Han J.-C.,Shaanxi Province Estate Development Corporation |
Han J.-C.,Engineering Research Center for Land Consolidation |
Han J.-C.,Key Laboratory of Degraded and Unused Land Consolidation Engineering |
Li X.-M.,Shaanxi Province Estate Development Corporation |
And 2 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2013
In the present paper, the meliorated saline-alkaline land by mixing sand in the north of Shaanxi province was chosen as the study area. The growth situation of the corn in the study area was measured, and soil samples and hyperspectral data were collected. The barrier factors for saline-alkaline land use were obtained by analysing the properties of soil samples. And the hyperspectral characteristics of the barrier factors were studied to elicit the quantitative inverse model, and the accuracy was verified. The study results indicated that the salt content in soil was the primary factor restricting the saline-alkaline land use, and capillary porosity was also the barrier factor because of its good correlation with the salt content. The precisions of quantitative inverse model of salt content and capillary porosity with hyperspectral data were good (the determinate coefficients R2 were 0.938 and 0.973). The test result with testing points showed that there were good correlations between the measured value and predicted value of salt content and capillary porosity (the slope was near to 1, and R2 was 0.8404 and 0.7965), the accuracy was good. It is of great promotion for guiding the saline-alkaline land consolidation and use that the barrier factors for saline-alkaline land use were interpreted quantitatively by hyperspectral data.
Han J.,Shaanxi Land Construction Group Co. |
Han J.,Key Laboratory of Degraded and Unused Land Consolidation Engineering |
Han J.,Engineering Research Center for Land Consolidation |
Zhang Y.,Shaanxi Land Construction Group Co. |
And 2 more authors.
Land Use Policy | Year: 2014
Based on the relationship between land policy and land engineering, we defined the concept of 'land engineering' and its contents, and demonstrated the significance of the establishment of land engineering. On the one hand, the land policy guided the development of the land engineering. On the other hand, the land engineering is an important means to improve and execute the land policy. The contents of land engineering are summarized as follows: (1) conversion of non-agricultural land into agricultural land; (2) conversion of low standard use land into a high standard use land; (3) conversion of current land into human construction use; (4) conversion of polluted and damaged land into usable land. Our study provides scientific support for the efficient utilization of land resources. © 2013 Elsevier Ltd.
Li X.-M.,Shaanxi Land Engineering Construction Group |
Li X.-M.,Key Laboratory of Degraded and Unused Land Consolidation Engineering |
Li X.-M.,Engineering Research Center for Land Consolidation |
Han J.-C.,Shaanxi Land Engineering Construction Group |
And 5 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2014
Hysperspectral inversion of soil salinity was researched in the present paper with the chosen study object of typical semiarid area in North Shaanxi Province. The studying sites were selected, the hyperspectral data were collected, and the soil samples were taken back for experiment analysis. The reflectance of soils (R), the logarithm of the reciprocal of the reflectance (Log(1/R)) and the continual removed reflectance (Rcr) were used to research the soil salinity. The correlations between the hyperspectral character and soil salinity was studied to filter the characteristics bands. Then the partial least squares regression (PLSR) was used to study the inversion model of soil salinity with Matlab program, and the precision was compared with the verifying sites. The research result showed that the root mean square error (RMSE) of the inversion with Rcr was the least (1.253<1.367<1.575), and its precision was the best; the correlation between the predicted value and the measured value was well (r2=0.761), the trend line was near y=x. In conclusion, the quantificational inversion model with the variables of Rcr establised by PLSR was well, which will improve the survey efficiency of soil salinity.