Evaluation Of Counties Geological Environment Carrying Capacity Based On Nuclear K-Means And GIS

"Thirteen Five" Plan proposed to improve the overall quality of the ecological environment. The production and lifestyle are becoming green with carbon levels decreasing. The development and utilization of energy resources increase dramatically; the consumption of energy and water, land for construction and carbon emissions have been effectively controlled while the emissions of major pollutants significantly reduce. The layout of the main functional areas and ecological security barrier has formed basically. However, due to the continuous strengthening of human activity, the scale and intensity of geological environment development, utilization and transformation are becoming bigger while the speed are becoming faster, resulting that problems of geological environment such as destruction of the ecological, geological disasters, environmental pollution and other issues are also increasingly prominent. Therefore, the study of geological countryenvironment carrying capacity has a certain significance on the urbanization and economic development of an area.People often use the analytic hierarchy process, fuzzy comprehensive evaluation method, network data envelopment analysis, gray comprehensive evaluation, GIS technology, set of analysis algorithms and so on to study the evaluation of geological country environmental carrying capacity, but few people use Nuclear K-means clustering algorithm. Based on the analysis of the connotations and factors of geological country environmental carrying capacity, the article does research on per capita density, GDP density, zoning and natural terrain features of Pengshan. Then establish the evaluation index system with setting Pengshan City natural topography unit as the basic unit of analysis and use Nuclear K-means clustering algorithm to analyze and evaluate the geological country environment carrying capacity.The main idea of Nuclear K-means clustering algorithm is: first,cluster the original sample space through a nonlinear mapping into a high-dimensional kernel space and highlight the differences of characteristic between the various types of samples. Then do K-means clustering analysis in the nuclear space. In order to verify the effectiveness of the algorithm, do K-means clustering and Nuclear K-means clustering on the index data of geological disaster vulnerability and risk of geological disasters respectively. The result shows that Nuclear K-means clustering analysis has better clustering effect on data than K-means clustering.Finally,using GIS technologydoesextraction.Analysisand processing on evaluation index layer, and finally help to get geological maps of Pengshan environmental carrying capacity which has a better effect.