The use of remote sensing to monitor nitrogen(N) in crops is important for obtaining both economic benefit and ecological value because it helps to improve the efficiency of fertilization and reduces the ecological an...The use of remote sensing to monitor nitrogen(N) in crops is important for obtaining both economic benefit and ecological value because it helps to improve the efficiency of fertilization and reduces the ecological and environmental burden.In this study,we model the total leaf N concentration(TLNC) in winter wheat constructed from hyperspectral data by considering the vertical N distribution(VND).The field hyperspectral data of winter wheat acquired during the 2013–2014 growing season were used to construct and validate the model.The results show that:(1) the vertical distribution law of LNC was distinct,presenting a quadratic polynomial tendency from the top layer to the bottom layer.(2) The effective layer for remote sensing detection varied at different growth stages.The entire canopy,the three upper layers,the three upper layers,and the top layer are the effective layers at the jointing stage,flag leaf stage,flowering stages,and filling stage,respectively.(3) The TLNC model considering the VND has high predicting accuracy and stability.For models based on the greenness index(GI),mND705(modified normalized difference 705),and normalized difference vegetation index(NDVI),the values for the determining coefficient(R2),and normalized root mean square error(nRMSE) are 0.61 and 8.84%,0.59 and 8.89%,and 0.53 and 9.37%,respectively.Therefore,the LNC model with VND provides an accurate and non-destructive method to monitor N levels in the field.展开更多
The concentration of total nitrogen (TN), total phosphorus (TP) and organic material (OM) at sixty grid division in Lake Chaohu basin around the lake was studied, in order to investigate their spatial distribution cha...The concentration of total nitrogen (TN), total phosphorus (TP) and organic material (OM) at sixty grid division in Lake Chaohu basin around the lake was studied, in order to investigate their spatial distribution characteristics. The results showed that the average concentrations of TN, TP and OM were 1027 mg/kg, 483 mg/kg, 1.95%, and their concentrations ranged from 253 mg/kg to 2273 mg/kg, 223 mg/kg to 1173 mg/kg and 0.291% to 5.48%, respectively. The high concentration areas were located at the basins of Tuogao river and Zhao river while the low concentration areas were located at basins of Pai river, Nanfei river and Dianpu river. The concentrations of TN and OM were higher in East part than in West part. The spatial distribution of TN, TP and OM concentrations of the surface soil showed inconsistent with those of the water quality of the inflow rivers and the lake and the TN and TP of lake sediment studied.展开更多
Soil carbon and nutrient contents and their importance in advancing our understanding of biogeochemical cycling in terrestrial ecosystem, has motivated ecologists to find their spatial patterns in various geographical...Soil carbon and nutrient contents and their importance in advancing our understanding of biogeochemical cycling in terrestrial ecosystem, has motivated ecologists to find their spatial patterns in various geographical area. Few studies have focused on changes in the physical and chemical properties of soils at high altitudes. Our aim was to identify the spatial distribution of soil physical and chemical properties in cold and arid climatic region. We also tried to explore relationship between soil organic carbon （SOC） and total nitrogen （TN）, total phosphorus （TP）, available nitrogen （AN）, available phosphorus （AP）, soil particle size distribution （PSD）. Samples were collected at 44 sites along a 300 km transect across the alpine grassland of northern Tibet. The study results showed that grassland type was the main factor influencing SOC, TN and TP distribution along the Gangdise Mountain-Shenzha-Shuanghu Transect. SOC, TN and TP contents were significantly higher in alpine meadow than alpine steppe ecosystems. SOC, TN, TP and AN contents in two soil layers （0-15 cm and 15-3o cm） showed no significant differences, while AP content in top soft （0-15 cm） was significantly higher than that in sub-top soil （15-30cm）. SOC content was correlated positively with TN and TP content （r = 0.901and 0.510, respectively）. No correlations were detected for clay content and fractal dimension of particle size distribution （D）. Our study results indicated the effects of vegetation on soil C, N and P seem to be more important than that of rocks itself along latitude gradient on the northern Tibetan Plateau. However, we did not found similar impacts of vegetation on soil properties in depth. Inaddition, this study also provided an interesting contribution to the global data pool on soil carbon stocks.展开更多
