Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review

Neelesh Yadav, Shrey Rakholia and Reuven Yosef ()
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Neelesh Yadav: Bioinformatics Center, Forest Research Institute, Dehradun 248006, Uttarakhand, India
Shrey Rakholia: Bioinformatics Center, Forest Research Institute, Dehradun 248006, Uttarakhand, India
Reuven Yosef: Eilat Campus, Ben Gurion University of the Negev, P.O. Box 272, Eilat 881020, Israel

Land, 2024, vol. 13, issue 2, 1-12

Abstract: In this study, tree-selection/plantation decision support systems (DSSs) were reviewed and evaluated against essential objectives in the available literature. We verified whether existing DSSs leverage multiple data sources and available online resources such as web interfaces. We compared the existing DSSs, and in this study mainly focused on five main objectives that DSSs can consider in tree selection, including (a) climate resilience, (b) infrastructure/space optimization, (c) agroforestry, (d) ecosystem services, and (e) urban sustainability. The climate resilience of tree species and urban sustainability are relatively rarely taken into account in existing systems, which can be integrated holistically in future DSS tools. Based on this review, deep neural networks (DNNs) are recommended to achieve trade-offs between complex objectives such as maximizing ecosystem services, the climate resilience of tree species, agroforestry conservation, and other benefits.

Keywords: decision support system; climate resilience; ecosystem services; deep neural networks; sustainability (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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