SPECIAL ISSUE |RESEARCH PAPER
h ps://doi.o g/10.1071/WF22102
A sa elli e-based bu ned a ea da ase o he no he n bo eal
egion om 1982 o 2020
José-And és Mo eno-Ruiz
A
, José-Ra ael Ga cía-Láza o
A
, Manuel A belo
B,*
and
Ped o A. He nández-Leal
B
ABSTRACT
Backg ound. Fi es in he bo eal o es occu wi h na u al equencies and pa e ns. Bu ned a ea
(BA) is an essen ial a iable in assessing he impac o clima e change in bo eal egions. Aims. Spa ial
wild i e occu ence da a since he 1950s a e a ailable o No h Ame ica. Howe e , he e a e no
eliable da a o Eu asia, mainly o Sibe ia, du ing he 1980s and 1990s. Me hods. A Bayesian-
ne wo k algo i hm was applied o he Long-Te m Da a Reco d (LTDR) Ve sion 5 o gene a e a BA
Da aSe (BA-LTDR-DS) o he Bo eal egion om 1982 o 2020, alida ed using o icial e e ence
da a and compa ed wi h he MODIS MCD64A1 p oduc . Key esul s. A high co ela ion (>93%)
wi h all he e e ence BA da ase s was ound. BA-LTDR-DS da a g ouped by decades es ima ed a
linea inc ease in BA o 4.47 million ha/decade. This end p o ides e idence o how global wa ming
a ec s i e ac i i y in hese bo eal o es s. Conclusions. BA-LTDR-DS cons i u es a unique da a
sou ce o he p e-MODIS e a, and becomes a eliable sou ce when o he p oduc s wi h highe
spa ial/spec al esolu ion a e no a ailable. Implica ions. The BA-LTDR-DS da ase cons i u es
he longes ime se ies de eloped o he bo eal egion a his spa ial esolu ion. BA-LTDR-DS
could be used as inpu in global clima e models, helping imp o e wild i e p edic ion capabili ies and
unde s and he in e ac ions be ween i e, clima e and ege a ion dynamics.
Keywo ds: AVHRR, Bayesian ne wo k algo i hm, bo eal o es , bu ned a ea mapping, Eu asia,
LTDR, MODIS, No h Ame ica, emo e sensing, Sibe ia, ime se ies analysis.
In oduc ion
The bo eal o es is he mos ex ensi e e es ial biome; i occupies ~14% o land on
Ea h in a ci cumpola bel su ounding he suba c ic egions o he no he n hemisphe e.
Two- hi ds o hese o es s a e in Eu asia (Scandina ia and Russia), he emaining hi d
in No h Ame ica (Canada and Alaska). Bo eal o es s play a c i ical ole in egula ing
clima e and he global ca bon cycle in he Ea h–a mosphe e sys em (Chapin e al. 2000;
Kasischke e al. 2005). Bo eal o es s ha e been conside ed o yea s as a ca bon sink
(Jobbágy and Jackson 2000; Ciais e al. 2010; Pan e al. 2011). In ac , mo e ca bon is
s o ed in he bo eal o es egions han in any o he egion o he plane , possibly up o
wice as much ca bon as is s o ed in opical o es s (B adshaw and Wa ken in 2015).
Howe e , ecen s udies show ha bo eal o es ca bon sinks could e en be becoming a
ne sou ce o emissions (Bonan 2008; Ku z e al. 2008; B adshaw and Wa ken in 2015;
Po ie e al. 2019; Eckdahl e al. 2022). The apid wa ming ha he bo eal and A c ic
egions ha e expe ienced o e he pas 30 yea s is modi ying he dynamics o na u al
dis u bances ha we e his o ically domina ed by i e (Walsh 2014). This anomalous
inc ease in empe a u e al e s he humidi y o he uels and, he e o e, modi ies he
se e i y, he na u al egime o bo eal o es i es and he bu ned a ea, which leads, in
u n, o possible eedback e ec s on clima e change (Goldamme and Fu yae 1996;
Flannigan e al. 2005; Balshi e al. 2009a, 2009b; Tchebako a e al. 2009; Geo giadi e al.
2010; de G oo e al. 2013; Kelly e al. 2013; Co ield e al. 2019). The moni o ing o
hese changes and he analysis o u u e scena ios a e o i al impo ance o implemen
Fo ull lis o au ho a ilia ions and
decla a ions see end o pape
*Co espondence o:
Manuel A belo
Depa amen o de Física, Uni e sidad de La
Laguna, 38200 San C is óbal de La Laguna,
Spain. Email: [email p o ec ed]
Recei ed: 22 June 2022
Accep ed: 15 Ap il 2023
Published: 4 May 2023
Ci e his:
Mo eno-Ruiz J-A e al. (2023)
In e na ional Jou nal o Wildland Fi e
32(6), 854–871. doi:10.1071/WF22102
© 2023 The Au ho (s) (o hei
employe (s)). Published by
CSIRO Publishing on behal o IAWF.
This is an open access a icle dis ibu ed
unde he C ea i e Commons A ibu ion-
NonComme cial-NoDe i a i es 4.0
In e na ional License (CC BY-NC-ND)
OPEN ACCESS
managemen policies on clima e change ha p o ec bo h
he bo eal o es and he ca bon i s o es (Bonan e al. 1992;
Kasischke e al. 1995; Fuchs e al. 2009; Shuman e al. 2011;
Loboda e al. 2012; K ylo e al. 2014; Ponoma e
e al. 2016).
