Integrated Multiscale Method for Obtaining Accurate Forest Surface Area Statistics over Large Areas

Abstract

Forest surface area is a fundamental input for forest-related research, such as carbon balance, biodiversity conservation, and ecosystem functioning and services. However, an accurate assessment of the area of forestland in China is not available because the forested area is usually calculated as a 2D projected area rather than a 3D surface area, and the impact of changes in the surface terrain on the area is ignored. In this study, we propose an integrated multiscale method that combines geomorphic regionalization and surface area algorithms to calculate the forest surface area in China. The results show that (1) China’s forested area is approximately 4.91% larger than the conventional estimates and corresponds to a carbon storage estimate that is approximately 383.72 million tons higher; (2) the integrated multiscale method exhibits good adaptability and high precision for large-scale surface area calculations; and (3) the calculation results of this method are superior to those of remote sensing data or single surface area algorithms, and the calculation efficiency is high.

Keywords

• integrated multiscale
• forestland
• geomorphic regionalization
• surface area algorithm