2022
DOI: 10.1016/j.rsase.2022.100834
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Two decades of land cover mapping in the Río de la Plata grassland region: The MapBiomas Pampa initiative

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Cited by 32 publications
(28 citation statements)
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“…To evaluate the effect of the unequal sample size and the increasing sampling effort with time on the estimation of cyanobacterial abundance (Hallegraeff et al, 2021), we conducted different strategies (Material S1): (i) aggregating the information as yearly average both including and excluding the periods with less data (between 1995 and 2003), (ii) aggregating the information every 5 years and performing unweighted and weighted regressions (weights proportional to the number of data points per period) and (iii) using bootstrapping type of re-sampling to produce 250 smaller samples of 15 cases and then producing 250 temporal TA B L E 1 Uruguay river (UR) basin and sub-basins areas, countries, MapBiomas (MB) collections and temporal period of the information used (MapBiomas Pampa: Baeza et al, 2022, Atlantic Forest Tri-national initiatives: Souza et al, 2020. Refer to Figure 1 for visual location.…”
Section: Discussionmentioning
confidence: 99%
“…To evaluate the effect of the unequal sample size and the increasing sampling effort with time on the estimation of cyanobacterial abundance (Hallegraeff et al, 2021), we conducted different strategies (Material S1): (i) aggregating the information as yearly average both including and excluding the periods with less data (between 1995 and 2003), (ii) aggregating the information every 5 years and performing unweighted and weighted regressions (weights proportional to the number of data points per period) and (iii) using bootstrapping type of re-sampling to produce 250 smaller samples of 15 cases and then producing 250 temporal TA B L E 1 Uruguay river (UR) basin and sub-basins areas, countries, MapBiomas (MB) collections and temporal period of the information used (MapBiomas Pampa: Baeza et al, 2022, Atlantic Forest Tri-national initiatives: Souza et al, 2020. Refer to Figure 1 for visual location.…”
Section: Discussionmentioning
confidence: 99%
“…Diff = (EqSOC -Reference SOC) x 100 / Reference SOC. We also calculated the proportion of area with annual crops in each soil unit by using the MapBiomas land cover map (Vallejos et al 2021, Baeza et al 2022 for the year 2018 to explore if SOC differences were related to the expansion of crop production. On the other hand, we obtained the proportion of MODIS pixels that had negative, positive and no trends in the ESSI estimations during the 2000-2022 period in each soil unit.…”
Section: Soc Maps and Data Analysismentioning
confidence: 99%
“…Even though the precision of the SOC estimation of a given paddock depends on knowing the initial C stocks, simulations can track the trend of changes and provide a reliable estimation of the expected differences between paddocks under different management. Nowadays, a critical part of the information required to perform such simulations can be derived from secondary data (soil maps, climate databases) and land cover maps, such as those provided by the MapBiomas Pampa project (Vallejos et al 2021, Baeza et al 2022.…”
Section: Patterns Of Reference and Current C Stocksmentioning
confidence: 99%
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“…These grasslands, dominated by C3 and C4 grasses, have a high richness of plant species and several endemism (Soriano, 1992;Andrade et al, 2018). Although the region experienced a high rate of transformation, it still has large areas of native grasslands, particularly in Uruguay (Baeza & Paruelo, 2020;Paruelo et al, 2022;Baeza et al, 2022). Extensive grazing by large herbivores (native and domestic) and fire are the two key disturbances in maintaining the structure and functioning of the Río de la Plata Grasslands (Paruelo et al, 2022).…”
Section: Introductionmentioning
confidence: 99%