The most detailed maps ever of Earth¿s land surface have been created with the help of ESA¿s Envisat environmental satellite. Land cover has been charted from space before, but this global map has a resolution 10 times sharper than any of its predecessors.JRC.H.3-Global environement monitorin

ACHARD Frederic

ARINO Olivier

BICHERON Patrice

LATHAM John

WEBER Jean-Louis

WITT Ron

JRC Publications Repository

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GlobCover	land	cover	over	South	America
European Space Agency | Bulletin 136 | November 2008 25
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Olivier Arino 
Directorate	of	Earth	Observation,	ESRIN,	Frascati,	Italy
Patrice Bicheron
MEDIAS	France,	Toulouse,	France
Frederic Achard 
JRC,	Ispra,	Italy
John Latham 
FAO,	Roma,	Italy
Ron Witt 
UNEP,	Chatelaine,	Switzerland
Jean-Louis Weber
EEA,	Copenhagen,	Denmark
The	new	global	portrait	is	based	on	40	terabytes	of	imagery	
–	equivalent	to	the	content	of	40	million	books	–	acquired	by	
Envisat’s	Medium	Resolution	Imaging	Spectrometer	(MERIS)	
The most detailed portrait of Earth
instrument.	ESA	made	a	continuous	effort	to	ensure	the	
acquisitions	and	the	production	of	the	MERIS	300	m	Full	
Resolution	Full	Swath	(FRS)	products	for	the	period	from	
1	December	2004	to	30	June	2006.	
In	addition	to	being	made	fully	available	to	the	public	upon	
its	completion	in	September	this	year,	scientists	will	use	the	
data	to	plot	worldwide	land-cover	trends,	study	natural	and	
managed	ecosystems	and	to	model	climate	change	extent	
and	impacts.	They	are	hailing	the	product	–	generated	under	
the	ESA-initiated	GlobCover	project	–	as	a	‘milestone’.
The most detailed maps ever of Earth’s land surface 
have been created with the help of ESA’s Envisat 
environmental satellite. Land cover has been 
charted from space before, but this global map 
has a resolution 10 times sharper than any of its 
predecessors. 
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the	regional	and	global	modelling	that	is	vital	for	climate	
impact	and	sustainability	research.	
The land cover product
The	GlobCover	land	cover	product	is	the	first	freely	
available	product	at	300	m	resolution	and	is	therefore	a	
milestone	product	that	will	be	fundamental	to	a	broad-level	
stakeholder	community.	There	are	22	different	land	cover	
types	shown	in	the	map,	including	croplands,	wetlands,	
forests,	artificial	surfaces,	water	bodies	and	permanent	snow	
and	ice.	For	maximum	user	benefit,	the	map’s	thematic	
legend	is	compatible	with	the	UN	Land	Cover	Classification	
System	(LCCS).
In	order	to	deliver	the	full	dataset,	the	MERIS	(FRS)	
acquisition	capacities	had	to	be	dramatically	increased.	
This	was	achieved	through	a	better	strategy	of	acquisition	
between	ASAR	and	MERIS	instruments	outside	the	view	of	
the	Artemis	Data	Relay	Satellite.	Nevertheless	some	parts	
of	the	world	(east	of	the	Amazonian	basin,	Central	America,	
the	Philippines,	north-east	Quebec	and	Labrador,	the	Korean	
More than a map
Bi-monthly	products	from	January	2005	to	June	2006	are	
available	online.	They	can	be	accessed	through	a	newly	
developed	map	server	tool	on	ESA’s	GlobCover	web	site.	In	
June	2007,	additional	bimonthly	global	composites	were	
made	available	as	well	as	the	first	part	of	a	global	land	cover	
map	over	Eurasia.
However	the	GlobCover	product	is	much	more	than	a	map.	
It	is	a	scientific	and	technical	demonstration	of	the	first	
automated	mapping	of	land	cover	on	a	global	scale,	and	
provides	a	basis	for	the	detailed	description	of	the	land	
surface	states	needed	for	regional	climate	modelling.	
Information	on	land	cover	is	an	essential	requirement	
