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For: Buters T, Belton D, Cross A. Multi-Sensor UAV Tracking of Individual Seedlings and Seedling Communities at Millimetre Accuracy. Drones 2019;3:81. [DOI: 10.3390/drones3040081] [Cited by in Crossref: 13] [Cited by in F6Publishing: 14] [Article Influence: 4.3] [Reference Citation Analysis]
Number Citing Articles
1 Yaxley KJ, Reid A, Kenworthy C, Hossny M, Baxter DP, Allworth MB, Mcgrath SR, Joiner KF, Abbass H. Building a Sky Shepherd for the future of agriculture. Smart Agricultural Technology 2022. [DOI: 10.1016/j.atech.2022.100137] [Reference Citation Analysis]
2 van der Heyde M, Bunce M, Nevill P. Key factors to consider in the use of environmental DNA metabarcoding to monitor terrestrial ecological restoration. Science of The Total Environment 2022;848:157617. [DOI: 10.1016/j.scitotenv.2022.157617] [Reference Citation Analysis]
3 Rejeb A, Abdollahi A, Rejeb K, Treiblmaier H. Drones in agriculture: A review and bibliometric analysis. Computers and Electronics in Agriculture 2022;198:107017. [DOI: 10.1016/j.compag.2022.107017] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
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5 Paraforos DS, Sharipov GM, Heiß A, Griepentrog HW. Position Accuracy Assessment of a UAV-Mounted Sequoia+ Multispectral Camera Using a Robotic Total Station. Agriculture 2022;12:885. [DOI: 10.3390/agriculture12060885] [Reference Citation Analysis]
6 Guan H, Sun X, Su Y, Hu T, Wang H, Wang H, Peng C, Guo Q. UAV-lidar aids automatic intelligent powerline inspection. International Journal of Electrical Power & Energy Systems 2021;130:106987. [DOI: 10.1016/j.ijepes.2021.106987] [Cited by in Crossref: 17] [Cited by in F6Publishing: 18] [Article Influence: 17.0] [Reference Citation Analysis]
7 Rominger KR, Denittis A, Meyer SE. Using drone imagery analysis in rare plant demographic studies. Journal for Nature Conservation 2021;62:126020. [DOI: 10.1016/j.jnc.2021.126020] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 6.0] [Reference Citation Analysis]
8 Banerjee BP, Sharma V, Spangenberg G, Kant S. Machine Learning Regression Analysis for Estimation of Crop Emergence Using Multispectral UAV Imagery. Remote Sensing 2021;13:2918. [DOI: 10.3390/rs13152918] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
9 Castro J, Morales‐rueda F, Navarro FB, Löf M, Vacchiano G, Alcaraz‐segura D. Precision restoration: a necessary approach to foster forest recovery in the 21st century. Restor Ecol 2021;29. [DOI: 10.1111/rec.13421] [Cited by in Crossref: 16] [Cited by in F6Publishing: 17] [Article Influence: 16.0] [Reference Citation Analysis]
10 Szczepanski CJ, Purushothaman R. Sensors for UAVs dedicated to agriculture: current scenarios and challenges. AEAT 2021;94:31-44. [DOI: 10.1108/aeat-11-2020-0257] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
11 Neumann C, Schindhelm A, Müller J, Weiss G, Liu A, Itzerott S. The Regenerative Potential of Managed Calluna Heathlands—Revealing Optical and Structural Traits for Predicting Recovery Dynamics. Remote Sensing 2021;13:625. [DOI: 10.3390/rs13040625] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Cross AT, Zhong H, Lambers H. Incorporating rock in surface covers improves the establishment of native pioneer vegetation on alkaline mine tailings. Sci Total Environ 2021;768:145373. [PMID: 33736352 DOI: 10.1016/j.scitotenv.2021.145373] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 5.0] [Reference Citation Analysis]
13 Feng A, Zhou J, Vories E, Sudduth KA. Evaluation of Cotton Emergence Using UAV-Based Narrow-Band Spectral Imagery with Customized Image Alignment and Stitching Algorithms. Remote Sensing 2020;12:1764. [DOI: 10.3390/rs12111764] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]