Agricultural Environmental Monitoring Data Classification of Fanjing Mountains: A Decision Tree Approach

Abstract

Fanjing Mountains is rich in wildlife resources (such as Guizhou golden monkey, dove tree, and other rare species) and tea resources (for example, Fanjing Mountains cui feng tea, Shiqian moss tea, Vatican black tea, Jin Qiangong black tea, Eight hour black tea, vine tea and other dozens of products), where is completely unable to find traces of artificial scenery, and its main peak “mushroom stone” is a landscape. So it has great important scientific and ecological value in researching the classification of agriculture environment data in Fanjing Mountains, so as to develop various sensors about new crops of growth environment factors (e.g. soil temperature, soil moisture content, air temperature, air humidity, light intensity and carbon dioxide (CO2) concentration), as well as the biometric information of individual animals (e.g. body temperature, pulse, location information), realize the intellectualization of agriculture, establish administrative policy with the pilot of scientific research, the basis of management and protection, and the guarantee of coordination, better promote the green development of agriculture, and assure the security of resource and ecology. This article analyzes the agricultural environment monitoring data adopting the classification method of decision tree in machine learning.