基金supported by the Natural Science Foundation of Beijing Academy of Agriculture and Forestry Sciences(BAAFS),China(QNJJ201834)the National Natural Science Foundation of China(41471285 and 41671411)the National Key R&D Program of China(2017YFD0201501)
文摘The use of remote sensing to monitor nitrogen(N) in crops is important for obtaining both economic benefit and ecological value because it helps to improve the efficiency of fertilization and reduces the ecological and environmental burden.In this study,we model the total leaf N concentration(TLNC) in winter wheat constructed from hyperspectral data by considering the vertical N distribution(VND).The field hyperspectral data of winter wheat acquired during the 2013–2014 growing season were used to construct and validate the model.The results show that:(1) the vertical distribution law of LNC was distinct,presenting a quadratic polynomial tendency from the top layer to the bottom layer.(2) The effective layer for remote sensing detection varied at different growth stages.The entire canopy,the three upper layers,the three upper layers,and the top layer are the effective layers at the jointing stage,flag leaf stage,flowering stages,and filling stage,respectively.(3) The TLNC model considering the VND has high predicting accuracy and stability.For models based on the greenness index(GI),mND705(modified normalized difference 705),and normalized difference vegetation index(NDVI),the values for the determining coefficient(R2),and normalized root mean square error(nRMSE) are 0.61 and 8.84%,0.59 and 8.89%,and 0.53 and 9.37%,respectively.Therefore,the LNC model with VND provides an accurate and non-destructive method to monitor N levels in the field.
文摘The concentration of total nitrogen (TN), total phosphorus (TP) and organic material (OM) at sixty grid division in Lake Chaohu basin around the lake was studied, in order to investigate their spatial distribution characteristics. The results showed that the average concentrations of TN, TP and OM were 1027 mg/kg, 483 mg/kg, 1.95%, and their concentrations ranged from 253 mg/kg to 2273 mg/kg, 223 mg/kg to 1173 mg/kg and 0.291% to 5.48%, respectively. The high concentration areas were located at the basins of Tuogao river and Zhao river while the low concentration areas were located at basins of Pai river, Nanfei river and Dianpu river. The concentrations of TN and OM were higher in East part than in West part. The spatial distribution of TN, TP and OM concentrations of the surface soil showed inconsistent with those of the water quality of the inflow rivers and the lake and the TN and TP of lake sediment studied.
基金supported by the Western Action Plan Project of the Chinese Academy of Sciences(Grant No.KZCX2-XB3-08)the Strategic Pilot Science and Technology Projects of Chinese Academy of Sciences(Grant No.XDB03030505)the One Hundred Young Persons Project of the Institute of Mountain Hazards and Environment(Grant No.SDSQB-2010-02)
文摘Soil carbon and nutrient contents and their importance in advancing our understanding of biogeochemical cycling in terrestrial ecosystem, has motivated ecologists to find their spatial patterns in various geographical area. Few studies have focused on changes in the physical and chemical properties of soils at high altitudes. Our aim was to identify the spatial distribution of soil physical and chemical properties in cold and arid climatic region. We also tried to explore relationship between soil organic carbon （SOC） and total nitrogen （TN）, total phosphorus （TP）, available nitrogen （AN）, available phosphorus （AP）, soil particle size distribution （PSD）. Samples were collected at 44 sites along a 300 km transect across the alpine grassland of northern Tibet. The study results showed that grassland type was the main factor influencing SOC, TN and TP distribution along the Gangdise Mountain-Shenzha-Shuanghu Transect. SOC, TN and TP contents were significantly higher in alpine meadow than alpine steppe ecosystems. SOC, TN, TP and AN contents in two soil layers （0-15 cm and 15-3o cm） showed no significant differences, while AP content in top soft （0-15 cm） was significantly higher than that in sub-top soil （15-30cm）. SOC content was correlated positively with TN and TP content （r = 0.901and 0.510, respectively）. No correlations were detected for clay content and fractal dimension of particle size distribution （D）. Our study results indicated the effects of vegetation on soil C, N and P seem to be more important than that of rocks itself along latitude gradient on the northern Tibetan Plateau. However, we did not found similar impacts of vegetation on soil properties in depth. Inaddition, this study also provided an interesting contribution to the global data pool on soil carbon stocks.
