add esses
a mul i-c i e ia assessmen o u ban hea - ela ed pa ame e s, allowing o a comp ehensi e
ci y-wide e alua ion. The no el y is based on le e aging he po en ial o he las Landsa 9
sa elli e, he applica ion o ke nel spa ial in e pola ion, and GIS open access da a, p o iding
e y high- esolu ion land su ace empe a u e images o e u ban spaces. Wi hin GIS
wo k low, he ci y is di ided in o LCZs, he mal ho spo s a e de ec ed, and inally, i is
analyzed o unde s and how u ban ac o s, such as u ban bounda ies, building densi y,
and ege a ion, a ec u ban scale LST, all using g aphical and analy ical c oss-assessmen .
The me hodology has been es ed in Se ille, a ep esen a i e wa m Medi e anean ci y,
whe e a ia ions o up o 10
◦
C ha e been ound be ween homogeneous esiden ial a eas.
The mal ho spo s ha e been loca ed, ep esen ing 11% o he o al esiden ial ab ic, while
esul s indica e a clea connec ion be ween he u ban ac o s s udied and o e hea ing. The
conclusions suppo he possibili y o gene a ing a powe ul a o dable ool o u u e
esea ch and he design o public policy enewal ac ions in ulne able a eas.
Keywo ds: u ban o e hea ing; land su ace empe a u e; local clima e zones; u ban densi y;
he mal ho spo s; ou doo en i onmen al com o
1. In oduc ion
Global wa ming’s accele a ion [
1
] p omp s u gen bioclima ic u ban egene a ion
s a egies [
2
], pa icula ly in wa m egions and ci ies as hey p ojec o hos 68% o he
global popula ion by 2050 [
3
,
4
]. Thus, esea ch mus p io i ize e icien u ban manage-
men , emphasizing u ban com o [
5
,
6
] and sus ainable planning [
7
,
8
], o e ing, he e o e,
guidelines and me hodologies o public specialis s and policymake s. In his sense, he
li e a u e has widely s udied he u ban hea island (UHI) phenomenon [
9
,
10
], which occu s
mainly du ing he nigh . Howe e , ecen s udies a e ocusing on diu nal u ban hea , as
du ing he day he empe a u es and cooling consump ion peaks a e eached [5,11].
Classical UHI s udies in ol e high- esou ce ield campaigns [
12
–
14
] o cha ac e ize
hea dis ibu ion, making i di icul o sample he en i e ci y. These s udies ypically ocus
Remo e Sens. 2025,17, 231 h ps://doi.o g/10.3390/ s17020231
Remo e Sens. 2025,17, 231 2 o 27
on ai empe a u e (AT) in he u ban canopy laye [
15
,
16
]; howe e , ecen s udies a e ana-
lyzing land su ace empe a u e (LST) and assessing he su ace u ban hea island (SUHI).
In a ed s udies [
17
] and emo e sensing echniques [
18
] based on sa elli e acquisi ion a e
c ucial o analyze SUHI, p o iding quick and e ec i e iden i ica ion o an a ea o in e es
(AOI), wi h high- esolu ion images o an en i e ci y o egional zone a he same ime.
I is impo an o cla i y ha LST is an indi ec measu e ha highly depends on
a iables such as spa ial esolu ion and he ma e ial p ope ies o each su ace. This can
c ea e limi a ions o s udying e ec i e ai empe a u e o ho oughly e alua ing he mal
com o . On he con a y, emo e sensing ob ains LST da a ins ead o AT; al hough he e is
a disc epancy be ween hem [
19
], ecen esea ch has ound a ce ain co ela ion [
20
,
21
],
mos ly wi h com o as i is highly in luenced by mean adian empe a u e [
22
]. Despi e
ha , nume ous p e ious s udies suppo i as a use ul ool o s udying he he mal and
clima ic pe o mance o he ci y [
17
], as i can cap u e la ge a eas and be compa ed wi h
many o he in e ela ed pa ame e s. Thus, unde s anding i s limi a ions and po en ial, i
becomes a powe ul ool o cha ac e iza ion and diagnosis a he ci y scale [
23
]. Speci ically,
his esea ch ocuses on he Landsa 9 sa elli e, launched by NASA and USGS [
24
]. The mal
in a ed senso s p o ide LST images wi h an accu acy o 0.4–1.98 K [25].
The u ban clima e li e a u e add esses se e al aspec s ha s ongly in luence he u ban
mic oclima e [
26
]. Among hese, i is wo h no ing he widesp ead concep o he local
clima e zone (LCZ) [
27
,
28
]. This classi ica ion, widely es ed in p e ious s udies [
29
], helps
o es ablish solid co ela ions be ween u ban ypologies and clima e pe o mance [
30
,
31
],
which also a ec s di ec ly buildings’ cooling ene gy [
32
,
33
]. O he s udies ha e ocused on
he land use–land co e (LULC) classi ica ion [
34
] and i s ela ionship wi h LST [
35
], while
o he s ha e es ablished au oma ic machine-lea ning UHI p edic ions based on LULC [
36
].
Rega ding his, he Cope nicus’ CORINE p og amme has de eloped a e y de ailed open-
access LULC classi ica ion map [
37
], whose esul s a e use ul o u ban esea ch. Addi ional
s udies ha e subs an ia ed conside ably o he se e al pa ame e s c ucial o unde s and
u ban hea pe o mance [
38
]. The Sky View Fac o (SVF) index [
39
,
40
] has been ound
o be c ucially ela ed o he po en ial o an a ea o ecei e sun adia ion and dissipa e
i la e [
41
,
42
]. O he ele an pa ame e s include g een s uc u es and he No malized
Di e ence Vege a ion Index (NDVI) [
43
,
44
]. Vege a ion can educe AT [
45
], bu also p o ec
om di ec sola adia ion, in luencing LST [
46
]. Fu he mo e, soils and pa emen ma e ials
ha e been ound ele an o LST and so u ban clima e [14,35].
To manage emo e sensing da a wi hin all hese u ban pa ame e s on la ge scales
in ol es ex ensi e p ocessing, and he geog aphical in o ma ion sys em (GIS) is spe-
cially designed o ace hese skills [
41
,
47
]. This esea ch uses Quan um GIS (QGIS)
e sion 3.34.6 [
48
], an open-sou ce so wa e, widely used which has been es ed by se e al
s udies [
49
,
50
]. Some o hem highligh he use ulness o emo e sensing in GIS ools
o u ban clima e and UHI e alua ion [
51
,
52
]. O he ecen s udies used GIS o com-
bine LST da a wi h u ban pa ame e analysis o ob ain socioeconomic and uel-ene gy
assessmen s [
53
,
54
], mapping ulne abili y u ban maps. O he esea ch combined mos
o he p e ious ields [
38
,
50
,
55
] o ocus speci ically on he sea ch o ho spo s o pa -
icula ly wa m a eas in he ci y [
56
,
57
], emphasizing he po en ial o hese esou ces as
diagnos ic ools.
A e his backg ound analysis, se e al gaps ha e been obse ed in he li e a u e.
Many s udies p o ide UHI cha ac e iza ion app oaches [
13
,
14
], bu mos a e esou ce-
in ensi e o can become di icul o add ess. O he app oaches a e based on au oma ized
algo i hms o spa ial classi ica ion [
25
,
34
,
58
]; howe e , his can esul in low accu acy o
de ailed u ban s udies. Mos o he esea ch uses he mal images wi h la ge-scale and
low- esolu ion images [
20
,
50
,
59
,
60
], which is use ul o egional la ge-scale s udies o o
Remo e Sens. 2025,17, 231 3 o 27
assessing SUHI empo al e olu ion. Howe e , he low spa ial esolu ion ails o p ope ly
add ess diagnos ics wi hin he u ban ab ic a he public space and s ee s scale. O he
esea ch es ima es SVF bu wi hou conside ing ees [
61
], which ha e a conside able e ec
o o e es ima ion o sola adia ion in u ban canyons. Finally, i has been no ed ha many
s udies do no p o ide de ailed a o dable me hodologies o guidelines. This hinde s
eplicabili y by echnicians and policymake s who a e no amilia wi h emo e sensing.
I hese me hods a e no p ecise, hey canno be p ope ly ep oduced and, he e o e, a e
no implemen ed in u ban policies, esul ing in a los oppo uni y o enhance he clima e
esilience o many wa m ci ies.
Based on he abo e, he no el y o his esea ch is o aise an open-access and eplicable
u ban-scale me hod which, by add essing he ole o he u ban en i onmen , p o ides
op imized images and pos -analysis, allowing o be e iden i ica ion o u ban he mal
ho spo s, as well as hei beha iou and pe o mance acco ding o u ban ea u es. In his
way, his me hodology p o ides essen ial ools o add ess he scien i ic issues necessa y
o he iden i ica ion and cha ac e iza ion o u ban he mal ho spo s. Fi s ly, he LST o
an en i e ci y is ob ained a a e y high esolu ion, hanks o he mal sa elli e images and
s a is ical escaling. Al hough LST is no equi alen o AT, acco ding o he li e a u e, i
p o ides aluable in o ma ion. Also, due o i s ine scale, i encompasses public space and
he dis ibu ion o hea in he ci y. Addi ionally, he c oss-mul i ac o analysis (land use,
building densi y, ege a ion, e c.) allows o he unde s anding o pa ame e s ela ed o
he mal pe o mance. The analysis examines ypical alues acco ding o he li e a u e,
iden i ies ela ionships, and hus p o ides insigh s in o he causes and diagnoses o he
men ioned ho spo s.