Sa elli e emo e sensing has become an e ec i e ech-
nique o he iden i ica ion and spa io- empo al cha ac e -
isa ion o o es i es and bu ned a eas owing o i s co e age
on bo h a global and egional scale (And eae 1991; Cooke
e al. 1996; Dwye e al. 2000; Duncan 2003; Chu and Guo
2015). Cu en ly, di e en pla o ms p o ide sa elli e
images ha a e used in algo i hms o map bu ned a ea
(BA) (Vi cha 2011; Mouillo e al. 2014; Campagnolo
e al. 2016; Chen e al. 2016a, 2016b). The Mode a e-
Resolu ion Imaging Spec o adiome e (MODIS) on boa d
NASA’s Te a and Aqua sa elli es and he Ad anced Ve y
High Resolu ion Radiome e (AVHRR) on boa d he se ies
o Na ional Oceanic and A mosphe ic Adminis a ion
(NOAA) sa elli es a e examples o such senso s. They p o ide
daily image y and highe -le el land and a mosphe e p oduc s
o global mapping. Fo eliabili y and pe iod co e ed, he
mos equen ly used BA p oduc s a e MODIS Collec ion 6
(MCD64A1) (Giglio e al. 2018; Bosche i e al. 2019) om
he yea 2000 onwa ds, he Global Fi e Emissions Da abase
e sion 4 (GFED-4) BA a ailable om mid-1995 h ough o
he p esen (Giglio e al. 2013), and he mos ecen MODIS
p oduc , Fi e_cci 5.1, a ailable o he yea s 2001–2020
(Chu ieco e al. 2018). As Chu ieco e al. (2008) a gue,
‘Longe ime se ies da a a e equi ed o acqui e a be e
unde s anding o i e egimes, and hei mu ual ela ionships
wi h global wa ming.’ In spi e o he ac ha cu en sa elli e
emo e sensing sys ems (and hei de i ed i e p oduc s)
ha e enhanced empo al, spa ial and spec al esolu ions,
he a ailabili y o well-buil geospa ial ime se ies is sca ce
o Eu asia, especially o Sibe ia (de G oo e al. 2013; Chen
e al. 2016a; Ebe le e al. 2016; Ponoma e e al. 2016). In
addi ion, measu es om sa elli e da a p esen s ong disc ep-
ancies in BA es ima ions wi h ega d o epo ed da a in he
o icial eco ds (Soja e al. 2004; Sukhinin e al. 2004; Vi cha
2011; Kuka skaya 2013; Chen e al. 2016b), unlike No h
Ame ica, which has been well s udied (Kasischke and
F ench 1995; Al-Saadi e al. 2008; Chu ieco e al. 2008;
Soja e al. 2009; Kasischke e al. 2011; Mo eno Ruiz e al.
2012; Loboda e al. 2013; Mo eno-Ruiz e al. 2014a,
2014b, 2019).
In his pape , we p esen he Bu ned A ea Long-Te m Da a
Reco d Da aSe (BA-LTDR-DS), a unique long- e m BA p od-
uc o he bo eal o es in he Clima e Modelling G id (CMG)
esolu ion o ou decades (1982–2020). The CMG o ma ,
in a la i ude/longi ude geog aphic p ojec ion wi h a esolu-
ion o 0.05°, allows he BA-LTDR-DS da ase o be used as
inpu in global clima e models, helping o imp o e wild i e
p edic ion capabili ies and unde s and he in e ac ions
be ween i e, clima e and ege a ion dynamics in he no h-
e n bo eal egion.
Ma e ials and me hods
S udy egion
The s udy egion is geog aphically delimi ed by he pa allels
60°N and 72.5°N, di ided in u n in o wo sub- egions,
No h Ame ica and Eu asia (Fig. 1). The i s sub- egion
includes Alaska and he no he n pa o he Canadian
bo eal egion and is bounded a he uppe igh co ne o
he map a 72.5°N, 168.5°W and he bo om le co ne a
60°N 43.5°W. The No h Ame ican sub- egion con ains
app oxima ely one- hi d o he en i e bo eal egion o his
con inen based on he map desc ibed by B and (2009). The
second egion s e ches om Scandina ia o he Paci ic coas s
o Sibe ia and is limi ed a he uppe igh co ne a 72.5°N
5°E and he bo om le co ne a 60°N 180°E. E e g een
coni e ous o es s (pine and sp uce) p edomina e in he wo
sub- egions. Howe e , deciduous o es s, mainly bi ch and
la ch, can also be ound, wi h a spa ial dis ibu ion in luenced
by pos - i e dynamics (Roge s e al. 2015). The o es s o
No h Ame ica end o ha e mo e black sp uce, whi e sp uce
and pine species wi h b anches lowe o he g ound, hinne
ba k and se o inous cones ha open a e being bu ned by
i e. The Eu asian o es s ha e mo e i e- esis an species wi h
hick ba k, we e needles and ewe low b anches. In addi-
ion, be ween 25 and 30% o he landscape o he bo eal o es
egion is pea land (o ganic soils) (Go ham 1991; Wiede e al.
2006; Beaulne e al. 2021; Nelson e al. 2021). The p esence
o di e en species be ween No h Ame ican and Eu asian
o es s ma ks a no able di e ence in i e egimes be ween
he wo egions (de G oo e al. 2013). Fi e egimes can di e
in he same biome, and he bo eal o es s o No h Ame ica
and Eu asia a e an example o his (Haas e al. 2022). Fi es in
No h Ame ica end o be la ge and mo e in ense, wi h highe
uel consump ion (c own i es); in con as , i es in Eu asia
end o be less in ense, wi h lowe uel consump ion (su ace
i es) (Woos e and Zhang 2004; Wi h 2005; de G oo e al.
2013; Si no and Mokho 2018).
