2026-10-07T11:10:28Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34032063 2026-09-30T12:31:30Z category_24019 item_type_3 month_year_09_2026

Data for: Seasonal disturbance mapping in temperate forests based on Harmonized Landsat and Sentinel-2 dataset with spatiotemporal deep learning Yuping Tian (25143606) Forest ecosystems Forest disturbance Forest remote sensing Spatiotemporal deep learning Temperate forests Harmonized Landsat and Sentinel-2 (HLS) <p dir="ltr">This dataset contains the accuracy assessment results of four spatiotemporal deep learning models—U-TAE, 3D-Unet, 3D TransUNet, and 3D TransUNet-TAE—for forest disturbance detecting over the three northeastern provinces of China (Heilongjiang, Jilin, and Liaoning). The models were trained and validated using NASA Harmonized Landsat and Sentinel-2 (HLS) data. The dataset includes model outputs accuracy metrics.</p> 2026-09-30T12:31:30Z Dataset Dataset 10.6084/m9.figshare.34032063.v1 https://figshare.com/articles/dataset/Data_for_Seasonal_disturbance_mapping_in_temperate_forests_based_on_Harmonized_Landsat_and_Sentinel-2_dataset_with_spatiotemporal_deep_learning/34032063 CC BY 4.0