Thus, his no el me hod, by o mula ing speci ic esea ch ques ions, and answe ing
hem wi h a o dable echnical app oaches, p o ides a powe ul diagnos ic ool o
iden i ying pa icula ly ho a eas, as well as imp o ing he unde s anding o u ban
o e hea ing and i s causes, and o e ing a glimpse o possible u u e eno a ions, all
ocused on he mos ulne able a eas unde he incoming CC haza ds. Fo his pu pose,
a de ailed s ep-by-s ep guide, based on open access da a, is p o ided and explained,
ensu ing ha he s anda diza ion o he esea ch makes i eplicable. Such con ibu ion
is impo an o u ban he mal en i onmen assessmen , especially du ing p olonged
hea wa es. The diagnos ic cha ac e makes i use ul o policymake s o p io i ize
necessa y in e en ions.
2. Ma e ials and Me hods
This s udy p oposes a h ee-s ep me hodology, based on he ollowing: (a) open access
emo e sensing da a; (b) GIS p ocessing and analysis; and (c) quali a i e and quali a i e
ho spo s assessmen , a s ep-by-s ep guide. All he esea ch is based on open access da a
eely a ailable (Table 1). The hea - ela ed pa ame e s we e cap u ed on he same analysis
day, while o he in o ma ion, such as buildings and land use, which depend on he la es
upda es om o icial sou ces, come om di e en da es. Howe e , o he de ailed analyzed
zones, all he u ban laye s ha e been isually checked and con as ed wi h ecen sa elli e
images o a oid inconsis encies wi h eali y. Finally, he me hod is es ed using a eal case
s udy selec ed in Se ille, Spain.
Remo e Sens. 2025,17, 231 4 o 27
Table 1. Resea ch da a sou ces.
Da a Desc ip ion Da e Sou ce
Local
clima e
Open access da a o ypical clima e and o icial
clima e eco ds o he s udied ame
2023
29 Augus 2023
OneBuilding.o g (epw) [62]
Local wea he s a ion [63]
Land co e Open access ec o ial Land co e maps o
de e mine he ype and use o u ban ab ic
2018
(Las ac l.)
Cope nicus’ CORINE
p og amme [37]
U ban LST Open access he mal image. O iginal SR o
100
×
100 m, p o ided esampled a 30
×
30 m
29 Augus 2023 USGS’s Landsa 9 [24,64]
Buildings da a Open access cadas al GIS laye s o buil
en i onmen wi h age, a ea and heigh da a 2022 Cadas e [65]
LCZ Classi ica ion acco ding o he o iginal
sou ce guidelines Ago-2023 S ewa and Oke [27]
T ee plans
Open access GIS laye s wi h posi ion, species
and size o u ban ees, o ue colou
sa elli e image
Ago-2023 Local da abases,
al e na i ely, NDVI
NDVI P ocessed image om an open-access sa elli e
image band 29 Augus 2023 USGS’s Landsa 9 [24] o
EOS’s C opMoni o [66]
2.1. Remo e Sensing P edic i e Model
This me hodology wo k low and he guidelines a e summa ized in Figu e 1. As his
wo k p esen s a me hodology ha can be eplica ed in o he case s udies, i is ini ially
p esen ed in a gene ic and de ailed manne , a oiding any case da a. Subsequen ly, a speci ic
and ep esen a i e case s udy, he ci y o Se ille, is selec ed, p o iding all he necessa y
da a. The me hodology is hen applied o e alua e i s po en ial in ob aining esul s and
discussing hem.
Remo e Sens. 2025, 17, x FOR PEER REVIEW 4 o 29
Table 1. Resea ch da a sou ces.
Da a Desc ip ion Da e Sou ce
Local
clima e
Open access da a o ypical clima e and official cli-
ma e eco ds o he s udied ame
2023
29 Augus 2023
OneBuilding.o g (epw) [62]
Local wea he s a ion [63]
Land co e Open access ec o ial Land co e maps o de e mine
he ype and use o u ban ab ic
2018
(Las ac l.)
Cope nicus’ CORINE
p og amme [37]
U ban LST Open access he mal image. O iginal SR o 100 × 100
m, p o ided esampled a 30 × 30 m 29 Augus 2023 USGS’s Landsa 9 [24,64]
Buildings
da a
Open access cadas al GIS laye s o buil en i onmen
wi h age, a ea and heigh da a 2022 Cadas e [65]
LCZ Classi ica ion acco ding o he o iginal sou ce guide-
lines Ago-2023 S ewa and Oke [27]
T ee plans Open access GIS laye s wi h posi ion, species and size
o u ban ees, o ue colou sa elli e image Ago-2023 Local da abases,
al e na i ely, NDVI
NDVI P ocessed image om an open-access sa elli e image
band 29 Augus 2023 USGS’s Landsa 9 [24] o EOS’s
C opMoni o . [66]
2.1. Remo e Sensing P edic i e Model
This me hodology wo k low and he guidelines a e summa ized in Figu e 1. As his
wo k p esen s a me hodology ha can be eplica ed in o he case s udies, i is ini ially
p esen ed in a gene ic and de ailed manne , a oiding any case da a. Subsequen ly, a spe-
ci ic and ep esen a i e case s udy, he ci y o Se ille, is selec ed, p o iding all he neces-
sa y da a. The me hodology is hen applied o e alua e i s po en ial in ob aining esul s
and discussing hem.
Figu e 1. G aphical ep esen a ion o he me hodology wo k low wi h iden i ica ion o he applied
ools and p ocesses.
2.1.1. A ea o S udy and Time F ame Selec ion
The ini ial phase o he me hodology in ol es he iden i ica ion o he u ban case
s udy and he de ini ion o he ime ame o analysis. As ou lined below, his me hodol-
ogy is speci ically ailo ed o u ban en i onmen s, wi h a pa icula emphasis on wa m
ci ies. Wi hin he selec ed loca ion, he clima ic cha ac e is ics o he ci y mus be me icu-
lously de ailed and analyzed be o ehand. The clima ic classi ica ion is de e mined using
he in e na ionally ecognized Köppen sys em [67], while speci ic clima ic pa ame e s a e
ob ained om au ho i a i e official eco ds. A ho ough unde s anding o he loca ion,
Figu e 1. G aphical ep esen a ion o he me hodology wo k low wi h iden i ica ion o he applied
ools and p ocesses.
2.1.1. A ea o S udy and Time F ame Selec ion
The ini ial phase o he me hodology in ol es he iden i ica ion o he u ban case
s udy and he de ini ion o he ime ame o analysis. As ou lined below, his me hod-
ology is speci ically ailo ed o u ban en i onmen s, wi h a pa icula emphasis on wa m
ci ies. Wi hin he selec ed loca ion, he clima ic cha ac e is ics o he ci y mus be me icu-
lously de ailed and analyzed be o ehand. The clima ic classi ica ion is de e mined using
he in e na ionally ecognized Köppen sys em [
67
], while speci ic clima ic pa ame e s a e
ob ained om au ho i a i e o icial eco ds. A ho ough unde s anding o he loca ion,
Remo e Sens. 2025,17, 231 5 o 27
including i s clima ic ype and p e ailing local wea he condi ions, is essen ial o selec ing
an app op ia e ime ame.
Conside ing ha he s udy ocuses on he mal ho spo s, i is p e e able o selec a
wa m day o analysis. This day mus accu a ely ep esen he ci y’s ypical he mal
condi ions du ing i s wa m season. I his is no possible o is needed o base he s udy
on di e en clima ic condi ions, i is possible o epea i o se e al days. To ensu e
his ep esen a i eness, a compa a i e analysis be ween he ci y’s clima ic no ms du ing
summe and he selec ed day’s me eo ological condi ions is equi ed. Thus, o ensu e he
alidi y o he analysis, i is c ucial o con i m ha he selec ed day is clea , wi h no high
le els o pollu ion o dus in he ai . Addi ionally, he clima ic a iables o he chosen day,
such as ai empe a u e and adia ion, should be ep esen a i e o he wa m season. I
is also impo an ha he wind speed on he selec ed day is low and below he annual
a e age o a oid he al e a ion o he e ec s o he u ban hea island [68].
Addi ionally, he chosen day mus align wi h he sa elli e da a acquisi ion schedule,
ensu ing ha ypical wa m wea he coincides wi h he sa elli e obse a ion. The acquisi ion
schedules o a ious sa elli e missions, including he Landsa 9 used by his esea ch [
64
],
a e publicly accessible online.
