Calib a ion o he Land Uses submodule o he
WILIAM-TERRA model
Ma ga i a Media illa, Feb ua y 2025
Con en s:
1. Land use change models
2. Gene al desc ip ion o he Land Uses submodule o WILIAM-TERRA
3. Da a sou ces
4. Calib a ion o he Lad Uses submodule
1. Land use change models
Mos simula ion models o land use changes a e based on a leas one o he ollowing
ou co e p inciples o land use changes (LUC) [1], no mu ually exclusi e:
Con inua ion o his o ical de elopmen . Fu u e land use can be p edic ed by
land use his o ical changes.
Sui abili y o land. Sui abili y co e s di e en aspec s, om e.g., maximum
ma ke p o i (economic sui abili y) o soil sui abili y (biophysical sui abili y) o
di e en uses.
Neighbou hood in e ac ion. The p obabili y o ansi ion om one use o land
o ano he is dependen on he biophysical o socio-economic d i e s
condi ioning he LU o i s su ounding cells.
Ac o in e ac ion. Land use change is he esul o in e ac ion be ween ac o s
acco ding wi h di e en socio-economic and poli ical d i e s.
I is a common p ac ise o modelle s o desc ibe he p ocesses o LUC acco ding o a
pa icula mechanism ha can be used o cha ac e ise hese changes. Main
mechanisms ound in li e a u e a e: cellula au oma a, s a is ical analysis, ma ko
chains, a i icial neu al ne wo ks, economic-based models and agen -based sys ems.
This mechanism o LUC is hen codi ied in o algo i hms, which lead o di e en
compu e simula ion models. A huge di e si y o model app oaches can be ound
wi hin li e a u e.
F om he poin o iew o he spa ial disagg ega ion, land use models can be classi ied
as spa ial e sos non-spa ial models:
Spa ial models. Spa ial models (also called Geog aphical models) aim a spa ially
explici ep esen a ions o land-use change (LUC) a some le el o spa ial de ail
(pixels in a as e model, o o he uni s –adminis a i e, ecological, e c.- in a ec o
model). They a e o en associa ed wi h Geog aphical In o ma ion Sys ems (GIS).
Non-spa ial models. Non-spa ial models ocus on modelling land-use change
wi hou speci ic conside a ion o i s spa ial dis ibu ion, equen ly economic land-
use models.
In [2, 3, 4] models a e classi ied in ou ypes:
I. Geog aphical land-use models. These models alloca e land a ea o land demand
based on biophysical and socioeconomic p ope ies, and he esul ing sui abili y o
land o a speci ic use.
II. Economic land-use models. Models ha use demand and supply unc ions as
he main d i e s o land-use change, gi ing o al a eas o speci ic land-use ypes wi hin
de ined geog aphical egions.
III. In eg a ed land-use models. These models combine na u al and human
subsys ems. In mos cases, hese models consis o a combina ion o sepa a e
economic and en i onmen al p ocesses capable o spa ially explici modelling, ypically
a la ge (global) scales.
IV. O he ype o models. He e, he classi ica ion includes U ban g ow h, Machine
lea ning and agen -based models.
The e is a my iad o LUC models, many o hem cu en ly used in IAM models, some o
he mos popula and ele an ones a e:
1. The CLUE F amewo k. Se o models e ol ed om he o iginal CLUE model [5].
I simula es LUC using empi ically quan i ied ela ions be ween land use and
se e al d i ing ac o s in combina ion wi h dynamic land compe i ion alloca ed
in a as e based sys em. The ex apola ion o ends in land use change is a
common echnique o calcula e land use equi emen s bu , hese ends can be
co ec ed o changes in popula ion g ow h and/o diminishing land esou ces.
I is a spa ially explici model and can be eely downloaded om he model
websi e.
2. The IMAGE modelling [6] is an ecological-en i onmen al model amewo k ha
simula es he en i onmen al consequences o human ac i i ies wo ldwide. I
ep esen s in e ac ions be ween socie y, he biosphe e and he clima e sys em
o assess sus ainabili y issues such as clima e change, biodi e si y and human
well-being. Is a spa ially explici model and uses eg ession-based sui abili y
assessmen o de e mine u u e land-use pa e ns. IMAGE has had se e al
e sions and has been in eg a ed wi h o he models such as he ege a ion
g ow h model LPJmL [7], he CLUMondo [8] o mo e p ecise LU ep esen a ion.
3. The MAgPIE model is a global land-use alloca ion model [9] which is connec ed
o he g id-based dynamic ege a ion model LPJmL, wi h a spa ial esolu ion o
0.5°x0.5°. I akes egional economic condi ions such as demand o ag icul u al
commodi ies, echnological de elopmen and p oduc ion cos s as well as
spa ially explici da a on po en ial c op yields, land and wa e cons ain s ( om
LPJmL) in o accoun . Based on hese, he model de i es speci ic land use
pa e ns, yields and o al cos s o ag icul u al p oduc ion o each g id cell.
4. GCAM [10,11] is a ecu si e -dynamics pa ial-equilib ium global IAM ha
ep esen s he in e ac ions be ween ene gy, wa e , ag icul u e and land use,
economy, and clima e. I is a dynamic- ecu si e model wi h echnology
ep esen a ions o he economy, ene gy sec o , land use and wa e linked o a
clima e model ha can be used o explo e clima e change mi iga ion policies
including ca bon axes, ca bon ading, egula ions and accele a ed deploymen
o ene gy echnology. I is no based on g idded da a bu he ag icul u e and
land module uses mo e han 300 sub egions and app oxima ely a dozen ypes
o land co e s.
