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Although land use/cover maps are widely used to support management and environmental policies, only some studies have reported their accuracy using sound and complete assessments. Thematic map accuracy assessment is typically achieved by comparing reference sites labeled with the “ground-truth” category to the ones depicted in the land use/cover map. A variety of sampling designs are used to select these references sites. The estimators for accuracy indices and the variance of these estimators depend on the sampling design. However, the tools used to assess accuracy available in the main program packages compute the accuracy indices without taking into account the sampling and give inconsistent estimates. As an alternative, we present free user-friendly tools that enable users beyond the Geographic Information Science Community to compute accuracy indices and estimate corrected areas of given categories with their respective confidence intervals. The tool runs in Dinamica EGO, a free platform for environmental spatial modeling as well as a Q-GIS plugin and aRpackage. Additionally, a practical application example is described using a case study area in central-west Mexico.

Gebhardt et al. (2014) presented the Monitoring Activity Data for the Mexican REDD+ program (MAD-MEX), an automatic nation-wide land cover monitoring system for the Mexican REDD+ MRV. Though MAD-MEX represents a valuable first effort toward establishing a national reference emissions level for the implementation of REDD+ in Mexico, in this paper, we argue that this land cover system has important limitations that may prevent it from becoming operational for REDD+ MRV. Specifically, we show that (1) the accuracy assessment of MAD-MEX land cover maps is optimistically biased; (2) the ability of MAD-MEX to monitor land cover change, including deforestation and forest degradation; is poor and (3) the use of an entirely automatic classification approach, such as that followed by MAD-MEX, is highly problematic in the case of a large and heterogeneous country like Mexico. We discuss these limitations and call into question the ability of a land cover monitoring system, such as MAD-MEX, both to elaborate a national reference emissions level and to monitor future forest cover change, as part of a REDD+ MRV system. We provide some insights with the aim of improving the development of nation-wide land cover monitoring systems in Mexico and elsewhere.