Remote sensing of forest productivity in Northeastern forests

Background/Question/Methods

Remote sensing can provide a relatively low-cost and low-impact approach to large scale assessment of forest condition and productivity. However, the connection between canopy spectral signatures and scalable field productivity metrics is not well understood. To explore this relationship, we compared annual basal area increment (BAI) at 51 sites throughout northern Vermont and New Hampshire to a suite of vegetation indices derived from annual growing season Landsat 5 TM imagery, over the period 1984-2009.

Results/Conclusions

From 47 spectral bands and known indices, a hyperspectral-derived chlorophyll fluorescence index showed the strongest overall correlation with plot-level annual BAI (ρ = 0.2658, p<0.0001). This was a stronger relationship than the normalized difference vegetation index (NDVI) traditionally used for productivity estimates (ρ = 0.11, p= 0.002). The strength of this relationship varies from year to year (ρ from 0.75 to 0.02), with most of the error in higher than normal BAI years. Comparing the lagged BAI measurements (e.g., previous or subsequent BAI yearly growth) to yearly indices did not improve the strength or significance of the relationship.

While a significant stepwise multiple linear regression model was created to predict BAI growth using a combination of 3 indices (r² = 0.11, p< 0.0001), average residuals were high (mean standard error = 39.8). This indicates that while identifying relative changes in productivity is possible, using remote sensing techniques for accurate carbon accounting may be limited. The relationship between BAI, canopy characteristics and remotely-sensed metrics at the plot level is likely nuanced, and complicated by heterogeneous species composition, variability in tree response to abiotic stressors, and the inability of single data imagery to characterize the quality of an entire growing season. While many have utilized remote sensing to quantify landscape scale productivity, the resulting coverages should be viewed conservatively.