5. GLOBIOM [12,13] is a land use model ha wo ks wi h he ecu si e-dynamic
pa ial-equilib ium MESSAGE model designed o add ess a ious LUC ela ed
opics (bioene gy policy impac s, de o es a ion dynamics, clima e change
adap a ion and mi iga ion om ag icul u e, long- e m ag icul u al p ospec ). I
is a pa ial equilib ium economic model ha op imizes an objec i e unc ion
de ined as he sum o p oduce and consume su pluses unde a ce ain
numbe o cons ain s. LUC a e based on a spa ially explici gid based
amewo k.
Mos o hese models a e spa ially explici (all excep GCAM). This spa ial
ep esen a ion allows hem o use e y de ailed in o ma ion abou he physical
sui abili y o land use changes, bu is compu a ionally in ensi e. These models ha e a
s uc u e ha is mainly based on linea lows o in o ma ion, as desc ibed in Figu e 1.
In a linea low, in o ma ion abou demand, sui abili y, and he socio-economic ac o s
ha d i e land use change is p o ided in a p io i scena ios gene a ed by o he models
(o pa s o he same model), and he model calcula es land use changes based on
op imiza ion o ecu si e algo i hms. LUCs a e hen used o p o ide in o ma ion on
c ops o ene gy p oduc ion, emissions, and o he ypes o en i onmen al o social
impac s. Al hough some models include eedbacks, g id based da a, ecu si e
algo i hms and op imiza ions a e no he bes ools o ep esen ing eedback- ich
models wi h s ong in e ac ions, o which sys em dynamics simula ions a e he mos
app op ia e ool.
These models use economic d i e s o land use changes such as ag icul u al p ices,
income, p ice elas ici ies o ela i e land p o i abili y [15]. On he o he hand, he mos
common policies applied a e de ailed deca boniza ion policies such as ca bon axes,
subsidies, ag icul u al quo as o land p o ec ion policies.
Figu e 1: lineal in o ma ion lows o LUC models
2. Gene al desc ip ion o he Land Uses submodule o
WILIAM-TERRA
WILIAM model is a Sys em Dynamics eedback- ich model ha add esses he
biophysical limi s o he ene gy ansi ions, and i s spa ial scale is global wi h a di ision
in 9 la ge egions. Economic indica o s such as p ices o elas ici ies a e ha dly eliable
a his le el o agg ega ion, while he huge cul u al and sociopoli ical di e ences
be ween wo ld egions make i e y di icul es ima e he e ec o de ailed
deca boniza ion policies.
This is he eason why he app oach o WILIAM-TERRA di e s om ha o o he IAMS.
The policies used in WILIAN-TERRA a e no de ailed poli ical measu es bu physical
ou comes ha can be de i ed om all kinds o go e nmen measu es o social changes
(simila o hose in he Wo ld 3 model [16]). Land use changes a e d i en by he
con inua ion o obse ed ends and some basic demands plus he applica ion o a
wide ange o policies. Thus, i is a policy e alua ion model, no aimed a p edic ing he
u u e, bu a analysing he dynamic e ec s and in e ac ions o a wide ange o policies.
WILIAM-TERRA can be classi ied as a model o con inua ion o his o ical de elopmen
wi h limi s o land expansion se by he land sui abili y and some ea u es o ac o
in e ac ion. I is a non-spa ial model (since he e y de ailed g id-based models a e
ha dly compa ible wi h sys em dynamics) and an In eg a ed model ha combines
human and na u al in e ac ions. I is no an economic model, since i does no use
demand and supply unc ions as he main d i e s o land-use changes since hei
au ho s do no belie e ha eliable da a o supply, demand and p ices can be ound o
calib a e hese exchanges o a global model a he le el o agg ega ion used.
The s uc u e and submodules o WILIAM-TERRA a e shown in Figu e 2. I inco po a es
a wide ange o policies (in pink in he diag am o Figu e 2), including die a y changes,
land use changes and land p o ec ion, li es ock manu e managemen , a o es a ion,
u ban densi y, ansi ion o sus ainable ag icul u e and o indus ial ag icul u e, o es
exploi a ion, c ops alloca ion be ween egions and uses, and ca bon cap u e in
g assland soils. This documen desc ibes only he calib a ion and alida ion o he Land
Uses submodule o his WILIAM-TERRA.
Figu e 2. WILIAM-TERRA module and i s connec ion wi h he es o WILIAM model modules.
Whi e-g een boxes a e submodules o WILIAM-TERRA, boxes in o he colou belong o o he
modules o WILIAM. Va iables in pink a e exogenous policies chosen by he use .
The WILIAM-TERRA Land Uses submodule is in cha ge o alloca ing he land among 12
uses. The demands o all uses a e comp ised in a ec o named Vec o o land use
change demands, and i is gene a ed by adding wo componen s:
His o ical ends o land use changes, which a e es ima ed using lineal
app oxima ions o e he pe iod om 2005 o 2019 (Sou ce FAO).
Land use changes d i en by a ious demands:
ou ban expansion (d i en by popula ion g ow h)
osola ene gy (d i en by he demand o sola elec ici y)
oc opland loss due o sea le el ise
opolicies o land demand such as e o es a ions and land
p o ec ion
onew c opland (d i en by he global physical sho age o c ops)
The compe i ion be ween he demand o di e en uses akes place wi hin a dynamic o
“all agains all” compe i ion in which all uses ha e he same p io i y when i comes o
demand om o he s and only land o sola ene gy and c opland ha e pa ame e s ha
allow p io i izing hei use o e he es .
The expansion o land uses mus be ob ained om o he land uses in o de o ensu e
he physical cohe ence o he land alloca ion. This is speci ied in he ma ix o land use
change demands (Eq. 1), ha desc ibes he demand o changes om land use o
ano he land use :
(1)
Whe e, , ep esen s he ec o o land use change demand by
egion and land ype ; and
ep esen s he sha e o land use ha is ob ained om use . The
a e cons an ma ices.
The land use changes demanded migh no be ul illed i policies o land use p o ec ion
a e ac i a ed. is ans o med in o a
in which hose land use changes ha a e no
compa ible wi h he physical bounda ies o wi h he bounda ies imposed by he use 's
policies a e disca ded.
