Remote sensing of sagebrush canopy nitrogen

REMOTE SENSING OF ENVIRONMENT

卷:124

Article

Mitchell, Jessica J.¹  Glenn, Nancy F.¹  Sankey, Temuulen T.¹  Derryberry, DeWayne R.²  Germino, Matthew J.³ 

[1] Idaho State Univ, Boise Ctr Aerosp Lab, Dept Geosci, Boise, ID 83702 USA

[2] Idaho State Univ, Dept Math, Pocatello, ID 83209 USA

[3] US Geol Survey, Forest & Rangeland Ecosyst Sci Ctr, Boise, ID 83706 USA

关键词: nitrogen;    hyperspectral;    continuum removal;    derivative analysis;    sagebrush;   

DOI  :  10.1016/j.rse.2012.05.002

来源: Elsevier

【 摘 要 】

This paper presents a combination of techniques suitable for remotely sensing foliar Nitrogen (N) in semiarid shrublands - a capability that would significantly improve our limited understanding of vegetation functionality in dryland ecosystems. The ability to estimate foliar N distributions across arid and semi-arid environments could help answer process-driven questions related to topics such as controls on canopy photosynthesis, the influence of N on carbon cycling behavior, nutrient pulse dynamics, and post-fire recovery. Our study determined that further exploration into estimating sagebrush canopy N concentrations from an airborne platform is warranted, despite remote sensing challenges inherent to open canopy systems. Hyperspectral data transformed using standard derivative analysis were capable of quantifying sagebrush canopy N concentrations using partial least squares (PLS) regression with an R-2 value of 0.72 and an R-2 predicted value of 0.42 (n = 35). Subsetting the dataset to minimize the influence of bare ground (n = 19) increased R-2 to 0.95 (R-2 predicted = 0.56). Ground-based estimates of canopy N using leaf mass per unit area measurements (LMA) yielded consistently better model fits than ground-based estimates of canopy N using cover and height measurements. The LMA approach is likely a method that could be extended to other semiarid shrublands. Overall, the results of this study are encouraging for future landscape scale N estimates and represent an important step in addressing the confounding influence of bare ground, which we found to be a major influence on predictions of sagebrush canopy N from an airborne platform. (c) 2012 Elsevier Inc. All rights reserved.

【 授权许可】

Free