120 citations as recorded by crossref.

1. VARIABILIDADE ESPACIAL E TEMPORAL DO ÍNDICE VEGETAÇÃO MPRI APLICADO ÀS IMAGENS DE GRAMA SÃO CARLOS OBTIDAS POR AERONAVE REMOTAMENTE PILOTADA L. Gonçalves et al. 10.18011/bioeng2017v11n4p340-349
2. Replacing Manual Rising Plate Meter Measurements with Low-cost UAV-Derived Sward Height Data in Grasslands for Spatial Monitoring G. Bareth & J. Schellberg 10.1007/s41064-018-0055-2
3. Techniques, Answers, and Real-World UAV Implementations for Precision Farming A. Srivastava & J. Prakash 10.1007/s11277-023-10577-z
4. Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production M. Domingues Franceschini et al. 10.3390/s17061428
5. UAV-Based Estimation of Carbon Exports from Heterogeneous Soil Landscapes—A Case Study from the CarboZALF Experimental Area M. Wehrhan et al. 10.3390/s16020255
6. Optimizing the Timing of Unmanned Aerial Vehicle Image Acquisition for Applied Mapping of Woody Vegetation Species Using Feature Selection G. Weil et al. 10.3390/rs9111130
7. On the Use of Unmanned Aerial Systems for Environmental Monitoring S. Manfreda et al. 10.3390/rs10040641
8. SEAIS: Secure and Efficient Agricultural Image Storage Combining Blockchain and Satellite Networks H. Yang et al. 10.3390/math12182861
9. A Back Propagation Neural Network-Based Radiometric Correction Method (BPNNRCM) for UAV Multispectral Image Y. Zhang et al. 10.1109/JSTARS.2022.3223781
10. Identifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systems J. Maire et al. 10.3389/fsufs.2018.00010
11. Spectral band selection for vegetation properties retrieval using Gaussian processes regression J. Verrelst et al. 10.1016/j.jag.2016.07.016
12. Estimation of Winter Wheat Above-Ground Biomass Using Unmanned Aerial Vehicle-Based Snapshot Hyperspectral Sensor and Crop Height Improved Models J. Yue et al. 10.3390/rs9070708
13. Soybean crop coverage estimation from NDVI images with different spatial resolution to evaluate yield variability in a plot A. de la Casa et al. 10.1016/j.isprsjprs.2018.10.018
14. Direct Reflectance Measurements from Drones: Sensor Absolute Radiometric Calibration and System Tests for Forest Reflectance Characterization T. Hakala et al. 10.3390/s18051417
15. Calibration and Validation from Ground to Airborne and Satellite Level: Joint Application of Time-Synchronous Field Spectroscopy, Drone, Aircraft and Sentinel-2 Imaging P. Naethe et al. 10.1007/s41064-022-00231-x
16. Chip-scale short-wavelength infrared InGaAs microspectrometer based on a linear variable optical filter J. Jeon et al. 10.1039/D3TC01239E
17. A Systematic Review of the Factors Influencing the Estimation of Vegetation Aboveground Biomass Using Unmanned Aerial Systems L. G. Poley & G. J. McDermid 10.3390/rs12071052
18. Low-cost unmanned aerial vehicle-based digital hemispherical photography for estimating leaf area index: a feasibility assessment L. Brown et al. 10.1080/2150704X.2020.1802527
19. Multicolor Fluorescence Imaging as a Candidate for Disease Detection in Plant Phenotyping M. Pérez-Bueno et al. 10.3389/fpls.2016.01790
20. Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows H. Aasen et al. 10.3390/rs10071091
21. Using Unmanned Aerial Vehicles to assess the rehabilitation performance of open cut coal mines K. Johansen et al. 10.1016/j.jclepro.2018.10.287
22. A feature-supervised generative adversarial network for environmental monitoring during hazy days K. Wang et al. 10.1016/j.scitotenv.2020.141445
23. Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance H. Aasen et al. 10.1016/j.isprsjprs.2015.08.002
24. Narrow-to-Broadband Conversion for Albedo Estimation on Urban Surfaces by UAV-Based Multispectral Camera X. Xu et al. 10.3390/rs12142214
