Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In...Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM＋ images of 1989, 2001, and 2006, and supported by Geographic Information System （GIS） spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSl （vegetation, bare soil and shadow indices） suitable for TM/ETM＋ irrlages, constructed with FCD （forest canopy density） model principle and put forward by ITTO （International Tropical Timber Organization）, was used, and it was applied to estimate the VFC. The estimation accuracy was later prow^n to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover diigital images to deeply analyze the reason behind the variation.展开更多
In order to assess the effects of chemical properties of soil salinity on electrical conductivity of 1：5 soil/water extract （EC1：5）, the study focused on revealing the main chemical factors contributing to EC of s...In order to assess the effects of chemical properties of soil salinity on electrical conductivity of 1：5 soil/water extract （EC1：5）, the study focused on revealing the main chemical factors contributing to EC of soil extracts and their relative importance. The relationship between EC1：5 and the chemical properties of soil salinity in the delta oasis of Weigan and Kuqa rivers, China, were studied using path coefficient analysis, a path analysis method. We studied each key element affecting EC1：5 either directly or indirectly. The results obtained show that the salt content, total dissolved solids （TDS）, and the sum of the sodium ion concentration and the kalium ion concentration are the most influential factors on 1：5 soil/ water extract （EC1：5） in the 0-10 cm and the 30-50 cm soil layer. The results show that the sequence of direct path coefficients in the 0-10 cm and the 30-50 cm soil layers on soil conductivity is TDS→Na^＋ ＋ K^＋→Salt content→Ca^2＋→Cl-→the sodium dianion ratio （SDR）→pH→ SO4^2-→HCO3^-→Mg^2＋→the soluble sodium percentage （SSP） sodium absorption ratio （SAR） and TDS→Salt content→Na^＋ ＋ K^＋→Ca^2＋→SDR→Mg^2＋→HCO3^-→SSP→pH→SO4^2-→SAR→Cl^-. The salt content, chlorine ion, and SAR are the main factors affecting 1：5 soil/water extract （EC1：5） in the 10-30 centimeter soil layer. The order of direct path coefficients result is as follows： Salt content→Cl^-→SAR→SSP→TDS→Ca^2＋→Mg^2＋= SO4^2-→HCO3^-→pH→SDR→Na^- ＋ K^＋. Moreover, the effects of HCO3^-, pH were very weak. Though the direct path coefficients between EC1：5 and SAR, SO4^2- and Ca^2＋ were not high, influence of other chemical factors caused the coefficients to increase, making the summation of their direct and indirect path coefficients relatively high. The models of the different soil layers were structured separately. Evidences showed that multiple regression relations between EC1：5 and most of the primary facto展开更多
基金supported by the National Basic Research Program of China (2009CB421302)the Joint Fundsof the National Natural Science Foundation of China(U1138303)+4 种基金the National Natural Science Foundation of China(41261090,41161063)the Open Foundation of State Key Laboratory of Resources and Environment Information Systems (2010KF0003SA)Scientific Research Foundation for Doctor (BS110125)Xinjiang Natural Science Foundation for Young Scholars (2012211B04)Research Fund for Training Young Teachers (XJEDU2012S03)
文摘Vegetation fractional coverage （VFC） is an important index to describe and evaluate the ecological system. The vegetation index is widely used to monitor vegetation coverage in the field of remote sensing （RS）. In this paper, the author conducted a case study of the delta oasis of Weigan and Kuqa rivers, which is a typical saline area in the Tarim River Watershed. The current study was based on the TM/ETM＋ images of 1989, 2001, and 2006, and supported by Geographic Information System （GIS） spatial analysis, vegetation index, and dimidiate pixel model. In addition, VBSl （vegetation, bare soil and shadow indices） suitable for TM/ETM＋ irrlages, constructed with FCD （forest canopy density） model principle and put forward by ITTO （International Tropical Timber Organization）, was used, and it was applied to estimate the VFC. The estimation accuracy was later prow^n to be up to 83.52%. Further, the study analyzed and appraised the changes in vegetation patterns and revealed a pattern of spatial change in the vegetation coverage of the study area by producing the map of VFC levels in the delta oasis. Forest, grassland, and farmland were the three main land-use types with high and extremely-high coverage, and they played an important role in maintaining the vegetation. The forest area determined the changes of the coverage area, whereas the other two land types affected the directions of change. Therefore, planting trees, protecting grasslands, reclaiming farmlands, and controlling unused lands should be included in a long-term program because of their importance in keeping regional vegetation coverage. Finally, the dynamic variation of VFC in the study area was evaluated according to the quantity and spatial distribution rendered by plant cover diigital images to deeply analyze the reason behind the variation.
基金supported by the National Natural Science Foundation of China(40861020)the Natural Science Foundation of Xinjiang(200821128)+1 种基金the Key Laboratory of Oasis Ecology in Xinjiang University(XJDX0201-2008-03)the Fund of Young Teachers Scientific Research in Xinjiang University(QN070122),China
文摘In order to assess the effects of chemical properties of soil salinity on electrical conductivity of 1：5 soil/water extract （EC1：5）, the study focused on revealing the main chemical factors contributing to EC of soil extracts and their relative importance. The relationship between EC1：5 and the chemical properties of soil salinity in the delta oasis of Weigan and Kuqa rivers, China, were studied using path coefficient analysis, a path analysis method. We studied each key element affecting EC1：5 either directly or indirectly. The results obtained show that the salt content, total dissolved solids （TDS）, and the sum of the sodium ion concentration and the kalium ion concentration are the most influential factors on 1：5 soil/ water extract （EC1：5） in the 0-10 cm and the 30-50 cm soil layer. The results show that the sequence of direct path coefficients in the 0-10 cm and the 30-50 cm soil layers on soil conductivity is TDS→Na^＋ ＋ K^＋→Salt content→Ca^2＋→Cl-→the sodium dianion ratio （SDR）→pH→ SO4^2-→HCO3^-→Mg^2＋→the soluble sodium percentage （SSP） sodium absorption ratio （SAR） and TDS→Salt content→Na^＋ ＋ K^＋→Ca^2＋→SDR→Mg^2＋→HCO3^-→SSP→pH→SO4^2-→SAR→Cl^-. The salt content, chlorine ion, and SAR are the main factors affecting 1：5 soil/water extract （EC1：5） in the 10-30 centimeter soil layer. The order of direct path coefficients result is as follows： Salt content→Cl^-→SAR→SSP→TDS→Ca^2＋→Mg^2＋= SO4^2-→HCO3^-→pH→SDR→Na^- ＋ K^＋. Moreover, the effects of HCO3^-, pH were very weak. Though the direct path coefficients between EC1：5 and SAR, SO4^2- and Ca^2＋ were not high, influence of other chemical factors caused the coefficients to increase, making the summation of their direct and indirect path coefficients relatively high. The models of the different soil layers were structured separately. Evidences showed that multiple regression relations between EC1：5 and most of the primary facto
