## 4 Conclusions  
The present research explored the potential of applying the multi-temporal NDVI derived from Sentinel through the Google Earth Engine for the mapping and monitoring of mangrove patterns. The Overlap Algorithm was used to explore the signal value of the NDVI, showing the mangrove conditions based on the referenced mangrove populations. Moreover, the validation involved the evaluation of the accuracy of the information classified from the NDVI. The results revealed that the NDVI values greater than 0.3 reflect the mangrove patterns (with \(O\)-index \(>\) 0.85), other than non-mangrove in the study area. The accuracy assessment also revealed, showing substantial agreement, with the Kappa statistic of 0.7 and the overall classification accuracy of 83% for the NDVI greater than 0.3. The spatiotemporal trend of the mangrove forest was characterized using a Mann-Kendal significance test. Furthermore, the examination of land use/land cover change was employed to determine the common parameters impacting on mangrove forest dynamics in the context of economic development. It was revealed that the high density of vegetation was explored in the core and buffer zones, while no vegetation was discovered around the transition zone or residential area. Additionally, a declined area of 2357 ha in total was explored during the period of five years. The variations of mangrove forests mainly occurred in the transition zone and a part of the buffer zone. Figure 7: Proposition for land use in Can Gio district (red and pink) with a scale of 1:5000 in 2025 [18]. Furthermore, the study focused and demonstrated the potential of time series Sentinel-2 imagery for the discrimination of various mangrove species and for the spatiotemporal analysis of mangroves, which supports the planner, forester and government agencies to strictly implement mitigation measures for the conservation and preservation of mangrove cover. Moreover, Sentinel-derived indices, obtained from the GEE and time-series analysis, are efficient tools for mangrove monitoring and assessment in district scales. They reduced the influence of cloud cover or missing coverage in the study area, located in the tropical region. However, the environments in which mangrove forest growth is complicated were a mixture of wetlands and temporary inundation water covered by the vegetation canopy to some extent, although the high density of mangrove species covered most of study area. Hence, they require an exploration of Synthetic Aperture Radar (SAR) and Optical data for the accurate monitoring of the mangrove pattern, especially in waterbodies covered by mangrove vegetation canopies. Further research, therefore, needs to integrate Sentinel-1A SAR-data, which could provide a solution to enhance and discriminate the structural and geographical features underlying vegetation canopies. Finally, the study also observed that shrimp farming and built-up development around the transition and buffer zones enacted damage on the long-term sustainability of mangrove forests. Moreover, the development of the sea-encroached urban-tourism zone with an area of 2870 ha in the future will pose a threat to bio-diversity degradation as well as the eco-sustainability of the Biosphere Reserve Area. Furthermore, this study informs the local government on maintaining a balance between developing economic activities and protecting the environment. The proposed planning for tourism development should be strictly adhered to, and prohibited in relation to changes in environmental issues. [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] conceived the idea of the study. [PERSON], [PERSON], and [PERSON] conducted the field work. [PERSON], [PERSON], [PERSON], [PERSON], and [PERSON] processed the data and analysed the results. All authors contributed to the writing and revision of the manuscript. All authors have read and agreed to the published version of the manuscript.