在正确的地方植树：使用算法融合推荐合适的植树地点
Planting trees at the right places: Recommending suitable sites for growing trees using algorithm fusion
摘要：
大规模植树已被提议作为减少碳排放的低成本自然解决方案，但由于植树地点选择不当而受到阻碍，特别是在发展中国家。为了帮助选址，我们开发了ePSA（电子种植园网站助理）推荐系统的基础上，结合基于物理学的/传统的林业科学知识与机器学习的算法融合。ePSA通过识别森林区域内的空白斑块并根据树木生长潜力对每个斑块进行排名来帮助森林管理人员。实验，用户研究和部署结果的特点效用的推荐系统在塑造长期成功的树木种植园作为自然气候解决方案，在印度北部及以后的碳减排。
英文摘要：
Large-scale planting of trees has been proposed as a low-cost natural solution for carbon mitigation, but is hampered by poor selection of plantation sites, especially in developing countries. To aid in site selection, we develop the ePSA (e-Plantation Site Assistant) recommendation system based on algorithm fusion that combines physics-based/traditional forestry science knowledge with machine learning. ePSA assists forest range officers by identifying blank patches inside forest areas and ranking each such patch based on their tree growth potential. Experiments, user studies, and deployment results characterize the utility of the recommender system in shaping the long-term success of tree plantations as a nature climate solution for carbon mitigation in northern India and beyond.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
