Yadav, N.; Rakholia, S.; Yosef, R. Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review. Land2024, 13, 230.
Yadav, N.; Rakholia, S.; Yosef, R. Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review. Land 2024, 13, 230.
Yadav, N.; Rakholia, S.; Yosef, R. Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review. Land2024, 13, 230.
Yadav, N.; Rakholia, S.; Yosef, R. Decision Support Systems in Forestry and Tree-Planting Practices and the Prioritization of Ecosystem Services: A Review. Land 2024, 13, 230.
Abstract
In this study, tree selection/plantation DSS (Decision Support Systems) were reviewed and assessed based on essential objectives in the available literature. We reviewed existing DSS using multiple data sources and available online resources such as web interfaces. We compared the existing DSS, focusing primarily on five primary objectives in this study, which DSS may address when it comes to the tree selection, including a) Climate resilience, b) Infrastructure/Space Optimization, c) Agroforestry, d) Ecosystem services, e) Urban sustainability. Climate resilience of tree species and urban sustainability is addressed relatively less in existing systems, which can be holistically internalized in future DSS tools Based on this review, DNN (Deep Neural Networks) is recommended to address achieving trade-offs between complex objectives such as maximizing ecosystem services, climate resilience of tree species, maintaining Agroforestry, and other benefits.
Keywords
Decision Support System; Climate Resilience; Ecosystem Services; Deep Neural Networks; Sustainability
Subject
Environmental and Earth Sciences, Sustainable Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
