Leveraging explainable machine learning models to assess forest health: A case study in Hainan, China.

ABSTRACT: Global forest area has declined over the past few years, forest quality has declined, and ecological and environmental events have increased with climate change and human activity. In the context of ecological civilization, forest health issues have received unprecedented attention. By improving forest health, forests can better perform their ecosystem service functions and promote green development. This study was carried out in the WuZhi Shan area of Hainan Tropical Rainforest National Park. We employed a decision tree algorithm, a machine learning technique, for our modeling due to its high accuracy and interpretability. The objective weighted method using criteria of importance through intercriteria correlation (CRITIC) was used to determine forest health classes based on survey and ex

SUBMITTER: Li J 

PROVIDER: S-EPMC10518842 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature