59 citations as recorded by crossref.

1. The critical benefits of snowpack insulation and snowmelt for winter wheat productivity P. Zhu et al.
2. In-silico evidence for improving irrigated maize productivity in the Great Plains: A high-resolution spatial simulation approach I. Onyekwelu et al.
3. Derivation of crop yield response factor (Ky) based on satellite data and machine learning methods A. Motlagh et al.
4. Assessment of soybean response to irrigation variability in eastern Nebraska using the AquaCrop model A. Singh et al.
5. High resolution annual irrigation water use maps in China based-on input variables selection and convolutional neural networks J. Zhang et al.
6. Investigating the vulnerability and resilience capacity of different land cover types to flash drought: A case study in the Mississippi River Basin S. Bakar et al.
7. Appropriate spatiotemporal scale selection for water use simulation in China J. Zhang et al.
8. A model-data fusion approach for quantifying the carbon budget in cotton agroecosystems across the United States R. Qin et al.
9. Downscaled global 60-meter resolution estimates of irrigation water sources (2000–2015) F. Hung et al.
10. Mapping of irrigated vineyard areas through the use of machine learning techniques and remote sensing E. López-Pérez et al.
11. New water accounting reveals why the Colorado River no longer reaches the sea B. Richter et al.
12. Spatial and temporal forecasting of groundwater anomalies in complex aquifer undergoing climate and land use change A. Talib et al.
13. A review of globally available data sources for modelling the Water-Energy-Food Nexus J. Lodge et al.
14. Opportunities for water quality improvements in a Mississippi River Basin watershed: Hotspots for agricultural conservation practices Y. Makhtoumi et al.
15. Remote sensing of irrigation: Research trends and the direction to next-generation agriculture through data-driven scientometric analysis V. Manivasagam
16. Annual irrigated cropland mapping reveals uneven expansion and rising water demand in Africa from 2000 to 2021 A. Tolera et al.
17. Mapping Irrigated Areas Based on Remotely Sensed Crop Phenology and Soil Moisture W. Zuo et al.
18. Precrop payoffs: causal machine learning reveals large but variable yield benefits of crop rotation in major breadbaskets D. Kluger et al.
19. Estimating agricultural irrigation water consumption for the High Plains aquifer region with integrated energy- and water-balance evapotranspiration modeling approaches L. Ji et al.
20. CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO2 fertilization Y. Kang et al.
21. Global drivers of local water stresses and global responses to local water policies in the United States I. Haqiqi et al.
22. IrriMap_CN: Annual irrigation maps across China in 2000–2019 based on satellite observations, environmental variables, and machine learning C. Zhang et al.
23. Cropland abandonment between 1986 and 2018 across the United States: spatiotemporal patterns and current land uses Y. Xie et al.
24. Mapping winter irrigation areas and timing in arid regions using time series remote sensing data S. Yan et al.
25. Quantifying future climate impacts on maize productivity under different irrigation management strategies: A high-resolution spatial analysis in the U.S. Great Plains I. Onyekwelu et al.
26. Mapping 20 years of irrigated croplands in China using MODIS and statistics and existing irrigation products C. Zhang et al.
27. Comparison and evaluation of the suitability of existing irrigation area products in the Yellow River Basin R. Wang et al.
28. Comparative evaluation of the accuracy of mapping irrigated areas using sentinel 1 images in the Bilate and Gumara watersheds, Ethiopia A. Yimer et al.
29. Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin D. Purnamasari et al.
30. Mapping irrigated croplands in China using a synergetic training sample generating method, machine learning classifier, and Google Earth Engine C. Zhang et al.
31. Satellite data and physics-constrained machine learning for estimating effective precipitation in the Western United States and application for monitoring groundwater irrigation M. Hasan et al.
32. GMIE: a global maximum irrigation extent and central pivot irrigation system dataset derived via irrigation performance during drought stress and deep learning methods F. Tian et al.
33. CIrrMap250: annual maps of China's irrigated cropland from 2000 to 2020 developed through multisource data integration L. Zhang et al.
34. Field-scale irrigated winter wheat mapping using a novel cross-region slope length index in 3D canopy hydrothermal and spectral feature space Y. Zhang et al.
35. ECIRA - European crop-specific irrigated area at 1 km resolution annually from 2010 to 2020 W. Zhu et al.
36. Machine Learning-Based Bioclimatic Suitability Modeling for Maize Cultivation Under Future Projections A. Monavarian et al.
37. Overconsumption gravely threatens water security in the binational Rio Grande-Bravo basin B. Richter et al.
38. Bias correction of satellite based crop water stress index using machine learning methods E. Zoratipour et al.
39. Large-scale irrigation area mapping: Status and challenges W. Zhu et al.
40. A novel Greenness and Water Content Composite Index (GWCCI) for soybean mapping from single remotely sensed multispectral images H. Chen et al.
41. United States multi-sector land use and land cover base maps to support human and Earth system models J. Oliver & R. McManamay
42. Remote sensing of canopy water status of the irrigated winter wheat fields and the paired anomaly analyses on the spectral vegetation indices and grain yields S. Solgi et al.
43. Estimating irrigation consumptive use for the conterminous United States: coupling satellite-sourced estimates of actual evapotranspiration with a national hydrologic model D. Martin et al.
44. Cashing out? Farmland quality and the adoption of utility-scale solar energy J. Winikoff et al.
45. Temperature thresholds of extreme heat-induced yield loss in maize and soybean reveal geographic heterogeneity across the Northern Hemisphere Q. Zhao et al.
46. Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions S. Majumdar et al.
47. Irrigation by Crop in the Continental United States From 2008 to 2020 P. Ruess et al.
48. Multi-model ensemble mapping of irrigated areas using remote sensing, machine learning, and ground truth data M. Akbar et al.
49. CropSight-US: an object-based crop type ground truth dataset using street view and Sentinel-2 satellite imagery across the contiguous United States, 2013–2023 Z. Zhou et al.
50. An attention-enhanced spatial–temporal high-resolution network for irrigated area mapping using multitemporal Sentinel-2 images W. Li et al.
51. Machine Learning Crop Yield Models Based on Meteorological Features and Comparison with a Process-Based Model Q. Liu et al.
52. Value of microwave soil moisture and thermal-infrared evapotranspiration retrievals for the mapping of irrigation coverage W. Crow et al.
53. Alleviating water scarcity by optimizing crop mixes B. Richter et al.
54. Disentangling contributions to past and future trends in US surface soil moisture L. Vargas Zeppetello et al.
55. A global open-source dataset of monthly irrigated and rainfed cropped areas (MIRCA-OS) for the 21st century E. Kebede et al.
56. Impacts of agrisolar co-location on the food–energy–water nexus and economic security J. Stid et al.
57. Large increases in maize residue carbon inputs in the US Corn Belt from 1980 to 2020 A. Ruiz et al.
58. Half of twenty-first century global irrigation expansion has been in water-stressed regions P. Mehta et al.
59. Climate-driven interannual variability in subnational irrigation areas across Europe W. Zhu & S. Siebert