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The land characterized as forest by this product include large portions of weeded land and other various types of land that although not properly forest do not meet the criteria of the other land classes either. With a 26.9% of the total watershed in 2012 (most recent year released by this product) lands characterized with some type of cropland activity composed one of the three most extent land class after forest and weeds 41.6% followed by grasslands and pastures 25.5% (Table 3). Fig. 7 displays a characterization of land cover in (a) 2001 and (b) 2012, most recent year of this product release. Fig. 8 depicts a time series of the 2001�C2012 inter-annual trends of land cover where the land covered with forest and other weeded and high vegetation presented a significant increase (p? of the land cover classification. 67.5% was the overall accuracy. The most accurate land cover classification was urban with a 100% accuracy followed in order by water, wetland, forest, grassland and cropland with an 89.5%, 73.3%, 66.7%, 52.2% and 40.7%, respectively. It is important to mention that the land cover evaluation was conducted in December of 2014 and the MCD12Q1 product used was 2012. The low availability of data during the rainy seasons, appreciated from the Julian day axis on Fig. 3, is due to the fact that the MOD09GQ product registers surface reflectance in the red section of the spectrum (620�C670?nm). Any radiation in the visible wavelength is obstructed by clouds, which are obviously more abundant during the rainy season. Since we analyzed the inter-annual water surface reflectance temporal trends based solely on data from the first three months of the year, which are also the driest, the fluctuation of such trends do not necessarily represents the fluctuation of the inter-annual impacts on the Rosario Islands. However, even though the described cloud coverage issue impede trend analysis during the seasons where most sediment loading is expected, still temporal trends analysis during the dry season are useful as they show the conditions at which the impact is expected to be lower.