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The production of Land Use and Land Cover (LULC) maps is essential to the understanding of landscape dynamics in space and time. LULC maps are a tool for the measurement of human footprint and social processes in the landscape and for the sustainable use of finite resources on the planet, a growing challenge in our densely populated societies. LULC maps with detailed forest taxonomy constitute a basis for sustainable forest management, especially in highly biodiverse areas. However, these maps are affected by misclassification errors, partly due to the intrinsic limitations of the satellite imagery used for map production. Misclassification occurs especially when categories of the classification system (classes) are not well distinguished, or ambiguous, in the satellite imagery. Therefore, statistical information on the quality, or accuracy, of these maps is critical because it provides error margins for the derived trends of land cover change, biodiversity loss and deforestation, these parameters being some of the few means that governmental agencies can provide as a guarantee of sustainable forest management practices associated with international conservation agreements. Assessing the accuracy of LULC maps is a common procedure in geo-science disciplines, as a means, for example, of validating automatic classification methods on a satellite image. For regional scale LULC maps, because of budget constraints and the distribution of many classes over the large extension of the map, the complexity of accuracy assessments is considerably increased. Only relatively recently have comprehensive accuracy assessments, with estimates for each class, been built and applied to regional or continental, detailed LULC maps. However, the quasi totality of the cartography that has been assessed is for countries located in mainly temperate climates with low biodiversity. Instead, LULC maps in highly bio-diverse areas still lack this information, partly because their assessment faces uncertainty due to a high taxonomic diversity and unclear borders between forest classes. This research focuses on the evaluation of the accuracy of detailed LULC regional maps in highly bio-diverse regions. These are provided by agencies of countries located in the subtropical belt, where no such comprehensive assessment has been done at high taxonomic resolution. This cartography is characterized by a greater taxonomic diversity (number of classes) than the cartography in low biodiversity areas. For example, in the United States of Mexico (USM, thereafter ‘Mexico’), located in a ‘mega-diverse’ area, the map of the National

The Quality of Detailed Land Cover Maps in Highly Bio-Diverse Areas: Lessons Learned from the Mexican Experience