NATURAL RESOURCES DEPARTMENT (NR)
International Symposium on Land Cover
Mapping for the African Continent
June 25-27, 2013
UNEP HQ & RCMRD, Nairobi, Kenya
FAO Land Cover Mapping methodology,
tools and standards
&
GLC–SHARE database
Renato Cumani & John Latham
Land and Water Division (NRL)
NATURAL RESOURCES DEPARTMENT (NR)
Content
 FAO Global Land Cover Network
 Standards for Land Cover
mapping
 FAO Land Cover Mapping Toolbox
 African land cover databases
 Global Land Cover SHARE
database
 Conclusions
NATURAL RESOURCES DEPARTMENT (NR)
Main activities of the organization




Putting information within reach
Sharing policy expertise
Providing a meeting place for nations
Bringing knowledge to the field
NATURAL RESOURCES DEPARTMENT (NR)
FAO Global Land Cover Network (GLCN)
Main Objectives:
 To improve linkages between global, regional and
national studies on land cover and the environment
 To improve standardization, homogenization,
compatibility and efficiency of information provided
by different applications
 To provide information that improves design and
efficiency of sampling for validation of land cover
products at global, regional and national levels.
 To increase use and sharing of remote sensing data
and its derived datasets
 To provide comparable products at global, regional,
and national and lower levels
 To undertake capacity development and institution
strengthening to maximize benefits for developing
countries
 To support operational development and use by
national stakeholders of products emanating from
the programme
multi-date landsat imagery
NATURAL RESOURCES DEPARTMENT (NR)
FAO GLCN Core activities
 Establish global network
 Develop Land cover mapping methodology
 Standards development (LCCS/LCML)
 Land Cover Mapping Toolbox
(LCCS/MadCat/ADG)
 Technical assistance to national experts
for land cover mapping activities
 Preparation of guidelines, manuals,
templates, workshops, technical papers,
metadata
 Capacity building
 Awareness raising workshops, training
resources and sessions
 Dissemination and outreach (FAO
GeoNetwork and FAO GLCN website)
 Enable use of the land cover information
Sudan
•Nepal
multi-date landsat imagery
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
Standards and Classification System
LCCS / LCML / ISO 19144-2:2012
 LCCS: Comprehensive methodology for description,
characterization, classification and comparison of
most land cover features identified anywhere in the
world, at any scale or level of detail: basis for
comparative classification. (6 UN official languages)
 Created in response to a need for a harmonized
and standardized collection and reporting on the
status and trends of land cover
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
LCCS databases
Global Land Cover
(GLC) 2000
1 km resolution
The dataset was
sponsored by
members of the
VEGETATION
programme,
including JRC.
Each partner used
the Land Cover
Classification
System (LCCS)
produced by FAO
and UNEP, which
ensured that a
standard legend
was used across
the globe
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
LCCS databases
GlobCover ~2006
300 m resolution
The GlobCover
Land Cover
product is based
on ENVISAT
MERIS data at
full resolution
from January
2005 to June
2006. The
GlobCover Land
Cover product is
labelled
according to the
UN Land Cover
Classification
System
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
FAO Land Cover Mapping Toolbox
THEMATIC
& CART.
ASPECT
INTERPRETATION
EFFICIENCY
ACCURACY MULTI USER
DATA BASE
ANALISYS
BROWSER
Land
Map
Advanc.
cover
Acc.
Database
class.
Prog.
GATEW.
Syst.
