Assessment of Carbon Sequestration Capacity of in Ruyang County and Its Ecological Suitability Zoning Based on Satellite Images of GF-6.

Oliver. () is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of is important for understanding the carbon sequestration capacity and ecological suitability zoning of . In previous tree mapping studies, no studies on the spectral characteristics of and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify was selected by calculating the separability of from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the planting areas in Ruyang County. Thirdly, the annual NPP values of were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of , making its overall accuracy reach 96.62%; the high NPP value of was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM·a. The ecological suitability zone of can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of , highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of .