2.1.2. Land Use–Land Co e
The ini ial s ep in ol es ob aining he LULC laye in o ma ion o he ci y om he
open-access CORINE p og amme da abase [
37
]. The mos ecen upda e om 2018, (i
needs o be e ised wi h ac ualized images in apidly changing u ban a eas) p o ides a
GIS ec o laye wi h s anda dized LULC da a ea u ing a geome ic esolu ion accu acy o
<10 m [
37
]. This da ase o e s c i ical insigh s in o he ypes o land po ions wi hin each
zone, which a e s ongly co ela ed wi h adia ion exposu e and ypical he mal beha iou .
Fu he mo e, he map iden i ies esiden ial a eas, which a e u ilized o c opping and
ocusing on subsequen s ages o he s udy. The use o his classi ica ion allows, on one
hand, he subdi ision o he ci y in o globally ecognized land zones, and on he o he , he
iden i ica ion o u ban e olu ion pa e ns. I acili a es easy compa ison o his ci y wi h
o he s and p o ides a p elimina y es ima e o he expec ed he mal beha iou based on
land use ypes and ypical ma e ials, all wi h a high spa ial esolu ion o 10 m app op ia e
o u ban mic o-scale s udies.
2.1.3. Ci y’s Land Su ace Tempe a u e
Once he u ban case s udy and da e ha e been de e mined, and he land co e in o -
ma ion con ex ualized, he ocus shi s o analyzing he LST a a mic o-u ban scale. Diu nal
LST images o he u ban su ace laye a e ob ained om he Landsa 9 sa elli e [
16
]. These
images a e eely accessible on he Ea h Explo e pla o m p o ided by he USGS [
69
],
whe e he mal band L10 da a a e made a ailable. Landsa 9 in oduces he no el Le el 2
p ocessing p oduc , which p o ides spec al and a mosphe ic co ec ions ac oss a ious
bands. As epo ed in he li e a u e and by he da a p o ide [
70
], he LST can be de i ed
wi h high accu acy ( anging om 0.4 o 1.98 K) using minimal pos -p ocessing ia he QGIS
as e calcula o .
The Band 10-LST image can be downloaded in GeoTIFF o ma . Al hough he o iginal
da a acquisi ion SR o B-10 is 100
×
100 m, USGS p o ides i wi h a esampled SR o
30
×
30 m, making i equal o he Landsa 9 non- he mal bands. This as e ile is
subsequen ly uploaded in o QGIS, whe e u ban map laye s, sou ced om au ho i a i e
bases such as cadas al websi es [
65
] and global open-access eposi o ies [
71
], a e al eady
in eg a ed. Subsequen ly, he SR o he he mal image is enhanced o imp o e he i-
sual in e p e a ion o he mal dis ibu ion a he mic o-u ban scale. To ha end, and
Remo e Sens. 2025,17, 231 6 o 27
h ough geop ocessing in QGIS, he image esolu ion is e ined o 5
×
5 m using a bicubic
4
×
4 Ke nel in e pola ion. This p ocess analyses he 16 nea es pixels o pe o m esam-
pling, hus imp o ing isualiza ion quali y. Bicubic in e pola ion is widely adop ed in
image p ocessing o enhancing image cla i y [
72
] and suppo ing eclassi ica ion asks [
73
].
The algo i hmic basis o Ke nel in ol es his bicubic in e pola ion me hod, which is chosen
o i s abili y o main ain he in eg i y o he o iginal da a while enhancing esolu ion [
72
].
This me hod ensu es accu acy by ca e ully conside ing he alues o he su ounding
pixels, hus a oiding he in oduc ion o a i ac s. Addi ionally, he in e pola ion p o-
cess is designed o p e en o e -smoo hing, which can obscu e impo an he mal de ails.
Main aining he o iginal empe a u e h esholds ensu es ha he e ined images a e bo h
accu a e and eliable while enabling e icien compu a ional p ocessing wi hin QGIS.
Once he escaled image is ob ained, i is delimi ed and c opped acco ding o he
adminis a i e bounda ies o he ci y and o e lapped wi h u ban laye s and building
oo p in s. The analysis hen speci ically a ge s he LST o s ee s and u ban open spaces
loca ed be ween buil s uc u es.
2.1.4. Residen ial A ea Delimi a ion and LCZ Classi ica ion
The s udy p io i izes homogeneous esiden ial se lemen s, wi h pa icula a en ion
o u ban public li able spaces such as s ee s, squa es, and unbuil a eas. To his end, i
is necessa y o delinea e he AOI o ocus exclusi ely on esiden ial-use zones. Indus ial
and in as uc u e a eas, which ypically exhibi signi ican ly highe diu nal LST alues, as
well as pa ks and la ge g een spaces wi h lowe LST alues, a e excluded as hey do no
accu a ely ep esen he mal pa e ns in esiden ial s ee s and public u ban spaces [
74
]. To
de ine his AOI, he CORINE LULC [
37
] map is u ilized o iden i y and c op esiden ial-
use a eas, which a e hen o e laid wi h he he mal LST map. The LST h esholds o he
selec ed AOI a e eassigned acco ding o he new LST bounda ies. The esul ing AOI is hen
classi ied in o LCZ ca ego ies [
27
]. This c oss-e alua ion o su ace empe a u e and LCZ is
no no el in he li e a u e, bu as in p e ious s udies [
28
–
30
], i helps o di ide he u ban
ab ic in o homogeneous zones, which, acco ding o he li e a u e, end o ha e simila
he mal beha iou s. Addi ionally, a complemen a y analysis is p oposed whe e u ban and
he mal aspec s a e combined wi h an e alua ion o ege a ion and he esul ing SVF. This
s eng hens he esul s and compa isons be ween zones and con i ms he hypo heses pu
o wa d by he au ho s o he o iginal LCZ s udy [27].
While au oma ed LCZ classi ica ion me hods a e widely acknowledged in he li e a-
u e [
58
,
75
], hey o en ace challenges in achie ing he esolu ion necessa y o mic o-u ban
scale analyses, pa icula ly due o hei dependency on he a ailabili y and quali y o ain-
ing a eas. As highligh ed by [
76
], au oma ed me hods a e e ec i e o la ge-scale analyses
bu may lack he speci ici y equi ed o accu a ely ep esen local u ban ea u es, as can be
seen in many a ailable maps [
77
]. On he con a y, LCZ classi ica ion, based on si e da a,
isual in e p e a ion, and expe knowledge, accu a ely ma ches he local ea u es [
27
,
78
],
bu can also become labou -in ensi e. This s udy adop s a hyb id GIS-based app oach,
combining de ailed GIS pa ame e s, expe knowledge, and sa elli e image y alida ion.
The classi ica ion p ocess was cu a ed in QGIS and supe ised by he au ho s’ knowledge
o egional u ban mo phology. This hyb id me hodology le e ages he ad an ages o
ensu e a eliable classi ica ion ailo ed o he speci ic case s udy cha ac e is ics. Al hough i
can become mo e ime-consuming, his app oach is pa icula ly sui able o single-ci y case
s udies whe e cap u ing mic o and local speci ici y is c i ical. Fo b oade -scale s udies,
howe e , emo e sensing and au oma ed me hods p o ide a mo e e icien and ep oducible
al e na i e, as no ed by [76].
Remo e Sens. 2025,17, 231 7 o 27
2.1.5. Ho spo s’ De ec ion and Mul i-C i e ia Assessmen
Once he ex ac ed esiden ial a ea LST as e o e laps wi h he LCZ classi ica ion,
he ho spo de ec ion is add essed. This s udy p oposes a wo-phase de ec ion o he mal
ho spo s, based on he dis ibu ion o empe a u es and he concen a ion and densi y o
ho zones. Ini ially, he analysis begins wi h he dis ibu ion o empe a u es wi hin he
h eshold, iden i ying ex eme alues and hei dis ibu ion. Subsequen ly, he empe a u e
qua iles o he AOI a e calcula ed, es ablishing he empe a u e alue equi alen o he
hi d qua ile as pa icula ly wa m, as p e iously used in he li e a u e [
56
]. Thus, he
i s phase isola es he a eas wi h he op 25% o empe a u es. Following his, using
QGIS so wa e ools, a p oximi y and densi y clus e analysis is conduc ed o ob ain uly
ep esen a i e ho spo s and igno e i ele an ones. Wi h he selec ed ho pixels and a
ans o ma ion o ec o s, a clus e ing p ocess is pe o med based on he o iginal da a g id,
in his case, a 100
×
100 m SR om Landsa 9. Clus e s o pixels con aining pa icula ly
wa m empe a u es and g ouped in se s la ge han one o iginal pixel a e conside ed.
A e his phase, he ho and ele an clus e s in p oximi y and densi y ha e been selec ed,
dis ega ding isola ed and non- ep esen a i e a eas. In his way, he ho spo s o he AOI
ha e been ob ained and can be ep esen ed on he map.