Re e ence da a
The only da abases ha include eliable in o ma ion on i es
de ec ed in bo eal o es s o mo e han ou decades a e
hose c ea ed and main ained by US and Canadian o es y
agencies. Fo Eu asia, howe e , he e is no eliable BA
e e ence se co e ing he s udy pe iod unde conside a ion
(1980–2020), wi h only MODIS senso -de i ed BA p oduc s
a ailable since 2000.
The Alaska Fi e Se ice (AFS), a Fo Wainw igh , AK,
USA, main ains a de ailed eco d o all de ec ed i e e en s
since 1940 (h ps:// i e.ak.blm.go /). This da abase, in
addi ion o p o iding he pe ime e o each BA, includes
addi ional i e- ela ed in o ma ion such as he managemen
o ice, i e name, geog aphical coo dina es, es ima ed a ea,
cause and ele an commen s. The pe ime e s a e always
delinea ed om he bes a ailable da a sou ce, which can
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855
include ae ial and high spa ial esolu ion sa elli e image y
(Landsa ype), as well as opog aphic maps. AFS ecognises
di e ences in he scale and accu acy o he pe ime e s
depending on he pe iod. Fi es la ge han 400 ha a e included
o i es be o e 1987, hose la ge han 40 ha om 1987 o
1989, whe eas om 1990 onwa ds, all i es wi h a BA la ge
han 4 ha a e conside ed.
The Canadian Na ional Fi e Da abase (CNFDB) is com-
piled and main ained by he Canadian Fo es Se ice (h ps://
cw is.c s.n can.gc.ca/ha/n db). CNFDB eco ds i e da a o all
sizes since 1959 ha include i e loca ion and pe ime e da a
supplied by Canadian e i o ial i e managemen agencies.
The in o ma ion con ained in he CNFDB may no be comple e
o e o - ee owing o he di e en mapping echniques used.
In addi ion, he comple eness and quali y o he da a may a y
be ween agencies and be ween yea s. The quali y o his
da abase and i s use ulness ha e been demons a ed in se e al
publica ions (Ami o e al. 2001; S ocks e al. 2003; Pa isien
e al. 2006; Bu on e al. 2008; Hanes e al. 2019).
Recen ly, he Canada Cen e o Mapping and Ea h
Obse a ion and he Canadian Fo es Se ice de eloped a
new da abase called he Na ional Bu ned A ea Composi e
(NBAC) (Hall e al. 2020; Skakun e al. 2021). NBAC imp o es
he BA de e mina ion o he CNFDB da abase using an au o-
ma ic me hod based on ho spo s and he No malized
Di e ence Vege a ion Index (NDVI) applied o high spa ial
esolu ion (less han 30 m) sa elli e image y (Hall e al.
2020). NBAC is a ailable o i es eco ded om 1986
onwa ds (Skakun e al. 2022).
The MODIS p oduc selec ed was he MCD64A1 Collec ion
6 (Giglio e al. 2018), based on da a om he Te a and Aqua
sa elli es and dis ibu ed by he Land P ocesses Dis ibu ed
Ac i e A chi e Cen e (LP DAAC). MCD64A1 is he NASA
o icial BA p oduc . I is a global mon hly g idded p oduc
o 500-m spa ial esolu ion. The algo i hm used o de ec
bu ned pixels conside s a mosphe ically co ec ed su ace
e lec ances o he sho wa e in a ed Bands 5 and 7 h ough
a no malised ege a ion index in conjunc ion wi h ac i e i e
da a a 1-km esolu ion. The p oduc con ains he es ima ed
bu n da e, unbu ned, o e en unmapped a eas i he e we e
no da a o es ablish bu ned/unbu ned s a us (Giglio e al.
2018). MCD64A1 C6 is cu en ly he p oduc wi h he high-
es eliabili y compa ed wi h he o he BA p oduc s (Padilla
e al. 2015; Mo eno-Ruiz e al. 2020), and i has he lowes
commission and omission e o s in he bo eal o es egion
(Bosche i e al. 2019).
P e-p ocessing o he Long-Te m Da a
Reco d (LTDR)
The LTDR unded by he Clima e Da a Reco d P og am o he
NOAA Na ional Clima ic Da a Cen e is a consis en long- e m
da ase a a spa ial esolu ion o 0.05° (~5 km) based on daily
da a om he AVHRR onboa d he NOAA sa elli es and daily
da a acqui ed by MODIS onboa d NASA’s Te a and Aqua
sa elli es (Pedel y e al. 2007). The daily global LTDR e sion
5 (1981–2021) used in he p esen s udy was downloaded
om h ps://l d .nascom.nasa.go /cgi-bin/l d /l d Page.cgi.
130°W
50°W 40°W 30°W 20°W 10°W 0°E 10°E 20°E 30°E 40°E 50°E
140°W 150°W 160°W 170°W 180°W 170°E 160°E 150°E 140°E 130°E
120°E
110°E
100°E
90°E
80°E
70°E
60°E
120°W
110°W
100°W
90°W
80°W
70°W
60°W
Fig. 1. The s udy egion ( ed pe ime e ) co e s he no he n bo eal egion. I is di ided in o wo
sub- egions: No h Ame ica (72.5°N 168.5°W; 60°N 43.5°W) and Eu asia (72.5°N 5°E; 60°N 180°E).
Bo eal o es (g een) is di e en ia ed om all he o he land co e s (b own), ice (whi e) and wa e
bodies (blue).
