Digital mapping of coastal landscapes integrating ocean-environment relationships and machine learning

Currently, the Internet of Things (IoT) is in a premature phase. Although it is growing at a steady pace, there is still a need for further research in the field of security. In this work, the Fujian Province was selected as the study area. The climate, parent material and topographic information of the area were obtained, and the soil-landscape quantitative model was used to quantitatively obtain the relationship between the attributes of coastal sand and gravel soil. On the basis of soil type map, according to the difference of soil type elevation distribution, further predict the soil type distribution and make a map. The results show that the method can achieve more than 80% coincidence with the survey results on the scale of soil digital mapping and can make up for the missing areas of the survey.