Dynamic stratification of the landscape of Mexico: Analysis of vegetation patterns observed with multitemporal remotely sensed images

Abstract

Rapid deforestation in Mexico, when coupled with poor access to current and consistent ecological information across the country underscores the need for an ecological classification system that can be readily updated and new data become available. In this study, regional vegetation resources in Mexico were evaluated using remotely sensed information. Multitemporal Global Vegetation Index (GVI) data from Advanced Very High Resolution Radiometer images provided ecological information at regional scales by being interpreted as phenological patterns of vegetation productivity and seasonality. Principal component analysis on GVI monthly composites identified spatial and temporal vegetation patterns, reducing their variation to five phenologically meaningful components. Sixty land‐cover and natural vegetation classes were then derived via unsupervised classification from the five principal components. Additional phenological information (e.g., onset and peak of greenness, periods of growth) was obtained for each class. These data, along with seasonality measures (e.g., summer vs. winter peak of greenness) were used as criteria for grouping similar vegetation and land‐cover types into a classification for Mexico.