Evaluating the Marginal Contribution of Remote Sensing for Forest Biomass Estimation When Inventory Data Exists

Mon, 14 Sep 2026 00:00:00 +0000

Figure 1. Workflow of the study. SA = stand age, CC = canopy cover, T = temperature, P = precipitation, ELE = elevation, SDE = soil depth, SVR = Support Vector Regression, RF = Random Forest, MLP = Multi-Layer Perceptron.

Yufeng Chi | Shaoqing Dai

Evaluating the Marginal Contribution of Remote Sensing for Forest Biomass Estimation When Inventory Data Exists