A Mapping Approach for Eucalyptus Plantations Canopy and Single Tree Using High-Resolution Satellite Images in Liuzhou, China

Accurate canopy and single-tree mapping is important to obtain information on the ecological structure and biogeophysical parameters for forests. Although some airborne radars can retrieve canopy and single-tree information within a smaller area, the optical satellite imagery-based approaches for rapidly and accurately mapping them over a large region are still limited. In this study, based on Eucalyptus canopy and single-tree texture and spectral features, we proposed a mapping approach using the combinations of image morphology, the Otsu method, and an adaptive iterative erosion algorithm (EUMAP). Then, we applied the commonly used red/green/blue bands from the high-resolution satellite images, which are freely available, to map the canopy and single tree in Eucalyptus plantations in southern China. EUMAP consists of two steps: 1) Eucalyptus canopy identification for various canopy density regions and 2) adaptive iterative erosion to separate single tree. Our study was conducted in Chengzhong and Liubei, Liuzhou, China. The accuracy evaluation was carried out in the state-owned Sanmenjiang forest farm. The results showed that the average ${F}1$ score for mapping canopy and single tree reached 88.34% and 86.40%, respectively. For the whole study area, there were 7033021 Eucalyptus trees and the average density was 819 trees per hectare. The approach adopted in this study, combining the prior knowledge about image morphology and single-tree texture features of Eucalyptus plantations, was highly efficient for satellite image processing and had excellent applicability to large-scale Eucalyptus plantation mapping. Our study highlights the necessity of prior knowledge for forest mapping using satellite images without requiring a training sample and provides a universal approach of accurate large-scale mapping for specific forest species with common red/green/blue images.