A e ha , wi h all he mal ho spo s ep esen ed in he ci y, his esea ch p oposes
he selec ion o wo speci ic ho spo a eas based on hei u ban uni o mi y. These wo
ho spo a eas a e compa ed wi h wo o he a eas ha exhibi lowe empe a u es. The main
u ban hea - ela ed pa ame e s o he inal ou selec ed a eas a e ex ac ed and assessed
o de e mine hei in luence on u ban o e hea ing. The me hodology p oposed allows a
discussion based on he c oss-analysis o hese pa ame e s esul s. They a e calcula ed
om open access and o icial sou ces da a, in he i s e m hey a e ob ained g aphically,
in he o m o maps o hea maps. Then, he main s a is ics a e ex ac ed in summa ized
ables, and inally, he alues dis ibu ion g aphs a e ob ained. In his way, a comple e
c oss-e alua ion can be made.
•Building en i onmen and pa emen s
The building laye s a e ob ained om cadas al sou ces [
65
], which in many coun ies
include in o ma ion on he geome y, a ea, heigh , and e en age o buildings. The pa emen
laye can be ob ained om municipali y open da a. Fou di e en pa ame e s a e s udied,
all using he o icial GIS laye in o ma ion.
-
Building su ace ac ion (BSF): a a io ha exp esses he pe cen age o he o al AOI
su ace ha is occupied by he loo a ea o buildings.
-
Floo a ea a io (FAR): buildings’ g oss loo a ea o he size o he lo upon which
hey a e buil .
-
Mean building heigh (MBH): he weigh ed a e age heigh o all buildings in he AOI.
-
Pa emen pe meabili y ac ion: a io o pe ious pa emen o he o al AOI
pa ed a ea.
•Land su ace empe a u e
The LST o he s udied a ea is analyzed on he unbuil a ea. This is shown as a
hea map, and he main s a is ical alues a e ex ac ed om he images using he QGIS
as e analysis ools. The mean, maximum, and minimum LST a e ob ained, subsequen ly,
he alues’ dis ibu ion pe pixel is analyzed.
•G een s uc u es
Two measu emen s a e assessed as hey ha e an impo an impac on sun adia ion
and LST.
Remo e Sens. 2025,17, 231 8 o 27
-
T ee canopy ac ion: a io o ee-co e ed a ea o he o al AOI a ea. Da a a e ob ained
om o icial local adminis a ion sou ces. Howe e , i can also be suppo ed by
LIDAR maps.
-
NDVI: s udies he quan i y and heal h o he ege a ion. Al hough i can be ob-
ained di ec ly om sa elli e images (Landsa 8–9 o Sen inel 2), in his case, C op
Moni o ing [66], was used.
The esul s a e shown, i s ly, as a 5
×
5 m SR hea map supe imposed on he ci y’s
u ban laye s. Secondly, i s main s a is ical alues—mean and maximum NDVI a e ob ained
om he as e (minimum is always 0 in ci ies, as i ep esen s a eas wi h no ege a ion,
nega i e alues ha a e used o ep esen wa e , snow o clouds could no be p esen in
he AOI).
•SVF
SVF was calcula ed based on a 3D model impo ed om QGIS u ban laye s using
Rhinoce os-7 3D CAD so wa e. G aphic p og amming plugins G asshoppe , U bano
1.4.2 [
79
] and Ladybug 1.7.0 [
80
] we e hen used. This pape has he no el y o conside ing
he ees and he space unde hem in he conside a ion o he SVF, as mos o he s udy
only conside s he building con ex , o conside s he SVF on he op o ees, which is
inaccu a e. Thus, SVF is calcula ed based on he main u ban en i onmen (3D buildings
and ees), acco ding o p e ious s udies [
40
]. A 5
×
5 m SR is se o he pixels g id o he
esul ing image, as he LST as e . The SVF hea map is uploaded o QGIS and o e laps on
he u ban laye s. Finally, he main s a is ical pa ame e s, mean and maximum SVF, a e
ob ained o each AOI.
2.2. Field o Applica ion
The ield o applica ion o his esea ch is u ban se lemen s in wa m egions. Gi en
ha he aim is o iden i y ho spo s and analyze he causes and consequences o ho clima es
in u ban spaces, he s udy ocuses on ci ies loca ed in empe a e and ho clima e zones.
Fu he mo e, as he s udy is based on open GIS da a, a ailable geospa ial da a a e necessa y
o de elop he me hodology p ope ly.
2.3. Case S udy o Me hodology Applica ion
In o de o apply he me hodology p esen ed and o es he possibili ies in a eal
scena io, he case s udy selec ed is he ci y o Se ille in he sou he n Spanish egion o
Andalusia, one o he wa mes egions in Eu ope (Figu e 2). Se ille is he mos popula ed u -
ban se lemen in he egion, wi h 684,000 inhabi an s (las census 2022) in he municipali y.
The e o e, i is ca alogued as a me opoli an a ea acco ding o he OECD classi ica ion [
81
].
The ci y has a Csa Köppen clima e [
67
,
82
], cha ac e ized by ho and d y summe s, wa m
midseason, and empe a e win e s. Se ille can be conside ed a ep esen a i e example o a
medium-la ge ci ies in he Medi e anean a ea. I is a signi ican u ban se lemen subjec ed
o a wa m clima e, ea u ing a his o ically dense cen e and se e al ecen ly de eloped
ou e a eas wi h di e se u ban ypologies. The e o e, i s loca ion, u ban cha ac e is ics and
dis ibu ion, popula ion, and clima e make i a p ope example o sou he n Eu opean ci ies.
The esul s and conclusions de i ed om his s udy could be ex apola ed and compa ed
wi h hose om o he simila cases. Appendix A.1, a he end o he documen , shows
speci ic da a and clima e egis e s o Se ille o a ull yea .
Remo e Sens. 2025,17, 231 9 o 27
Remo e Sens. 2025, 17, x FOR PEER REVIEW 9 o 29
Figu e 2. Case s udy loca ion. Sou he n Eu ope LST du ing a hea wa e in he summe o 2023 (10
July 2023). (Sou ce: ep in ed/adap ed unde license CC BY-SA 3.0 IGO om ESA. [83], 2023).
3. Resul s and Discussion
This sec ion shows he esul s o he me hodology de ailed in Sec ion 2, now applied
o he ci y o Se ille, as a pilo case s udy, in o de o es he ope a ion o his u ban as-
sessmen me hod. In pa allel, he esul s a e also discussed in each subsec ion wi h di e se
ocuses, all suppo ed by he igu es.
3.1. A ea o S udy and Time F ame Selec ion o he Case S udy
The selec ed day is 29 Augus 2023. This day Se ille expe ienced a wa m day, ypical
o he season. Besides he sa elli e acquisi ion, he clima ic condi ions du ing he day we e
ep esen a i e o he wa m season. Appendix A.2 p o ides de ailed clima e da a o his
speci ic day. The eco ded da a a e compa ed wi h he a e age alues o a ypical day in
he wa m season in Se ille (15 June o 15 Sep embe ), showing a good ma ch:
• Clea day wi hou ele an episodes o pollu ion o a mosphe ic dus ;
• Mean ai empe a u e: 29 Augus : 30.3 °C _ Wa m season: 30.0 °C.;
• Mean global adia ion: 29 Augus : 270 W/m2 _ Wa m season: 295 W/m2;
• Wind speed: 29 Augus : 2.07 m/s _ Wa m season: 2.78 m/s.
I should also be no ed ha he e we e se e e d ough condi ions in he egion in he
selec ed pe iod; he e o e, mos o he g ass and wild low ege a ion was d y due o he
summe hea and wa e lack, which affec s he effec i e low ege a ion su ace empe a-
u e.
3.2. Land Use–Land Co e Resul s
A i s con ex o he ci y is p o ided, as well as he LULC map, which allows one o
dis inguish be ween di e se u ban uses and land ypes. This is ob ained om he Cope -
nicus’ CORINE maps [37]. The laye is hen p ocessed in QGIS wi h only minimal co ec-
ions. The esul ing map is shown in Figu e 3.
Figu e 2. Case s udy loca ion. Sou he n Eu ope LST du ing a hea wa e in he summe o 2023
(10 July 2023). (Sou ce: ep in ed/adap ed unde license CC BY-SA 3.0 IGO om ESA. [83], 2023).
3. Resul s and Discussion
This sec ion shows he esul s o he me hodology de ailed in Sec ion 2, now applied
o he ci y o Se ille, as a pilo case s udy, in o de o es he ope a ion o his u ban
assessmen me hod. In pa allel, he esul s a e also discussed in each subsec ion wi h
di e se ocuses, all suppo ed by he igu es.
3.1. A ea o S udy and Time F ame Selec ion o he Case S udy
The selec ed day is 29 Augus 2023. This day Se ille expe ienced a wa m day, ypical
o he season. Besides he sa elli e acquisi ion, he clima ic condi ions du ing he day we e
ep esen a i e o he wa m season. Appendix A.2 p o ides de ailed clima e da a o his
speci ic day. The eco ded da a a e compa ed wi h he a e age alues o a ypical day in
he wa m season in Se ille (15 June o 15 Sep embe ), showing a good ma ch:
•Clea day wi hou ele an episodes o pollu ion o a mosphe ic dus ;
•Mean ai empe a u e: 29 Augus : 30.3 ◦C _ Wa m season: 30.0 ◦C;
•Mean global adia ion: 29 Augus : 270 W/m2_ Wa m season: 295 W/m2;
•Wind speed: 29 Augus : 2.07 m/s _ Wa m season: 2.78 m/s.