J-A Mo eno-Ruiz e al. In e na ional Jou nal o Wildland Fi e
856
The o iginal iles, in hie a chical da a o ma , co e he globe
a a 0.05° esolu ion CMG wi h 7200 × 3600 cells. The o igi-
nal iles we e ans o med in o a bina y sequen ial o ma
(BSQ). Con e sion o physical alues (su ace e lec ance and
b igh ness empe a u e) conside ed he quali y assessmen
(QA) ields o he Daily Su ace Re lec ance p oduc
(AVH09C1) o emo e possible snow-co e ed pixels and o
il e o he p esence o clouds using he CLAVR-1 (Clouds
om AVHRR-Phase I) algo i hm (S owe e al. 1999). Missing
and in alid b igh ness empe a u e alues ound o he
NOAA-16 and 18 sa elli es om 2000 o 2008 we e di ec ly
eplaced by he equi alen alues om he MOD09CMG p od-
uc o ha pe iod (h ps://ladsweb.modaps.eosdis.nasa.go /
a chi e/allDa a/6/MOD09CMG). In addi ion, he signi ican ly
decaying o bi o he NOAA-19 sa elli e om 2018 (Julien and
Sob ino 2021; Giglio and Roy 2022) made i necessa y o use
he MOD09CMG p oduc o his pe iod as well. Finally, o
elimina e esidual clouds and cloud shadows ha could
in e e e wi h he disc imina ion o bu ned pixels, he
maximum b igh ness empe a u e (BT_CH3: 3.55–3.93 µm)
c i e ion cons uc ed 10-day composi es om he LTDR-BSQ
iles (Ba bosa e al. 1998). This composi ing c i e ion has
p o ed o be e ec i e in disce ning bu ned om unbu ned
a eas (Chu ieco e al. 2005). Tempe a u e alues abo e
350 K we e conside ed as e oneous alues. Nex , wo ege-
a ion indices de i ed om he o iginal bands we e calcu-
la ed, which we e use ul o BA disc imina ion in he bo eal
egions: Global En i onmen al Moni o ing Index (GEMI)
(Pin y and Ve s ae e 1992) and Bu ned Bo eal Fo es
Index (BBFI) (Mo eno Ruiz e al. 2012). Table 1 desc ibes
he band con igu a ions o each 10-day composi e ile in he
BSQ o ma wi h loa ing da a ype.
The bu ned a ea de ec ion algo i hm
The me hodology de eloped by Mo eno Ruiz e al. (2012),
based on a Bayesian ne wo k algo i hm (BA-LTDR), was
applied o he en i e s udy a ea o ob ain he annual BA
maps and hei co esponding empo al dis ibu ion (Mo eno
Ruiz e al. 2012). This me hodology has been p e iously
applied and success ully alida ed in di e en bo eal egions
and o di e en pe iods (Núñez-Casillas e al. 2013; Mo eno-
Ruiz e al. 2014a; Ga cía-Láza o e al. 2018). In he cu en
wo k, he s udy egion was ex ended o he no he n bo eal
egion (abo e 60°N) using a single algo i hm. This app oach
allowed he cohe ence in he wo sub- egions (No h
Ame ica and Eu asia) and he wo s udy pe iods (MODIS
and p e-MODIS e as) o be assessed join ly, such ha he
es ima es ob ained o one sub- egion and pe iod can be
ex apola ed o o he bo eal sub- egions and pe iods. The
di e en s eps ha cons i u e his me hodology a e sum-
ma ised in Fig. 2 and a e desc ibed in g ea e dep h in
p e ious s udies by he same au ho s (Mo eno-Ruiz e al.
2012, 2014b; Núñez-Casillas e al. 2013; Ga cía-Láza o e al.
2018; Guindos-Rojas e al. 2018). The algo i hm calcula es
12 s a is ical a iables based on he su ace e lec ance
bands ρ
1
and ρ
2
, he b igh ness empe a u e T, and he
BBFI and GEMI indices, o he 10-day composi e o po en-
ial i e da es be o e and a e he i e o he yea o he i e
e en , he yea be o e and he yea a e . In he no he n
bo eal o es , ege a ion akes se e al yea s o eco e , e en
mo e han a decade, which is why i was decided o also
analyse he yea be o e and a e he i e, wi h a du a ion o
2 mon hs o he p e- i e and pos - i e pe iods o each yea ,
s a ing om he hypo he ical igni ion da e de e mined by
he alue o he maximum o he BBFI (Mo eno Ruiz e al.
2012). The Bayesian ne wo k classi ie calcula ed he no -
malised p obabili y o he unbu ned and bu ned classes
using a aining se based on he pe ime e s o he BA ha
was la ge han 1000 ha in he NE Sibe ia egion in 2010.
These pe ime e s we e gene a ed om 53 pai s o Landsa -
TM images ob ained om he Uni ed S a es Geological
Su ey (USGS) conside ing p e- and pos - i e in o ma ion
a 30-m spa ial esolu ion (Ga cía-Láza o e al. 2018).
To imp o e he esul ing BA p obabili y maps, he spa ial
cohe ence was analysed using a il e ing p ocess based on
cellula au oma a heo y (Moja adi e al. 2004; Espinola
e al. 2015). Finally, he BA-LTDR algo i hm de eloped
was applied o he s udy egion in o de o gene a e a
da ase o BA annual maps o he no he n bo eal o es
Table 1. Bands con igu a ion o 10-days composi e iles.
Band name Desc ip ion Equa ion
ρ
1
Su ace e lec ance o ed channel SREFL_CH1 (0.5–0.7 µm)
ρ
2
Su ace e lec ance o nea -in a ed channel SREFL_CH2 (0.7–1.0 µm)
T Top o a mosphe e b igh ness empe a u e (K) BT_CH3 (3.55–3.93 µm)
GEMI Global En i onmen al Moni o ing Index
n n× (1 0.25 × ) 0.125
1
1
1
n=2 × ( ) + 1.5 × + 0.5 ×
+ + 0.5
22122 1
2 1
BBFI Bu ned Bo eal Fo es Index
+T1
2
2
QA Quali y assessmen ield
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857
(abo e 60°N) o he 1982–2020 pe iod a 0.05° (~5 km)
esolu ion. We e e o his da ase as he BA-LTDR-DS.