25. Comparison of MEMS-Based and FOG-Based IMUs to Determine Sensor Pose on an Unmanned Aircraft System D. Gautam et al. 10.1061/(ASCE)SU.1943-5428.0000225
26. Spatial and Temporal Pasture Biomass Estimation Integrating Electronic Plate Meter, Planet CubeSats and Sentinel-2 Satellite Data J. Gargiulo et al. 10.3390/rs12193222
27. Measuring fire severity using UAV imagery in semi-arid central Queensland, Australia P. McKenna et al. 10.1080/01431161.2017.1317942
28. Small Unmanned Aerial Systems (sUAS) for environmental remote sensing: challenges and opportunities revisited P. Hardin et al. 10.1080/15481603.2018.1510088
29. Reflectance calibration of UAV-based visible and near-infrared digital images acquired under variant altitude and illumination conditions L. Teixeira Crusiol et al. 10.1016/j.rsase.2020.100312
30. A Solar Trajectory Model for Multi-Spectral Image Correction of DOM from Long-Endurance UAV in Clear Sky S. Wu et al. 10.3390/drones9030196
31. Unmanned Aerial Vehicles in Agriculture: A Review of Perspective of Platform, Control, and Applications J. Kim et al. 10.1109/ACCESS.2019.2932119
32. Advance control strategies using image processing, UAV and AI in agriculture: a review I. Syeda et al. 10.1108/WJE-09-2020-0459
33. Mini-Unmanned Aerial Vehicle-Based Remote Sensing: Techniques, applications, and prospects T. Xiang et al. 10.1109/MGRS.2019.2918840
34. An Approach for Route Optimization in Applications of Precision Agriculture Using UAVs K. Srivastava et al. 10.3390/drones4030058
35. A Review of Applications and Communication Technologies for Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) Based Sustainable Smart Farming N. Islam et al. 10.3390/su13041821
36. Mapping vegetation biophysical and biochemical properties using unmanned aerial vehicles-acquired imagery B. Lu et al. 10.1080/01431161.2017.1363441
37. Role of Unmanned Aerial Systems for Natural Resource Management P. Mishra & A. Rai 10.1007/s12524-020-01230-4
38. Spatiotemporal variations in alpine grassland quality and its response to climate change and grazing activity on the Qinghai-Tibet plateau T. Zhan et al. 10.1016/j.ecofro.2025.05.011
39. Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI E. Berra et al. 10.1109/TGRS.2017.2655365
40. The potential of UAV-borne spectral and textural information for predicting aboveground biomass and N fixation in legume-grass mixtures E. Grüner et al. 10.1371/journal.pone.0234703
41. The Time of Day Is Key to Discriminate Cultivars of Sugarcane upon Imagery Data from Unmanned Aerial Vehicle M. Barbosa Júnior et al. 10.3390/drones6050112
42. Using Ordinary Digital Cameras in Place of Near-Infrared Sensors to Derive Vegetation Indices for Phenology Studies of High Arctic Vegetation H. Anderson et al. 10.3390/rs8100847
43. A meta-analysis and review of unmanned aircraft system (UAS) imagery for terrestrial applications K. Singh & A. Frazier 10.1080/01431161.2017.1420941
44. Comparison of leaf area index inversion for grassland vegetation through remotely sensed spectra by unmanned aerial vehicle and field-based spectroradiometer Z. Sha et al. 10.1093/jpe/rty036
45. Radiometric Correction of Multispectral UAS Images: Evaluating the Accuracy of the Parrot Sequoia Camera and Sunshine Sensor P. Olsson et al. 10.3390/rs13040577
46. A review on drone-based harmful algae blooms monitoring D. Wu et al. 10.1007/s10661-019-7365-8
47. UAV LiDAR-based grassland biomass estimation for precision livestock management C. Hütt et al. 10.1117/1.JRS.18.017502