I should also be no ed ha he e we e se e e d ough condi ions in he egion in he
selec ed pe iod; he e o e, mos o he g ass and wild low ege a ion was d y due o he
summe hea and wa e lack, which a ec s he e ec i e low ege a ion su ace empe a u e.
3.2. Land Use–Land Co e Resul s
A i s con ex o he ci y is p o ided, as well as he LULC map, which allows one
o dis inguish be ween di e se u ban uses and land ypes. This is ob ained om he
Cope nicus’ CORINE maps [
37
]. The laye is hen p ocessed in QGIS wi h only minimal
co ec ions. The esul ing map is shown in Figu e 3.
Remo e Sens. 2025,17, 231 16 o 27
he ci y, su ounded by ho a eas such as c op ields, indus y, o in as uc u e. Wi hin
hese neighbou hoods, a key ac o is he u ban planning employed. These a eas we e
designed wi h signi ican spacing be ween buildings, meaning high SVF, and he e o e,
g ea e exposu e o sola adia ion, as p e iously no ed [
27
]. Addi ionally, hese wide
and open public spaces usually lack subs an ial g een masses, esul ing in low NDVI
alues, which ansla es o a lack o shade and g een cooling. Finally, hese a eas a e o en
cha ac e ized using hea y ma e ials such as conc e e, cemen , and asphal pa king lo s,
all wi h medium o low albedo and high he mal ine ia, ensu ing o e hea ing and subse-
quen slow cooling h ough he p og essi e emission o longwa e adia ion in o he u ban
space. This analysis highligh s he in luence o bo h u ban planning and an h opogenic
ac o s on u ban he mal con igu a ion, unde sco ing he need o a deepe conside a ion o
hese aspec s.
I is necessa y o highligh ha his ype o u ban zone, LCZ-5, is he mos p e alen
in he ci y o Se ille, accoun ing o 48% o he o al esiden ial su ace a ea (Table 2), bu
is also widesp ead ac oss all Eu opean ci ies [
45
]. Thus, his issue ac should conce n
u ban planne s.
The esul s al eady ob ained p o ide signi ican in o ma ion on u ban hea dis ibu ion
and allow he iden i ica ion o a eas o oppo uni y o u he analysis o in e en ion.
Howe e , his esea ch also p oposes a mo e in-dep h analysis app oach o selec ed zones,
s udying he main pa ame e s ela ing o u ban hea . The e o e, o es he possibili ies o
his c oss-assessed me hod, wo ho spo s a e compa ed wi hin o he wo empe a e a eas,
conside ed as con ol zones (Figu e 7). This enables he compa ison o hei indi idual
hea - ela ed pa ame e alues, discussing he causes o he di e ences in he LST and he
easons why some become ho spo s while o he s do no . The u ban con ex s o he selec ed
zones and he inal selec ed c opped a eas a e shown in Figu e 8.
Remo e Sens. 2025, 17, x FOR PEER REVIEW 17 o 29
Figu e 8. U ban con ex and loca ion o he selec ed assessed zones: Tempe a e con ol a eas: Z-01
(a) and Z-03 (c). Ho spo s: Z-02 (b) and Z-04 (d).
The ollowing sec ions show he esul s o he u ban pa ame e s ob ained acco ding
o he me hodology p e iously de ailed (Sec ion 2.1.5), o he selec ed zones. The esul s
o hese pa ame e s a e shown in he o m o maps (Figu e 9), while he main da a a e
calcula ed in Table 3. Classi ica ion o selec ed a eas acco ding o LCZ ypes:
• Z-01: Tempe a e a ea. His o ic ci y cen e zone, LCZ-3;
• Z-02: Ho spo s. No he n neighbou hood zone, LCZ-5;
• Z-03: Tempe a e a ea. Mode n ci y cen e zone, LCZ-2;
• Z-04: Ho spo . Eas e n neighbou hood zone, LCZ-5.
Figu e 8. U ban con ex and loca ion o he selec ed assessed zones: Tempe a e con ol a eas: Z-01 (a)
and Z-03 (c). Ho spo s: Z-02 (b) and Z-04 (d).
Remo e Sens. 2025,17, 231 17 o 27
The ollowing sec ions show he esul s o he u ban pa ame e s ob ained acco ding
o he me hodology p e iously de ailed (Sec ion 2.1.5), o he selec ed zones. The esul s
o hese pa ame e s a e shown in he o m o maps (Figu e 9), while he main da a a e
calcula ed in Table 3. Classi ica ion o selec ed a eas acco ding o LCZ ypes:
•Z-01: Tempe a e a ea. His o ic ci y cen e zone, LCZ-3;
•Z-02: Ho spo s. No he n neighbou hood zone, LCZ-5;
•Z-03: Tempe a e a ea. Mode n ci y cen e zone, LCZ-2;
•Z-04: Ho spo . Eas e n neighbou hood zone, LCZ-5.
Remo e Sens. 2025, 17, x FOR PEER REVIEW 18 o 29
Figu e 9. G aphical display o he analyzed u ban pa ame e s. F om he op: Z-01, Z-02, Z-03, and
Z-04.
Table 3. U ban da a esul s.
Zone LCZ Build. En . & Pa em . Land Su .
Tempe a u e G een S uc u es Sky View
Fac o
BSF (%) FAR
MBH
(m)
Pe . Su .
(%)
Mean
(°C)
Max.
(°C)
Min.
(°C)
T ee
Cnp. (%)
NDVI
Mean
NDVI
Max. Mean Max.
Z-01 LCZ-3 70.3% 2.3 9.8 0.1% 43.4 44.5 42.3 1.3% 0.09 0.88 0.34 0.82
Z-02 LCZ-5 32.5% 1.2 11.2 14.4% 46.4 49.7 44.7 9.3% 0.14 0.46 0.43 0.84
Z-03 LCZ-2 42.0% 2.0 14.7 8.5% 43.0 44.5 41.6 5.3% 0.22 0.81 0.38 0.81
Z-04 LCZ-5 25.2% 1.0 12.0 4.6% 45.6 48.6 44.2 13.3% 0.17 0.72 0.29 0.82
Z-04
Z-03
Z-02
Z-01
Figu e 9. G aphical display o he analyzed u ban pa ame e s. F om he op: Z-01, Z-02, Z-03,
and Z-04.
Remo e Sens. 2025,17, 231 18 o 27
Table 3. U ban da a esul s.
Zone LCZ Build. En . & Pa em . Land Su .
Tempe a u e G een S uc u es Sky View
Fac o
BSF
(%) FAR MBH
(m)
Pe .
Su .
(%)
Mean
(◦C)
Max.
(◦C)
Min.
(◦C)
T ee
Cnp.
(%)
NDVI
Mean
NDVI
Max. Mean Max.
Z-01 LCZ-3 70.3% 2.3 9.8 0.1% 43.4 44.5 42.3 1.3% 0.09 0.88 0.34 0.82
Z-02 LCZ-5 32.5% 1.2 11.2 14.4% 46.4 49.7 44.7 9.3% 0.14 0.46 0.43 0.84
Z-03 LCZ-2 42.0% 2.0 14.7 8.5% 43.0 44.5 41.6 5.3% 0.22 0.81 0.38 0.81
Z-04 LCZ-5 25.2% 1.0 12.0 4.6% 45.6 48.6 44.2 13.3% 0.17 0.72 0.29 0.82
3.5.1. Building En i onmen and Pa emen s
The i s column in Figu e 9shows he g aphical analysis o he buil and pa ed u ban
GIS laye in o ma ion.
•
Building su ace ac ion (BSF): The la ge di e ences in he pe cen age o a eas occu-
pied by buildings can easily be seen on he maps, as e lec ed in he esul s (Table 3).
The BSF pe cen age o Z-01, 70.3%, should be no ed, as i co esponds o an ex ensi e
and dense his o ic ci y cen e, while he ypical ange gi en in he li e a u e o his
LCZ is 40–70% [
27
]. This is ollowed by Z-03, wi h 42.0%, a low alue, despi e he LCZ
sou ce classi ica ion as dense ab ic. The pe cen ages o he o he wo zones—Z-02
and Z-04, ho spo s, and open u ban ab ic a eas, s and a 32.5% and 25.2%, espec i ely,
while he gi en ange o hese ypes o ab ic is 20–40%.
•
Floo a ea a io (FAR): Building heigh appea s shaded in g eyscale in he i s column
o Figu e 9, while Table 3shows he esul ing a io be ween he o al buil a ea and
he o al ex ension o he zone. Z-01 also has he highes FAR alue as i is he mos
densely buil zone, al hough i is lowe in heigh han o he zones. In con as , Z-04 is
he leas dense zone and has he lowes loo a ea a io.
•
Mean building heigh (MBH): The calcula ed da a a e shown in Table 3. The highes
mean heigh is ha o Z-03, 14.6 m, ollowed by Z-02 and Z-04, all de ined as mid ise
LCZ, wi h a cha ac e is ic heigh o 10–25 m [27].