of	the	sustainable	management	of	natural	resources,	
environmental	protection,	food	security,	climate	change	
and	humanitarian	programmes.	It	forms	a	basis	for	ongoing	
studies	of	land-cover	and	land-use	dynamics	particularly	to	
improve	our	understanding	of	the	variation	of	the	nature-
society	dynamics	of	land	management,	thereby	facilitating	
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The	GlobCover	land	cover	product
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peninsula)	are	still	sparsely	covered.	A	new	methodology	
combining	MERIS	FR	and	MERIS	RR	is	under	investigation	to	
cover	these	problematic	areas.
In	order	to	be	able	to	use	the	time	series	of	measurements	
properly,	ESA	also	made	a	considerable	effort	to	improve	
MERIS	data	geo-location	accuracy.	A	resolution	of	150	m	was	
requested	by	the	user	community	and,	as	a	consequence,	
GlobCover	can	use	MERIS	only	if	such	requirement	is	
satisfied.	For	this	purpose,	ESA	commissioned	ACRI	to	
develop	the	AMORGOS	software	that	takes	as	input	the	
Level	1B	MERIS	FR,	the	restituted	attitude	file	and	operational	
or	precise	orbit	file.	AMORGOS	was	integrated	in	the	
GlobCover	processing	chain	by	MEDIAS,	complete	with	a	
projection	toolbox.	
The	quality	of	the	geolocation	accuracy	was	assessed	
using	146	pairs	of	MERIS	products	for	the	co-registration	
estimation.		The	absolute	geolocation	of	the	ortho-rectified	
MERIS	FRS	product	was	verified	using	10	scenes	from	Landsat	
ETM+	(30	m	spatial	resolution)	over	a	test	area	in	Spain	and	
Morocco.	The	result	of	this	exercise	was	that	the	total	RMS	
error	associated	with	geolocation	of	MERIS	FRS	data	was	
77.1	m	and	thus	the	accuracy	requirement	set	for	the	project	
was	achieved,	with	only	isolated	images	exceeding	150	m	
resolution.
The GlobCover system
The	GlobCover	system	consists	of	three	components:	
(1)	the	GlobCover	software,	(2)	the	execution	environment	
and	(3)	the	hardware.	The	system	has	to	be	capable	to	ingest	
all	Level	1B	MERIS	FRS	data	acquired	over	a	full	year	plus	
intermediate	and	final	products	of	the	pre-processing	and	
classification	chain.	In	total	this	amounts	to	a	data	load	of	
46	TB.	
The	pre-processing	chain	starts	with	the	geometric	
correction	of	the	MERIS	Level	1B	data.	After	the	geometric	
correction,	the	data	run	through	several	processing	steps	to	
calculate	surface	directional	reflectance	(SDR).	Algorithms	
have	been	implemented	to	adjust	images	for	atmospheric	
influences	(i.e.	gaseous	absorption,	Rayleigh	scattering,	
aerosol	effects),	to	detect	and	flag	clouds,	snow	areas	
and	land/water	bodies,	and	to	correct	the	images	for	the	
smile	effect	inherent	in	MERIS	data.	Before	archiving	the	
resulting	MERIS	FR	Level	2	data,	the	images	are	projected	
and	resampled	into	the	plate-carrée	projection.	The	previous	
full	swath	images	are	also	subset	into	5°	x	5°	tiles,	which	
represents	the	standard	size	for	a	GlobCover	product	(HDF	
format).
Level	3	processing	computes	bi-monthly,	seasonal	and	
annual	mosaics.	A	compositing	technique	using	the	
Bidirectional	Reflection	Distribution	Function	to	correct	
the	reflectance	for	different	illumination	and	viewing	
geometries	is	applied	for	the	bi-monthly	mosaics.	Temporal	
compositing	is	then	used	to	generate	seasonal	and	annual	
mosaics	by	averaging	monthly	mosaics	over	the	selected	
period.
The	classification	subsystem	generates	a	global	land	cover	
map	out	of	these	cloud-free	mosaics.	The	classification	runs	
separately	for	22	equal-reasoning	areas	and	is	organised	
into	five	steps.	The	first	process	classifies	the	selected	
mosaics	spectrally	in	a	large	number	of	classes.	These	classes	
are	then	temporally	characterised	by	the	computation	of	
