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For: Grüner E, Wachendorf M, Astor T. The potential of UAV-borne spectral and textural information for predicting aboveground biomass and N fixation in legume-grass mixtures. PLoS One 2020;15:e0234703. [PMID: 32584839 PMCID: PMC7316270 DOI: 10.1371/journal.pone.0234703] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/02/2020] [Indexed: 11/18/2022]  Open
Number Cited by Other Article(s)
1
Dhakal R, Maimaitijiang M, Chang J, Caffe M. Utilizing Spectral, Structural and Textural Features for Estimating Oat Above-Ground Biomass Using UAV-Based Multispectral Data and Machine Learning. SENSORS (BASEL, SWITZERLAND) 2023;23:9708. [PMID: 38139554 PMCID: PMC10748049 DOI: 10.3390/s23249708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 10/31/2023] [Accepted: 12/05/2023] [Indexed: 12/24/2023]
2
Niu X, Song Z, Xu C, Wu H, Luan Q, Jiang J, Li Y. Prediction of Needle Physiological Traits Using UAV Imagery for Breeding Selection of Slash Pine. PLANT PHENOMICS (WASHINGTON, D.C.) 2023;5:0028. [PMID: 36939412 PMCID: PMC10017333 DOI: 10.34133/plantphenomics.0028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/16/2022] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
3
Xia M, Yang R, Yin G, Chen X, Chen J, Zhao N. A method based on a one-dimensional convolutional neural network for UV-vis spectrometric quantification of nitrate and COD in water under random turbidity disturbance scenario. RSC Adv 2022;13:516-526. [PMID: 36605648 PMCID: PMC9773182 DOI: 10.1039/d2ra06952k] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]  Open
4
Wu J, Zheng D, Wu Z, Song H, Zhang X. Prediction of Buckwheat Maturity in UAV-RGB Images Based on Recursive Feature Elimination Cross-Validation: A Case Study in Jinzhong, Northern China. PLANTS (BASEL, SWITZERLAND) 2022;11:3257. [PMID: 36501299 PMCID: PMC9737888 DOI: 10.3390/plants11233257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/22/2022] [Accepted: 11/25/2022] [Indexed: 06/17/2023]
5
Ren H, Zhao Y, Xiao W, Zhang J, Chen C, Ding B, Yang X. Vegetation growth status as an early warning indicator for the spontaneous combustion disaster of coal waste dump after reclamation: An unmanned aerial vehicle remote sensing approach. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022;317:115502. [PMID: 35751291 DOI: 10.1016/j.jenvman.2022.115502] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 06/04/2022] [Accepted: 06/07/2022] [Indexed: 06/15/2023]
6
Fine-Scale Mapping of Soil Organic Matter in Agricultural Soils Using UAVs and Machine Learning. REMOTE SENSING 2022. [DOI: 10.3390/rs14143349] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
7
Herbage Mass, N Concentration, and N Uptake of Temperate Grasslands Can Adequately Be Estimated from UAV-Based Image Data Using Machine Learning. REMOTE SENSING 2022. [DOI: 10.3390/rs14133066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
8
Multisite and Multitemporal Grassland Yield Estimation Using UAV-Borne Hyperspectral Data. REMOTE SENSING 2022. [DOI: 10.3390/rs14092068] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
9
Quantification of Grassland Biomass and Nitrogen Content through UAV Hyperspectral Imagery—Active Sample Selection for Model Transfer. DRONES 2022. [DOI: 10.3390/drones6030073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
10
Spectral-Based Classification of Plant Species Groups and Functional Plant Parts in Managed Permanent Grassland. REMOTE SENSING 2022. [DOI: 10.3390/rs14051154] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
11
Cunliffe AM, Anderson K, Boschetti F, Brazier RE, Graham HA, Myers‐Smith IH, Astor T, Boer MM, Calvo LG, Clark PE, Cramer MD, Encinas‐Lara MS, Escarzaga SM, Fernández‐Guisuraga JM, Fisher AG, Gdulová K, Gillespie BM, Griebel A, Hanan NP, Hanggito MS, Haselberger S, Havrilla CA, Heilman P, Ji W, Karl JW, Kirchhoff M, Kraushaar S, Lyons MB, Marzolff I, Mauritz ME, McIntire CD, Metzen D, Méndez‐Barroso LA, Power SC, Prošek J, Sanz‐Ablanedo E, Sauer KJ, Schulze‐Brüninghoff D, Šímová P, Sitch S, Smit JL, Steele CM, Suárez‐Seoane S, Vargas SA, Villarreal M, Visser F, Wachendorf M, Wirnsberger H, Wojcikiewicz R. Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems. REMOTE SENSING IN ECOLOGY AND CONSERVATION 2022;8:57-71. [PMID: 35873085 PMCID: PMC9290598 DOI: 10.1002/rse2.228] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/01/2021] [Accepted: 06/07/2021] [Indexed: 05/03/2023]
12
Sharma P, Leigh L, Chang J, Maimaitijiang M, Caffé M. Above-Ground Biomass Estimation in Oats Using UAV Remote Sensing and Machine Learning. SENSORS (BASEL, SWITZERLAND) 2022;22:601. [PMID: 35062559 PMCID: PMC8778966 DOI: 10.3390/s22020601] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/08/2022] [Accepted: 01/09/2022] [Indexed: 02/01/2023]
13
Comparison of Multi-Methods for Identifying Maize Phenology Using PhenoCams. REMOTE SENSING 2022. [DOI: 10.3390/rs14020244] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
14
Potentials and Limitations of WorldView-3 Data for the Detection of Invasive Lupinus polyphyllus Lindl. in Semi-Natural Grasslands. REMOTE SENSING 2021. [DOI: 10.3390/rs13214333] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
15
Application of Multispectral Camera in Monitoring the Quality Parameters of Fresh Tea Leaves. REMOTE SENSING 2021. [DOI: 10.3390/rs13183719] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
16
Improving Accuracy of Herbage Yield Predictions in Perennial Ryegrass with UAV-Based Structural and Spectral Data Fusion and Machine Learning. REMOTE SENSING 2021. [DOI: 10.3390/rs13173459] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
17
Assessing Spatial Variability of Barley Whole Crop Biomass Yield and Leaf Area Index in Silvoarable Agroforestry Systems Using UAV-Borne Remote Sensing. REMOTE SENSING 2021. [DOI: 10.3390/rs13142751] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
18
The Application of an Unmanned Aerial System and Machine Learning Techniques for Red Clover-Grass Mixture Yield Estimation under Variety Performance Trials. REMOTE SENSING 2021. [DOI: 10.3390/rs13101994] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
19
Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform. REMOTE SENSING 2021. [DOI: 10.3390/rs13091795] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
20
Understanding Growth Dynamics and Yield Prediction of Sorghum Using High Temporal Resolution UAV Imagery Time Series and Machine Learning. REMOTE SENSING 2021. [DOI: 10.3390/rs13091763] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
21
Grüner E, Astor T, Wachendorf M. Prediction of Biomass and N Fixation of Legume-Grass Mixtures Using Sensor Fusion. FRONTIERS IN PLANT SCIENCE 2020;11:603921. [PMID: 33597959 PMCID: PMC7883874 DOI: 10.3389/fpls.2020.603921] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 12/15/2020] [Indexed: 05/20/2023]
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