•
Pa emen pe meabili y ac ion: This is shown in he o m o g een pa hs ( i s column
in Figu e 9, while Table 3shows he calcula ed da a). The e is a la ge di e ence
be ween he zones, wi h a minimum alue o 0.1% in Z-01, co esponding only o
a eas wi h ees; o he maximum alue o 14.4% in Z-02, whe e he e a e se e al open
squa es ull o pe ious e ains.
3.5.2. Land Su ace Tempe a u e
This is he main pa ame e measu ed o de e mine he in ensi y o ho spo s. The
second column in Figu e 9shows he conside able di e ences ound be ween he LST
o he di e se zones, wi h di e ences o up o 9
◦
C be ween a eas. In gene al, ho spo
zones Z-02 and Z-04 display highe empe a u es han he Z-1 and Z-3. Due o he spa se
u ban ab ic, and hus, highe SVF, sun adia ion hea s he u ban su aces u he , speeding
up and inc easing AT in he a ea due o he adian hea and ai con ec ion. Acco ding
o he calcula ed da a in Table 3, he Z-02 and Z-04 mean LST a e 3–4.5
◦
C highe han
in empe a e zones, while he maximum and minimum alues o he ho zones a e also
conside ably highe , wi h a 3–5 ◦C inc ease.
3.5.3. G een S uc u es
•
T ee canopy ac ion: An abs ac ep esen a ion o he ee canopy is shown in he i s
column in Figu e 9in he o m o g een ci cles; howe e , i s p esence and in ensi y a e
Remo e Sens. 2025,17, 231 19 o 27
be e ep esen ed in he hi d column, wi h he NDVI g aph. G een canopy calcula ed
da a a e in Table 3. The lowes alues a e ob ained by Z-01, he denses a ea, wi h
1.29% o ee co e . In con as , he highes alues a e hose o Z-04, he leas dense
a ea, wi h 13.3% o g een co e .
•
NDVI: Hea maps a e shown in he hi d column in Figu e 9, whe e majo di e ences
can be obse ed, as is he case in he calcula ed da a o Table 3. Again, he mos
ex eme si ua ion co esponds o Z-01, whe e he mean NDVI is 0.09, an ex emely de-
na u alized alue. Howe e , his zone displays he maximum NDVI alue, a ibu ed
o he p esence o a la ge heal hy ee in he middle o he cen al squa e, e en hough
he e is ha dly any ege a ion in he es o he a ea. Mo eo e , i is also wo h no ing
he high NDVI alue o Z-03 which, despi e ha ing a compac ab ic, has a mean NDVI
sligh ly highe han ha o o he open zones, while i s maximum is e en highe (0.81).
This is due o he p esence o a small u ban ga den in he middle o he zone. The
g aphics in Figu e 9show he clea dependency be ween he index and he ege a ion
plan in he i s column.
3.5.4. SVF
The sky iew ac o hea maps, shown in he ou h column in Figu e 9, exp ess no
only he building compac ness bu also he heigh and densi y o he ege a ion. The esul s
calcula ed a e shown in Table 3. I is no able ha Z-01, e en wi h a highe buil densi y,
does no ha e he minimum SVF. This is due o he low heigh o he building and he
low exis ence o ees ha block he sky iew. Mo eo e , he esul s show how e en he
open ab ic zones, Z-02 and Z-04, ha e medium-low main SVF alues, as he po en ial
exposu e allowed by he buildings is blocked by he exis ing ege a ion, and so, highe
NDVI. SVF, as he index ha measu es he sky exposu e, cons i u es an e icien indi idual
measu e o all he p e ious building densi y pa ame e s, condensing all he calcula ions
in o a single alue. The e o e, a conside able ela ion can also be obse ed be ween SVF
and LST. Al hough he e a e o he pa ame e s o be aken in o accoun , c oss- e e encing
SVF and LST esul s con i ms ha he highe he SVF, he highe he diu nal LST.
Once he esul s a e p esen ed (Figu e 9and Table 3), se e al aspec s can be discussed.
Two ho spo s AOI (Z-02 and Z-04) a e selec ed oge he wi h wo mo e empe a e a eas
(Z-01 and Z-03), in o de o ob ain a c oss-assessmen suppo ed by he esul s o he
u ban hea - ela ed pa ame e s. Mo eo e , a quan i a i e assessmen has been de eloped
in Figu e 10 o suppo he discussion o esul s. Finally, i is no ed ha he AOIs ha e
also been classi ied based on hei LCZ classi ica ion, which helps he compa ison be ween
di e en u ban ab ics and allows o ex apola ions based on hese s anda dized a che ypes
and expec ed an h opogenic pe o mance. In his sense, he ini ial buil en i onmen
analysis (Table 3) highligh s a main aspec . The calcula ed alues, associa ed wi h he
isual LCZ classi ica ion, s ongly co espond wi h he cha ac e is ic anges gi en by he
o iginal sou ce [
27
]. This con i ms he e ec i eness o hyb id sa elli e and GIS-suppo ed
classi ica ion agains au oma ic algo i hms ha may be inaccu a e o ine scales.
The esul s demons a e he high impac ha SVF has o e he LST, becoming a c ucial
pa ame e o be analyzed. In ac , his me hod includes a no el SVF calcula ion a he
mic o-u ban scale ha p ope ly conside s he e ec o ees, a c i ical u ban ea u e no
conside ed by some p e ious esea ch [
61
]. This is also p o ed by compa ing NDVI and
SVF dis ibu ion (Figu e 10). Mo eo e , he ob ained esul s, shown in Figu e 9and mos ly
in Figu e 10 also p o e how he SVF becomes one o he p incipal LST- ela ed ac o s.
As a esul , he LCZ classi ica ion o an u ban a ea also e lec s his end, as p e iously
shown in Figu e 6. Wi hin he analyzed AOIs, he ho spo s a e p ima ily loca ed in LCZ-5,
cha ac e ized by i s spa se u ban ab ic, while he coole , empe a e a eas a e concen a ed
Remo e Sens. 2025,17, 231 20 o 27
in he dense and g eene zones o LCZ-3 and LCZ-2. Howe e , no all LCZ classes exhibi
he same he mal beha iou , as highligh ed in Figu e 10. This a ia ion a ises om he
b oad na u e o he LCZ classi ica ion, which encompasses di e se u ban ab ic ypes in o
gene alized classes; howe e , dis inc pa e ns eme ge, o e ing aluable insigh s.
Remo e Sens. 2025, 17, x FOR PEER REVIEW 20 o 29
NDVI sligh ly highe han ha o o he open zones, while i s maximum is e en
highe (0.81). This is due o he p esence o a small u ban ga den in he middle o he
zone. The g aphics in Figu e 9 show he clea dependency be ween he index and he
ege a ion plan in he i s column.
3.5.4. SVF
The sky iew ac o hea maps, shown in he ou h column in Figu e 9, exp ess no
only he building compac ness bu also he heigh and densi y o he ege a ion. The e-
sul s calcula ed a e shown in Table 3. I is no able ha Z-01, e en wi h a highe buil den-
si y, does no ha e he minimum SVF. This is due o he low heigh o he building and
he low exis ence o ees ha block he sky iew. Mo eo e , he esul s show how e en
he open ab ic zones, Z-02 and Z-04, ha e medium-low main SVF alues, as he po en ial
exposu e allowed by he buildings is blocked by he exis ing ege a ion, and so, highe
NDVI. SVF, as he index ha measu es he sky exposu e, cons i u es an efficien indi id-
ual measu e o all he p e ious building densi y pa ame e s, condensing all he calcula-
ions in o a single alue. The e o e, a conside able ela ion can also be obse ed be ween
SVF and LST. Al hough he e a e o he pa ame e s o be aken in o accoun , c oss- e e -
encing SVF and LST esul s con i ms ha he highe he SVF, he highe he diu nal LST.
Once he esul s a e p esen ed (Figu e 9 and Table 3), se e al aspec s can be discussed.
Two ho spo s AOI (Z-02 and Z-04) a e selec ed oge he wi h wo mo e empe a e a eas
(Z-01 and Z-03), in o de o ob ain a c oss-assessmen suppo ed by he esul s o he u -
ban hea - ela ed pa ame e s. Mo eo e , a quan i a i e assessmen has been de eloped in
Figu e 10 o suppo he discussion o esul s. Finally, i is no ed ha he AOIs ha e also
been classi ied based on hei LCZ classi ica ion, which helps he compa ison be ween
diffe en u ban ab ics and allows o ex apola ions based on hese s anda dized a che-
ypes and expec ed an h opogenic pe o mance. In his sense, he ini ial buil en i on-
men analysis (Table 3) highligh s a main aspec . The calcula ed alues, associa ed wi h
he isual LCZ classi ica ion, s ongly co espond wi h he cha ac e is ic anges gi en by
he o iginal sou ce [27]. This con i ms he effec i eness o hyb id sa elli e and GIS-sup-
po ed classi ica ion agains au oma ic algo i hms ha may be inaccu a e o ine scales.