The is collapsed in o a
by adding he changes ha a e gi en o each use
and sub ac ing he ones ha demand om i :
(2)
The loss o ag icul u al land due o sea le el ise is sub ac ed o his ec o . And his
loss is de e mined in ou module by adap ing he me hod epo ed Roson & Sa o i [3]
o WILIAM-TERRA egions and d i en by he empe a u e change ecei ed om he
WILIAM Clima e module.
Finally, he is calcula ed as he in eg al o
al hough, he module only in eg a es some o he uses in he
s ock o and excludes we lands, snow, ice
and wa e bodies and sh ubland a ea. These land uses a e no calcula ed ia he
because hey a e no d i en di ec ly by he policies o he es o
he module and, a p esen s age, a e le cons an .
3. Da a sou ces
The Land Uses submodule is mainly based on land use da a om FAOSTAT and land
co e da a om he same sou ce, ying o main ain he consis ency o hese sou ces
al hough ele an disc epancies a e ound be ween hem. Da a sou ces a e de ailed in
Table 1.
Some o he WILIAM ca ego ies come om “land uses” ca ego ies and o he s om
“land co e ”. SHRUBLAND and OTHER LAND a e calcula ed using a mix o land uses and
land co e . The ca ego ies CROPLAND_RAINFED, CROPLAND IRRIGATED, FOREST
MANAGED, FOREST PRIMARY, FOREST PLANTATIONS and GRASSLANDS a e aken om
FAO “land use”. URBAN, SNOW-ICE-WATERBODIES and WETLAND a e ob ained om
“land co e ” da a.
SHRUBLAND and OTHER LAND (basically ba e a eas) a e adap ed, since aking hem
om land co e c ea es incohe ences ( he sum o all ca ego ies is g ea e o smalle
han he o al a ea in some cases, o example). In o de o a oid hose incohe ences,
all he uses excep SHRUBLAND and OTHER LAND a e sub ac ed om o al land and
he esul ing a e is di ided be ween SHRUBLAND and OTHER LAND on he bases o he
sha e ob ained wi h he da a o land co e .
Table 2 desc ibes he land use FAO ca ego ies. Table 3 desc ibes he FAO land uses and
Table 4 he mix o bo h sou ces o in o ma ion used o he ca ego ies o WILIAM-
TERRA model. The numbe s beside he desc ip ion co espond o FAO codes [18]. As
poin ed ou by Tubiello e al. [19] he e a e big disc epancies be ween land use
measu es o di e en sou ces including sa elli e da a, he e o e FAO da abase has been
used as he s anda d da a despi e hese incohe ences. All he FAO da a has been
e ised o check hose yea s when coun ies do no epo and he da a ha appea s in
ables in ze o. In hose cases, he da a has been in e pola ed. The his o ical alues o
land use a ea a e shown in able 5 and he co espondence o WILIAM egions and
coun ies is in able 6.
Table 1: da a sou ces o he Land Uses submodule
Table 2. “Land use” FAO ca ego ies
L. empo a y c ops
6630
L. empo a y
meadows and
pas u es 6633
L. empo a y
allow 6640
L. pe manen c ops
6650
L. pe manen
meadows and
pas u es cul i a ed
6656
L. pe manen
meadows and
pas u es na u ally
g owing 6659
P o ec i e co e
(buildings in
ag icul u a land)
6649
p ima y o es
6714
na u ally
egene a ed
o es 6717
plan ed o es
6716
Inland wa e s
6680
Coas al wa e s
6773
a able land 6621
L. pe manen
meadows and
pas u es 6655
o es land
6646
wa e
bodies
o al
a ea
Land a ea
6601
ag icul u e
6602
ag icul u al land
6610
c opland 6620
Land use by
ca ego y
housand ha Food and Ag icul u e O ganiza ion o he
Uni ed Na ions (FAO), S a is ics Di ision
(ESS), En i onmen S a is ics eam
h p://www. ao.o g/
aos a /en/#da a/RL
Land co e by land
co e class
housand ha Food and Ag icul u e O ganiza ion o he
Uni ed Na ions (FAO), S a is ics Di ision
(ESS), En i onmen S a is ics eam
h p://www. ao.o g/
aos a /en/#da a/RL
Table 6: co espondence o coun ies and WILIAM egions
COUNTRY REGION COUNTRY REGION
Aus ia EU27 Res o Oceania LROW
Belgium EU27 Mongolia LROW
Bulga ia EU27 Res o Eas Asia LROW
C oa ia EU27 Res sou h Eas Asia LROW
Cyp us EU27 Bangladesh LROW
Czech Republic EU27 Pakis an LROW
Denma k EU27 Sh i Lanka LROW
Es onia EU27 Res Sou h Asia LROW
Finland EU27 Res o No h Ame ica LROW
F ance EU27 Ecuado LROW
Ge many EU27 Pa aguay LROW
G eece EU27 U uguay LROW
Hunga y EU27 Venezuela LROW
I eland EU27 Res Sou h Ame ica LROW
I aly EU27 Gua emala LROW
La ia EU27 Hondu as LROW
Li huania EU27 Nica agua LROW
Luxembou g EU27 El sal ado LROW
Mal a EU27 Panama LROW
Ne he lands EU27 Res cen al Ame ica LROW
Poland EU27 Republica dominicaDa LROW
Po ugal EU27 Jamaica LROW
Romania EU27 Pue o Rico LROW
Slo akia EU27 T inidad y Tobago LROW
Slo enia EU27 es Ca ibe LROW
