参考文献：
[1] Cheng, K., Yang, H., Guan, H., et al. Unveiling China’s natural and planted forest spatial-temporal dynamics from 1990 to 2020 [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2024, 209: 37-50.
[2] Cheng, K., Su, Y., Guan, H., et al. Mapping China’s planted forests using high resolution imagery and massive amounts of crowdsourced samples [J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2023, 196: 356-371.
[3] Xiao, Y., Wang, Q., Zhang, H.K. Global natural and planted forests mapping at fine spatial resolution of 30 m [J]. Journal of Remote Sensing, 2024, 4: 0204.
[4] Du, Z., Yu, L., Yang, J., et al. A global map of planting years of plantations [J]. Scientific Data, 2022, 9(1): 141.
[5] John, A., Allotey, S., Koebe, T., et al. A global dataset of location data integrity-assessed reforestation efforts [J]. Scientific Data, 2025, 12(1): 1714.
[6] Naboureh, A., Li, A., Bian, J., et al. Accuracies, discrepancies, and challenges of the 10 m global land cover products in mountains [J]. GIScience, Remote Sensing, 2025, 62(1): 2556064.
[7] 周广胜, 任鸿瑞, 刘通等. 一种基于地形-气候-遥感信息的区域植被制图方法及其在青藏高原的应用 [J]. 中国科学 (地球科学), 2023, 53(2): 227-235.
[8] Clark, A., Phinn, S., Scarth, P. Optimised U-Net for land use-land cover classification using aerial photography [J]. PFG-Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 2023, 91(2): 125-147.
[9] Tarasiou, M., Chavez, E., Zafeiriou, S. Vits for sits: Vision transformers for satellite image time series; proceedings of the Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, F [C]. 2023: 10418-10428.
[10] Heidarianbaei, M., Kanyamahanga, H., Dorozynski, M. Temporal ViT-U-Net tandem model: enhancing multi-sensor land cover classification through transformer-based utilization of satellite image time series [J]. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2024, X-3-2024: 169-177.
[11] Zhu, Z., Woodcock, C.E. Continuous change detection and classification of land cover using all available Landsat data [J]. Remote sensing of Environment, 2014, 144: 152-171.
[12] Tolan, J., Yang, H.-.I., Nosarzewski, B., et al. Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidar [J]. Remote Sensing of Environment, 2024, 300: 113888.
[13] Shang, R., Lin, X., Chen, J.M., et al. China's annual forest age dataset at 30 m spatial resolution from 1986 to 2022 [J]. Earth System Science Data Discussions, 2025, 2025: 1-31.
[14] Running, S.W., Nemani, R.R., Heinsch, F.A., et al. A continuous satellite-derived measure of global terrestrial primary production [J]. Bioscience, 2004, 54(6): 547-560.