12 citations as recorded by crossref.

1. CROPGRIDS: a global geo-referenced dataset of 173 crops F. Tang et al. 10.1038/s41597-024-03247-7
2. Winter Wheat Extraction Using Time-Series Sentinel-2 Data Based on Enhanced TWDTW in Henan Province, China X. Wang et al. 10.3390/su15021490
3. Assessment of Land Suitability for Sugarcane Cultivation Using TOPSIS and Parametric Methods in Southwestern Iran A. Azadi et al. 10.1134/S1064229322602268
4. Exploring the effects of training samples on the accuracy of crop mapping with machine learning algorithm Y. Fu et al. 10.1016/j.srs.2023.100081
5. Impacts of ground-level ozone on sugarcane production A. Cheesman et al. 10.1016/j.scitotenv.2023.166817
6. Advances in safe processing of sugarcane and bagasse for the generation of biofuels and bioactive compounds A. Wani et al. 10.1016/j.jafr.2023.100549
7. High-resolution distribution maps of single-season rice in China from 2017 to 2022 R. Shen et al. 10.5194/essd-15-3203-2023
8. A Robust Index Based on Phenological Features to Extract Sugarcane from Multisource Remote Sensing Data Y. Liu et al. 10.3390/rs15245783
9. A new method for classifying maize by combining the phenological information of multiple satellite-based spectral bands Q. Peng et al. 10.3389/fenvs.2022.1089007
10. Water consumption in the production process of the sugar-energy industry: case study in the northwest of São Paulo (Brazil) W. Barroquela et al. 10.5327/Z2176-94781559
11. Mapping Land Use and Land Cover Classes in São Paulo State, Southeast of Brazil, Using Landsat-8 OLI Multispectral Data and the Derived Spectral Indices and Fraction Images Y. Shimabukuro et al. 10.3390/f14081669
12. Crop mapping using supervised machine learning and deep learning: a systematic literature review M. Alami Machichi et al. 10.1080/01431161.2023.2205984