Spain EU27 No way LROW
Sweden EU27 Res o EFTA LROW
Uni ed Kingdom EU27 Albania LROW
Canada USMCA Uc ania LROW
Mexico USMCA R es o eas e n eu ope LROW
Uni ed S a es USMCA Geo gia LROW
A gen ina LATAM I an LROW
B azil LATAM Is ael LROW
Chile LATAM Jo dania LROW
Colombia LATAM Kuwai LROW
Cos a Rica LATAM Oman LROW
Pe u LATAM Qa a LROW
China (People's Republic
o ) China Saudi A abia LROW
Taiwan Tu key LROW
Hong Kong SAR China Uni ed A ab Emi a es LROW
India India Res wes e Asia LROW
Russian Fede a ion Russia Egip LROW
Aus alia EASOC Ma occo LROW
B unei Da ussalam EASOC Tunisia LROW
Cambodia EASOC Res no h A ica LROW
Chinese Taipei EASOC Benin LROW
Indonesia EASOC Bu kina aso LROW
Japan EASOC Came un LROW
Ko ea EASOC C'o e D'I oi e LROW
Malaysia EASOC Ghana LROW
New Zealand EASOC Ginea LROW
Philippines EASOC Nige ia LROW
Singapo e EASOC Senegal LROW
Thailand EASOC Togo LROW
Vie Nam EASOC Res wes A ica LROW
Res cen al A ica LROW
Res sou h cen al A ica LROW
E iopia LROW
Kenya LROW
Madagasca LROW
Malawi LROW
Mau i ius LROW
Mozambique LROW
Rwanda LROW
Tanzania LROW
Uganda LROW
Zambia LROW
Zimbawe LROW
aa icaRes Eas A ica LROW
Bo wana LROW
Namibia LROW
Sou h A ica LROW
Res o sou h A ica cu LROW
Res LROW
4. Calib a ion o he Lad Uses submodule
This sec ion desc ibes he ob en ion o he ends o he ec o o ends o
and he ma ices o sha es o land uses om o he ,
, desc ibed in p e ious sec ion based on
his o ical da a and model calib a ion.
The model is based on he hypo hesis ha he e a e some land use changes ha a e
d i en by demands, since hey a e economically o socially in e es ing (c oplands,
o es s, g asslands, sola land, u ban, e c.) and o he ha a e no demanded and only
abso b he demand o he es (o he land and sh ubland). In any case, all he land
demands compe e wi h each o he and abso b he demand o o he uses. T end
demands a e calcula ed on he basis o his o ical land use ends, and in some cases
ha e been adjus ed o ake accoun o e iden changes in ends ha canno be
ex apola ed in o he u u e (such as he sha p loss o ag icul u al land in he EU in
ecen decades due o ag icul u al policies, which does no appea o be con inuing).
In u u e eleases o he model, a GIS-based analysis is planned o be used o
de e mine based on his o ical da a, he eal sha es o land use om o he . This
would de e mine wha ha e eally been he ac ual lows o land om one use o
ano he and imp o e a lo he calib a ion o his model. In he mean ime, his
adjus men aims o s ablish he mos ele an ends o pas land use changes o he
mos ele an uses.
I is assumed ha he p ima y o es canno be inc eased, since i is de ined as e y
ma u e o es s whose c ea ion goes back o cen u ies ago. When o es p ima y
inc eases in he his o ical da a, we assume i is due o changes in de ini ion and
assume he g ea es alue as he ini ial one. Sola land is he land unde pho o ol aic
and concen a ed sola powe elec ici y appliances, since i s his o ical alues a e e y
low, we do no ake i in o accoun in he calib a ion. Fo sola land, he ini ial sha es
ha e been ob ained applying Geog aphic In o ma ion Sys ems (GIS) echniques
analyzing he alloca ion o cu en sola powe capaci y. This analysis has been done o
each o he 9 egions o WILIAM-TERRA module and i is based on da a p ocessed om
he “Global Da abase o Powe Plan s” combined wi h land co e da a (see [22] o a
comple e desc ip ion).
These hypo hesis o land use ends a e used o calcula e he land use changes aken
om o he uses in each simula ion ime s ep acco ding o equa ion 1 using ini ial
alues o he ma ices o sha es o land uses om o he , (
) ob ained by he analysis o he li e a u e
desc ibed in [20, 21] (see Table 7) and he esul ing land use changes a e con on ed o
his o ical da a. The disc epancy be ween es ima ed and his o ical da a is used o
accommoda e he ma ix . An ini ial
compu e calib a ion o hese sha es was done wi h Vensim So wa e calib a ion ools,
bu he inal adjus men was made by hand, since he complexi y o he ask made
au oma ic calib a ion wo se han he human-made. The main e o s ha e been
dedica ed o he calib a ion o he mos ele an and con lic i e uses (c oplands and
o es s), he e o e he e o s accumula e in sh ubland and o he land, whose his o ical
da a was no p ope ly ound (as desc ibed in sec ion 3). Snow, ice and wa e bodies and
we lands ha e no been calib a ed a his s age o he model and hey a e le cons an
in he model.