Technical alida ion
To assess he accu acy o he BA-LTDR-DS da ase , we spli
he ime se ies o bo h sub- egions (Eu asia and No h
Ame ica), in o wo – p e-MODIS and pos -MODIS. Since
2000 (MODIS e a), accu acy assessmen o he Eu asian
sub- egion was accomplished using only he MCD64A1 C6
BA p oduc . Al hough MODIS da a a e no he mos sui able
o quan i a i e alida ion o he BA-LTDR-DS p oduc , as
hey a e a ec ed by e o s due o hei spa ial esolu ion o
500 m, hei use may be conside ed acco ding o he p o o-
col o he Commi ee on Ea h Obse a ion Sa elli es
(CEOS). CEOS ecommends ha an assessmen can be
made o sys ema ic quali y con ol o a p oduc by s a is i-
cal compa ison wi h independen ly ob ained BA da ase s o
be e spa ial esolu ion when no o he o icial e e ence se
exis s (Mo ise e e al. 2006; Bosche i e al. 2009). Be o e
2000 (p e-MODIS e a), accu acy assessmen s could no be
e alua ed in his way because o he BA p oduc s wi h a
highe spa ial esolu ion o his s udy sub- egion (Eu asia)
we e no a ailable. Fo una ely, his is no he case o he
No h Ame ican sub- egion, o which o icial e e ence da a
a e a ailable o compa e wi h he BA-LTDR-DS da ase , as
desc ibed in Re e ence da a sec ion. The AFS da abase and
he CNFDB ha e al eady been used success ully as e e ence
da a o assess he accu acy o sa elli e-de i ed BA p oduc s
(Chu ieco e al. 2008; Chang and Song 2009; Giglio e al.
2009; Núñez-Casillas e al. 2013; Mo eno-Ruiz e al. 2019,
2020). The new e e ence da abase NBAC, a ailable o he
pe iod 1986–2020, was used as he e e ence se o Canada.
The i s 4 missing yea s (1982–1985) we e comple ed wi h
da a om CNFDB. NBAC signi ican ly imp o es he CNFDB
BA polygons by including small i es and some i es in
emo e loca ions no p e iously conside ed in CNFDB, and
by emo ing unbu ned islands and wa e bodies wi hin
hose polygons (Hall e al. 2020; Skakun e al. 2021,
2022). The polygons o all he i es egis e ed in he AFS
and CNFDB + NBAC be ween 1982 and 2020 we e used o
p oduce he annual ec o laye s o g ound- u h e i ica-
ion. Nex , hese ec o laye s we e ep ojec ed o a geo-
g aphic p ojec ion wi h a pixel size o 0.005° (~500 m) o
gene a e annual g ound- u h maps. To de e mine how he
pixel was assigned a bu ned/non-bu ned alue, he me hod
o maximum a ea wi hin he pixel was used (A none
e al. 2016).
Howe e , o compu e spa ial and empo al accu acy, he
annual BA maps om he BA-LTDR-DS and he MCD64A1
C6 da ase s we e clipped o he No h Ame ican (72.5°N,
168.5°W, 60°N, 141°W) and Eu asian (72.5°N, 5°E, 60°N,
180°E) bo eal sub- egions. All e e ence da a maps we e
esized o a geog aphic p ojec ion wi h a pixel size o
5 × 5 km by pixel agg ega ion (an agg ega ed pixel ep e-
sen s he pe cen age o BA a he subpixel le el).
Daily LTDR-BSQ
(No he n bo eal egion) MOD09CMG
10-day composi es
(ρ, T, GEMI, BBFI)
p e- and pos - i e
No h Ame ica
Eu asia
AFS + (CNFDB + NBAC)
(1982–2020)
MCD64A1 C6
(2001–2020)
MCD64A1 C6
(2001–2020)
Accu acy
assessmen
Bayesian ne wo k
algo i hm
Bu ned p obabili y
maps
Spa ial cohe ence
analysis
160°W
70°N
65°N
60°N
150°W
Daily global LTDR e sion 5
(1981–2021)
Fig. 2. Flowcha o he p ocess o ob ain annual
maps o he BA-LTDR-DS (Bu ned A ea Long-Te m
Da a-Reco d Da ase ) in he no he n bo eal egion
o 1982–2020 and o assess hei accu acy agains
e e ence da a ( Mo eno Ruiz e al. 2012; Núñez-
Casillas e al. 2013; Mo eno-Ruiz e al. 2014b;
Ga cía-Láza o e al. 2018; Guindos-Rojas e al. 2018).
J-A Mo eno-Ruiz e al. In e na ional Jou nal o Wildland Fi e
858

The empo al accu acy o he BA-LTDR-DS p oduc in
each sub- egion was assessed conside ing he o al calcu-
la ed annual BA. A iming dis ibu ion o he BA-LTDR-DS
p oduc was ep esen ed on a cha oge he wi h he ime
se ies o e e ence BAs, and a co ela ion analysis was ca -
ied ou . The ela i e pe cen ages o he annual BA o he
BA-LTDR-DS p oduc we e calcula ed wi h espec o he
e e ence da a o he common yea s when a ailable.
Fo he spa ial accu acy assessmen , sca e plo s o he
annual BA p opo ions on 50 × 50 km g ids dis ibu ed uni-
o mly o he BA-LTDR-DS da ase agains he e e ence
da a in each sub- egion we e cons uc ed and a linea
eg ession analysis was pe o med. Nex , a de ailed analysis
o he spa ial accu acy o he BA-LTDR-DS da ase was
made based on e o ma ixes e sus he e e ence maps a
he pixel le el on an annual basis, calcula ing commission
and omission e o s o he bu ned class (S ehman 1997).
