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Using hyper-spectral indices to detect soil phosphorus concentration for various land use patterns

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Abstract

The management of nonpoint source pollution requires accurate information regarding soil phosphorus concentrations for different land use patterns. The use of remotely sensed information provides an important opportunity for such studies, and the previous studies showed that soil phosphorus shows no clear spectral response feature, while the phosphorus concentrations can be indirectly detected from the normalised difference vegetation indices (NDVI). Therefore, this study uses an optimised index in the RED and near-infrared (NIR) wavelengths to estimate total phosphorus and Olsen-P concentrations. The prediction accuracy is not entirely satisfactory with respect to a mixed land use dataset in which the determination coefficient was maintained at approximately 0.6, with particularly poor performance obtained for forest land group. However, the prediction accuracy increases markedly with the separation of samples into broad land use categories, even the R 2 was exceeded 0.8 for tea plantation group. The soil phosphorus prediction effect showed obvious variance for different land use patterns, which was related to vegetation growth conditions and critical soil properties including soil organic matter and mechanical composition.

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Acknowledgments

Financial supports were provided by The National Natural Science Foundation of China (Grant No. 41301227) and Research Fund of Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Land and Resource (2013CZEPK06) and Research Fund of State Key Laboratory of Soil and Sustainable Agriculture, Nanjing Institute of Soil Science, Chinese Academy of Science (Y412201427). Data were supported by Scientific Data Sharing Platform for Lake and Watershed, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences

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Authors and Affiliations

  1. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing, 210008, China

    Chen Lin, Ronghua Ma & Qing Zhu

  2. The Key Laboratory of the Coastal Zone Exploitation and Protection, Ministry of Land and Resource, Nanjing, 210008, China

    Chen Lin

  3. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, 210008, China

    Chen Lin

  4. School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210093, China

    Jingtao Li

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  1. Chen Lin
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  2. Ronghua Ma
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  3. Qing Zhu
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  4. Jingtao Li
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Correspondence to Chen Lin.

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Submitted to: Environmental Monitoring and Assessment

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Lin, C., Ma, R., Zhu, Q. et al. Using hyper-spectral indices to detect soil phosphorus concentration for various land use patterns. Environ Monit Assess 187, 4130 (2015). https://doi.org/10.1007/s10661-014-4130-x

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  • DOI: https://doi.org/10.1007/s10661-014-4130-x

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