| Wasteland soil organic matter hyperspectral characteristics and inversion model research in Fukang, Xinjiang |
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| DOI：10.7606/j.issn.1000-7601.2018.05.30 |
| Key Words: wasteland soil organic matter hyperspectral significant band partial least squares regression method（PLSR） |
| Author Name | Affiliation | | QIAO Juan-feng | College of Resources & Environment Science, Xinjiang University, Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi, Xinjiang 830046, China | | XIONG Hei-gang | College of Art & Science, Beijing Union University, Beijing 100083,China | | WANG Xiao-ping | College of Resources & Environment Science, Xinjiang University, Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi, Xinjiang 830046, China | | ZHENG Man-di | College of Resources & Environment Science, Xinjiang University, Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi, Xinjiang 830046, China | | LIU Jing-chao | College of Resources & Environment Science, Xinjiang University, Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi, Xinjiang 830046, China | | LI Rong-rong | College of Resources & Environment Science, Xinjiang University, Key Laboratory of Oasis Ecology(Xinjiang University)Ministry of Education, Urumqi, Xinjiang 830046, China |
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| Abstract: |
| It is difficult to determine concentration of soil nutrition and organic matter accurately and quickly for poverty of soil with less organic matter in waste land, arid region. Concentration of organic matter and field spectra of 64 soil samples from barren land in central Fukang, were analyzed. Based on the original reflectance (R), the software ENVI5.1 was used to extract the first derivative reflectance (R′), logarithmic reciprocal (lg(1/A)), the logarithm of reciprocal derivative (lg(1/A)′),to envelope (CR) and other 4 kinds of spectral reflectance. The correlation between the 5 spectral reflectance transformation form and concentration of soil organic matter was analyzed. Based on the full band (450~2 350 nm) and significant band (correlation coefficient by P=0.01 level test), prediction models of soil organic matter conenttation were regressed by partial least squares regression (PLSR) hyperspectral. The results showed that:(1)The spectral curve absorption characteristics of soil with different organic matter concentration were more significant.Concentration of soil organic matter, correlated inversely to the spectral reflectance of soil.(2)The correlation coefficient between soil reflectance and the concentration of organic matter was enhanced by mathematical transformation.(3)In the whole band of PLSR, the RPD of CR, R′ and lg(1/R) model was greater than 2, which indicated that the prediction ability was excellent. Among them, the prediction accuracy of CR was the most prominent, and the model R2 and RMSE were 0.79 and 4.12, respectively, and RPD was 2.18. In a significant band of PLSR, while RPD R′ and CR model were greater than 2, could accurately predict the concentation of organic matter. However, R2 and RPD of the CR were higher precision, full spectrum PLSR model was slightly better than significant band based and increased the amount of calculation for its use of large amount of data. At the same time, the RPD of the CR model was only 0.03 higher than which of the significant band model. Therefore, it is more concise, scientific and feasible to choose the significant band CR model as a model to estimate the content of organic matter in the uncultivated land. |
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