48. High-Resolution Classification of South Patagonian Peat Bog Microforms Reveals Potential Gaps in Up-Scaled CH4 Fluxes by use of Unmanned Aerial System (UAS) and CIR Imagery J. Lehmann et al. 10.3390/rs8030173
49. Remote sensing of plant trait responses to field-based plant–soil feedback using UAV-based optical sensors B. van der Meij et al. 10.5194/bg-14-733-2017
50. Plasmonic mid-infrared photodetector with narrow trenches for reconstructive spectroscopy S. Yasunaga & T. Kan 10.1364/OE.458896
51. Classifying Reflectance Targets under Ambient Light Conditions Using Passive Spectral Measurements A. Hamidisepehr et al. 10.3390/s20185375
52. Measurement of land surface temperature from oblique angle airborne thermal camera observations R. Byerlay et al. 10.1080/01431161.2019.1699672
53. Drones in agriculture: A review and bibliometric analysis A. Rejeb et al. 10.1016/j.compag.2022.107017
54. Teaching Remote Sensing Techniques With High-Quality, Low-Cost Sensors [Education] T. Schuettler et al. 10.1109/MGRS.2018.2878596
55. Spectroradiometric detection of competitor diatoms and the grazer Poteriochromonas in algal cultures T. Reichardt et al. 10.1016/j.algal.2020.102020
56. Automatic Identification of Shrub-Encroached Grassland in the Mongolian Plateau Based on UAS Remote Sensing Y. Dong et al. 10.3390/rs11131623
57. A system of UAV application in indoor environment Y. Khosiawan & I. Nielsen 10.1080/21693277.2016.1195304
58. Task scheduling system for UAV operations in indoor environment Y. Khosiawan et al. 10.1007/s00521-018-3373-9
59. Detection of crop water status using UAV mounted sensor J. Coulombe et al. 10.17660/ActaHortic.2020.1279.39
60. A low-cost UAV framework towards ornamental plant detection and counting in the wild E. Bayraktar et al. 10.1016/j.isprsjprs.2020.06.012
61. Variation of nutritive value, measured by proximal hyperspectral sensing, of herbage offered to grazing dairy cows F. Duranovich et al. 10.1080/00288233.2021.1914687
62. The q-rung fuzzy LOPCOW-VIKOR model to assess the role of unmanned aerial vehicles for precision agriculture realization in the Agri-Food 4.0 era F. Ecer et al. 10.1007/s10462-023-10476-6
63. Spectral Comparison of UAV-Based Hyper and Multispectral Cameras for Precision Viticulture S. Di Gennaro et al. 10.3390/rs14030449
64. Multi-temporal high-resolution imaging spectroscopy with hyperspectral 2D imagers – From theory to application H. Aasen & A. Bolten 10.1016/j.rse.2017.10.043
65. Rice Growth-Stage Recognition Based on Improved YOLOv8 with UAV Imagery W. Cai et al. 10.3390/agronomy14122751
66. Mapping biological soil crusts in a Hawaiian dryland E. Collier et al. 10.1080/01431161.2021.2003904
67. UAV Remote Sensing Technology for Wheat Growth Monitoring in Precision Agriculture: Comparison of Data Quality and Growth Parameter Inversion J. Liu et al. 10.3390/agronomy15010159
68. Influence of tillage systems on soil physical properties, spectral response and yield of the bean crop R. Martins et al. 10.1016/j.rsase.2021.100517
69. Estimating Plant Traits of Grasslands from UAV-Acquired Hyperspectral Images: A Comparison of Statistical Approaches A. Capolupo et al. 10.3390/ijgi4042792
70. UAVs technology for the development of GUI based application for precision agriculture and environmental research K. Srivastava et al. 10.1016/j.rsase.2019.100258
71. Visible to long-wave infrared chip-scale spectrometers based on photodetectors with tailored responsivities and multispectral filters J. Cadusch et al. 10.1515/nanoph-2020-0114
72. Drone-Related Agrotechnologies for Precise Plant Protection in Western Balkans: Applications, Possibilities, and Legal Framework Limitations A. Ivezić et al. 10.3390/agronomy13102615
