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作 者:Huibiao PAN Xiajie QIN Ronghui HU Zeyao ZHANG Jian TANG
机构地区:[1]Guangxi State-owned Huangmian Forest Farm,Chongzuo 532200,China [2]Guangxi Zhuang Autonomous Region Forestry Research Institute/Guangxi Research and Development Center for New Forestry Fertilizer,Nanning 530002,China
出 处:《Meteorological and Environmental Research》2023年第2期61-65,共5页气象与环境研究(英文版)
基 金:Supported by Autonomous Project of the Key Laboratory for Cultivating Excellent Timber Forest Resources in Guangxi (2020-A-04-01);Special Fund of Guangxi Innovation Driven Development (GUIKE AA17204087-11)。
摘 要:Soil information is the basis of soil management and precise variable fertilization. The traditional method of obtaining soil information through chemical detection of laboratory has high cost and poor timeliness, which is difficult to meet the needs of digital forestry, soil monitoring and real-time management of nutrients. Taking red soil of Eucalyptus plantation in northern Guangxi as the research object, the spectral data of samples with different soil available potassium contents were measured, and the spectral characteristics were analyzed, and the inversion model was established by using PLS method. The results showed that the spectral sensitive bands of available potassium content in red soil of the region mainly concentrated in 400-600, 1 450, 2 200 nm and so on. After the first derivative transformation, the redundant information in the original spectral data can be significantly reduced, and the correlation between spectral indexes and soil available potassium content can be improved. The full-band modeling results of R and FDR were better than those of significant bands. The optimal model was full-band-FDR-PLS, R2=0.862, and RMSE=2.718. The results of this study can be used for the application of near-earth remote sensing in Guangxi, such as soil digital mapping, precise variable fertilization and real-time monitoring of soil available potassium.
关 键 词:Visible-near-infrared spectroscopy Near-earth remote sensing Linear model PLANTATION Soil information
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