Examination of the performance of ASEL and MPViT algorithms for classifying mangrove species of multiple natural reserves of Beibu Gulf, south China

作者：Bolin Fu, Xu He, Yiyin Liang, Tengfang Deng, Huajian Li, Hongchang He, Mingming Jia, Donglin Fan, Feng Wang · 发表于：Ecological Indicators · 年份：2023 · DOI：10.1016/j.ecolind.2023.110870 · 被引用次数：13 · 研究领域：Coastal wetland ecosystem dynamics、Identification and Quantification in Food、Remote-Sensing Image Classification

Mangrove is the highest productive ecosystems in the global coastal zone, which has high blue carbon sink function and carbon neutrality potential. Fine species classification is essential for mangrove conservation and sustainable development, and has attracted much attention in recent years using ensemble learning and multi-dimensional data. However, the current mangrove species classification based on traditional stacking ensemble learning still faces challenges due to the correlation between base classifiers, differences in meta-classifier capabilities, the subjectivity of parameter tuning, and data redundancy. To address these issues, this paper utilized unmanned aerial vehicle (UAV) multispectral images of three mangrove nature reserves in Beibu Gulf, south China, to examine the classification and generalization ability of our proposed Adaptive Stacking Ensemble Learning (ASEL) algorithm for different mangrove species. We also aim to verify the feasibility of the Multi-Path Vision Transformer for Dense Prediction (MPViT) algorithm for mangrove species mapping, and compare its performance with the ASEL algorithm for mangrove species classification. Finally, we used the SHapley Additive Explanations (SHAP) method to measure the contribution of feature variables to the model, exploring the sensitivity of different image features to mangrove species mapping. This study highlights that: (1) The two ASEL algorithms achieved high accuracy classification of mangrove species with...