73. Technological opportunities for sensing of the health effects of weather and climate change: a state-of-the-art-review V. Anderson et al. 10.1007/s00484-020-02063-z
74. Unmanned Aerial Vehicles in Smart Agriculture: Applications, Requirements, and Challenges P. Reddy Maddikunta et al. 10.1109/JSEN.2021.3049471
75. Plant Leaf Disease Detection, Classification, and Diagnosis Using Computer Vision and Artificial Intelligence: A Review A. Bhargava et al. 10.1109/ACCESS.2024.3373001
76. Species classification using Unmanned Aerial Vehicle (UAV)-acquired high spatial resolution imagery in a heterogeneous grassland B. Lu & Y. He 10.1016/j.isprsjprs.2017.03.011
77. Hierarchical land cover and vegetation classification using multispectral data acquired from an unmanned aerial vehicle O. Ahmed et al. 10.1080/01431161.2017.1294781
78. Unmanned Aerial System multispectral mapping for low and variable solar irradiance conditions: Potential of tensor decomposition S. Wang et al. 10.1016/j.isprsjprs.2019.06.017
79. Construction of an unmanned aerial vehicle remote sensing system for crop monitoring S. Jeong et al. 10.1117/1.JRS.10.026027
80. Mapping field-scale soil organic carbon with unmanned aircraft system-acquired time series multispectral images L. Guo et al. 10.1016/j.still.2019.104477
81. Plasmonic photodetector with submicron grating for reconstructive spectroscopy of low-intensity broadband light Y. Kaneda et al. 10.1016/j.optlaseng.2024.108501
82. Radiometric and spectral comparison of inexpensive camera systems used for remote sensing C. Coburn et al. 10.1080/01431161.2018.1466085
83. Pixel- and object-based multispectral classification of forest tree species from small unmanned aerial vehicles S. Franklin 10.1139/juvs-2017-0022
84. Bidirectional Reflectance Distribution Function Modeling Considerations in Small Unmanned Multispectral Systems R. Fischer et al. 10.1109/JSTARS.2022.3171393
85. A Systematic Study of Estimating Potato N Concentrations Using UAV-Based Hyper- and Multi-Spectral Imagery J. Zhou et al. 10.3390/agronomy12102533
86. Multispectral UAV monitoring of submerged seaweed in shallow water Y. Taddia et al. 10.1007/s12518-019-00270-x
87. Experimental Evaluation and Consistency Comparison of UAV Multispectral Minisensors H. Lu et al. 10.3390/rs12162542
88. Using Proximal Hyperspectral Sensing to Predict Herbage Nutritive Value for Dairy Farming F. Duranovich et al. 10.3390/agronomy10111826
89. State of Major Vegetation Indices in Precision Agriculture Studies Indexed in Web of Science: A Review D. Radočaj et al. 10.3390/agriculture13030707
90. Phenological analysis of unmanned aerial vehicle based time series of barley imagery with high temporal resolution A. Burkart et al. 10.1007/s11119-017-9504-y
91. Predicting pasture biomass using a statistical model and machine learning algorithm implemented with remotely sensed imagery D. De Rosa et al. 10.1016/j.compag.2020.105880
92. Emerging Technologies for Automation in Environmental Sensing: Review S. Borah et al. 10.3390/app14083531
93. Drone-Based Monitoring and Mapping for LMO Confined Field Management under the Ministry of Environment S. Han et al. 10.3390/app131910627
94. Task scheduling system for UAV operations in agricultural plant protection environment F. Sun et al. 10.1007/s12652-020-01969-1
95. Airborne Hyperspectral Data Predict Fine-Scale Plant Species Diversity in Grazed Dry Grasslands T. Möckel et al. 10.3390/rs8020133
96. Drone Laser Scanning for Modeling Riverscape Topography and Vegetation: Comparison with Traditional Aerial Lidar J. Resop et al. 10.3390/drones3020035
