TSP-Former: A Phenology-Guided Transformer for Tobacco Mapping Using Satellite Image Time Series
文献类型：期刊论文
| 作者 | Gao, Huaming3,4; Bai, Yongqing3,4; Sun, Qing2; Wang, Haoran3,4; Tian, Xiangyu1,4; Ma, Hui3,4; Li, Yixiang3,4; Che, Xianghong5; Chen, Zhengchao3,4 |
| 刊名 | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
 |
| 出版日期 | 2026 |
| 卷号 | 19页码:2423-2438 |
| 关键词 | Crops Time series analysis Remote sensing Deep learning Accuracy Earth Feature extraction Economics Satellite images Biological system modeling Deep learning (DL) phenological priors remote sensing (RS) Sentinel-2 time series tobacco mapping |
| ISSN号 | 1939-1404 |
| DOI | 10.1109/JSTARS.2025.3645265 |
| 产权排序 | 4 |
| 文献子类 | Article |
| 英文摘要 | Tobacco is a phenology-sensitive and economically significant crop that requires accurate and timely spatial mapping to support agricultural planning and public health regulation. However, single-date spectral similarity among crops and regional differences in planting practices limit the generalizability of existing approaches, particularly deep learning (DL) models. To address these challenges, we propose a novel phenologyguided DL framework that leverages satellite image time series (SITS) to capture crop-specific growth dynamics. Specifically, we introduce the tobacco spectral-phenological variable (TSP), which captures change rates in Red Edge-2 during peak growth. It serves as crop-specific prior knowledge for model guidance. Based on this, we develop TSP-Former, a transformer architecture that incorporates two novel modules: a central prior attention module (CPAM), which adaptively fuses spectral information with phenological priors, and an NDVI-enhanced temporal decoder (NDTD), which reinforces temporal learning by emphasizing phenologically critical stages using NDVI-weighted sequences. Extensive experiments across four major tobacco regions using Sentinel-2 imagery demonstrate the method's superior cross-regional robustness. TSP-Former achieves an average weighted F1-score of 87.1% and an overall accuracy of 85.9%, significantly outperforming random forest and competing DL approaches. Notably, in challenging regions characterized by substantial phenological shifts, the proposed method surpasses the emerging remote sensing foundation model, AlphaEarth with a fine-tuned lightweight multilayer perceptron, by over 15% in accuracy. These findings highlight the effectiveness of integrating phenological priors into temporal deep models, enabling robust and transferable crop mapping across heterogeneous and data-constrained regions, with clear implications for scalable agricultural monitoring and policy development. |
| URL标识 | 查看原文 |
| WOS研究方向 | Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001655690800009 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/219653]  |
| 专题 | 生态系统网络观测与模拟院重点实验室_外文论文 |
| 通讯作者 | Bai, Yongqing |
| 作者单位 | 1.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 2.Chinese Acad Meteorol Sci, State Key Lab Severe Weather Meteorol Sci & Techno, Beijing 100081, Peoples R China; 3.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing & Digital Earth, Beijing 100101, Peoples R China; 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 5.Chinese Acad Surveying & Mapping, Beijing 100830, Peoples R China |
| 推荐引用方式 GB/T 7714 | Gao, Huaming,Bai, Yongqing,Sun, Qing,et al. TSP-Former: A Phenology-Guided Transformer for Tobacco Mapping Using Satellite Image Time Series[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2026,19:2423-2438. |
| APA | Gao, Huaming.,Bai, Yongqing.,Sun, Qing.,Wang, Haoran.,Tian, Xiangyu.,...&Chen, Zhengchao.(2026).TSP-Former: A Phenology-Guided Transformer for Tobacco Mapping Using Satellite Image Time Series.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,19,2423-2438. |
| MLA | Gao, Huaming,et al."TSP-Former: A Phenology-Guided Transformer for Tobacco Mapping Using Satellite Image Time Series".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 19(2026):2423-2438. |
入库方式： OAI收割
来源：地理科学与资源研究所
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