Dynamic Disturbance Analysis of Grasslands Using Neural Networks and Spatiotemporal Indices Fusion on the Qinghai-Tibet Plateau - Zou, Fengli; Hu, Qingwu; Li, Haidong; Lin, Jie; Liu, Yichuan; Sun, Fulin (Frontiers in Plant Science, 2022)
Grassland is the vegetation type with the widest coverage on the Qinghai-Tibet Plateau. Under the influence of multiple factors such as global climate change and human activities, grassland is undergoing temporal and spatially different disturbances and changes, which have a significant impact on the grassland ecosystem of the Qinghai-Tibet Plateau. Therefore, timely and dynamic monitoring of grassland disturbances and distinguishing the reasons for the changes are essential for ecological understanding and management. The purpose of this research was to propose a knowledge-based strategy to realize grassland dynamic distribution mapping and analysis of grassland Disturbance changes in the region, which is suitable for the Qinghai-Tibetan Plateau. So, the purpose of this study is to propose an analysis algorithm that first Annual Mapping and then establishes Temporal Disturbance Rules (AMTDR), which is applicable to the integrated exploration of disturbance changes in highland type grasslands. The characteristic indexes of greenness index and disturbance index in growing period were constructed and integrated with deep neural network learning to dynamically map the grassland for many years. The overall accuracy of grassland mapping was 94.11%, and that of Kappa was 0.845. The results showed that the area of grassland increased by 11.18% from 2001 to 2017. Then the grassland disturbance change analysis method is proposed in the monitoring grassland distribution range, and it is found that the area of grassland with significant disturbance change accounts for 10.86% of the total area of the Qinghai-Tibet Plateau, and the types of disturbance changes are specifically divided into 7 types. Among them, the type of degradation after disturbance mainly occurs in Tibet, while the main types of vegetation greenness increase in Qinghai and Gansu. At the same time, the study found that climate change, altitude and human grazing activities are the main factors affecting grassland disturbance changes in the Qinghai-Tibetan Plateau, and there are spatial differences.