Estimation of soil pH at Mount Beigu Wetland based on visible and near infrared reflectance spectroscopy

Yongguang Hu; Pingping Li; Hanping Mao; Bin Chen; Xi Wang

doi:10.1117/12.697779

22 December 2006 Estimation of soil pH at Mount Beigu Wetland based on visible and near infrared reflectance spectroscopy

Yongguang Hu, Pingping Li, Hanping Mao, Bin Chen, Xi Wang

Author Affiliations +

Proceedings Volume 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications; 640515 (2006) https://doi.org/10.1117/12.697779
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India

Abstract

pH of the wetland soil is one of the most important indicators for aquatic vegetation and water bodies. Mount Beigu Wetland, just near the Yangtse River, is under ecological recovery. Visible and near infrared reflectance spectroscopy was adopted to estimate soil pH of the wetland. The spectroradiometer, FieldSpec 3 (ASD) with a full spectral range (350-2500 nm), was used to acquire the reflectance spectra of wetland soil, and soil pH was measured with the pH meter of IQ150 (Spectrum) and InPro 3030 (Mettler Toledo). 146 soil samples were taken with soil sampler (Eijkelkamp) according to different position and depth, which covered the wider range of pH value from 7.1 to 8.39. 133 samples were used to establish the calibration model with the method of partial least square regression and principal component analysis regression. 13 soil samples were used to validate the model. The results show that the model is not good, but the mean error and root mean standard error of prediction are less (1.846% and 0.186 respectively). Spectral reflectancebased estimation of soil pH of the wetland is applicable and the calibration model needs to be improved.

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Yongguang Hu, Pingping Li, Hanping Mao, Bin Chen, and Xi Wang "Estimation of soil pH at Mount Beigu Wetland based on visible and near infrared reflectance spectroscopy", Proc. SPIE 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, 640515 (22 December 2006); https://doi.org/10.1117/12.697779

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KEYWORDS

Soil science

Calibration

Statistical modeling

Error analysis

Visible radiation

Near infrared

Reflectivity

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