Based on the prediction results of over twenty new climate models provided by Intergovernmental Panel on Climate Change(IPCC) ,the climate change trends in Yangtze-Huaihe region during 2011-2100 were analyzed under th...Based on the prediction results of over twenty new climate models provided by Intergovernmental Panel on Climate Change(IPCC) ,the climate change trends in Yangtze-Huaihe region during 2011-2100 were analyzed under the SRES A1B scenario. The results showed that annual mean temperature in Yangtze-Huaihe region would go up gradually under the background of global warming,and temperature increase rose from southeast to northwest,while annual average temperature would increase by 3.3 ℃ in the late 20th century. Meanwhile,annual average precipitation would rise persistently,and precipitation increase would go up with the increase of latitude and the lapse of time,being obviously strengthened after 2041.展开更多
Wheat scab(WS,Fusarium head blight),one of the most severe diseases of winter wheat in Yangtze-Huaihe river region,whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and a...Wheat scab(WS,Fusarium head blight),one of the most severe diseases of winter wheat in Yangtze-Huaihe river region,whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and achieve the purpose of reducing yield loss.In the present study,remote sensing monitoring on WS was conducted in 4 counties in Yangtze-Huaihe river region.Sensitive factors of WS were selected to establish the remote sensing estimation model of winter wheat scab index(WSI)based on interactions between spectral information and meteorological factors.The results showed that:1)Correlations between the daily average temperature(DAT)and daily average relative humidity(DAH)at different time scales and WSI were significant.2)There were positive linear correlations between winter wheat biomass,leaf area index(LAI),leaf chlorophyll content(LCC)and WSI.3)NDVI(normalized difference vegetation index),RVI(ratio vegetation index)and DVI(difference vegetation index)which had a good correlation with LAI,biomass and LCC,respectively,and could be used to replace them in modeling.4)The estimated values of the model were consistent with the measured values(RMSE=5.3%,estimation accuracy=90.46%).Estimation results showed that the model could efficiently estimate WS in Yangtze-Huaihe river region.展开更多
基金Supported by Research Fund Project of Nanjing University of Information Science & Technology(9922)
文摘Based on the prediction results of over twenty new climate models provided by Intergovernmental Panel on Climate Change(IPCC) ,the climate change trends in Yangtze-Huaihe region during 2011-2100 were analyzed under the SRES A1B scenario. The results showed that annual mean temperature in Yangtze-Huaihe region would go up gradually under the background of global warming,and temperature increase rose from southeast to northwest,while annual average temperature would increase by 3.3 ℃ in the late 20th century. Meanwhile,annual average precipitation would rise persistently,and precipitation increase would go up with the increase of latitude and the lapse of time,being obviously strengthened after 2041.
基金supported by the National Natural Science Foundation of China(No.41571323)Key Research&Development Plan of Jiangsu Province(BE2016730)+1 种基金Open Research Fund of Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences(No.2016LDE007)the Fund of Jiangsu Academy of Agriculture Sciences(6111647).
文摘Wheat scab(WS,Fusarium head blight),one of the most severe diseases of winter wheat in Yangtze-Huaihe river region,whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and achieve the purpose of reducing yield loss.In the present study,remote sensing monitoring on WS was conducted in 4 counties in Yangtze-Huaihe river region.Sensitive factors of WS were selected to establish the remote sensing estimation model of winter wheat scab index(WSI)based on interactions between spectral information and meteorological factors.The results showed that:1)Correlations between the daily average temperature(DAT)and daily average relative humidity(DAH)at different time scales and WSI were significant.2)There were positive linear correlations between winter wheat biomass,leaf area index(LAI),leaf chlorophyll content(LCC)and WSI.3)NDVI(normalized difference vegetation index),RVI(ratio vegetation index)and DVI(difference vegetation index)which had a good correlation with LAI,biomass and LCC,respectively,and could be used to replace them in modeling.4)The estimated values of the model were consistent with the measured values(RMSE=5.3%,estimation accuracy=90.46%).Estimation results showed that the model could efficiently estimate WS in Yangtze-Huaihe river region.
