Symbolic regression-based allometric model development of a mangrove forest LAI using structural variables and digital hemispherical photography

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@Article{PARAMANIK:2022:AG,

• author = "S. Paramanik and M. D. Behera and J. Dash",
• title = "Symbolic regression-based allometric model development of a mangrove forest {LAI} using structural variables and digital hemispherical photography",
• journal = "Applied Geography",
• volume = "139",
• pages = "102649",
• year = "2022",
• ISSN = "0143-6228",
• DOI = "doi:10.1016/j.apgeog.2022.102649",
• URL = "https://www.sciencedirect.com/science/article/pii/S0143622822000200",
• keywords = "genetic algorithms, genetic programming, Symbolic regression, Allometric equation, Diameter at breast height, Tree density, Canopy height, BhitarKanika wildlife sanctuary",
• abstract = "The leaf area index (LAI) serves as a proxy to understand the dynamics of plant productivity, energy balance, and gas exchange. Cost-effective and accurate estimation of LAI is essential for under-assessed carbon-rich tropical forests, e.g., mangroves. Here, we developed allometric equations to estimate LAI using a combination of non-destructive, optical measurements through digital hemispherical photographs (DHP), and genetic programming-based Symbolic Regression (SR). We used three structural variables: diameter at breast height (DBH), tree density (TD), and canopy height (Ht) for a mangrove forest in the BhitarKanika Wildlife Sanctuary (BWS), located along the Eastern coast of India. Triplet combination using SR provided the best equation (R2 = 0.51) than any singlet or duplet combination of the variables, and even it was better than Partial Least Square (PLS) based regression (R2 = 0.42). To the best of our knowledge, the current study is the maiden attempt to develop an allometric model to estimate LAI for a mangrove ecosystem in India. In-situ measurements of structural variables such as DBH, Ht, and TD can be used for LAI estimates, as shown here. LAI estimates using cost-effective methods would greatly enhance our understanding of the spatial and temporal dynamics of mangrove ecosystems",

}

Genetic Programming entries for Somnath Paramanik Mukunda Dev Behera J Dash

Citations