97. A Fog Computing Framework for Intrusion Detection of Energy-Based Attacks on UAV-Assisted Smart Farming J. Sajid et al. 10.3390/app13063857
98. Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review K. Neupane & F. Baysal-Gurel 10.3390/rs13193841
99. Estimating reed loss caused by Locusta migratoria manilensis using UAV-based hyperspectral data P. Song et al. 10.1016/j.scitotenv.2020.137519
100. Performance modeling and analysis of a UAV path planning and target detection in a UAV-based wireless sensor network P. Sun & A. Boukerche 10.1016/j.comnet.2018.09.022
101. Modeling Mid-Season Rice Nitrogen Uptake Using Multispectral Satellite Data J. Brinkhoff et al. 10.3390/rs11151837
102. Assessing the accuracy of an infrared-converted drone camera with Orange-Cyan-NIR filter for vegetation and environmental monitoring A. Louw et al. 10.1016/j.rsase.2024.101229
103. Can nitrogen input mapping from aerial imagery improve nitrous oxide emissions estimates from grazed grassland? J. Maire et al. 10.1007/s11119-022-09908-0
104. Optimizing Data Consistency in UAV Multispectral Imaging for Radiometric Correction and Sensor Conversion Models W. Yang et al. 10.3390/rs17122001
105. Cyberthreats and Security Measures in Drone-Assisted Agriculture K. Tychola & K. Rantos 10.3390/electronics14010149
106. Quantifying Aboveground Biomass of Shrubs Using Spectral and Structural Metrics Derived from UAS Imagery L. Poley et al. 10.3390/rs12142199
107. Spectral-Based Classification of Plant Species Groups and Functional Plant Parts in Managed Permanent Grassland R. Britz et al. 10.3390/rs14051154
108. Examining the influence of bare soil UAV imagery combined with auxiliary datasets to estimate and map soil organic carbon distribution in an erosion-prone agricultural field J. Biney et al. 10.1016/j.scitotenv.2023.161973
109. Accurate Conversion of Land Surface Reflectance for Drone-Based Multispectral Remote Sensing Images Using a Solar Radiation Component Separation Approach H. Sun et al. 10.3390/s25082604
110. Derivation of High Spatial Resolution Albedo from UAV Digital Imagery: Application over the Greenland Ice Sheet J. Ryan et al. 10.3389/feart.2017.00040
111. Development of a Radiometric Calibration Method for Multispectral Images of Croplands Obtained with a Remote-Controlled Aerial System T. Shin et al. 10.3390/rs15051408
112. A pilot project combining multispectral proximal sensors and digital cameras for monitoring tropical pastures R. Handcock et al. 10.5194/bg-13-4673-2016
113. A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images H. Zhang et al. 10.1016/j.gecco.2022.e01999
114. Error Budget for Geolocation of Spectroradiometer Point Observations from an Unmanned Aircraft System D. Gautam et al. 10.3390/s18103465
115. The use of machine learning methods to estimate aboveground biomass of grasslands: A review T. Morais et al. 10.1016/j.ecolind.2021.108081
116. Monitoring drought response and chlorophyll content in Quercus by consumer-grade, near-infrared (NIR) camera: a comparison with reflectance spectroscopy S. Raddi et al. 10.1007/s11056-021-09848-z
117. Multispectral UAS Data Accuracy for Different Radiometric Calibration Methods A. Poncet et al. 10.3390/rs11161917
118. Rice Leaf Chlorophyll Content Estimation Using UAV-Based Spectral Images in Different Regions S. Ban et al. 10.3390/agronomy12112832
119. The role of forage management in addressing challenges facing Australasian dairy farming L. Cranston et al. 10.1071/AN18570
120. Predicting Biomass and Yield in a Tomato Phenotyping Experiment Using UAV Imagery and Random Forest K. Johansen et al. 10.3389/frai.2020.00028