27 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. Integration of deep learning into a spatial data infrastructure for automatic delineation of agricultural parcels in rural areas S. Sahraoui et al. https://doi.org/10.1007/s12518-026-00780-5
10. 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
11. Optical, radar, and hybrid indices to detect farming practices in Europe P. Dal Lago et al. https://doi.org/10.1016/j.rse.2026.115553
12. 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
13. 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
14. 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
15. Interactive Dual-Branch Transformer for Precise Agricultural Parcel Delineation from Remote Sensing Imagery Y. Wu et al. https://doi.org/10.3390/rs17223664
16. 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
17. 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
18. A study on the classification and production methods of <?A3B2 pi6?>AI-ready scientific datasets Z. Chen et al. https://doi.org/10.1360/CSB-2026-0374
19. Zero-shot parcel instance delineation in fragmented agricultural landscapes: Cross-source evaluation and structure-aware validation J. Calisto et al. https://doi.org/10.1016/j.atech.2026.102384
20. 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
21. Persistence patterns in subfield crop water use to guide variable rate management C. Deval et al. https://doi.org/10.1088/3033-4942/addc8f
22. EuroCrops v2.0: multi-annual harmonized parcel level crop type data linked to European Union-wide survey, statistical, and Earth Observation products M. Claverie et al. https://doi.org/10.5194/essd-18-4075-2026
23. 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
24. 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
25. 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
26. Spectral Representation-Enhanced Multitask SAM for Cropland Parcel Delineation A. Hu et al. https://doi.org/10.1109/TGRS.2026.3689191
27. AI4SmallFarms: A Dataset for Crop Field Delineation in Southeast Asian Smallholder Farms C. Persello et al. https://doi.org/10.1109/LGRS.2023.3323095