Table 7: Ini ial sha es o land use changes om o he as s a ed in Campano 2021 [21]
INITIAL_SHARE_OF_CROPLAND_RAINFED_FORM_OTHER_LANDS_BY_REGION (REGIONS_I,LANDS_I)
LANDS_I RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_P
RIMARY
FOREST_P
LANTATION
S
SHRUBLAN
D
GRASSLAN
D
WETLAND URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_LA
ND
REGIONS_I [%] [%] [%] [%] [%] [%] [%] [%] [%] [%] [%]
EU27 0 0 0.8 0 0 0.12 0.06 0 0 0 0 0.02
UK 0 0 0.8 0 0 0.12 0.06 0 0 0 0 0.02
CHINA 0 0 0.44 0 0 0.16 0.25 0 0 0 0 0.16
EASOC 0 0 0.19 0.66 0 0.15 0.01 0 0 0 0 0.01
INDIA 0 0 0.18 0.3 0 0.24 0.18 0 0 0 0 0.11
LATAM 0 0 0.18 0.63 0 0.18 0.01 0 0 0 0 0
RUSSIA 0 0 0.2 0 0 0.52 0.25 0 0 0 0 0.04
USMCA 0 0 0.11 0.38 0 0.23 0.27 0 0 0 0 0
LROW 0 0 0.18 0.28 0 0.38 0.1 0 0 0 0 0.07
INITIAL_SHARE_OF_GRASSLAND_FORM_OTHER_LANDS_BY_REGION (REGIONS_I,LANDS_I)
pond emos que g assland no iene demanda sal o en LATAM
LANDS_I RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_P
RIMARY
FOREST_P
LANTATION
S
SHRUBLAN
D
GRASSLAN
D
WETLAND URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_LA
ND
REGIONS_I [%] [%] [%] [%] [%] [%] [%] [%] [%] [%] [%]
EU27 0 0 0 0 0 0 0 0 0 0 0 0
UK 000000000000
CHINA 0 0 0 0 0 0 0 0 0 0 0 0
EASOC 0 0 0 0 0 0 0 0 0 0 0 0
INDIA 0 0 0 0 0 0 0 0 0 0 0 0
LATAM 0.34 0 0.12 0.44 0 0.04 0 0 0 0 0 0.05
RUSSIA 0 0 0 0 0 0 0 0 0 0 0 0
USMCA 0 0 0 0 0 0 0 0 0 0 0 0
LROW 0 0 0 0 0 0 0 0 0 0 0 0
INITIAL_SHARE_OF_FOREST_PLANTATIONS_FORM_OTHER_LANDS_BY_REGION (REGIONS_I,LANDS_I)
LANDS_I RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_P
RIMARY
FOREST_P
LANTATION
S
SHRUBLAN
D
GRASSLAN
D
WETLAND URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_LA
ND
REGIONS_I [%] [%] [%] [%] [%] [%] [%] [%] [%] [%] [%]
EU27 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
UK 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
CHINA 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
EASOC 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
INDIA 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
LATAM 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
RUSSIA 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
USMCA 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
LROW 0.23 0 0.61 0 0 0.1 0.6 0 0 0 0 0
INITIAL_SHARE_OF_NEW_URBAN_FORM_OTHER_LANDS_BY_REGION (REGIONS_I,LANDS_I)
LANDS_I RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_P
RIMARY
FOREST_P
LANTATION
S
SHRUBLAN
D
GRASSLAN
D
WETLAND URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_LA
ND
REGIONS_I [%] [%] [%] [%] [%] [%] [%] [%] [%] [%] [%]
EU27 0.75 0 0.08 0 0 0.04 0.06 0 0 0 0 0.06
UK 0.75 0 0.08 0 0 0.04 0.06 0 0 0 0 0.06
CHINA 0.76 0 0.03 0 0 0.06 0.14 0 0 0 0 0.02
EASOC 0.82950502 0 0.06475246 0 0 0.06306926 0.01297029 0 0 0 0 0.03
INDIA 0.84 0 0.03 0 0 0.07 0.05 0 0 0 0 0.01
LATAM 0.45 0 0.11 0 0 0.35 0.08 0 0 0 0 0.02
RUSSIA 0.67 0 0.08 0 0 0.12 0.09 0 0 0 0 0.04
USMCA 0.40465181 0 0.17046426 0 0 0.24418755 0.16313836 0 0 0 0 0.01244197
LROW 0.53574826 0 0.09093677 0 0 0.19739033 0.06602194 0 0 0 0 0.10978433
INITIAL SHARE_OF_NEW_SOLAR_FORM_OTHER_LANDS_BY_REGION (REGIONS_I,LANDS_I)
LANDS_I RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_P
RIMARY
FOREST_P
LANTATION
S
SHRUBLAN
D
GRASSLAN
D
WETLAND URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_LA
ND
REGIONS_I [%] [%] [%] [%] [%] [%] [%] [%] [%] [%] [%]
EU27 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
UK 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
CHINA 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
EASOC 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
INDIA 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
LATAM 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
RUSSIA 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
USMCA 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
LROW 0.125 0 0 0 0 0.125 0.125 0 0 0 0 0.625
EU27
In Table 8 one can see he his o ical ends o land use change in EU. EU27 has had a
dec ease o ain ed c opland ha shows a s agna ion in he las yea s and a simila
g ow h o i iga ed c opland ha ha e been main ained. Fo es p ima y g ows in he
his o ical da a and has been accommoda ed o be ze o, as explained in p e ious
sec ion. Sh ubland, snow ice and wa e bodies and o he land a e assumed o ha e no
demand. The his o ical demand o plan a ions and u ban is main ained. Managed
o es demand is se equal o he alue o annual de o es a ion eco ded in FAO da a.
G assland shows a signi ican loss ha is cohe en wi h he abandonmen o ex ensi e
a ming seen in he EU and is main ained wi h a small inc ease o adjus he es o he
uses. Table 9 shows he calib a ed sha es.
The e o be ween he his o ical and he simula ed land use a eas a e he calib a ion
a e shown in Figu e 3. The a e age e o is less han 0.4% and, al hough some land
uses such as c opland ain ed and o es managed each 4% in some yea s, his esul is
conside ed o be accep able aking in o accoun he big disc epancies ha a e always
p esen in land use da a a his le el o agg ega ion.
