Analysis of Human-Land Coupled Bearing Capacity of Qiangtang Meadow in Northern Tibet Based on Fuzzy Clustering Algorithm

Aiming to address the problems of high energy consumption, low efficiency, low correlation between the analyzed and actual results, and poor rationality of research indexes in current methods of analysis of human-land coupled bearing capacity of meadows, a novel method of human-land coupled bearing capacity analysis of Qiangtang meadow in northern Tibet, based on fuzzy clustering algorithm, is proposed. Basic geographic information data in Tibet were acquired, the collected data images were registered by ENVI4.2 software, and the collected data were vectorized by ArcGIS 9.3 software to construct a basic geographic information database in Tibet. Based on the frequency domain processing algorithm, the geographic information image was suppressed by noise and filtered by using a high-pass filter to realize the geographic information data processing in the study area. The human-land coupled bearing capacity analysis of Qiangtang meadow in northern Tibet was evaluated through fuzzy clustering, bearing capacity evaluation, and bearing capacity calculation under the sharing of closure. The experimental results showed that the average running energy consumption of the method was 81 J, and 97% of the analyzed results were consistent with the actual situation. These results indicate that the operation efficiency of the method is high, and the rationality coefficient of the research index is large. The proposed method has superior performance and feasibility.