DATA PRODUCERS
DATA USERS
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
LCCS 2: 2001
(use LCCS)
LCCS 3: 2013
(use LCML/UML)
ADG 2: 2003
ADG 3: 2013
ADG 3 for ArcGIS 10.x: 2013
NATURAL RESOURCES DEPARTMENT (NR)
Standards and Tools
Mapping Device – Change Analysis Tools
(MADCAT)
 Application designed by FAO
 Uses object-base classification
 Current version – Release June 2013
 Wizard driven installation
 Implemented using .Net Framework
 Coding with LCCS2 and LCCS3
 Requires Windows XP / Vista / 7 /8 (32 and 64
bit)
 Free to use for FAO programmes
 One time activation needed:
 Institution, User Name, Address, PC CODE
 send request by email
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
FAO’s Land Cover Mapping in Africa
Country scale (30m or better resolution)
•on going ECONET
Ethiopia
•2012
Fouta Djallon
Highlands
Malawi
•2011
Sudan
•2010
South Sudan
Tunisia
Kenya Update
•2007
Somalia
•2006
Kenya LCC
•2005
Senegal
•2004
Libya
•1998- 2002
AFRICOVER
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
GLCN/AFRICOVER: East Africa Module
Development of a regional database and regional aggregation
 Project facts:
 Mapped area: 8.5 million
Km2
 Countries covered: 10
 Landsat Scenes used:
more than 400
 Period of activity: 19982004
 Result: Multipurpose
Africover Database for
the Environmental
Resources produced at a
1:200,000 scale
(1:100,000 for small
countries and specific
areas)
Burundi, DR Congo, Egypt, Eritrea,
Kenya, Rwanda, Somalia, Sudan,
Tanzania and Uganda.
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Fouta Djallon Highlands land cover change
 Fouta Djallon AOI: ca. 400,000 Km2
 5 Countries within the AOI:
Guinea, Guinea-Bissau, Mali, Senegal,
Sierra Leone
LANDSAT coverage (30m res) 1990-2005
ASTER coverage (17 m res) 2008-2011
RapidEye coverage (5 m res) ~2005
Fouta Djallon
Highlands land cover
changes
1990
14000
13000
12000
11000
10000
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
2008
AG
NVH NVS
NVT URB WAT
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Malawi Land Cover change database (1990’s-2010’s)
From other to cropland
(square blue) and vice versa
(circle orange)
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Sudan Land Cover
Primary datasets:
 Landsat 30m (~2000, ~2005-2007 )
 Spot4 imagery
2009-2010, 2.5-5m, 10-20 m res
 IRS 2007, 15-22m res
 Aster 2005-2010,15 m res.
Ancillary:
 Googe Earth high resolution imagery
 Africover dataset (dated 1999-2000)
 ATLAS of Sudan
 Digital ATLAS (DVD)
 Posters
 Skin
 Implemented in Sudan
 Capacity to undertake land cover
assessments
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Land Cover Map of South Sudan
Primary:
 Landsat ETM imagery (GLS),
30m res., false color.
• 2000 circa
• 2005-2007
 Spot4 imagery
• 2006-2008, 10-20 m res.,
true color.
Ancillary
 Google Earth high resolution
imagery
 Africover datasets
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Senegal Land Cover Change: 2005
 55 land cover classes
 Landsat 1990’s and
2005’s
 Completed in Senegal
with involvement of
national exerts
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
Libya Land Cover database
 Landsat ETM+ imagery 2001’s
and 2002’s
 88 landsat scenes in total
ECO–NET Africa
BASIC OBJECTS
PROPRERTIES
CHARACTERISTICS
Herbaceous
Cover 30 – 50 %
Tree
Cover 1 -3 %
Natural
Eight 5 -8 m.
Disposition: irregular
Leaf type: Broadleaf
Leaf type % 100
Scrub
Cultivated
Rainfed
Field size 1 ha
Cover 2 – 4 %
Natural
Eight 1 – 3 m.
Disposition: irregular
Leaf type: Broadleaf
Leaf type % 100
Average
0.30
0.10
Total St. Deviation
0.24
0.08
0.18
0.06
0.12
0.04
0.06
0.02
0.00
0.00
1
3
5
7
9 11 13 15 17 19 21 23 25 27 29 31 33 35
Dekad
NDVI Standard Deviation
 Earth Cover Network Africa
 Sample tiles at 10 by 10 Km
at half degree
 Very high resolution
imagery (targeted 5m or
better)
 Detailed land cover
mapping using LCML
enriched with vegetation
index(es) from remote
sensing
 About 9,000 sampling sites
 Coordinated and supervised
by FAO GLCN with
engagement of national
experts
NDVI Average
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
NATURAL RESOURCES DEPARTMENT (NR)
Africa Land Cover products
ECONET Outcomes
 Create a database with extremely
detailed information, global or regional,
comparable and continually updated in
support of a wide range of activities.
