Hyperspectral Analysis of Soil Nitrogen, Carbon, Carbonate, and Organic Matter Using Regression Trees

Sensors

Stephan Gmur¹  Daniel Vogt²  Darlene Zabowski² 

[1] School of Environmental and Forest Sciences, College of the Environment, University of Washington, Seattle, WA 98195, USA;

关键词: soil horizons;    Washington;    Oregon;    ASD;   

DOI  :  10.3390/s120810639

来源: mdpi

【 摘 要 】

The characterization of soil attributes using hyperspectral sensors has revealed patterns in soil spectra that are known to respond to mineral composition, organic matter, soil moisture and particle size distribution. Soil samples from different soil horizons of replicated soil series from sites located within Washington and Oregon were analyzed with the FieldSpec Spectroradiometer to measure their spectral signatures across the electromagnetic range of 400 to 1,000 nm. Similarity rankings of individual soil samples reveal differences between replicate series as well as samples within the same replicate series. Using classification and regression tree statistical methods, regression trees were fitted to each spectral response using concentrations of nitrogen, carbon, carbonate and organic matter as the response variables. Statistics resulting from fitted trees were: nitrogen R² 0.91 (p < 0.01) at 403, 470, 687, and 846 nm spectral band widths, carbonate R² 0.95 (p < 0.01) at 531 and 898 nm band widths, total carbon R² 0.93 (p < 0.01) at 400, 409, 441 and 907 nm band widths, and organic matter R² 0.98 (p < 0.01) at 300, 400, 441, 832 and 907 nm band widths. Use of the 400 to 1,000 nm electromagnetic range utilizing regression trees provided a powerful, rapid and inexpensive method for assessing nitrogen, carbon, carbonate and organic matter for upper soil horizons in a nondestructive method.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.