Customized crop feature construction using genetic programming for early- and in-season crop mapping

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@Article{DBLP:journals/cea/WenLBXSSWW25,

• author = "Caiyun Wen and Miao Lu and Ying Bi and Lang Xia and Jing Sun and Yun Shi and Yanbing Wei and Wenbin Wu",
• title = "Customized crop feature construction using genetic programming for early- and in-season crop mapping",
• journal = "Computers and Electronics in Agriculture",
• year = "2025",
• volume = "231",
• pages = "109949",
• month = apr,
• keywords = "genetic algorithms, genetic programming, Remote Sensing, Crop mapping, Feature Construction, Customized feature",
• ISSN = "0168-1699",
• timestamp = "Fri, 07 Mar 2025 18:31:09 +0100",
• biburl = "https://dblp.org/rec/journals/cea/WenLBXSSWW25.bib",
• bibsource = "dblp computer science bibliography, https://dblp.org",
• DOI = "doi:10.1016/J.COMPAG.2025.109949",
• size = "12 pages",
• abstract = "Early- and in-season crop mapping provides vital information for precision agriculture. It is still a challenge for early- and in-season crop mapping because of the limited available images and similar spectral information. This study aims to enhance early- and in-season crop mapping by developing a Genetic Programming (GP) method to construct customized crop features. GP automatically generated candidate features for the target-crop using early- or in-season images, selected programs with substantial value disparities between target and non-target crops through the fitness function, and finally outputted the customized feature after the evolutionary process. These customized features were then compared with commonly used spectral bands and vegetation indices to evaluate their effectiveness for early- and in-season crop mapping. The results proved that the customized crop features had significant advantages in both early- and in-season crop mapping. The early-season accuracy in April after crop planting was 3.97 percent to 9.53 percent higher than spectral features and vegetation indices. Based on the incremental classification for the in-season crop mapping, the customized crop features maintained the best performance. Advantages of customized crop features include the ability to automatically select effective bands of useful months without requiring expert knowledge, the ability to catch and enlarge the subtle spectral differences with the early- and in-season images, and the little information redundancy compared with spectral features and vegetation indices. It can be concluded that the customized crop features are outstanding for early- and in-season crop mapping.",
• notes = "State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China",

}

Genetic Programming entries for Caiyun Wen Miao Lu Ying Bi Lang Xia Jing Sun Yun Shi Yanbing Wei Wenbin Wu

Citations