81 citations as recorded by crossref.

1. Estimation of Maize Foliar Temperature and Stomatal Conductance as Indicators of Water Stress Based on Optical and Thermal Imagery Acquired Using an Unmanned Aerial Vehicle (UAV) Platform K. Brewer et al. 10.3390/drones6070169
2. Evapotranspiration estimation using high-resolution aerial imagery and pySEBAL for processing tomatoes S. Peddinti et al. 10.1007/s00271-024-00943-5
3. Development of a new UAV-thermal imaging based model for estimating pecan evapotranspiration E. Mokari et al. 10.1016/j.compag.2022.106752
4. Mapping and Estimating Weeds in Cotton Using Unmanned Aerial Systems-Borne Imagery B. Sapkota et al. 10.3390/agriengineering2020024
5. A comprehensive review on recent applications of unmanned aerial vehicle remote sensing with various sensors for high-throughput plant phenotyping L. Feng et al. 10.1016/j.compag.2021.106033
6. Diurnal and Seasonal Mapping of Water Deficit Index and Evapotranspiration by an Unmanned Aerial System: A Case Study for Winter Wheat in Denmark V. Antoniuk et al. 10.3390/rs13152998
7. Thermal Sensor Calibration for Unmanned Aerial Systems Using an External Heated Shutter J. Virtue et al. 10.3390/drones5040119
8. Inversion of soil salinity according to different salinization grades using multi-source remote sensing D. Wang et al. 10.1080/10106049.2020.1778104
9. Spectral Index Fusion for Salinized Soil Salinity Inversion Using Sentinel-2A and UAV Images in a Coastal Area Y. Ma et al. 10.1109/ACCESS.2020.3020325
10. Effect of aggregation and disaggregation of land surface temperature imagery on evapotranspiration estimation S. Peddinti & I. Kisekka 10.1016/j.rsase.2022.100805
11. Quantitative Estimation of Wheat Phenotyping Traits Using Ground and Aerial Imagery Z. Khan et al. 10.3390/rs10060950
12. Disturbance Mapping in Arctic Tundra Improved by a Planning Workflow for Drone Studies: Advancing Tools for Future Ecosystem Monitoring I. Eischeid et al. 10.3390/rs13214466
13. Agricultural Drought Assessment in a Typical Plain Region Based on Coupled Hydrology–Crop Growth Model and Remote Sensing Data Y. Zhang et al. 10.3390/rs14235994
14. Comparison Between Thermal-Optical and L-Band Passive Microwave Soil Moisture Remote Sensing at Farm Scales: Towards UAV-Based Near-Surface Soil Moisture Mapping N. Ye et al. 10.1109/JSTARS.2023.3329015
15. Landscape-level vegetation classification and fractional woody and herbaceous vegetation cover estimation over the dryland ecosystems by unmanned aerial vehicle platform H. Wang et al. 10.1016/j.agrformet.2019.107665
16. Leaf temperatures and environmental conditions predict daily stem radial variations in a temperate coniferous forest W. Weygint et al. 10.1002/ecs2.4465
17. Pre-harvest weed mapping of Cirsium arvense in wheat and barley with off-the-shelf UAVs J. Rasmussen et al. 10.1007/s11119-018-09625-7
18. Unmanned Aerial Vehicles in Agriculture: A Review of Perspective of Platform, Control, and Applications J. Kim et al. 10.1109/ACCESS.2019.2932119
19. The digitization of agricultural industry – a systematic literature review on agriculture 4.0 R. Abbasi et al. 10.1016/j.atech.2022.100042
20. Unmanned-Aerial-Vehicle Data as an Effective Tool for the Evaluation of Ancient Khorasan and Modern Kabot Spring Wheat Varieties under Different Tillage Systems K. Balážová et al. 10.3390/agronomy14010147
21. A Comprehensive Survey of the Recent Studies with UAV for Precision Agriculture in Open Fields and Greenhouses M. Aslan et al. 10.3390/app12031047
22. REMOTE DETECTION OF WATER AND NUTRITIONAL STATUS OF SOYBEANS USING UAV-BASED IMAGES A. Andrade Junior et al. 10.1590/1809-4430-eng.agric.v42n2e20210177/2022
23. UAV-Based High Resolution Thermal Imaging for Vegetation Monitoring, and Plant Phenotyping Using ICI 8640 P, FLIR Vue Pro R 640, and thermoMap Cameras V. Sagan et al. 10.3390/rs11030330
24. Water deficit index to evaluate water stress status and drought tolerance of rainfed barley genotypes in cold semi-arid area of Iran V. Feiziasl et al. 10.1016/j.agwat.2021.107395
25. Canopy Height Estimation of Three Sugarcane Varieties Using an Unmanned Aerial Vehicle (UAV) G. Simões et al. 10.5902/2236499465070
