{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T15:36:18Z","timestamp":1781019378836,"version":"3.54.1"},"reference-count":35,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of KwaZulu-Natal funded Big data for Science society (BDSS) programme and the DST\/NRF funded SARChI chair in land use planning and management","award":["84157"],"award-info":[{"award-number":["84157"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Tree-based Pipeline Optimization Tool (TPOT) is a state-of-the-art automated machine learning (AutoML) approach that automatically generates and optimizes tree-based pipelines using a genetic algorithm. Although it has been proven to outperform commonly used machine techniques, its capability to handle high-dimensional datasets has not been investigated. In vegetation mapping and analysis, multi-date images are generally high-dimensional datasets that contain embedded information, such as phenological and canopy structural properties, known to enhance mapping accuracy. However, without the implementation of a robust classification algorithm or a feature selection tool, the large sets and the presence of redundant variables in multi-date images can impede accurate and efficient landscape classification. Hence, this study sought to test the efficacy of the TPOT on a multi-date Sentinel-2 image to optimize the classification accuracies of a landscape infested by a noxious invasive plant species, the parthenium weed (Parthenium hysterophorus). Specifically, the models created from the multi-date image, using the TPOT and an algorithm system that combines feature selection and the TPOT, dubbed \u201cReliefF-Svmb-EXT-TPOT\u201d, were compared. The results showed that the TPOT could perform well on data with large feature sets, but at a computational cost. The overall accuracies were 91.9% and 92.6% using the TPOT and ReliefF-Svmb-EXT-TPOT models, respectively. The study findings are crucial for automated and accurate mapping of parthenium weed using high-dimensional geospatial datasets with limited human intervention.<\/jats:p>","DOI":"10.3390\/rs14071687","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T21:34:29Z","timestamp":1648762469000},"page":"1687","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Determining the Capability of the Tree-Based Pipeline Optimization Tool (TPOT) in Mapping Parthenium Weed Using Multi-Date Sentinel-2 Image Data"],"prefix":"10.3390","volume":"14","author":[{"given":"Zolo","family":"Kiala","sequence":"first","affiliation":[{"name":"Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3201, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Odindi","sequence":"additional","affiliation":[{"name":"Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3201, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7358-8111","authenticated-orcid":false,"given":"Onisimo","family":"Mutanga","sequence":"additional","affiliation":[{"name":"Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3201, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1016\/j.rser.2012.12.011","article-title":"Review on Parthenium hysterphorus as a potential energy source","volume":"20","author":"Swati","year":"2013","journal-title":"Renew. 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