Monitoring System of Carbon Neutralization Forestland in Plateau based on Edge Computing

Abstract

The traditional carbon monitoring system uses eddy covariance, remote sensing and geographic information system combined with artificial ground survey, which is difficult to achieve long-term, large-scale forest carbon measurement, and has uncertainty. Through statistics of carbon emission and absorption data, we design algorithms on edge computing nodes with intelligent analysis, real-time collection of forest resources, the type of ground vegetation, soil nutrients, carbon dioxide and meteorological data, the establishment of mountain forest carbon dioxide fuzzy measurement monitoring model, to estimate forest absorption. This project aims to improve the measurement accuracy of carbon neutralization in high mountain forest land, further densify the data acquisition from grid sample plots of forest, increase the number of sample plots, and reveal the spatiotemporal evolution law through the implementation of scientific and effective comprehensive real-time monitoring of carbon dioxide absorption of forest resources, so as to provide theoretical and technical support for the study of regional carbon peak estimation.