Table 8. EU27 ini ial and calib a ed land use end demands
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
EU27 Ini ial ends o land
demand (km2/Yea )
-4471.5 517.9 -303.2 233.6 3515.1 749.0 -3280.0 0.0 691.9 0.0 23.6 2323.4
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
EU27 calib a ed ends o land
demand (km2/Yea )
-4471.5 517.9 1127.0 0.0 3515.1 0, -4000.0 0, 691.9 0.0 0.0 0.0
Table 9. EU27 calib a ed ma ices o sha es o land use changes om o he s
Calib a ed sha es o land use changes om o he s (EU27)
sha e o --> ha comes om: RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
RAINFED 0.00 1, 0.3, 0, 0.23 0, 0, 0, 0.75, 0.13, 0, 0;
IRRIGATED 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
FOREST_MANAGED 0.06 0, 0, 0, 0.61 0, 0, 0, 0.08, 0, 0, 0;
FOREST_PRIMARY 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
FOREST_PLANTATIONS 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
SHRUBLAND 0.80 0, 0.3, 0, 0.10 0, 0, 0, 0.04, 0.13, 0, 0;
GRASSLAND 0.12 0, 0.4, 0, 0.06 0, 0, 0, 0.06, 0.13, 0, 0;
WETLAND 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
URBAN 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
SOLAR 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
SNOW_ICE_WATERBODIES 0.00 0, 0, 0, 0.00 0, 0, 0, 0, 0, 0, 0;
OTHER_LAND 0.02 0, 0, 0, 0.00 0, 1, 0, 0.06, 0.63, 0, 0;
Figu e 3. Pe cen o e o be ween his o ical and simula ed alues o land uses in EU27
a e he calib a ion.
UK
In Table 10 one can see he his o ical ends o land use change in UK. UK shows no
signi ican change o o es s and sh ublands and loss o i iga ed c opland ( hough he
absolu e alue o i iga ed c opland in UK is e y small). His o ical ends o c opland
ain ed and plan a ions ha e been educed a bi o adjus he loss o o he land. Table
11 shows he calib a ed sha es. In gene al, land use changes a e small in UK and he
e o be ween he his o ical and he simula ed land use a eas a e he calib a ion a e
less han 6% o mos land uses (Figu e 4). The ela i e e o o c opland i iga ed is no
conside ed impo an because he small a ea o his land use in UK makes i negligigle.
Table 10. UK ini ial and calib a ed land use end demands
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
UK Ini ial ends o land
demand (km2/Yea )
352.0 -98.0 0.0 0.0 125.0 0.0 150.0 0.0 12.0 0.0 -1.0 -540.0
UK calib a ed ends o land
demand (km2/Yea )
254.0 0.0 0.0 0.0 94.0 0.0 0.0 0.0 12.4 0.0 0.0 0.0
Table 11. UK calib a ed ma ices o sha es o land use changes om o he s
Calib a ed sha es o land use changes om o he s (UK)
sha e o --> ha comes om: RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
RAINFED 0.00 1.00 0.30 0.00 0.30 0.00 0.00 0.00 0.75 0.45 0.00 0.00
IRRIGATED 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_MANAGED 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
FOREST_PRIMARY 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_PLANTATIONS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
SHRUBLAND 0.92 0.00 0.30 0.00 0.30 0.00 0.00 0.00 0.13 0.12 0.00 0.00
GRASSLAND 0.06 0.00 0.40 0.00 0.40 0.00 0.00 0.00 0.06 0.40 0.00 0.00
WETLAND 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
URBAN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SOLAR 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SNOW_ICE_WATERBODIES 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
OTHER_LAND 0.02 0.00 0.00 0.00 0.00 0.00 1.00 0.00 0.06 0.00 0.00 0.00
Figu e 4. Pe cen o e o be ween his o ical and simula ed alues o land uses in UK
a e he calib a ion.
CHINA
In Table 12 one can see he his o ical ends o land use change in China. China shows a
la ge inc ease o o es s, plan a ions and c oplands ha seems o come om o he
land. I iga ed land is much la ge han in o he egions. U ban expansion is la ge and
i iga ed land demand is inc eased o cope wi h he demands om u ban. Table 13
shows he calib a ed sha es and he e o be ween he his o ical and he simula ed
land use a eas a e he calib a ion a e shown in Figu e 5. The a e age e o is less han
6% o all uses.
Table 12. China ini ial and calib a ed land use end demands
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
China Ini ial ends o land
demand (km2/Yea )
1336.0 0.0 6991.0 0.0 13933.0 -29.0 0.0 0.0 3876.0 0.0 149.0 -26256.0
China calib a ed ends o land
demand (km2/Yea )
4772.1 49056.1 6990.6 0.0 13933.1 0.0 0.0 0.0 3875.9 0.0 0.0 0.0
Table 13. China calib a ed ma ices o sha es o land use changes om o he s
Calib a ed sha es o land use changes om o he s (China)
sha e o --> ha comes om: RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
RAINFED 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 0.76 0.15 0.00 0.00
IRRIGATED 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
FOREST_MANAGED 0.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.03 0.01 0.00 0.00
FOREST_PRIMARY 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_PLANTATIONS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
SHRUBLAND 0.60 0.00 0.50 0.00 0.50 0.00 0.00 0.00 0.20 0.04 0.00 0.00
GRASSLAND 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00
WETLAND 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
URBAN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SOLAR 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SNOW_ICE_WATERBODIES 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.00
OTHER_LAND 0.00 0.00 0.50 0.00 0.50 0.00 1.00 0.00 0.01 0.65 0.00 0.00
Figu e 5. Pe cen o e o be ween his o ical and simula ed alues o land uses in China
a e he calib a ion.
EASOC
In Table 14 one can see he his o ical ends o land use change in EASOC. Bo h
c oplands expe imen impo an inc eases ha seem o be compensa ed wi h he
dec ease o o es managed and p ima y. Table 15 shows he calib a ed sha es.
The e o be ween he his o ical and he simula ed land use a eas a e he calib a ion
a e shown in Figu e 6. The e is a ele an e o o sh ubland and o he land ha we
canno compensa e wi h he calib a ion. I seems o come om he ac ha sh ubland
and o he land a eas ha e no been ob ained om eal his o ical da a bu om and
app oxima ion (assuming cons an p opo ions be ween hem) and his assump ion
migh no hold. In any case, hese uses a e o e y li le impo ance o ou model.
