16 citations as recorded by crossref.

1. AHAD: African major crops harvested area dataset for the years of 2000, 2010, and 2020 W. Zhang et al. https://doi.org/10.1038/s41597-025-05977-8
2. Investigating the Earliest Identifiable Timing of Sugarcane at Early Season Based on Optical and SAR Time-Series Data Y. Yang et al. https://doi.org/10.3390/rs17162773
3. Remote sensing for crop mapping: A perspective on current and future crop-specific land cover data products C. Zhang et al. https://doi.org/10.1016/j.rse.2025.114995
4. Improved maize mapping using multi-source data fusion coupled with height-spectral Gaussian mixture modeling G. Xiao et al. https://doi.org/10.1080/15481603.2026.2671603
5. Mapping complex cropping patterns in China (2018–2021) at 10 m resolution: a data-driven framework based on multi-product integration and Google satellite embedding X. Li & L. Yu https://doi.org/10.5194/essd-18-5601-2026
6. High-Resolution Crop Mapping and Suitability Assessment in China’s Three Northeastern Provinces (2000–2023): Implications for Optimizing Crop Layout X. Wang et al. https://doi.org/10.3390/agronomy15112587
7. Evaluating Remote Sensing Foundation Model Embeddings for Cross-City Thematic Mapping of Eucalyptus Plantations in Guangxi, China T. Zhang et al. https://doi.org/10.3390/rs18183248
8. Progress and Perspectives of Crop Type Mapping With Remote Sensing: A review J. Huang et al. https://doi.org/10.1109/MGRS.2025.3648119
9. A 30-m annual distribution dataset of major crops in China from 2001-2024 Y. Fu et al. https://doi.org/10.1038/s41597-026-07370-5
10. Decoding the Mystery of Sugarcane Genome‐Based Breeding: Current Advancements, Strategies, and Future Challenges Q. Du et al. https://doi.org/10.1111/pce.70679
11. National 10-m soybean maps for South Africa from 2018 to 2025 X. Huang et al. https://doi.org/10.1038/s41597-026-07295-z
12. SPAF-SegNeXt: Prior-Guided Attention and Frequency-Spatial Hybrid Fusion for Multimodal Sugarcane Segmentation in Remote Sensing W. Zhang et al. https://doi.org/10.1109/JSTARS.2026.3716367
13. Knowledge-informed cascaded sampling for corn mapping across heterogeneous growing environments G. Xiao et al. https://doi.org/10.1016/j.jag.2026.105259
14. Enabling maize mapping in double-cropping regions of Argentina and Brazil without ground reference data by leveraging multiple satellite platforms R. Kwon et al. https://doi.org/10.1016/j.jag.2026.105489
15. An efficient and transferable remote sensing spectral index for regional corn mapping M. Han & J. Chai https://doi.org/10.1016/j.srs.2025.100308
16. Woody vegetation cover on cleared areas in the Amazon Basin: temporal mixture mapping suggests a revised conceptual model of deforestation M. Honey et al. https://doi.org/10.1007/s10113-024-02337-x