| 光谱学与光谱分析 |
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| Hyperspectral Extraction of Soil Available Nitrogen in Nan Mountain Coal Waste Scenic Spot of Jinhuagong Mine Based on Enter-PLSR |
| LIN Li-xin1，2，3, WANG Yun-jia1，2，3*, XIONG Ji-bing1，2，3 |
1. School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
2. National Administration of Surveying, Mapping and Geo-Information (NASG) Key Laboratory of Land Environment and Disaster Monitoring, Xuzhou 221116, China
3. Jiangsu Provincial Key Lab of Resources and Environment Information Engineering, Xuzhou 221116, China |
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Abstract Soil available nitrogen content is an important index reflecting soil fertility. It provides dynamic information for land reclamation and ecological restoration if soil available nitrogen can be monitored and evaluated using hyperspectral technology. Facing the study blank of soil available nitrogen in National Mine Park and the deficiency of poor computational efficiency of partial least squares regression (PLSR) method, the present paper presents the relationship between soil spectrum and soil available nitrogen based on spectrum curves (ranging from 350 to 2 500 nm) of 30 salinized chestnut soil samples, which were collected from southern mountain coal waste scenic spot, located in Jinhuagong mine in Datong city, Shanxi Province, China (one part of Jinhuagong national mine park). Soil reflection spectrum was mathematically manipulated into first derivative and inverse-log spectral curves, then a corresponding estimation model was built and examined by PLSR and Enter-partial least squares regression (Enter-PLSR) based on characteristic absorption. The result indicated that Enter-PLSR corresponding estimation model greatly increased the computation efficiency by reducing the number of independent variables to 12 from 122 in case of a close accuracy of PLS corresponding estimation model. By using hyperspectral technology and Enter-PLSR method, the study blank of soil available nitrogen in National Mine Park was filled. At the same time, the computation efficiency problem of PLSR was resolved.
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Received: 2013-09-21
Accepted: 2013-12-20
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Corresponding Authors:
WANG Yun-jia
E-mail: wyj4139@163.com
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