Figu e 10. Quan i a i e assessmen o he analyzed AOI’s u ban pa ame e s.
The esul s demons a e he high impac ha SVF has o e he LST, becoming a c u-
cial pa ame e o be analyzed. In ac , his me hod includes a no el SVF calcula ion a he
mic o-u ban scale ha p ope ly conside s he effec o ees, a c i ical u ban ea u e no
conside ed by some p e ious esea ch [61]. This is also p o ed by compa ing NDVI and
SVF dis ibu ion (Figu e 10). Mo eo e , he ob ained esul s, shown in Figu e 9 and mos ly
in Figu e 10 also p o e how he SVF becomes one o he p incipal LST- ela ed ac o s. As
Figu e 10. Quan i a i e assessmen o he analyzed AOI’s u ban pa ame e s.
Aligned wi h he abo e, he NDVI and he ee canopy co e also ha e a local ela ion
a a ine scale wi h LST, no only due o sun exposu e p o ec ion bu also due o he cooling
e ec s o g een s uc u es. This is clea ly shown in he SVF hea map (Figu e 9). Howe e ,
examining he SVF da a dis ibu ion o Z-02 and Z-03 in Table 3, no g ea di e ences a e
obse ed. These zones, wi h di e en LCZ classi ica ions, ha e simila SVF alues due o
he p esence o ege a ion. As a conclusion o his c oss-assessmen , a s ong ela ion a he
ine scale is obse ed be ween SVF and LST. Thus, g ea e u ban compac ness seems o
esul in lowe diu nal empe a u es.
Con a y o he p e iously discussed SVF-LST ela ion, Z-02 and Z-04 bo h ha e la ge
open u ban spaces wi h high SVF alues ( ou h column Figu e 9). Howe e , Z-02 eaches
much highe LST in hose (second column Figu e 9). Bo h AOIs seem o ha e se e al
p e ious soil a eas acco ding o he pa h in he i s column o Figu e 9; howe e , he
di e ence is e iden in he hi d column o Figu e 9. The NDVI hea map con i ms a g ea e
p esence o ac i e ege a ion in Z-04, bo h in he ee canopy ( ela ed o he i s column),
and in g een soils. High NDVI alues indica e ha he ege a ion has enough quali y
and wa e access o s ill p oduce cooling e ec s, which is no he case in unbuil a eas
o Z-02. This is also shown in he exposed a eas o Z-03, which pe o ms empe a e LST,
hanks o high NDVI alues, as con i med by Figu e 10. These nuanced esul s highligh
he impo ance o a mul i-pe spec i e a ine-scale analysis o such a complex eali y. Only
by c oss-assessing mul i-pa ame e da a, i is possible o each maximum in o ma ion and
accu a e conclusions.
3.6. S udy Limi a ions and Fu he Resea ch
To conclude, some s udy limi a ions should be no ed. Fi s ly, his me hod p oposes a
hyb id LCZ classi ica ion based on GIS pa ame e s, expe knowledge and isually cu a ed
su ey wi h sa elli e maps. Al hough i can become mo e ime-consuming, his ensu es he
accu acy o he classi ica ion a a ine scale. Howe e , u u e esea ch should explo e an
au oma ic classi ica ion me hod based on geop ocessing ha semi-au oma ically calcula es
u ban pa ame e s using GIS laye s da a and compa es hem wi h he LCZ classi ica ion,
which will accele a e he p ocess.
Remo e Sens. 2025,17, 231 21 o 27
Fu he mo e, his esea ch is based on indi ec LST sa elli e acquisi ions wi h an o igi-
nal image SR o 100
×
100 m. The li e a u e and sa elli e p o ide s ensu e he quali y o he
ob ained da a o u ban s udies; howe e , i is impo an o no e ha hese da a a e s a is i-
cally esampled o ep esen a ion pu poses. The eal u ban en i onmen highly depends
on he p ope ies o each ma e ial and ends o be sha pe and mo e he e ogeneous. Also,
di ec measu emen s (LST, AT, and o he s) will be necessa y o subsequen in es iga ions
ha ocus mo e in-dep h on he localized ho a eas mic oclima e.
Ano he ele an aspec o no e is ha only one day o diu nal hea has been analyzed.
I is well known ha u ban hea has a di e en beha iou du ing he day and nigh [
19
].
Howe e , highe empe a u es a e eached du ing he day. This a ec s no only u ban
ou doo com o bu also indoo condi ions and cooling ene gy consump ion [
5
,
89
]. This
is impo an o ake in o accoun when wo king on u ban clima e esilience. Some li -
e a u e [
6
] ocuses on UHI mi iga ion echniques, whe e high SVF a eas a e ex emely
bene icial due o hei abili y o elease hea o he sky a nigh ime. Howe e , as his
esea ch has p o ed, he e is also a no able ela ionship be ween SVF and diu nal hea
exposu e. As one o he main aims o esea ch in u ban clima ic s udies is o imp o e
he li es o ci y esiden s, a holis ic app oach o u ban hea mus be aken. In his sense,
u he esea ch should p opose a balanced solu ion o mi iga e hea du ing he day-
ime, bu also allow i o be eleased du ing nigh ime; ha is maximizing he u ban hea
cycle mi iga ion [10].
In addi ion, once his me hodology is es ablished, u he esea ch should ex end
his app oach o mo e ci ies wi h di e en clima es, as he p esen esea ch has ocused
only on one ci y, one clima e case s udy. This could assess he me hodology’s capabili ies
in di e se clima es and loca ions, which would p o ide a subs an ial clima ic da abase.
This could se e o u he in es iga ions, such as inding and compa ing co ela ions
be ween a ious u ban pa ame e s depending on he ci y’s clima e, he eby expanding he
s udy’s conclusions.
Finally, as he aim o his esea ch is o conduc a s aigh o wa d analysis o iden i y
ho spo s in he ci y, i employs a low- esou ce and easily add essed me hodology ha
allows o he iden i ica ion o c i ical zones o a eas o oppo uni y. Thus, his is no
an exhaus i e hea analysis bu a he a diagnosis and iden i ica ion o a eas using he
po en ial o emo e sensing. Howe e , once c i ical ho spo s ha e al eady been loca ed,
mo e ad anced spa io empo al analysis me hods would be necessa y o signi ican ly
enhance he examina ion o he hea en i onmen and i s d i ing ac o s.
4. Conclusions
This pape p o ides an a o dable GIS-based me hodology, p esen ed as a s ep-by-s ep
guideline ha analyses wi h a c oss-assessmen he u ban hea . The main no el y o his
s udy lies in p esen ing an easily app oachable me hodology ha , based on a weal h o
knowledge and p e ious s udies, and using simple compu a ional ools, all based on open
da a and so wa e, can p o ide a solu ion o he apid diagnosis and de ec ion o ho spo s
in ci ies. Such con ibu ion is impo an o u ban he mal en i onmen assessmen , es-
pecially du ing p olonged hea wa es and syne gy wi h UHI phenomena o de ec and
measu e u ban he mal ho spo s, g aphically showing hei loca ion in he u ban ab ic.
Fu he mo e, all his esea ch has been de eloped based on s anda dized GIS open da a
in o ma ion om o icial sou ces and can be p ocessed on pe sonal compu e s wi h ee
use - iendly so wa e. This makes he guidelines accessible o designe s and policymake s.
The e o e, his me hodology can be ex apola ed and ep oduced in mos wa m ci ies,
cons i u ing in i sel a ecommenda ion o u ban sus ainabili y policy and clima e change
mi iga ion, as i se es as a powe ul ool o la ge-scale p elimina y diagnosis.
Remo e Sens. 2025,17, 231 22 o 27
The applica ion o he me hodology in he speci ic case s udy o Se illa ci y has ini ially
illed in ele an in o ma ion on u ban hea pe o mance. In his case, di e ences in mo e
han 10
◦
C in LST ha e been ound wi hin esiden ial a eas, while he ci y ho spo s ha e
been loca ed and mapped, ob aining ha 11% o he esiden ial a eas su e a highe LST
exposu e. Mo eo e , i has been shown ha he mos ex ended u ban ab ic, LCZ-5 a eas
(Open mid ise buil ype acco ding o S ewa and Oke [
27
]), is mo e p one o su e high
hea exposu e du ing he day. In addi ion, hanks o he ine spa ial esolu ion, u ban
measu able pa ame e s, such as compac ness, SVF, ege a ion and i s quali y o ypes o
u ban ma e ials, ha e been ound o be c ucial o imp o ing o wo sening he diu nal
he mal com o o ci y inhabi an s.