Omission e o s we e calcula ed as he a io o bu ned pixels
classi ied as unbu ned o he o al bu ned pixels in he BA
e e ence map, while commission e o s we e calcula ed as
he a io o unbu ned pixels classi ied as bu ned o he o al
bu ned pixels in each BA p oduc unde analysis. We con-
side ed a pixel size o 50 km o p e en e o s de i ed om
geo- e e encing o he images due o he di e ence in spa ial
esolu ion (Mo eno-Ruiz e al. 2014a).
Resul s
Annual bu ned a ea maps o he no he n
bo eal egion (LTDR-BA-DB)
Fig. 3 p esen s he g ouping by decade o he annual maps o
BAs o he wo bo eal sub- egions conside ed (No h
Ame ica and Eu asia) ob ained om he LTDR-BA-DS p od-
uc wi h he bu ned pixels ep esen ed in ed. Fig. 4 shows a
composi ion wi h he ou decades o he BA de ec ed by BA-
LTDR-DS o he no he n bo eal egion conside ed be ween
he pa allels 60°N and 72.5°N.
Annual dis ibu ion o he bu ned a ea es ima es
Fig. 5 shows he es ima ed annual dis ibu ion o BA in he
no he n bo eal egion o he pe iod 1982–2020 om he
BA-LTDR-DS. A non-uni o m pa e n was obse ed wi h yea s
whe e s ong i e ac i i y was de ec ed (BA > 3 million ha)
and o he yea s whe e ba ely 0.5 million ha BA was de ec ed.
On a e age, o he en i e egion and pe iod, ~1.84 million ha
bu ned pe yea , bu wi h high a iabili y. Fo example, in
2014 ( he yea wi h he g ea es BA de ec ed), 5.41 million ha
bu ned whe eas in 1992 ( he yea wi h he leas BA de ec ed),
~0.26 million ha bu ned. Fo he en i e pe iod analysed,
No h Ame ica had 35.9% o he BA compa ed wi h 64.1%
in Eu asia. Howe e , his a e age con ibu ion o each sub-
egion seems o ha e no s a is ical signi icance owing o he
la ge annual luc ua ions. I should be no ed, o example, ha
he g ea es imbalances occu ed in he yea 2020, wi h a
con ibu ion o 0.8% om No h Ame ica compa ed wi h
99.2% om Eu asia, o he opposi e case o 2004, whe e
No h Ame ica con ibu ed 96.7% o he o al compa ed wi h
3.3% om he es .
Tempo al accu acy
No h Ame ica
In he No h Ame ica bo eal sub- egion, he o al BA
egis e ed by he AFS and CNFDB + NBAC da abases in he
1982–2020 pe iod was 41.23 million ha, wi h an i egula
annual dis ibu ion. The highes i e ac i i y (4.79 million ha)
occu ed in 2004, and he lowes in 1984, when only
0.10 million ha bu ned. Fig. 6 shows he annual dis ibu ion
o BA om he e e ence AFS and CNFDB + NBAC da abases,
he es ima ed BA o he BA-LTDR-DS p oduc o he pe iod
1982–2020 and es ima es o he MCD64A1 C6 p oduc o
he pe iod 2000–2020. The BA-LTDR-DS de ec ed 62% o he
e e ence BA, unde es ima ing he BA in all yea s in he ime
se ies. The e is a s ong co ela ion (0.93) be ween he LTDR-
BA-DS da a and he e e ence da a. I we di ide he ime
se ies in o wo pa s, p e-MODIS (1982–1999) and MODIS
(2000–2020), he BA-LTDR-DS p esen s almos homogeneous
beha iou , bo h in he pe cen age o he es ima e o BA (66%
s 60%) and in he co ela ion coe icien (0.97 s 0.93) wi h
espec o he e e ence da a. Fo i s pa , he MCD64A1 C6
p oduc unde es ima ed BA in No h Ame ica by app oxi-
ma ely 69% wi h a co ela ion coe icien o 0.99 wi h
espec o he e e ence da a. Making an in e -compa ison
o he BA-LTDR-DS wi h MCD64A1 C6 o he common
pe iod (2000–2020), a co ela ion o 0.93 was ound.
Eu asia
Fo he ime accu acy assessmen in he Eu asian sub-
egion, a co ela ion analysis be ween he ime se ies o he
BA-LTDR-DS and he MCD64A1 C6 p oduc was conduc ed
(Fig. 7). MCD64A1 C6 was used as he e e ence da a o he
common yea s (2000–2020). MCD64A1 C6 es ima ed a BA
o 47.10 million ha o hese yea s and he BA-LTDR-DS
~66% o ha alue. The BA-LTDR-DS unde es ima ed he
BA in all common yea s excep o 2000. Howe e , i s
empo al pa e n i s ema kably well wi h ha o he e e -
ence, yielding a co ela ion coe icien be ween MCD64A1
C6 and BA-LTDR-DS o 0.95.