Table 14. EASOC ini ial and calib a ed land use end demands
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
EASOC Ini ial ends o land
demand (km2/Yea )
15692.0 -155.0 -6669.0 -1477.0 3309.0 466.0 ###### 0.0 1341.0 0.0 -53.0 25710.0
EASOC calib a ed ends o
land demand (km2/Yea )
15691.9 -155.0 0.0 0.0 3640.3 0.0 ###### 0.0 1341.3 0.0 0.0 0.0
Table 15. EASOC calib a ed ma ices o sha es o land use changes om o he s
Calib a ed sha es o land use changes om o he s (EASOC)
sha e o --> ha comes om: RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
RAINFED 0.00 1.00 0.30 0.00 0.30 0.00 0.00 0.00 0.75 0.63 0.00 0.00
IRRIGATED 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00
FOREST_MANAGED 0.40 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.08 0.06 0.00 0.00
FOREST_PRIMARY 0.14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_PLANTATIONS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.00 0.00
SHRUBLAND 0.46 0.00 0.30 0.00 0.30 0.00 0.00 0.00 0.04 0.06 0.00 0.00
GRASSLAND 0.00 0.00 0.40 0.00 0.40 0.00 0.00 0.00 0.06 0.08 0.00 0.00
WETLAND 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
URBAN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SOLAR 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SNOW_ICE_WATERBODIES 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
OTHER_LAND 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.00 0.07 0.02 0.00 0.00
In Table 24 one can see he his o ical ends o land use change in LROW, ha shows a
la ge c opland expansion ha can explain he losses o managed and p ima y o es s.
Table 25 shows he calib a ed sha es. The e o s a e below 6% and can be assumed.
Table 24. LROW ini ial and calib a ed land use end demands
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
LROW Ini ial ends o land
demand (km2/Yea )
28841.0 -7048.0 -50912.0 -12302.0 3430.0 -4258.0 ###### 0.0 2872.0 0.0 -2231.0 66945.0
LROW calib a ed ends o
land demand (km2/Yea )
14000.0 -7048.2 -37000.0 -7000.0 3429.7 0.0 ###### 0.0 2872.4 0.0 0.0 0.0
Table 25. LROW calib a ed ma ices o sha es o land use changes om o he s
Calib a ed sha es o land use changes om o he s (LROW)
sha e o --> ha comes om: RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
RAINFED 0.00 1.00 1.00 1.00 0.30 0.30 0.00 0.00 0.00 0.00 0.00 0.00
IRRIGATED 1.00 0.00 0.00 0.00 0.54 0.54 0.08 0.08 0.00 0.00 0.00 0.00
FOREST_MANAGED 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_PRIMARY 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FOREST_PLANTATIONS 0.70 0.70 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SHRUBLAND 0.00 0.00 0.00 0.00 0.09 0.09 0.02 0.02 0.00 0.00 0.00 0.00
GRASSLAND 0.30 0.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
WETLAND 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
URBAN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SOLAR 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02 0.00 0.00 0.00 0.00
SNOW_ICE_WATERBODIES 0.00 0.00 0.00 0.00 0.30 0.30 0.00 0.00 0.00 0.00 0.00 0.00
OTHER_LAND 0.00 0.00 0.00 0.00 0.20 0.20 0.08 0.08 0.00 0.00 0.00 0.00
Figu e 11. Pe cen o e o be ween his o ical and simula ed alues o land uses in
LROW a e he calib a ion.
The u u e ends o land expansion used in he model when he his o ical pe iod ends
a e no necessa ily he same as he his o ical ones, since some uses show clea up u e
o he pas ends. The ends used a e he his o ical da a a e shown in able 26.
Table 26. T ends o land expansion used in he simula ion o he model a e he
his o ical pe iod
TRENDS OF FUTURE LAND
DEMAND BY REGION
RAINFED IRRIGATED
FOREST_M
ANAGED
FOREST_
PRIMARY
FOREST_
PLANTATI
ONS
SHRUB
LAND
GRAS
SLAND
WETL
AND
URBAN SOLAR
SNOW_ICE
_WATERB
ODIES
OTHER_
LAND
REGIONS_I|LANDS_I
[Mm2/Yea ]
[Mm2/Yea ] [Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ]
[Mm2/Yea ] [Mm2/Yea ]
EU27 0 0 0.00112702 0 0.003515 0 0 0 0.0007 0 0 0
UK 0 0 0 0 0.000125 0 0 0 1E-05 0 0 0
CHINA 0.004 0.00342736 0.01 0 0.013933 0 0 0 0.0039 0 0 0
EASOC 0.015551 9.0001E-05 0 0 0.00364 0 0 0 0.0013 0 0 0
INDIA 0 0 0.000484 0 0.001533 0 0 0 0.0007 0 0 0
LATAM 0.008 0.00193252 -0.03 0 0.004762 0 0 0 0.0006 0 0 0.04
RUSSIA 6.29E-05 -0.0001621 0.00122584 0.001404 0.0011 0 0 0 0.0003 0 0 0
USMCA 0 0.00074409 0 -0.001057 0.006813 0 0 0 0.0021 0 0 0
LROW 0.028841 0 -0.0509123 -0.012302 0.001715 0 0 0 0.0029 0 0 0.044
REFERENCES
[1] an Sch ojens ein Lan man, J., Ve bu g, P.H., B eg , A., Gee man, S., 2011. Co e
P inciples and Concep s in Land-Use Modelling: A Li e a u e Re iew, in: Koomen, E.,
Bo sboom- an Beu den, J. (Eds.),
[2] Heis e mann, M., Mülle , C., Ronnebe ge , K., 2006. Land in sigh ?: Achie emen s,
de ici s and po en ials o con inen al o global scale land-use modeling. Ag ic. Ecosys .
