A Two-Step Ensemble-based Genetic Algorithm for Land Cover Classification

Accurate land use and land cover (LULC) maps are effective tools to help achieve sound urban planning and precision agriculture. As an intelligent optimization technology, genetic algorithm (GA) has been successfully applied to various image classification tasks in recent years. However, simple GA f...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing Jg. 16; S. 1 - 9
Hauptverfasser:	Cao, Yang, Feng, Wei, Quan, Yinghui, Bao, Wenxing, Dauphin, Gabriel, Song, Yijia, Ren, Aifeng, Xing, Mengdao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Classification Classification algorithms Clustering algorithms Clusters Computation Convergence Engineering Sciences Environmental Sciences Evolutionary computation Gene mapping genetic algorithm Genetic algorithm (GA) Genetic algorithms Genetics Global Changes Image classification Immunity Land cover Land use land use and land cover land use and land cover (LULC) Methods neighborhood window Neighborhoods Objective function Optimization Precision agriculture Probability theory remote sensing image classification Signal and Image processing Task analysis Task complexity Two-step ensemble Urban agriculture Urban planning
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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