26. Assessing Different Plant‐Centric Water Stress Metrics for Irrigation Efficacy Using Soil‐Plant‐Atmosphere‐Continuum Simulation J. Zhang et al. 10.1029/2021WR030211
27. A Comparative Estimation of Maize Leaf Water Content Using Machine Learning Techniques and Unmanned Aerial Vehicle (UAV)-Based Proximal and Remotely Sensed Data H. Ndlovu et al. 10.3390/rs13204091
28. Assessment for crop water stress with infrared thermal imagery in precision agriculture: A review and future prospects for deep learning applications Z. Zhou et al. 10.1016/j.compag.2021.106019
29. Revisiting crop water stress index based on potato field experiments in Northern Germany E. Ekinzog et al. 10.1016/j.agwat.2022.107664
30. Methodological Ambiguity and Inconsistency Constrain Unmanned Aerial Vehicles as A Silver Bullet for Monitoring Ecological Restoration T. Buters et al. 10.3390/rs11101180
31. Distributed operation of collaborating unmanned aerial vehicles for time-sensitive oil spill mapping P. Odonkor et al. 10.1016/j.swevo.2019.01.005
32. Smart Farming in Europe V. Moysiadis et al. 10.1016/j.cosrev.2020.100345
33. Determining the Effects of Nanonutrient Application in Cabbage (Brassica oleracea var. capitate L.) Using Spectrometry and Biomass Estimation with UAV I. Sinde-González et al. 10.3390/agronomy12010081
34. Simulation of Crop Water Demand and Consumption Considering Irrigation Effects Based on Coupled Hydrology‐Crop Growth Model Y. Zhang et al. 10.1029/2020MS002360
35. Using UAV-thermal imaging to calculate crop water use and irrigation efficiency in a flood-irrigated pecan orchard A. Garcia-Vasquez et al. 10.1016/j.agwat.2022.107824
36. An Automatic Non-Destructive Method for the Classification of the Ripeness Stage of Red Delicious Apples in Orchards Using Aerial Video S. Sabzi et al. 10.3390/agronomy9020084
37. UAV-enabled approaches for irrigation scheduling and water body characterization M. Yadav et al. 10.1016/j.agwat.2024.109091
38. Drones provide spatial and volumetric data to deliver new insights into microclimate modelling J. Duffy et al. 10.1007/s10980-020-01180-9
39. A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses J. Barbedo 10.3390/drones3020040
40. Detection of oak decline using radiative transfer modelling and machine learning from multispectral and thermal RPAS imagery A. Hornero et al. 10.1016/j.jag.2024.103679
41. A systematic review on the application of UAV-based thermal remote sensing for assessing and monitoring crop water status in crop farming systems H. Ndlovu et al. 10.1080/01431161.2024.2368933
42. Development of a novel and fast XRF instrument for large area heavy metal detection integrated with UAV F. Huang et al. 10.1016/j.envres.2022.113841
43. A Review of Crop Water Stress Assessment Using Remote Sensing U. Ahmad et al. 10.3390/rs13204155
44. Estimation of instantaneous, diurnal, and daily evaporative fraction using readily available inputs in the wetlands of South Florida, United States A. Yagci 10.1080/01431161.2023.2195574
45. Current and potential capabilities of UAS for crop water productivity in precision agriculture G. Ezenne et al. 10.1016/j.agwat.2019.03.034
46. UAS-based high resolution mapping of evapotranspiration in a Mediterranean tree-grass ecosystem J. Simpson et al. 10.1016/j.agrformet.2022.108981
47. Crop stress detection from UAVs: best practices and lessons learned for exploiting sensor synergies E. Chakhvashvili et al. 10.1007/s11119-024-10168-3
48. Mapping Root-Zone Soil Moisture Using a Temperature–Vegetation Triangle Approach with an Unmanned Aerial System: Incorporating Surface Roughness from Structure from Motion S. Wang et al. 10.3390/rs10121978
49. Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review K. Berger et al. 10.1016/j.rse.2022.113198
50. Estimation of Water Stress in Grapevines Using Proximal and Remote Sensing Methods A. Matese et al. 10.3390/rs10010114
51. Challenges and Best Practices for Deriving Temperature Data from an Uncalibrated UAV Thermal Infrared Camera J. Kelly et al. 10.3390/rs11050567
52. Droplet deposition density of organic liquid fertilizer at low altitude UAV aerial spraying in rice cultivation M. Abd. Kharim et al. 10.1016/j.compag.2019.105045
