Title:

Can Broad-Band Remote Sensing Provide Regional Estimates of Foliar Nitrogen and Photosynthetic Capacity?

Foliar nitrogen (N) and photosynthetic capacity (Amax) are two important and tightly coupled variables in forested ecosystems. The strong relationship between foliar N and Amax—at both leaf and canopy scale—reflects an overall coupling between terrestrial carbon and nitrogen cycling. The ability to use remote sensing to estimate these variables over broad spatial scales would open new doors for terrestrial ecosystem modelling efforts, as N is often a key model input parameter. Empirical estimation of foliar N concentrations across a range of biomes and ecosystem types using airborne imaging spectroscopy has been well demonstrated, though nearly all this work has been constrained to localized scales. Multiple studies have shown that common regression analyses used to predict foliar N are largely driven by reflectance over broad portions of the near infrared (NIR) region. Lepine et al. (2016) demonstrated that the relationship between NIR and foliar N could likely be exploited by broad-band sensors to produce continuous estimates of foliar N in closed-canopy forests at relatively high spatial resolution (e.g., 30m, Landsat-8 OLI). Here, we examine the potential to make regional estimates of foliar N and Amax derived from Landsat-8, using the northeastern United States as a test case. We calibrate and validate our foliar N predictive model using field-measured whole canopy N estimates from 250 forested plots spanning a wide range of canopy N (0.71 – 2.67 g N 100 g foliage-1) and forest functional type. We then estimate Amax from our regional N predictions based on a relationship between foliar N and Amax derived from measurements made on over 600 individual leaf samples for common species in the northeastern US. Our results are presented with respect to sources of error and plans for future work.

Name

Comment*

Comments are viewable only by submitter

Captcha*