## 2 Materials and Methods
### Data Sources  
The mangrove label data used in this study primarily come from multiple sources, including multi-source satellite remote sensing data, historical reference data, field survey data, and government planning documents. The satellite data include high-resolution images provided by multiple satellites such as Beijing-2, Beijing-3, Gaofen-7, SuperView-1, and Jilin-1, spanning from 2018 to 2022. The selection of these data sources was based on principles of multi-source nature, timeliness, high resolution, reliability, and complementarity. In practical data experiments, we first screened remote sensing satellite data according to the officially recognized protected area boundaries provided in the \"Beihai Mangrove Resource Protection Plan (2020-2030)\" and then conducted preliminary verification using the Chinese Mangrove Long Time Series Satellite Remote Sensing Monitoring Dataset (1978-2018) [36] as a historical reference for corresponding years. Finally, cross-validation and refined verification were performed using GPS-positioned field survey data to ensure the accuracy of data labeling. This three-step progressive data processing workflow of \"official planning guidance--historical data reference--field verification\" not only guarantees the authority of study area selection but also ensures the spatiotemporal continuity and practical applicability of mangrove distribution information. Through the comprehensive utilization of these multi-source, multi-temporal, and multi-scale data, we were able to generate more accurate and reliable mangrove labels, providing high-quality foundational data for subsequent deep learning model training while also ensuring that the annotation results reflect current conditions and possess practical application value.  
Beijing-2 satellite (BJ-2) was launched in July 2015 from the Satish Dhawan Space Center Sriharikota in India (Beijing time). For effective mangrove segmentation, five 0.8 m  
Figure 2: The geographic location of the study area. (**A**) The coastal area of Beihai City, Guangxi, China. (**B**) The study area (a. Coastal National Wetland Park of Beihai, Guangxi, and Hengluoshan area of Yinhai District, Beihai, Guangxi, b. Dugong and Shankou National Nature Reserve area of Hepu, Guangxi; c. the coastal area of Lianzhou Bay of Hepu, Beihai, Guangxi; and d. the coastal area of Maowei Sea and Dafeng River, Guangxi).  
resolution multispectral images with blue, green, red, and near-infrared bands were selected. Beijing-3 satellite (BJ-3) was launched in June 2021 from the Taiyuan Satellite Launch Center in China (Beijing time), and one 0.3 m resolution multispectral image with blue, green, red, and near-infrared bands was selected. Gaofen-7 satellite (GF-7) was successfully launched in November 2019 from the Taiyuan Satellite Launch Center, and one 0.5 m resolution multispectral image with blue, green, red, and near-infrared bands was selected. SuperView-1 satellite (SV-1) was launched in December 2016 from the Taiyuan Satellite Launch Center, and one 0.5 m resolution multispectral image with blue, green, red, and near-infrared bands was selected. Jilin-1 satellite (JL-1) is China's core commercial high-resolution remote sensing satellite project under construction, encompassing multiple series of high-performance optical remote sensing satellites with high-resolution, wide-swath, video, and multispectral capabilities. One 0.8 m resolution multispectral image with blue, green, red, and near-infrared bands was selected. The relevant remote sensing data information is shown in Table 1.