Three economic plants from the loess gully areas in China to explore the changing vertical distribution characteristics of soil organic carbon.The results showed that:(1) with the increase of depth,the average SOC con...Three economic plants from the loess gully areas in China to explore the changing vertical distribution characteristics of soil organic carbon.The results showed that:(1) with the increase of depth,the average SOC content of economic plants decreased from 13.98 to 1.39 g/kg on the 0-100 cm soil profile,in the form of a power function;(2) the constructed depth spatial distribution models for different plants could help accurately assess the spatial distribution pattern of soil organic carbon;(3) compared with traditional agricultural planting,the carbon sink function for walnut and grape at a soil depth of 100 cm increased by 92.8±8.98 t/hm^(2) and 45.7±7.7 t/hm^(2),respectively.The adjustment of agricultural planting structure increases the content of soil organic carbon,and economic plants are of great significance to enhance the carbon sink function of the agricultural ecosystem in the loess gully area.展开更多
Dae to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in die remote sensing investigation of the sloping field. Taking the loess hil...Dae to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in die remote sensing investigation of the sloping field. Taking the loess hill and gully area of northern Shaanxi Province as a test area, a research was conducted to extract sloping field and other land use categories by applying an integrated classification. Based on an integration of supervised classification aad unsupervised classification, sampling method is remarkably unproved. The results show that the classification accuracy is satisfactory by the method and is of critical significance in obtaining up-to-date information of the sloping field, which should be helpful in the state key project of converting farmland to forest and grassland on slope land in this area. This research sought to improve the application accuracy of image classification in complex terrain areas.展开更多
基金Supported by National Science Foundation of China (32271848)。
文摘Three economic plants from the loess gully areas in China to explore the changing vertical distribution characteristics of soil organic carbon.The results showed that:(1) with the increase of depth,the average SOC content of economic plants decreased from 13.98 to 1.39 g/kg on the 0-100 cm soil profile,in the form of a power function;(2) the constructed depth spatial distribution models for different plants could help accurately assess the spatial distribution pattern of soil organic carbon;(3) compared with traditional agricultural planting,the carbon sink function for walnut and grape at a soil depth of 100 cm increased by 92.8±8.98 t/hm^(2) and 45.7±7.7 t/hm^(2),respectively.The adjustment of agricultural planting structure increases the content of soil organic carbon,and economic plants are of great significance to enhance the carbon sink function of the agricultural ecosystem in the loess gully area.
基金National Nature Science Foundation of China,No.40271089High-visiting scholar fund of The Key Laboratory of LIESMARS
文摘Dae to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in die remote sensing investigation of the sloping field. Taking the loess hill and gully area of northern Shaanxi Province as a test area, a research was conducted to extract sloping field and other land use categories by applying an integrated classification. Based on an integration of supervised classification aad unsupervised classification, sampling method is remarkably unproved. The results show that the classification accuracy is satisfactory by the method and is of critical significance in obtaining up-to-date information of the sloping field, which should be helpful in the state key project of converting farmland to forest and grassland on slope land in this area. This research sought to improve the application accuracy of image classification in complex terrain areas.
