Data Source:Spatiotemporal dynamics of global typical mangroves and their physiological responses to climatic and hydrological drivers

The original remote sensing image data adopted in this study include Landsat series satellite images (Landsat-5 TM, Landsat-7 ETM+, Landsat-8 OLI, Landsat-9 OLI-2) covering the entire study area from 1988 to 2024, and Sentinel-2 Multispectral Instrument (MSI) surface reflectance images from 2018 to 2024. Based on the above datasets, the analysis of mangrove expansion and abrupt disturbance trajectories was carried out, and the access address of the relevant analysis code is: https://code.earthengine.google.com/c6e2fabad1a8c94073bddb6eb95cc8db. The original remote sensing image data adopted in this study include Landsat series satellite images (Landsat-5 TM, Landsat-7 ETM+, Landsat-8 OLI, Landsat-9 OLI-2) covering the entire study area from The raw physiological parameter dataset of mangroves (Raw physiological parameter dataset.zip) was derived from Landsat series satellite imagery (Landsat-5 TM, Landsat-7 ETM+, Landsat-8 OLI, and Landsat-9 OLI-2) and organized as a monthly time-series dataset. The data extraction code is available at: https://code.earthengine.google.com/2b8025277a56233d4ecbb4067063de1c.After processing missing and abnormal values, a cleaned dataset (Physiological parameter dataset.zip) was obtained. Long-term trend components (Physiological parameter trend item.zip) were further extracted from the processed dataset. Hierarchical clustering analysis (Circular hierarchical clustering dendrogram.zip) and medoid sample extraction were then performed to generate representative samples (Medoid sample points.zip). The above data processing workflow is implemented in the code file "Preprocessing of Physiological parameters and extraction of medoid samples.txt".Based on the medoid samples, seasonal cycle characteristics and peak timing of physiological parameters were further derived using the scripts "Seasonal cycle extraction.txt" and "Peak timing extraction of physiological parameters.txt", respectively. The climate-hydrological dataset (Climate-hydrological dataset) used in this study was compiled with multi-source meteorological data: wind speed, precipitation, dew point temperature, daily maximum temperature, daily minimum temperature and daily average temperature were all derived from the National Oceanic and Atmospheric Administration (NOAA); solar radiation data were obtained from the ERA5-Land hourly reanalysis dataset released by the European Centre for Medium-Range Weather Forecasts (ECMWF).