# Analysis of a Landscape Intensely Modified by Agriculture in the Tiete-Jacare Watershed, Brazil
## 5 Conclusions  
The Tiete-Jacare Watershed has high potential for the development of agricultural activities, as observed by the land use and land cover classification documenting the predominance of such activities in the region. Furthermore, these datasets corroborate the demographic analyses of 1970, 1980, 1991, and 2015 [22]. They show that the region's growth process is due to the intensification of the urbanization processes (especially the large municipalities, such as Sao Carlos, Araraquara, Bauru, and Jauj) and the expansion of land use areas due to agricultural activities. The growth of anthropic activities and the loss of natural areas can compromise the biodiversity still present in the study site. Furthermore, it may represent a loss of environmental services and functions, and consequently of benefits from natural areas that provide resources and support for the maintenance of urban and agricultural activities. Therefore, necessary actions such as the revision of the Forest Code and other environmental laws should be discussed more scientifically, focusing on the conservation of ecosystems. In this way, they should aim at the benefits of the preservation and conservation of natural areas, rather than focusing on the advance of anthropogenic activities or financial interests. The diversification and rotation of crops is a possibility to control soil fertilization since monocultures interfere with nutrient cycles, causing soil impoverishment and leading to problems such as desertification and salinization. Desertification is a dynamic process that results in the transformation of certain areas into a desert, whereas salinization refers to the degradation of environments under humid climates with the formation of islands of exposed and loose sand. The use of Sentinel-2 images and the random forest machine learning approach enabled a temporal analysis of the Tiete-Jacare Watershed region. This methodology allowed us to identify the driving forces that promote the changes in the landscape, contributing to discussions about their consequences over time. Such tools can also accelerate the analysis of evidence of the loss of natural areas and the regional environmental quality, as well as the growth of negative impacts on the watershed landscape, which culminate in the reduction of vegetation areas and water networks. Additionally, the implementation and use of machine learning can increase the efficiency and accuracy of the analysis in studies related to deforestation and the impacts of land use and land cover changes in natural and anthropic landscapes, which is an important factor for the sustainability of the different biomes worldwide. Conceptualization, D.P.T., L.E.M. and H.B. ; Data curation, D.P.T. and P.C.B. ; Formal analysis, D.P.T. and P.C.B. ; Funding acquisition, D.P.T. and L.E.M. ; Investigation, D.P.T. and P.C.B. ; Methodology, D.P.T. and P.C.B. ; Project administration, D.P.T., P.C.B., L.E.M. and H.B. ; Resources, D.P.T., L.E.M. and H.B. ; Software, D.P.T., P.C.B. and Y.G. ; Supervision, L.E.M. and H.B. ; Validation, D.P.T., P.C.B. and Y.G. ; Visualization, D.P.T. and P.C.B. ; Writing--Original draft, D.P.T., P.C.B., L.E.M., V.L. and H.B. ; Writing--Review and editing, D.P.T., P.C.B., L.E.M., Y.G., V.L., A.H., B.F.S. and H.B. All authors have read and agreed to the published version of the manuscript. Tevisan D.P. was supported by the Sao Paulo Research Support Foundation (FAPESP) (under grant Nos. 2015/19918-3 and 2018/00162-4). Bispo P.C. received the financial support from the European Union's Horizon 2020 (Research and innovation program under the Marie Sklodowska-Curie grant agreement No. 660020). Balzter H. was supported by the UK's Natural Environment Research Council (agreement between the NERC and National Centre for Earth Observation (NCEO) No. PR140015). Liesenberg V. acknowledges the financial support from the National Council for Scientific and Technological Development (CNPQ) (under grant No.