Spa ial accu acy
No h Ame ica
Table 2 shows he esul s o he linea eg ession analysis
o he BA pe cen ages o he BA-LTDR-DS and he MCD64A1
C6 p oduc s e sus he e e ence da a. The a e age de e mi-
na ion coe icien (R
2
) o e he 1982–2020 pe iod o he
BA-LTDR-DS p oduc was 0.78, wi h a slope o 0.73, wi h no
www.publish.csi o.au/w In e na ional Jou nal o Wildland Fi e
859
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W
70°N
65°N
60°N
70°N
65°N
60°N
60°W 50°W
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W
(a) No h Ame ica 1980s
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W
70°N
65°N
60°N
70°N
65°N
60°N
60°W 50°W
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W
(b) No h Ame ica 1990s
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W
70°N
65°N
60°N
70°N
65°N
60°N
60°W 50°W
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W
(c) No h Ame ica 2000s
160°W 150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W
70°N
65°N
60°N
70°N
65°N
60°N
70°N
65°N
60°N
70°N
65°N
60°N
60°W 50°W
160°W
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
150°W 140°W 130°W 120°W 110°W 100°W 90°W 80°W 70°W 60°W 50°W
(d) No h Ame ica 2010s
(e) Eu asia 1980s
70°N
65°N
60°N
70°N
65°N
60°N
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
( ) Eu asia 1990s
70°N
65°N
60°N
70°N
65°N
60°N
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
( ) Eu asia 1990s
70°N
65°N
60°N
70°N
65°N
60°N
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
10°E 20°E 30°E 40°E 50°E 60°E 70°E 80°E 90°E 100°E 110°E 120°E 130°E 140°E 150°E 160°E 170°E 180°E
(h) Eu asia 2010s
Fig. 3. Decadal bu ned a ea maps o No h Ame ica (a–d), and Eu asia (e–h) sub- egions om he Bu ned A ea
Long-Te m Da a Reco d Da aSe (BA-LTDR-DS). Red, bu ned a ea; blue, wa e ; g een, non-bu ned.
J-A Mo eno-Ruiz e al. In e na ional Jou nal o Wildland Fi e
860
signi ican di e ences be ween he wo ime sub-in e als
(p e and MODIS e as). The a e age de e mina ion
coe icien (R
2
) o e he 2000–2020 pe iod o MCD64A1
C6 and he BA-LTDR-DS p oduc s was 0.88 and 0.78, wi h a
slope o 0.69 and 0.69, espec i ely.
A de ailed analysis o he spa ial accu acy o he No h
Ame ican sub- egion on an annual basis o he BA p oduc s
BA-LTDR-DS and MCD64A1 C6 is shown in Table 3. The
a e age commission and omission e o s o he BA-LTDR-
DS a e 0.14 and 0.47 espec i ely o he en i e s udy pe iod
whe eas o he MODIS e a, he MCD64A1 C6 p oduc p es-
en s a commission e o o 0.09 and omission e o o 0.37.
Eu asia
Table 4 shows he esul s o he accu acy o he BA
es ima e ob ained om he linea eg ession analysis o
he BA pe cen ages om he BA-LTDR-DS p oduc e sus
MCD64A1 C6 using 50 × 50 km g ids. The a e age de e mi-
na ion coe icien (R
2
) o e he 2001–2020 pe iod o he
BA-LTDR-DS p oduc was 0.78, wi h a slope o 0.81.
Table 5 shows he commission and omission e o s de i ed
om he e o ma ix o each yea , aking as e e ence he
MCD64A1 C6 p oduc (only a ailable om he yea 2000).
140°W 160°W 160°E 140°E
130°E
110°E
90°E
70°E
50°E
130°W
110°W
90°W
70°W
50°W
40°W
1980s 1990s 2000s 2010s
20°W 20°E 40°E0°
0°
Fig. 4. Mapping o bu ned a eas de ec ed by BA-LTDR-DS (Bu ned
A ea Long-Te m Da a-Reco d Da ase ) om 1982 o 2020 o he
no he n bo eal egion be ween 60°N and 72.5°N. Colou s co e-
spond o bu ned a eas by decade.
AFS + (CNFDB _NBAC)
BA-LTDR-DS
MCD64A1 C6
0
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
1
2
3
Bu ned a ea (million. ha)
4
5
Yea
Fig. 6. Annual dis ibu ion o bu ned a ea es ima e (ha) in he No h Ame ican bo eal sub- egion
om e e ence da a o AFS (Alaska Fi e Se ice) and CNFDB + NBAC (Canadian Na ional Fi e
Da abase + Na ional Bu ned A ea Composi e), and he BA-LTDR-DS (Bu ned A ea Long-Te m
Da a-Reco d Da ase ) and he MODIS Collec ion 6 MCD64A1 C6 bu ned a ea p oduc s.
0
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
1
2
3
Bu ned a ea (million. ha)
4
5Eu asia
No h Ame ica
Yea
6
Fig. 5. Annual dis ibu ion o bu ned
a ea es ima e (ha) in he no he n
bo eal egion om he BA-LTDR-DS
(Bu ned A ea Long-Te m Da a-Reco d
Da ase ).
www.publish.csi o.au/w In e na ional Jou nal o Wildland Fi e
861
Fo his pe iod, he a e age commission and omission e o s
o he BA-LTDR p oduc we e 0.21 and 0.47, espec i ely.
Discussion
In his pape , we desc ibe he BA-LTDR-DS da ase , which
p o ides annual BA a a spa ial esolu ion o 0.05° om 1982
o 2020 o he bo eal egion be ween 60°N and 72.5°N. We
buil his da ase om he la es eleased Ve sion 5 o he
LTDR da ase . The LTDR Ve sion 5 inco po a es imp o e-
men s o he Bidi ec ional Re lec ance Dis ibu ion Func ion
(BRDF) co ec ion, he calib a ion o AVHRR/3 da a on boa d
pla o ms NOAA-16, 18 and 19, composi ing a mosphe ic
co ec ions and he QAs (h ps://landweb.modaps.eosdis.
nasa.go /cgi-bin/l d /l d /l d Page.cgi? ileName=LTDR_
upda e). Howe e , as has been discussed in p e ious s udies
(O ón e al. 2019, 2021; Giglio and Roy 2022), hese e ec s
canno be elimina ed. Indeed, in his new e sion, we
de ec ed missing and w ong alues o he TOA b igh ness
empe a u e bands om he NOAA-16 and 18 sa elli es ( om
2000 o 2008) in he no he n bo eal egion. To p ese e he
cohe ence o he empe a u e bands in he LTDR da ase ,
we eplaced he Band T3 wi h he Band 20 B igh ness
Tempe a u e (3.360–3.840 μm) o he MOD09CMG p oduc .
