Abstract: Estimating forest area at a national scale within the United Nations program of Reducing Emissions from Deforestation and Forest Degradation (REDD) is primarily based on land cover information using remote sensing technologies. Timely delivery for a country of a size like Mexico can only be achieved in a standardized and cost-effective manner by automatic image classification. This paper describes the operational land cover monitoring system for Mexico. It utilizes national-scale cartographic reference data, all available Landsat satellite imagery, and field inventory data for validation. Seven annual national land cover maps between 1993 and 2008 were produced. The classification scheme defined 9 and 12 classes at two hierarchical levels. Overall accuracies achieved were up to 76%. Tropical and temperate forest was classified with accuracy up to 78% and 82%, respectively. Although specifically designed for the needs of Mexico, the general process is suitable for other participating countries in the REDD+ program to comply with guidelines on standardization and transparency of methods and to assure comparability. However, reporting of change is ill-advised based on the annual land cover products and a combination of annual land cover and change detection algorithms is suggested.
This is an open access article distributed under the
Creative Commons Attribution License which permits unrestricted use, distribution,
and reproduction in any medium, provided the original work is properly cited.
Export to BibTeX
MDPI and ACS Style
Gebhardt, S.; Wehrmann, T.; Ruiz, M.A.M.; Maeda, P.; Bishop, J.; Schramm, M.; Kopeinig, R.; Cartus, O.; Kellndorfer, J.; Ressl, R.; Santos, L.A.; Schmidt, M. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sens. 2014, 6, 3923-3943.
Gebhardt S, Wehrmann T, Ruiz MAM, Maeda P, Bishop J, Schramm M, Kopeinig R, Cartus O, Kellndorfer J, Ressl R, Santos LA, Schmidt M. MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data. Remote Sensing. 2014; 6(5):3923-3943.
Gebhardt, Steffen; Wehrmann, Thilo; Ruiz, Miguel A.M.; Maeda, Pedro; Bishop, Jesse; Schramm, Matthias; Kopeinig, Rene; Cartus, Oliver; Kellndorfer, Josef; Ressl, Rainer; Santos, Lucio A.; Schmidt, Michael. 2014. "MAD-MEX: Automatic Wall-to-Wall Land Cover Monitoring for the Mexican REDD-MRV Program Using All Landsat Data." Remote Sens. 6, no. 5: 3923-3943.