To evaluate the current state of the environmental quality of agricultural soils in Taiyuan City, a hotspot for China's industrial development, the concentrations of 8 heavy metals in soils were investigated by me...To evaluate the current state of the environmental quality of agricultural soils in Taiyuan City, a hotspot for China's industrial development, the concentrations of 8 heavy metals in soils were investigated by means of extensive sampling in farmlands, forestlands,and grasslands in the city. Statistical analyses and spatial distribution maps were used to identify the most significant heavy metal pollutants. The mean concentrations of As, Cd, Cu, Hg, Pb, Zn, Ni, and Cr were slightly higher than their background values in Taiyuan's topsoil, but were lower than the maximum permissible concentrations in the Chinese Environmental Quality Standard for agricultural soils. Farmland soils in Taiyuan had the highest average Cd, Cu, Hg, Pb, Zn, and Cr concentrations, but the As and Ni concentrations did not differ significantly among the farmland, forestland, and grasslands. Soil contamination by Cd, Cu, Hg, Pb,Zn, and Cr was mainly derived from farming practices, especially the use of sewage water for irrigation. In contrast, As and Ni might derive mainly from the soil parent material. The identification of heavy metal sources in agricultural soils may provide a basis for taking appropriate action to protect soil quality.展开更多
The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identify...The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.展开更多
叶面积指数是表征作物光合作用能力大小的重要参数。本文利用无人机数码相机获取9个棉花品种全生育期冠层数字图像,基于归一化绿-红差值指数Normalized green-red difference index,NGRDI、可见光大气阻抗植被指数(Visible atmospherica...叶面积指数是表征作物光合作用能力大小的重要参数。本文利用无人机数码相机获取9个棉花品种全生育期冠层数字图像,基于归一化绿-红差值指数Normalized green-red difference index,NGRDI、可见光大气阻抗植被指数(Visible atmospherically resistant index,VARI)、过绿指数(Excess green index,ExG)、过绿减过红植被指数(Excess green minus excess red index,ExGR)和绿叶植被指数(Green leaf index,GLI)5种常用的可见光颜色指数,通过多阈值分割,提取小区中心部位植被覆盖指数,研究不同植被覆盖指数反映棉花叶面积指数的差异。通过设置相机不同曝光时间筛选出在自动曝光下表现较稳定的基于颜色指数的植被覆盖指数GLI、NGRDI与ExG。然后研究了棉花叶面积指数以及基于GLI、NGRDI与ExG的植被覆盖指数变化规律,以及两者的相关性。结果表明:叶面积指数随播种后时间的增加先增大后减小,花铃期叶面积指数达到峰值;基于ExG、GLI、NGRDI的3种植被覆盖指数在生育期内都呈现开口向下的二次曲线;叶面积指数与基于NGRDI、ExG的植被覆盖指数呈显著线性相关,尤其是在吐絮期前,决定系数(R^2)分别为0.913、0.912,基于NGRDI的估测效果显著好于ExG。利用基于NGRDI的植被覆盖指数预测试验田叶面积指数并形成分布图。因此,利用无人机搭载普通数码相机获取棉田叶面积指数是可行的,该方法可为指导生产管理提供参考。展开更多
基金supported by the Science & Technology Pillar Program of Shanxi Province, China (No. 20121101011)the National Natural Science Foundation of China (Nos. 41271513 and 41101013)
文摘To evaluate the current state of the environmental quality of agricultural soils in Taiyuan City, a hotspot for China's industrial development, the concentrations of 8 heavy metals in soils were investigated by means of extensive sampling in farmlands, forestlands,and grasslands in the city. Statistical analyses and spatial distribution maps were used to identify the most significant heavy metal pollutants. The mean concentrations of As, Cd, Cu, Hg, Pb, Zn, Ni, and Cr were slightly higher than their background values in Taiyuan's topsoil, but were lower than the maximum permissible concentrations in the Chinese Environmental Quality Standard for agricultural soils. Farmland soils in Taiyuan had the highest average Cd, Cu, Hg, Pb, Zn, and Cr concentrations, but the As and Ni concentrations did not differ significantly among the farmland, forestland, and grasslands. Soil contamination by Cd, Cu, Hg, Pb,Zn, and Cr was mainly derived from farming practices, especially the use of sewage water for irrigation. In contrast, As and Ni might derive mainly from the soil parent material. The identification of heavy metal sources in agricultural soils may provide a basis for taking appropriate action to protect soil quality.
基金supported by the National High-Tech Research and Development Program (863) of China(No.2006AA120101)the National Natural Science Foundation of China(No.40871158/D0106)the Key Technologies Research and Development Program of China(No.2006BAD10A01)
文摘The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer(MODIS) data in China.Paddy rice fields were extracted by identifying the unique char-acteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization.The characteristic could be reflected by the enhanced vegetation index(EVI) and the land surface water index(LSWI) derived from MODIS sensor data.Algorithms for single,early,and late rice identification were obtained from selected typical test sites.The algorithms could not only separate early rice and late rice planted in the same fields,but also reduce the uncertainties.The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics,and the spatial matching was examined by ETM+(enhanced thematic mapper plus) images in a test region.Major factors that might cause errors,such as the coarse spatial resolution and noises in the MODIS data,were discussed.Although not suitable for monitoring the inter-annual variations due to some inevitable factors,the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale,and they might provide reference for further studies.
文摘叶面积指数是表征作物光合作用能力大小的重要参数。本文利用无人机数码相机获取9个棉花品种全生育期冠层数字图像,基于归一化绿-红差值指数Normalized green-red difference index,NGRDI、可见光大气阻抗植被指数(Visible atmospherically resistant index,VARI)、过绿指数(Excess green index,ExG)、过绿减过红植被指数(Excess green minus excess red index,ExGR)和绿叶植被指数(Green leaf index,GLI)5种常用的可见光颜色指数,通过多阈值分割,提取小区中心部位植被覆盖指数,研究不同植被覆盖指数反映棉花叶面积指数的差异。通过设置相机不同曝光时间筛选出在自动曝光下表现较稳定的基于颜色指数的植被覆盖指数GLI、NGRDI与ExG。然后研究了棉花叶面积指数以及基于GLI、NGRDI与ExG的植被覆盖指数变化规律,以及两者的相关性。结果表明:叶面积指数随播种后时间的增加先增大后减小,花铃期叶面积指数达到峰值;基于ExG、GLI、NGRDI的3种植被覆盖指数在生育期内都呈现开口向下的二次曲线;叶面积指数与基于NGRDI、ExG的植被覆盖指数呈显著线性相关,尤其是在吐絮期前,决定系数(R^2)分别为0.913、0.912,基于NGRDI的估测效果显著好于ExG。利用基于NGRDI的植被覆盖指数预测试验田叶面积指数并形成分布图。因此,利用无人机搭载普通数码相机获取棉田叶面积指数是可行的,该方法可为指导生产管理提供参考。