In addi ion, he signi ican ly decaying o bi o he NOAA-19
sa elli e om 2018 (Julien and Sob ino 2021; Giglio and Roy
2022) made i necessa y o use he MOD09CMG p oduc o
his pe iod. Finally, he QA bi was upda ed p ope ly. Using
his new modi ied e sion o he LTDR, we ha e gene a ed he
longes BA ime se ies ye buil a a spa ial esolu ion o 0.05°
in he CMG o he no he n bo eal egion. To do his, a
machine lea ning algo i hm based on a Bayesian ne wo k
was used, de eloped speci ically o he de ec ion o BA in
ha egion. The BA-LTDR-DS ex ends by mo e han 10 yea s
he ime in e al o he Global Fi e Emissions Da abase
(GFED4), which is om 1995 o he p esen (Giglio e al.
2013), and imp o es i s spa ial esolu ion by up o i e
imes ( om 0.25° o 0.05°) as well as he be a long- e m BA
da ase (Fi eCCILT1.0) de eloped by he Clima e Change
Ini ia i e (CCI) p og am o he Eu opean Space Agency. In a
ecen e sion o he CCI p og am, O ón e al. (2021) ob ained
a new p oduc (Fi eCCILT11) a he same spa ial esolu ion as
he BA-LTDR-DS. This p oduc uses a andom o es algo i hm
ha calcula es he pe cen ages o BA o each pixel (so
classi ica ion), unlike BA-LTDR-DS, which only de e mines
whe he he pixel is comple ely bu ned o no (ha d classi i-
ca ion). The main p oblem encoun e ed when compa ing
BA-LTDR_DS wi h FIRECCILT11 ela es o he yea s compos-
ing bo h ime se ies: Fi eCCILT11 is 2 yea s sho e (ending in
2018) and does no include he yea 1994, which conside a-
bly dis o s he compa ison as 1994 was he yea wi h he
la ges BA in No h Ame ica.
E alua ing he spa ial and empo al accu acy o he
en i e ime se ies o BA ob ained (BA-LTDR-DS) seems
e y di icul gi en he non-exis ence o ano he se o e -
e ence da a o he bo eal o es egion and he pe iod
analysed ( om 1982 o 2020) compa ed wi h simila p od-
uc s, ei he ob ained om i e eco ds pe ime e s o o icial
agencies o om p oduc s de i ed om sa elli e images.
Tha is why we we e o ced o e alua e ou p oduc o
he wo sub- egions al eady desc ibed (Eu asia and No h
Ame ica) and wo di e en pe iods ma ked by he yea 2000
when he MODIS senso was pu in o ope a ion.
Fo he assessmen o he BA-LTDR-DS accu acy in he
no he n sub- egion o No h Ame ica, he bes a ailable
baseline da a (g ound- u h) we e used, i.e. he pe ime e s
o BAs eco ded by he AFS and Canada (CFSFND + NBAC).
Few coun ies ha e de ailed egis ies o BA pe ime e s
a ailable o use o a ull assessmen o p oduc s esul ing
om sa elli e images. The a ailabili y o he abo e in o ma-
ion made i possible o conduc a de ailed s udy o he
a ious p oduc s based on he o al amoun o i es a he
han a simple sample (Mo eno-Ruiz e al. 2019). These da a-
bases, al hough egula ly main ained and upda ed, may
con ain e o s mainly due o he omission o small i es
0
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
1
2
3
Bu ned a ea (million. ha)
4
5BA-LTDR-DS
MCD64A1 C6
Yea
Fig. 7. Annual dis ibu ion o bu ned a ea es ima e (ha) in he Eu asian bo eal sub- egion om he
BA-LTDR-DS (Bu ned A ea Long-Te m Da a-Reco d Da ase ) and he MODIS Collec ion 6
MCD64A1 C6 bu ned a ea p oduc s.
J-A Mo eno-Ruiz e al. In e na ional Jou nal o Wildland Fi e
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Con lic s o in e es . The au ho s decla e no con lic o in e es .
Decla a ion o unding. This esea ch was unded by he Minis e io de Ciencia, Inno ación y Uni e sidades (MCIU), he Agencia Es a al de In es igación
(AEI) and he Fondo Eu opeo de Desa ollo Regional (FEDER) h ough p ojec RTI2018-099171-B-I00.
Acknowledgemen s. The au ho s wish o hank he LTDR p ojec and i s eam o making he da a a ailable, and Alaska Fi e Se ice, he Canada Cen e
o Mapping and Ea h Obse a ion o Na u al Resou ces Canada, he Canadian Fo es Se ice, NASA, NOAA and USGS o p ocessing and dis ibu ing he
AFS, CFNDB, NBAC, MCD64A1 and LTDR da ase s.
Au ho con ibu ions. J.A.M.-R. and J.R.G.-L. concei ed, designed and applied he me hodology. All au ho s ob ained, analysed and discussed he esul s;
M.A. and P.A.H.-L. in collabo a ion wi h he es o he au ho s w o e and con ibu ed o he edi ing o he manusc ip .
Au ho a ilia ions
A
Depa amen o de In o má ica, Uni e sidad de Alme ía, 04120 Alme ía, Spain. Email: [email p o ec ed]; [email p o ec ed]
B
Depa amen o de Física, Uni e sidad de La Laguna, 38200 San C is óbal de La Laguna, Spain. Email: [email p o ec ed]; [email p o ec ed]
www.publish.csi o.au/w In e na ional Jou nal o Wildland Fi e
871