Land Cover Mesoamérica 2018 - CCI ESA
Parameter
Land Cover Mesoamérica
10 classes
Represented classes
0. No Data
1. Tree cover areas
2. Shrub cover areas
3. Grassland
4, Cropland
5. Vegetation aquatic or regularly flooded
6. Lichen Mosses/ Sparse vegetation
7. Bare areas
8. Built up areas
9, Snow and/or Ice
10. Open Water
Description
Prototype high resolution LC map at 10m over Mexico and Central America based on more than 2 years of Sentinel-2A and 2B observations from January 2016 to March 2018. The main objective of the 'S2 prototype LC map at 10m of Mesoamerica' release is to collect users feedback in order to improve the next generation of HR Land Cover products and drive the R&D activities to achieve that objective. The typology of the 'S2 prototype LC map at 10m of Mesoamerica' was defined using the Land Cover Classification System (LCCS) (FAO) which defines LC classes using a set of classifiers. The system was designed as a hierarchical classification, which allows adjusting the thematic detail of the legend to the amount of information available to describe each LC class, whilst following a standardised classification approach. In this LC mapping exercise, the regional landscape of Mexico and Central America is described in 10 generic LC classes: "trees cover areas", "shrubs cover areas", "grassland", "cropland", "vegetation aquatic or regularly flooded", "sparse vegetation", "bare areas", "built up areas", "snow and/or ice" and "open water". © Contains modified Copernicus data (2016/2017/2018) © ESA Climate Change Initiative - Land Cover project 2018
European Space Agency (ESA)
Source data
Description
The CCI Land Cover (LC) team is proud to announce the successful development of a prototype high resolution LC map at 10m over Mexico and Central America based on more than 2 years of Sentinel-2A and 2B observations from January 2016 to March 2018. The main objective of the 'S2 prototype LC map at 10m of Mesoamerica' release is to collect users feedback in order to improve the next generation of HR Land Cover products and drive the R&D activities to achieve that objective.
The Coordinate Reference System used for this dataset is a geographic coordinate system (GCS) based on the World Geodetic System 84 (WGS84) reference ellipsoid and using a Plate Carrée projection.
Spatial resolution
Continental coverage: Africa
10m spatial resolution
Temporal resolution
Period of observation:
2018