53. A New Technique to Estimate Sensible Heat Fluxes around Micrometeorological Towers Using Small Unmanned Aircraft Systems T. Lee et al. 10.1175/JTECH-D-17-0065.1
54. Burrow-Nesting Seabird Survey Using UAV-Mounted Thermal Sensor and Count Automation J. Virtue et al. 10.3390/drones7110674
55. Estimating rice yield by assimilating UAV-derived plant nitrogen concentration into the DSSAT model: Evaluation at different assimilation time windows H. Ge et al. 10.1016/j.fcr.2022.108705
56. Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems C. Brenner et al. 10.1080/01431161.2018.1471550
57. AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture J. Su et al. 10.1016/j.neucom.2022.11.020
58. Correlation between Ground Measurements and UAV Sensed Vegetation Indices for Yield Prediction of Common Bean Grown under Different Irrigation Treatments and Sowing Periods A. Lipovac et al. 10.3390/w14223786
59. Evaluation of the Water Conditions in Coffee Plantations Using RPA S. Santos et al. 10.3390/agriengineering5010005
60. Manual geo-rectification to improve the spatial accuracy of ortho-mosaics based on images from consumer-grade unmanned aerial vehicles (UAVs) S. Azim et al. 10.1007/s11119-019-09647-9
61. On the Use of Rotary-Wing Aircraft to Sample Near-Surface Thermodynamic Fields: Results from Recent Field Campaigns T. Lee et al. 10.3390/s19010010
62. Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk M. Ayaz et al. 10.1109/ACCESS.2019.2932609
63. Multi-Sensor UAV Tracking of Individual Seedlings and Seedling Communities at Millimetre Accuracy T. Buters et al. 10.3390/drones3040081
64. Advance control strategies using image processing, UAV and AI in agriculture: a review I. Syeda et al. 10.1108/WJE-09-2020-0459
65. Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture N. Khan et al. 10.3390/su13094883
66. High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms X. Jin et al. 10.1109/MGRS.2020.2998816
67. High-throughput field crop phenotyping: current status and challenges S. Ninomiya 10.1270/jsbbs.21069
68. Evaluating the feasibility of using Sentinel-2 and Sentinel-3 satellites for high-resolution evapotranspiration estimations R. Guzinski & H. Nieto 10.1016/j.rse.2018.11.019
69. Latent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck F. Tauro et al. 10.1016/j.rse.2021.112771
70. Dependence of CWSI-Based Plant Water Stress Estimation with Diurnal Acquisition Times in a Nectarine Orchard S. Park et al. 10.3390/rs13142775
71. Remotely Piloted Aircraft Systems to Identify Pests and Diseases in Forest Species: The global state of the art and future challenges F. Eugenio et al. 10.1109/MGRS.2021.3087445
72. Identification of Water Layer Presence in Paddy Fields Using UAV-Based Visible and Thermal Infrared Imagery G. Wei et al. 10.3390/agronomy13071932
73. Improving the spatiotemporal resolution of remotely sensed ET information for water management through Landsat, Sentinel-2, ECOSTRESS and VIIRS data fusion J. Xue et al. 10.1007/s00271-022-00799-7
74. Decision Support System for Variable Rate Irrigation Based on UAV Multispectral Remote Sensing X. Shi et al. 10.3390/s19132880
75. Spatiotemporal Winter Wheat Water Status Assessment Improvement Using a Water Deficit Index Derived from an Unmanned Aerial System in the North China Plain V. Antoniuk et al. 10.3390/s23041903
76. Assimilation of LAI Derived from UAV Multispectral Data into the SAFY Model to Estimate Maize Yield X. Peng et al. 10.3390/rs13061094
77. Independent estimates of net carbon uptake in croplands: UAV-LiDAR and machine learning vs. eddy covariance J. Revenga et al. 10.1016/j.agrformet.2024.110106
78. Using UAV-Based SOPC Derived LAI and SAFY Model for Biomass and Yield Estimation of Winter Wheat Y. Song et al. 10.3390/rs12152378
79. Estimation of Water Stress in Potato Plants Using Hyperspectral Imagery and Machine Learning Algorithms J. Duarte-Carvajalino et al. 10.3390/horticulturae7070176
80. Identifying species from the air: UAVs and the very high resolution challenge for plant conservation S. Baena et al. 10.1371/journal.pone.0188714
81. Winter Wheat Canopy Height Extraction from UAV-Based Point Cloud Data with a Moving Cuboid Filter Y. Song & J. Wang 10.3390/rs11101239