Modelling Forest Aboveground Biomass Based on GF-3 Dual-Polarized and WorldView-3 Data: A Case Study in Datong National Wetland Park, China

Table 3

Regression models for estimating aboveground biomass (AGB) using observed AGB as the dependent variable and vegetation indexes (VIs) and radar backscatter data as independent variables.

Data source	Model type	Variable	Best model	F-value	R^2	RMSE /ha	Relative RMSE (%)
WorldView-3	VIs model	NDVI	AGB = 2.467 × e^6.417 × NDVI	7.17	0.76	43.74	30.12
		DVI	AGB = 117.39 − 0.14 × DVI	6.87	0.37	—	31.90
		RDVI	AGB = 1.06 × e^1.04 × RDVI	7.34	0.73	45.68	32.73
		RVI	AGB = 32.7 × e^0.066 × RVI	5.74	0.43	—	34.80
GF-3	Backscatter coefficient model	HH	AGB = 10.34 × e^0.157 × HH	7.47	0.823	36.37	29.14
		HV	AGB = 11.469 × e^0.173 × HV	7.63	0.836	30.87	26.74
		HH & HV	AGB = 0.67  HV + 9.87  HH + 4.01	7.21	0.81	35.13	28.74
—	Combination model	HV & NDVI	AGB = 0.34  HV + 4.67  NDVI + 5.37	7.9	0.861	26.72	19.36

Note. Confidence is at the 0.05 level and F is the joint hypothesis test (≥7.09). Variable. Pixel value of the parameter maps. The RMSE of RVI and DVI in the VIs model is low; thus, it is not shown.