phenological	parameters	(start,	end	and	duration	of	the	
vegetation	period),	using	the	time	series	of	MERIS	mosaics.	
The	subsequent	clustering	algorithm	uses	the	previous	
spectral	and	temporal	information	to	group	classes	with	
similar	characteristics	in	a	manageable	number	of	spectro-
temporal	classes.	The	fourth	processor,	the	referenced-based	
labelling	function,	transforms	these	spectro-temporal	
classes	into	previously	defined	LCCS	land	cover	classes.	The	
final	procedure	is	the	expert-based	labelling.	This	applies	an	
upgraded	set	of	labelling	rules	to	improve	the	referenced-
based	labelling	and	to	produce	the	final	land	cover	map.	
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Geolocation	accuracy	of	the	MERIS	products	after	
AMORGOS	processing.	Upper	plot	shows	the	relative	
accuracy	between	MERIS-MERIS	couples.	Plot	on	the	
bottom	shows	the	absolute	accuracy	between	MERIS-
Landsat	couples.	Semicircles	represent	the	minimum	
accuracy	requested	by	the	GlobCover	project
European Space Agency | Bulletin 136 | November 2008 29
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(Based	on	a	random	sampling	of	2186	cases,	the	experts	
achieved	the	following	results	for	homogeneous	land	cover.	
For	the	principal	classes,	the	users’	accuracies	are	as	follows:	
82.7%	for	cultivated	and	managed	terrestrial	land,	69.5%	
for	natural	and	semi	natural	terrestrial	vegetation,	19%	for	
natural	and	semi-natural	aquatic	vegetation,	63.6	%
for	artificial	surfaces,	88.1	for	bare	areas,	74.1%	for	water	
snow	and	ice,	while	that	for	producers	accuracies	are	69.6,	
87.8,	19.0,	43.8,	77.1	and	82.2%,	leading	to	an	overall	accuracy	
of	77.9%.	This	value	is	principally	due	to	the	difficulty	in	
mapping	aquatic	vegetation	and	artificial	surfaces,	which	is	
being	addressed	in	version	2.)
Interfacing with expert communities
An	international	network	of	partners	is	working	with	ESA	
on	the	GlobCover	project,	including	the	UN	Environment	
Programme	(UNEP),	the	UN	Food	and	Agriculture	
Organization	(FAO),	the	European	Commission’s	Joint	
Research	Centre	(JRC),	the	European	Environmental	Agency	
(EEA),	the	International	Geosphere	Biosphere	Programme	
(IGBP)	and	the	Global	Observations	of	Forest	Cover	and	
Global	Observations	of	Land	Dynamics	(GOFC-GOLD)	
Implementation	Team	Project	Office.	
Building	on	the	success	of	the	GLC-2000	project	(Global	Land	
Cover	map	for	the	year	2000)	coordinated	by	the	JRC,	ESA	
decided	to	launch	the	GlobCover	initiative	in	the	framework	
of	its	Data	User	Element	(DUE).	The	GlobCover	system,	
developed	and	operated	by	Medias-France,	together	with	
Brockmann	Consult,	the	Université	Catholique	de	Louvain	
and	partners,	is	a	great	step	forward	in	our	capacity	to	
automatically	produce	new	global	land	cover	products	with	
a	finer	resolution	and	a	more	detailed	thematic	content	than	
ever	achieved	in	the	past.	
A	unique	and	fundamental	component	of	the	project	was	
the	continuous	interface	with	this	community	of	eventual	
users	and	the	land	cover	expert	community,	to	make	sure	
that	the	resulting	products	were	‘fit	for	purpose’	and	that	
the	user	community	was	ready	to	exploit	the	products	once	
they	became	available.	
The	user	community	is	represented	in	the	project	by	key	
individuals	from	UNEP,	FAO,	JRC,	EEA,	IGBP	and	GOFC-
GOLD.	Their	involvement	was	managed	through	four	user	
consultations	held	at	ESRIN,	JRC	and	FAO	where	all	elements	
of	the	project	were	discussed	and	reviewed.	The	automatic	
rules	were	tuned	according	to	feedback	from	the	user	
community	received	at	these	meetings.	In	addition,	a	team	
of	regional	land	cover	experts	was	engaged	to	advise	on	the	
interpretation	of	the	spectral-temporal	classes	and	thus	
