LCCS3 BASIC CODER (V 0.4) LCCS3 Basic Coder is a
QGis Plugin (developed in PYTHON) aiming at facilitating the use of LCCS3 legends to code
geographical features. It has a user-friendly graphical interface and is designed for a fast
coding without going in depth on all the opportunities of the object-oriented model behind LCML
(Land Cover Meta Language). Same functionality is available through the FAO's MAD-CAT software.
Global Land Cover SHARE
GLC-SHARE database of year 2014, beta-release 1.0, is a global land cover data under one roof
representing the most-reliable global view of planetary land cover assembled to-date. Click here for more
info and download.
AFRICOVER full res data
FAO just made
publicly available the full resolution land cover datasetd of the
AFRICOVER project: Burundi, DRC, Egypt, Eritrea, Kenya, Rwanda,
Somalia, Sudan, Tanzania and Uganda.
[more..]
Tools: MAD-CAT
MAD-CAT
is a stand alone application that integrates land cover mapping,
change detection and validation functions. It allows delineations from
satellite imagery using object-based classification techniques.
[more..]
PROGRAMME BACKGROUND
The GLCN initiative (brochure) is
the result of a common effort of
partners
and sponsors to answer the need, expressed by the international
community, for a standardized global land cover database.
This initiative has been launched at the conference "Strategies
for Global Land Cover Mapping and Monitoring" held in Florence
6-8 May 2002.
OBJECTIVES
Harmonize land cover definitions, classification systems,
mapping and monitoring specifications.
Develop standards for global mapping.
Initiate building of a global database.
Promote outreach initiatives
on development methodologies and applications of land cover data.
Provide advisory services.
Function as an international, politically neutral and not-for-profit
clearinghouse for land cover information at global and regional levels.