22 citations as recorded by crossref.

1. A weakly supervised approach for large-scale agricultural parcel extraction from VHR imagery via foundation models and adaptive noise correction W. Zhao et al. https://doi.org/10.1016/j.isprsjprs.2026.01.030
2. Boosting crop classification by hierarchically fusing satellite, rotational, and contextual data V. Barriere et al. https://doi.org/10.1016/j.rse.2024.114110
3. A Comprehensive Review of Agricultural Parcel and Boundary Delineation From Remote Sensing Images: Recent progress and future perspectives J. Zheng et al. https://doi.org/10.1109/MGRS.2026.3658493
4. Transferability of spatial and temporal learning models for winter wheat mapping in data-scarce environments: A case study in Armenia A. Tiwari et al. https://doi.org/10.1016/j.rsase.2026.101885
5. A large-scale VHR parcel dataset and a novel hierarchical semantic boundary-guided network for agricultural parcel delineation H. Zhao et al. https://doi.org/10.1016/j.isprsjprs.2025.01.034
6. MT4AFE: A Deep Learning Benchmark Dataset for Agricultural Field Extraction G. Amin et al. https://doi.org/10.1109/LGRS.2025.3613688
7. On the Use of Graphs for Satellite Image Time Series: A comprehensive review C. Dufourg et al. https://doi.org/10.1109/MGRS.2025.3622200
8. A Synergistic Framework for Coupling Crop Growth, Radiative Transfer, and Machine Learning to Estimate Wheat Crop Traits in Pakistan R. Ishaq et al. https://doi.org/10.3390/rs16234386
9. AgriFM: A multi-source temporal remote sensing foundation model for Agriculture mapping W. Li et al. https://doi.org/10.1016/j.rse.2026.115234
10. AI-based 2-m super-resolution of Sentinel-2 imagery for high-resolution SDG monitoring D. Jin et al. https://doi.org/10.1080/15481603.2026.2640266
11. CT-HiffNet: A contour-texture hierarchical feature fusion network for cropland field parcel extraction from high-resolution remote sensing images H. Wu et al. https://doi.org/10.1016/j.compag.2025.111010
12. FLAIR-HUB: Large-scale multimodal dataset for land cover and crop mapping A. Garioud et al. https://doi.org/10.1016/j.isprsjprs.2026.04.017
13. Interactive Dual-Branch Transformer for Precise Agricultural Parcel Delineation from Remote Sensing Imagery Y. Wu et al. https://doi.org/10.3390/rs17223664
14. The role of digitalisation in supporting farmers and strategic policies for food security and sustainability in Europe: A review G. Kandel et al. https://doi.org/10.1016/j.sftr.2026.101702
15. Using a Vegetation Index as a Proxy for Reliability in Surface Reflectance Time Series Reconstruction (RTSR) P. Kempeneers et al. https://doi.org/10.3390/rs15092303
16. Towards individual agricultural parcel vectorization from VHR imagery: A coarse-to-fine and multi-task learning method A. Zhao et al. https://doi.org/10.1016/j.isprsjprs.2026.05.003
17. Persistence patterns in subfield crop water use to guide variable rate management C. Deval et al. https://doi.org/10.1088/3033-4942/addc8f
18. Advancing agricultural remote sensing: A comprehensive review of deep supervised and Self-Supervised Learning for crop monitoring M. da Silva et al. https://doi.org/10.1016/j.cag.2025.104434
19. A CNN-Transformer Hybrid Network With Boundary Guidance for Mapping Cropland Field Parcels From High-Resolution Remote Sensing Imagery J. Xie et al. https://doi.org/10.1109/TGRS.2026.3651284
20. A scalable matching approach for the comparison of agricultural land use maps based on corresponding field polygons A. Naumann et al. https://doi.org/10.1080/17538947.2026.2632420
21. Spectral Representation-Enhanced Multitask SAM for Cropland Parcel Delineation A. Hu et al. https://doi.org/10.1109/TGRS.2026.3689191
22. AI4SmallFarms: A Dataset for Crop Field Delineation in Southeast Asian Smallholder Farms C. Persello et al. https://doi.org/10.1109/LGRS.2023.3323095