The combina ion o high- esolu ion he mal images wi h he simul aneous analysis
o hese di e se u ban pa ame e s has p o ed o be e y use ul in p o iding ex ensi e
knowledge o hea pe o mance. This ype o c oss-assessmen da a allows a new p elimi-
na y app oach ha ocuses on he diu nal hea , s udied less han noc u nal hea , e en i
his p oduces he highes empe a u e and cooling ene gy demand peaks. Al hough his
esea ch has ocused on his aspec , u u e s udies should conside he whole day hea cycle
pe o mance in o de o imp o e unde s anding o he ci y clima es. Beyond he key limi-
a ion iden i ied in he p e ious sec ion, ha could be add essed as u u e de elopmen s
om his s udy. In his sense, i is necessa y o op imize he sa elli e scanning equency
and mos ly, he SR, wi h compa a i e day and nigh ine images, which can analyze he
e olu ion o he ci y’s he mal pe o mance in di e en imes and zones. Howe e , his will
depend on pa icula eques s o a pa icula sweep o he sa elli es. Bo h he cu en and
u u e esul s will op imize u ban com o and imp o e he ene gy e iciency o buildings.
The eplicabili y o his me hodology in o he ci ies could p o ide a aluable i s
app oach, making i possible o o ganize and p io i ize mo e in-dep h s udies. This con-
ibu es o p o iding a use ul and a o dable diagnos ic ool o de ec ulne able zones
ha can be con e ed in o a eas o oppo uni y o in e en ions. These aspec s should be
aken in o accoun by public adminis a ions when p oposing u u e in e en ions o u ban
e u bishmen s, as his will help o gua an ee mo e li eable u ban spaces and imp o e he
sus ainabili y o ci ies agains o e hea ing haza ds.
Au ho Con ibu ions: Concep ualiza ion, C.G.-M.; me hodology, J.S.-C. and A.S.-J.; so wa e, J.S.-C.;
alida ion, A.S.-J. and C.R.-G.; o mal analysis, J.S.-C.; in es iga ion, J.S.-C. and A.S.-J.; esou ces,
C.R.-G. and C.G.-M.; da a cu a ion, J.S.-C.; w i ing—o iginal d a p epa a ion, J.S.-C. and A.S.-J.;
w i ing— e iew and edi ing, C.R.-G. and C.G.-M.; isualiza ion, J.S.-C.; supe ision, C.G.-M.; p ojec
adminis a ion, C.G.-M.; unding acquisi ion, C.R.-G. and C.G.-M. All au ho s ha e ead and ag eed
o he published e sion o he manusc ip .
Funding: This wo k has been suppo ed by he p ojec PID2021-124539OB-I00 unded by MI-
CIU/AEI/10.13039/501100011033 and by “ERDF A way o making Eu ope”, p ojec TED2021-
129347B-C21 unded by MICIU/AEI/10.13039/501100011033 and by he “Eu opean Union Nex Gen-
e a ionEU/PRTR”; and p edoc o al con ac g an ed o J.S.C (FPU21/02458).
Da a A ailabili y S a emen : The o iginal con ibu ions p esen ed in his s udy a e included in he
a icle. Fu he inqui ies can be di ec ed o he co esponding au ho .
Acknowledgmen s: The au ho s wan o acknowledge USGS, NASA, and ESA-Cope nicus o
p o iding Landsa 9, LULC and he mal open-access images; also, o Ca as o and Ay o. de Se illa o
p o iding open GIS da a; AEMe , and he Ayuda de In e nacionalización de In es igación IUACC-23
y VII P.P. US.
Con lic s o In e es : The au ho s decla e no con lic s o in e es .
Remo e Sens. 2025,17, 231 23 o 27
Nomencla u e and Abb e ia ions
AOI A ea o In e es SDGs Sus ainable De elopmen Goals
AT Ai Tempe a u e SR Spa ial Resolu ion
ESA Eu opean Space Agency SUHI Su ace U ban Hea Island
GIS Geog aphical In o ma ion Sys em SVF Sky View Fac o
LCZ Local Clima e Zone SVQ Se ille
LST Land Su ace Tempe a u e TIRS The mal In a ed Senso
LULC Land Use–Land Co e UHI U ban Hea Island
NDVI No malized Di e ence Vege a ion Index UCI U ban Cooling Island
RH Rela i e Humidi y UN Uni ed Na ions
Appendix A.
Appendix A.1. Se ille’s Clima e
The ollowing images show he s a is ical annual hou ly cha de eloped wi h he las
a ailable o icial egis e s (2007–2021). The main clima e pa ame e s ela ed o LST a e
exp essed as ollows: AT in ◦C (Figu e A1) and global adia ion in W·h/m2(Figu e A2).
Remo e Sens. 2025, 17, x FOR PEER REVIEW 24 o 29
Appendix A
Appendix A.1. Se ille’s Clima e
The ollowing images show he s a is ical annual hou ly cha de eloped wi h he
las a ailable official egis e s (2007–2021). The main clima e pa ame e s ela ed o LST
a e exp essed as ollows: AT in °C (Figu e A1) and global adia ion in W·h/m2 (Figu e A2).
Figu e A1. Annual hou ly cha o ai empe a u e (°C).
Figu e A2. Annual hou ly cha o di ec sola adia ion (W·h/m2).
Appendix A.2. S udied Day Reco ded Clima e
The clima e du ing he analyzed day was eco ded by an own wea he s a ion, placed
in he ci y. Ai empe a u e and global ho izon al adia ion a e shown in Figu e A3.
Figu e A3. Hou ly ai empe a u e and global adia ion in Se ille 29 Augus 2023, measu ed by an
own me eo ological s a ion in he ci y.
Re e ences
1. IPCC. Fi h Assessmen Repo . In Clima e Change 2014; IPCC: Gene a, Swi ze land, 2014.
2. IPCC. Clima e Change 2022: Impac s, Adap a ion and Vulne abili y; IPCC: Gene a, Swi ze land, 2022.
20
25
30
35
40
0
200
400
600
800
1000
01234567891011121314151617181920212223
(°C)
(W/m2) G. Rad. (W/m2) Ai Temp. (°C)
Figu e A1. Annual hou ly cha o ai empe a u e (◦C).
Remo e Sens. 2025, 17, x FOR PEER REVIEW 24 o 29
Appendix A
Appendix A.1. Se ille’s Clima e
The ollowing images show he s a is ical annual hou ly cha de eloped wi h he
las a ailable official egis e s (2007–2021). The main clima e pa ame e s ela ed o LST
a e exp essed as ollows: AT in °C (Figu e A1) and global adia ion in W·h/m2 (Figu e A2).
Figu e A1. Annual hou ly cha o ai empe a u e (°C).
Figu e A2. Annual hou ly cha o di ec sola adia ion (W·h/m2).
Appendix A.2. S udied Day Reco ded Clima e
The clima e du ing he analyzed day was eco ded by an own wea he s a ion, placed
in he ci y. Ai empe a u e and global ho izon al adia ion a e shown in Figu e A3.
Figu e A3. Hou ly ai empe a u e and global adia ion in Se ille 29 Augus 2023, measu ed by an
own me eo ological s a ion in he ci y.
Re e ences
1. IPCC. Fi h Assessmen Repo . In Clima e Change 2014; IPCC: Gene a, Swi ze land, 2014.
2. IPCC. Clima e Change 2022: Impac s, Adap a ion and Vulne abili y; IPCC: Gene a, Swi ze land, 2022.
20
25
30
35
40
0
200
400
600
800
1000
01234567891011121314151617181920212223
(°C)
(W/m2) G. Rad. (W/m2) Ai Temp. (°C)
Figu e A2. Annual hou ly cha o di ec sola adia ion (W·h/m2).
Appendix A.2. S udied Day Reco ded Clima e
The clima e du ing he analyzed day was eco ded by an own wea he s a ion, placed
in he ci y. Ai empe a u e and global ho izon al adia ion a e shown in Figu e A3.
Remo e Sens. 2025,17, 231 24 o 27
Remo e Sens. 2025, 17, x FOR PEER REVIEW 24 o 29
Appendix A
Appendix A.1. Se ille’s Clima e
The ollowing images show he s a is ical annual hou ly cha de eloped wi h he
las a ailable official egis e s (2007–2021). The main clima e pa ame e s ela ed o LST
a e exp essed as ollows: AT in °C (Figu e A1) and global adia ion in W·h/m2 (Figu e A2).
Figu e A1. Annual hou ly cha o ai empe a u e (°C).
Figu e A2. Annual hou ly cha o di ec sola adia ion (W·h/m2).
Appendix A.2. S udied Day Reco ded Clima e
The clima e du ing he analyzed day was eco ded by an own wea he s a ion, placed
in he ci y. Ai empe a u e and global ho izon al adia ion a e shown in Figu e A3.
Figu e A3. Hou ly ai empe a u e and global adia ion in Se ille 29 Augus 2023, measu ed by an
own me eo ological s a ion in he ci y.
Re e ences
1. IPCC. Fi h Assessmen Repo . In Clima e Change 2014; IPCC: Gene a, Swi ze land, 2014.
2. IPCC. Clima e Change 2022: Impac s, Adap a ion and Vulne abili y; IPCC: Gene a, Swi ze land, 2022.
20
25
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35
40
0
200
400
600
800
1000
01234567891011121314151617181920212223
(°C)
(W/m2) G. Rad. (W/m2) Ai Temp. (°C)
Figu e A3. Hou ly ai empe a u e and global adia ion in Se ille 29 Augus 2023, measu ed by an
own me eo ological s a ion in he ci y.
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