Monthly HLS Time Series & Multi-Index LandTrendr Outputs for Eucalyptus Age Mapping

This dataset contains the core data supporting “Eucalyptus Plantation Stand-Age Inversion Using Monthly HLS Time Series and a Multi-Index–Integrated, Improved LandTrendr Algorithm.”All files are openly shared under the CC BY 4.0 license. Content: Fusion_202412.tif Monthly fused HLS (Landsat–Sentinel) imagery for December 2024. Provided as a Cloud-Optimized GeoTIFF (COG) with surface-reflectance indices for downstream analysis. Study Area.zip Boundary of the study area (Luzhai County, Guangxi, China). Provided as a compressed Shapefile/GeoPackage with projection information. Samples_all.geojson Training and reference samples for eucalyptus-plantation classification and stand-age inversion. Includes training and validation points, stored as GeoJSON with geographic coordinates. Verification Point.zip Independent validation points for disturbance detection and stand-age mapping accuracy assessment. Provided as a compressed Shapefile package. Classified_dec2024.tif Classification result for December 2024 showing the spatial distribution of eucalyptus plantations. Raster map in GeoTIFF format. Yod_fused.tif Final fused Year of Disturbance (YOD) output generated by the improved LandTrendr algorithm. Represents detected disturbance events across the study area and the derived stand age. All rasters are provided in GeoTIFF format with defined spatial reference systems.Vector data are provided as GeoJSON or compressed Shapefiles.Together, these data enable full reproduction of the results, including training, classification, disturbance detection, and stand-age inversion.