En i on. 114, 141–158. doi:10.1016/J.AGEE.2005.11.015
[3] Schaldach, R., P iess, J.A., 2008. In eg a ed Models o he Land Sys em: A Re iew o
Modelling App oaches on he Regional o Global Scale. Li ing Re . Landsc. Res. 2, 1.
doi:10.12942/l l -2008-1
[4] an Soesbe gen, A., 2016. A e iew o land-use change models. UNEP Wo ld
Conse a ion Moni o ing Cen e, Camb idge UK.
[5] h ps://www.en i onmen algeog aphy.nl/si e/da a-models/models/
[6] S eh es , E., an Vuu en, D., Bouwman, L., K am, T., 2014. In eg a ed assessmen o
global en i onmen al change wi h IMAGE 3.0: Model desc ip ion and policy
applica ions. Ne he lands En i onmen al Assessmen Agency (PBL).
[7] h ps://www.pik-po sdam.de/en/ins i u e/depa men s/ac i i ies/biosphe e-wa e -
modelling/lpjml
[8] an Asselen, S., Ve bu g, P.H., 2013. Land co e change o land-use in ensi ica ion:
simula ing land sys em change wi h a global-scale land change model. Glob. Chang.
Biol. 19, 3648–3667. doi:10.1111/gcb.12331
[9] Die ich, J.P., Bodi sky, B.L., Humpenode , F., Weindl, I., S e ano ic, M., Ka s ens, K.,
K eidenweis, U., Wang, X., Mish a, A., Klein, D., Amb osio, G., A aujo, E., Yalew, A.W.,
Baums a k, L., Wi h, S., Giannousakis, A., Beie , F., Chen, D.M.-C., Lo ze-Campen, H.,
Popp, A., 2019. MAgPIE 4 - a modula open-sou ce amewo k o modeling global land
sys ems. Geosci. Model De . 12, 1299–1299.
[10] Wise, M., Cal in, K., Kyle, P., Luckow, P., Edmonds, J., 2014. Economic and physical
modeling o land use in GCAM 3.0 and an applica ion o ag icul u al p oduc i i y, land,
and e es ial ca bon. Clim. Chang. Econ. 05, 1450003.
doi:10.1142/S2010007814500031
[11] Wise, M., Cal in, K., Thomson, A., Cla ke, L., Bond-Lambe y, B., Sands, R., Smi h,
S.J., Jane os, A., Edmonds, J., 2009. Implica ions o limi ing CO2 concen a ions o land
use and ene gy. Science 324, 1183–6. doi:10.1126/science.1168475
[12] Ha lík, P., Schneide , U.A., Schmid, E., Bö che , H., F i z, S., Skalský, R., Aoki, K.,
Ca a, S. De, Kinde mann, G., K axne , F., Leduc, S., McCallum, I., Mosnie , A., Saue , T.,
Obe s eine , M., 2011. Global land-use implica ions o i s and second gene a ion
bio uel a ge s. Ene gy Policy 39, 5690–5702. doi:10.1016/J.ENPOL.2010.03.030
[13] Ha lík, P., Valin, H., Mosnie , A., F ank, S., Lau i, P., Leclè e, D., Palazzo, A., Ba ka,
M., Boe e, E., B ouwe , A., Deppe mann, A., E molie a, T., Fo sell, N., Di Ful io, F.,
Obe s eine, M., He e o, M., Schmid, E., Schneide , U., Hasegawa, T., 2018. GLOBIOM
Documen a ion. Laxenbu g, Aus ia.
[14] Ch is oph Mülle , Elke S eh es , Jelle G an Minnen, Ba S enge s, We ne on
Bloh, A hu H W Beusen, Sibyll Schapho , Tom K am and Wol gang Luch . D i e s and
pa e ns o land biosphe e ca bon balance e e sal. En i on.Res.Le . 2016. 11 044002
[15] Ma in on Lampe, Di k Willenbockel, Helal Ahammad, Elodie Blanc, Yongxia Cai,
Ka he ine Cal in, Shinichi o Fujimo i, Tomoko Hasegawa, Pe Ha lik, Edwina Heyhoe,
Page Kyle, He mann Lo ze-Campen, Daniel Mason d'C oz, Ge ald C. Nelson, Ronald D.
Sands, Ch is oph Schmi z, And zej Tabeau, Hugo Valin, Dominique an de
Mensb ugghe, Hans an Meijl. Why do global long- e m scena ios o ag icul u e
di e ? An o e iew o he AgMIP Global Economic Model In e compa ison. Ag icul u al
Economics, Volume45, Issue1, Janua y 2014. h ps://doi.o g/10.1111/agec.12086
[16] Meadows DH, Meadows DL, Rande s J, Beh ens WW. The limi s o g ow h. New
Yo k: Uni e se Books; 1972.
[17] Mapping SPAM (Spa ial P oduc ion Alloca ion Model). h ps://mapspam.in o/
[18] h ps://www. ao.o g/ aos a /en/#da a/RL/me ada a FAO de ini ions and
s anda ds land use
[19] F. N. Tubiello e al., “Measu ing he wo ld’s c opland a ea,” Na Food, ol. 4, no.
1, A . no. 1, Jan. 2023, doi: 10.1038/s43016-022-00667-9.
[20] Modelado de los cambios de uso de la ie a median e Dinámica de Sis emas pa a
su in eg ación en el modelo WILIAM. T abajo Fin de G ado, Uni e sidad de Valladolid.
[21] Ma ina Campano-Méndez, Land use Chnages Li e a u a Re iew. GEEDS in e nal
epo , July 2021. h ps://u adoc.u a.es/handle/10324/75091
[22] Fe e as-Alonso, N., Capellán-Pé ez, I., Adam, A., de Blas, I., Media illa, M. 2024.
Mi iga ion o land- ela ed impac s o sola deploymen in he Eu opean Union h ough
land planning policies. Ene gy, 302, 131617.
