Combining hyperspectral UAV and multispectral Formosat-2 imagery for precision agriculture applications
作者： C.M. Gevaert , J. Tang , F.J. Garcia-Haro , J. Suomalainen , L. Kooistra
DOI: 10.1109/WHISPERS.2014.8077607
关键词:
摘要: Remote sensing is a key tool for precision agriculture applications as it capable of capturing spatial and temporal variations in crop status. However, satellites often have an inadequate resolution applications. High-resolution Unmanned Aerial Vehicles (UAV) imagery can be obtained at flexible dates, but operational costs may limit the collection frequency. The current study utilizes data fusion to create dataset which benefits from Formosat-2 UAV with purpose monitoring growth potato field. correlation Weighted Difference Vegetation Index (WDVI) fused measured indicators field level added value enhanced are discussed. results STARFM method were restrained by requirement same-day base imagery. unmixing-based provided high accurately captured WDVI variation (r=0.969).
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narcis.nl参考文章(105)
Jie Liu, Klaus Regenauer-Lieb, Chris Hines, Shuxia Zhang, Paul Bourke, Florian Fusseis, David A. Yuen, Applications of Microtomography to Multiscale System Dynamics: Visualisation, Characterisation and High Performance Computation Springer-Verlag. pp. 653- 674 ,(2013) , 10.1007/978-3-642-16405-7_40
Konstantin Krivoruchko, Alexander Gribov, Pragmatic Bayesian Kriging for Non-Stationary and Moderately Non-Gaussian Data Lecture Notes in Earth System Sciences. pp. 61- 64 ,(2014) , 10.1007/978-3-642-32408-6_15
Christopher M. U. Neale, Saravanan Sivarajan, Yield Estimation and Validation of Potatoes Using Remote Sensing based Crop Yield Model ,(2011)
David Baulcombe, Ian Crute, Bill Davies, Jim Dunwell, Mike Gale, Jonathan Jones, Jules Pretty, William Sutherland, Camilla Toulmin, None, Reaping the Benefits: Science and the sustainable intensification of global agriculture Royal Society. ,(2009)
AS Rodrigues, ARS Marçal, M Cunha, None, Evaluation of data fusion methods for agricultural monitoring based on synthetic images. Remote sensing for a changing Europe. Proceedings of the 28th Symposium of the European Association of Remote Sensing Laboratories, Istanbul, Turkey, 2-5 June 2008. pp. 125- 133 ,(2009) , 10.3233/978-1-58603-986-8-125
Advances in Environmental Remote Sensing : Sensors, Algorithms, and Applications Advances in Environmental Remote Sensing: Sensors, Algorithm, and Applications. pp. 101- 142 ,(2011) , 10.1201/B10599
Hamlyn G. Jones, Robin A. Vaughan, Remote Sensing of Vegetation: Principles, Techniques, and Applications ,(2010)
David E. Clay, Francis J. Pierce, GIS Applications in Agriculture ,(2018)
R. S. Lunetta, C. D. Eividge, J. G. Lyon, B. Guindon, North American Landscape Characterization dataset development and data fusion issues Photogrammetric Engineering and Remote Sensing. ,vol. 64, pp. 821- 829 ,(1998)
Barbara G Tabachnick, Linda S Fidell, Jodie B Ullman, None, Using multivariate statistics ,(1983)