## 5 Conclusions  
This study provided a comprehensive analysis of deforestation and forest degradation using LULC changes in Manaus and Porto Velho, Brazil, within and around conservation units from 2018 to 2023. By employing advanced remote sensing techniques and object-based classification methods, this study has achieved high-accuracy mapping of LULC dynamics in the Brazilian Amazon landscape. Our findings reveal several key insights:  
1. Despite the continued dominance of Terra-Firme Forest in both study areas, significant forest loss and degradation were observed, highlighting ongoing pressures on ecosystems in the Brazilian Amazon. This study revealed a gain of 22,362 ha in Secondary Forest areas in Manaus and 29,088 ha in Agriculture/Pastureland in Porto Velho within the study period. 2. The effectiveness of conservation units varied considerably across management types and administrative levels. Full protection units generally showed lower deforestation compared to sustainable use units, but both categories still face substantial challenges in preventing forest degradation. 3. Buffer zones around conservation units experienced larger deforestation and degradation compared to the conservation units, highlighting the effectiveness of these protected areas. 4. The conversion of forest to Agriculture/Pastureland emerged as the primary driver of land cover change and forest loss, reflecting the ongoing tension between conservation and agricultural expansion in the Amazon. 5. Forest degradation consistently surpassed deforestation in most areas. These results have important implications for conservation policy and practice in the Brazilian Amazon. They suggest that while protected areas play a crucial role in forest conservation, current strategies may be insufficient to fully safeguard these ecosystems. The high-accuracy LULC classification achieved in this study demonstrates the potential of advanced remote sensing and machine learning techniques for monitoring complex tropical forest landscapes. These methods provide valuable tools for tracking progress toward conservation goals and informing adaptive management strategies. In conclusion, while conservation units in Manaus and Porto Velho play a vital role in forest protection, they face significant challenges from both internal and external pressures. By providing a detailed analysis of LULC dynamics in these areas, this study contributes to the evidence base needed to develop more effective and resilient conservation policies for these areas in the Brazilian Amazon. **Author Contributions:** Conceptualization and methodology, D.N.L. and S.T. ; formal analysis, investigation, data curation, and writing--original draft preparation, D.N.L. ; writing--review and editing, supervision, and project administration, S.T. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Data Availability Statement:** The data presented in this study are available on request from the first author. **Acknowledgments:** The authors would like to thank the Instituto de Protecao Ambiental do Amazonas (IPAAM) in Manaus, and the Secretaria Municipal de Planejamento, Orcamento e Gestao (SEMPOG) in Porto Velho for providing us with the official administrative boundaries of the conservation units. The authors would also like to express their gratitude to the reviewers for their comments and suggestions made to improve the quality of this article. **Conflicts of Interest:** The authors declare no conflicts of interest. Figure 12: Relative Feature Importance in percentage derived from the Random Forest model used to create LULC maps of Manaus for all years: (**a**) 2018; (**b**) 2019; (**c**) 2020; (**d**) 2021; (**e**) 2022; and (**f**) 2023. Figure 13: LULC maps of Manaus, resulting from the Random Forest model for all years: (**a**) 2018; (**b**) 2019; (**c**) 2020; (**d**) 2021; (**e**) 2022; and (**f**) 2023.