## 3 Results
### Comparing and Combining Results with Existing Datasets  
Given that this is the first study to map the agricultural areas in high-resolution, we can compare our results with self-reported surface areas of the agricultural zone from the 2014 agricultural census [40]. Table 14 lists the main categories used by the agricultural census on the left and the corresponding categories of this study to the right. We would expect to see discrepancies between the results for several reasons: the agricultural census does not encompass all producers, but rather a sample of 755 of the most productive and representative ones, whereas our study encompasses the entirety of the agricultural area. Therefore, our estimated land covers might include areas that are not tended by anyone. This might account for dramatic increases in reported permanent crops, for example, as many fruit trees within the agricultural area might simply be growing wild, and respondents might not have taken them into account for their responses. Furthermore, both sources have their own inaccuracies: while our study is susceptible to misclassifications, self-reported values may be susceptible to under or over-estimating surface areas. This might be the case for Transitory crops, where our classification might easily categorize 'tilled land' and possibly even fallow land as transitory crops. Perhaps not coincidentally, the two values become very similar if tilted and fallow lands are included in the estimate. Furthermore, respondents to the census may have different definitions of what falls within each category. For example, some farmers might not consider _P. guajava_ an invasive plant, as they might see it as an important element of their silvopastures. This is the reason why, for Table 14, we categorized _Pennisetum_ as a pasture and excluded it from the invasive category because farmers use this grass species for their cattle and would likely not consider it 'invasive'. Furthermore, the category \"Pioneer and forest species\" is a category that encompasses any vegetation that has no agricultural value for farmers, so it is very general.  
Despite the many ways in which these data might not match, the dramatic decrease in pastures and the astounding increase in invasive plants across all four islands are probably real trends. This would be consistent with the observed trend of decreasing pastures between the 2000 census (14,555 ha) and the 2014 census (11,126 ha) [41]. This would also be consistent with the fact that the region's worst-recorded drought occurred in 2016, which MAG officials reported drove many cattle ranchers to abandon this activity as many cattle died due to the dry conditions [personal communication]. A drop in pastures, combined with an increase in invasives, is exactly what we would expect from people abandoning their lands. Pastures have a spectral signature that is very different from other land cover types, so it is unlikely that they were so heavily misclassified. However, it is possible that even though we grouped silvopastures as part of our estimate for pastures, farmers might still identify more heavily wooded areas as \"pastures\" while our algorithm might have identified the same region as a forest of some type. Lastly, although it is hard to compare specific numbers due to differences in methodologies and missing information, authors did find a general decrease of pastures in the agricultural areas and an increase in invasive plants in Santa Cruz and San Cristobal from 1987 to 2006 [90]. The present study serves as much needed baseline data with a replicable methodology that can complement existing studies [42] to give us, for the first time, a truly complete view of land cover for the entire archipelago (Appendix C, Table A6).