improve	the	automatic	labelling	procedure.	
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Online distribution
The	‘online’	distribution	of	gigabytes	of	data	was	also	a	
key	issue	that	ESA	had	to	face.	The	solution	was	provided	
by	the	development	of	the	IONIA	GlobCover	Access	Tool	
(GCAT)	that	provides	easy	and	fast	internet	access	to	the	
GlobCover	data	products.	It	is	accessible	to	any	‘authorised	
web	user’	through	a	simple	password-protected	registration	
scheme.	Once	authorised,	users	can	select	any	subset	of	the	
GlobCover	data	product	through	a	Graphic	User	Interface	
from	where	the	type	of	product	(bi-monthly,	seasonal,	
annual),	geographical	area	and	time	period	can	be	set.	
Data	distribution	uses	the	BitTorrent	protocol	(P2P)	to	
capitalise	on	the	number	of	simultaneous	users	and	reduce	
the	overall	stress	on	the	server	during	peak	user	access.	
For	this	reason,	the	GlobCover	team	(ESA	and	partners)	
participating	in	the	distribution	operate	as	‘seeders’,	
in	bit	torrent	terminology.	In	other	words,	they	share	
servers	where	GlobCover	products	are	stored.	To	optimise	
distribution	performance,	each	GlobCover	composite	is	
sub-divided	in	Macro	Tiles	(4x4	GlobCover	Tiles).	Users	can	
select	which	type	of	GCAT	product	they	wish	to	download	
(GlobCover	tile,	Macro	tile,	continental	or	world	coverage).	
More	information	and	data	access	can	be	found	at	:
www.esa.int/due/ionia/globcover
The	following	people	also	contributed	to	this	project:
Franck	Ranera,	Nigel	Houghton,	Philippe	Goryl,	Henri	Laur	&	Stephen	Briggs	
	 													ESA	Directorate	of	Earth	Observation,	ESRIN,	Frascati,	Italy.
Marc	Leroy	MEDIAS	France,	Toulouse,	France.
Carsten	Brockman	Brockmann	Consult,	Geesthacht,	Germany.
Sophie	Bontemps,	Pierre	Defourny	and	Christelle	Vancutsem	
	 													Université	Catholique	de	Louvain,	Louvain-La-Neuve,	Belgium.
Hugh	Eva,	Hans	Jürgen	Stiebig	and	Philippe	Mayaux	JRC,	Ispra,	Italy.
Antonio	Di	Gregorio	FAO,	Roma,	Italy.
Jaap	Van	Voerden	UNEP,	Chatelaine,	Switzerland.
Andrus	Meiner	EEA,	Copenhagen,	Denmark.
Cristiana	Schumullius	Martin	Herold,	GOFC-GOLD,	Jena,	Germany.
Stephen	Plummer,	Tobias	Langanke	IGBP,	Stockholm,	Sweden.	
Leon	Shouten	Infram,	The	Netherlands.
Ludovic	Bourg	ACRI-ST,	Sophia-Antipolis,	France.
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GlobCover	land	cover	over	Africa
European Space Agency | Bulletin 136 | November 2008 31
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The	following	people	also	contributed	to	this	project:
Franck	Ranera,	Nigel	Houghton,	Philippe	Goryl,	Henri	Laur	&	Stephen	Briggs	
	 													ESA	Directorate	of	Earth	Observation,	ESRIN,	Frascati,	Italy.
Marc	Leroy	MEDIAS	France,	Toulouse,	France.
Carsten	Brockman	Brockmann	Consult,	Geesthacht,	Germany.
Sophie	Bontemps,	Pierre	Defourny	and	Christelle	Vancutsem	
	 													Université	Catholique	de	Louvain,	Louvain-La-Neuve,	Belgium.
Hugh	Eva,	Hans	Jürgen	Stiebig	and	Philippe	Mayaux	JRC,	Ispra,	Italy.
Antonio	Di	Gregorio	FAO,	Roma,	Italy.
Jaap	Van	Voerden	UNEP,	Chatelaine,	Switzerland.
Andrus	Meiner	EEA,	Copenhagen,	Denmark.
Cristiana	Schumullius	Martin	Herold,	GOFC-GOLD,	Jena,	Germany.
Stephen	Plummer,	Tobias	Langanke	IGBP,	Stockholm,	Sweden.	
Leon	Shouten	Infram,	The	Netherlands.
Ludovic	Bourg	ACRI-ST,	Sophia-Antipolis,	France.
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GlobCover	land	cover	over	Oceania
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GlobCover	land	cover	over	South	East	Asia


The Most Detailed Portrait of Earth

http://www.esa.int/esapub/bulletin/bulletin136/bul136d_arino.pdf

The Most Detailed Portrait of Earth

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