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Sensors 2018, 18(3), 830; doi:10.3390/s18030830

Detecting Sulfuric and Nitric Acid Rain Stresses on Quercus glauca through Hyperspectral Responses

Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
The Nurturing Station for the State Key Laboratory of Subtropical Silviculture, Zhejiang Agriculture and Forestry University, Hangzhou 311300, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
Author to whom correspondence should be addressed.
Received: 10 February 2018 / Revised: 6 March 2018 / Accepted: 7 March 2018 / Published: 9 March 2018
(This article belongs to the Section Remote Sensors)
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Acid rain, which has become one of the most severe global environmental issues, is detrimental to plant growth. However, effective methods for monitoring plant responses to acid rain stress are currently lacking. The hyperspectral technique provides a cost-effective and nondestructive way to diagnose acid rain stresses. Taking a widely distributed species (Quercus glauca) in Southern China as an example, this study aims to monitor the hyperspectral responses of Q. glauca to simulated sulfuric acid rain (SAR) and nitric acid rain (NAR). A total of 15 periods of leaf hyperspectral data under four pH levels of SAR and NAR were obtained during the experiment. The results showed that hyperspectral information could be used to distinguish plant responses under acid rain stress. An index (green peak area index, GPAI) was proposed to indicate acid rain stresses, based on the significantly variations in the region of 500–660 nm. Light acid rain (pH 4.5 SAR and NAR) promoted Q. glauca growth relative to the control groups (pH 5.6 SAR and NAR); moderate acid rain (pH 3.0 SAR) firstly promoted and then inhibited plant growth, while pH 3.0 NAR showed mild inhibitory effects during the experiment; and heavy acid rain (pH 2.0) significantly inhibited plant growth. Compared with NAR, SAR induced more serious damages to Q. glauca. These results could help monitor acid rain stress on plants on a regional scale using remote sensing techniques. View Full-Text
Keywords: acid rain stress; green peak area index (GPAI); damages; pH levels; leaf hyperspectral data acid rain stress; green peak area index (GPAI); damages; pH levels; leaf hyperspectral data

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, S.; Zhang, X.; Ma, Y.; Li, X.; Cheng, M.; Zhang, X.; Liu, L. Detecting Sulfuric and Nitric Acid Rain Stresses on Quercus glauca through Hyperspectral Responses. Sensors 2018, 18, 830.

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