 Serve as multi-statistical source of
information at any level of detail or
complexity. Using specific software on the
Web, any end users worldwide will be
able to define a geographical area and
the categories for which area statistics
will be generated.
 Provide the most consistent, detailed and
dynamic test site for calibration and/or
accuracy assessment of any future wallto-wall global, regional or national Land
Cover mapping programmes
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE approach
 FAO System of Environmental Economic
Accounts (SEEA) London Group process
 Global Consultations, interviews,
comments, questions, recommendation
 A significant step in improving the
information accuracy of global land cover
database
 It integrates the best land cover data
available (at sub-national, national,
regional and global level) into one single
harmonized database
 It uses international standards: ISO TC
211 – 19144-2:2013 LMCL
 Recommendation 19b.1: That the
Land Cover Classification System
(LCCS 3) developed by FAO should
be adopted as the land cover
classification system in the revised
SEEA and that the LCML (ISO
19144-2) should be adopted at the
methodology for linking to
external sources of land cover
data described in other land cover
systems.
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE design principles
 Use existing available land cover databases at national, regional and
global level;
 Use the best available spatio-temporal land cover databases;
 Use the land cover legend prepared by SEEA and FAO based on the
Land Cover Meta-Language;
 Make use of the harmonization of the land cover elements
addressing semantic requirements;
 Use data fusion technology;
 Progressively update the database getting input from the community
of users and include additional datasets as they become available.
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE: fact-sheet
 Uses the FAO SEEA LCML(*) legend
 30 arc-second pixel resolution
 11+1 layers indicating the % share of
each class
 Dominant land cover layer and quality
score
 Overall class accuracy ~80%
 Designed as a platform to facilitate
crowd-sourcing
 Compatible with FAOSTAT classification
 Designed to be used for GAEZ 2010
update
Methodology and datasets will be published in 2013
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE SEEA Legend
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE SEEA LCML Legend
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
Coverage of land cover databases
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
Processing Chain
 Multi-source and multi-resolution data fusion through
use of the land cover class elements and the LCML
 Class confidence levels used in the processing chain
to use the optimal spatio-temporal information at
pixel level
 Per product and per class rating assigned by technical
experts (experts opinion)
 Outputs include 11 rasters at 30 arc-second, 1
dominant land cover dataset, 1 quality indicator
dataset including source date, resolution, sensor and
confidence level per pixel, metadata, and technical
paper
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-Share Database
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
Quality Assessment
Distribution of the validation points
Used ~1,000 points (ArcGIS and Google Earth validation)
Overall dominant class accuracy ~80%
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
NATURAL RESOURCES DEPARTMENT (NR)
GLC-SHARE database
GLC-SHARE Summary
 GCL-SHARE is the first global database created using the
ISO standard for land cover classification ISO TC 211 –
19144-2 LMCL (Land Cover Meta Language) and is
designed to be improved over time
 GLC-SHARE will be used for GAEZ 2010 update
 GLC-SHARE will be used to update Land Use Systems
2010 (FAO)
 Planned to be made publicly available for comments and
feedback by end of 2013
 Fully documented, including metadata, LCML/LCCS3
legend
 Update of the beta release with new available datasets
including the global coverage of Landsat 30 meter and
new national land cover datasets
 Maintained by FAO and community of practice partners
such as GEO, CGIAR, JRC, IIASA
NATURAL RESOURCES DEPARTMENT (NR)
Thank you
Contacts:
renato.cumani@fao.org
john.latham@fao.org
FAO
Links:
www.fao.org
www.fao.org/nr/gaez
www.fao.org/geonetwork
www.glcn.org