An Efficient Approach for Inverting the Soil Salinity in Keriya Oasis, Northwestern China, Based on the Optical-Radar Feature-Space Model.

Soil salinity has been a major factor affecting agricultural production in the Keriya Oasis. It has a destructive effect on soil fertility and could destroy the soil structure of local land. Therefore, the timely monitoring of salt-affected areas is crucial to prevent land degradation and sustainable soil management. In this study, a typical salinized area in the Keriya Oasis was selected as a study area. Using Landsat 8 OLI optical data and ALOS PALSAR-2 SAR data, the optical remote sensing indexes NDVI, SAVI, NDSI, SI, were combined with the optimal radar polarized target decomposition feature component (VanZyl_vol_g) on the basis of feature space theory in order to construct an optical-radar two-dimensional feature space. The optical-radar salinity detection index (ORSDI) model was constructed to inverse the distribution of soil salinity in Keriya Oasis. The prediction ability of the ORSDI model was validated by a test on 40 measured salinity values. The test results show that the ORSDI model is highly correlated with soil surface salinity. The index ORSDI3 (R2 = 0.656) shows the highest correlation, and it is followed by indexes ORSDI1 (R2 = 0.642), ORSDI4 (R2 = 0.628), and ORSDI2 (R2 = 0.631). The results demonstrated the potential of the ORSDI model in the inversion of soil salinization in arid and semi-arid areas.

[Ecology-economy harmonious development based on the ecological services value change in Yanqi Basin, Northwest China].

In this paper, we used land use/cover ecosystem service value estimation model and ecological economic coordination degree model to analyze the changes of the ecosystem service value by the land use/cover changes during 1985, 1990, 1996, 2000, 2005 and 2011 in Yanqi Basin, Xin-jiang. Then we evaluated the ecology-economy harmony and the regional differences. The results showed that during 1985-2011, there was an increasing trend in the areas of waters, wetland, sand, cultivated land and construction land in Yanqi Basin. In contrast, that of the saline-alkali land, grassland and woodland areas exhibited a decreasing trend. The ecosystem service value in Yanqi Basin during this period presented an increasing trend, among which the waters and cultivated land contributed most to the total value of ecosystem services, while the grassland and the woodland had obviously declined contribution to the total value of ecosystem services. The research showed that the development of ecological economy in the study area was at a low conflict and low coordination level. So, taking reasonable and effective use of the regional waters and soil resources is the key element to maintain the ecosystem service function and sustainable and harmonious development of economy in Yanqi Basin.

[Study on estimation of deserts soil total phosphorus content from thermal-infrared emissivity].

Soil phosphorus provides nutrient elements for plants, is one of important parameters for evaluating soil quality. The traditional method for soil total phosphorus content (STPC) measurement is not effective and time-consuming. However, remote sensing (RS) enables us to determine STPC in a fast and efficient way. Studies on the estimation of STPC in near-infrared spectroscopy have been developed by scholars, but model accuracy is still poor due to the low absorption coefficient and unclear absorption peak of soil phosphorus in near-infrared. In order to solve the deficiency which thermal-infrared emissivity estimate desert soil total phosphorus content, and could improve precision of estimation deserts soil total phosphorus. In this paper, characteristics of soil thermal-infrared emissivity are analyzed on the basis of laboratory processing and spectral measurement of deserts soil samples from the eastern Junggar Basin. Furthermore, thermal-infrared emissivity based RS models for STPC estimation are established and accuracy assessed. Results show that: when STPC is higher than 0.200 g x kg(-1), the thermal-infrared emissivity increases with the increase of STPC on the wavelength between 8.00 microm and 13 microm, and the emissivity is more sensitive to STPC on the wavelength between 9.00 and 9.6 microm; the estimate mode based on multiple stepwise regression was could not to estimate deserts soil total phosphorus content from thermal-infrared emissivity because the estimation effects of them were poor. The estimation accuracy of model based on partial least squares regression is higher than the model based on multiple stepwise regression. However, the accuracy of second-order differential estimation model based on partial least square regression is higher than based on multiple stepwise regression; The first differential of continuous remove estimation model based on partial least squares regression is the best model with R2 of correction and verification are up to 0.97 and 0.82 respectively, and RMSE of correction and verification are only 0.0106 and 0.015 7 respectively, RPD is 2.62. Research results provide optimized models for remotely sensed analysis on deserts soil total phosphorus content and could realize timeliness and effective monitoring on the space-time dynamic of deserts soil total phosphorus content for future regional ecological restoration.