Machine learning for object-based crop classification using multi-temporal Landsat-8 imagery

作者: Jason Kane Gilbertson

DOI:

关键词: CropObject basedArtificial intelligenceMachine learningComputer science

摘要:

参考文章(137)
Gary Miner, John Elder, Robert Nisbet, Handbook of Statistical Analysis and Data Mining Applications ,(2009)
Matthew Wiener, Andy Liaw, Classification and Regression by randomForest ,(2007)
M. F. Baumgardner, C. J. Johannsen, R. M. Hoffer, Agricultural Applications of Remote Multispectral Sensing Proceedings of the Indiana Academy of Science. ,vol. 76, pp. 386- 396 ,(1966)
Marvin E. Bauer, The role of remote sensing in determining the distribution and yield of crops Advances in Agronomy. ,vol. 27, pp. 271- 304 ,(1975) , 10.1016/S0065-2113(08)70012-9
Z. Damla Uca Avci, Filiz Sunar, Process-based image analysis for agricultural mapping: A case study in Turkgeldi region, Turkey Advances in Space Research. ,vol. 56, pp. 1635- 1644 ,(2015) , 10.1016/J.ASR.2015.07.021
Emre Ozelkan, Gang Chen, Burak Berk Ustundag, None, Multiscale object-based drought monitoring and comparison in rainfed and irrigated agriculture from Landsat 8 OLI imagery International Journal of Applied Earth Observation and Geoinformation. ,vol. 44, pp. 159- 170 ,(2016) , 10.1016/J.JAG.2015.08.003
J. Schiewe, SEGMENTATION OF HIGH-RESOLUTION REMOTELY SENSED DATA - CONCEPTS, APPLICATIONS AND PROBLEMS ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. ,vol. 34, pp. 380- 385 ,(2002)