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
随着上海港海上运输业和石油产业链的日趋发达,海上溢油事故风险也随之加剧。本文就2012年发生在上海海域吴淞口和九段沙附近的2起重大溢油事故,基于美国NASA(National Aeronautics and Space Administration)中等分辨率MODIS(Moderate-...随着上海港海上运输业和石油产业链的日趋发达,海上溢油事故风险也随之加剧。本文就2012年发生在上海海域吴淞口和九段沙附近的2起重大溢油事故,基于美国NASA(National Aeronautics and Space Administration)中等分辨率MODIS(Moderate-resolution Imaging Spectroradiometer)与国产"环境一号"卫星HJ-1的多源卫星数据,对溢油信息进行对比,通过对油水敏感通道进行波段比值运算,突出油膜与背景海水的光谱反射率差异,再结合重柴油光谱特征,利用图像分割的阈值确定法,从疑似溢油区域中有效提取溢油信息,实现溢油区域定位、溢油面积和溢油量的诊断,为事发后海域应急响应工作提供基础性分析依据。展开更多
China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this pap...China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary.展开更多
Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this...Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.展开更多
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.
文摘随着上海港海上运输业和石油产业链的日趋发达,海上溢油事故风险也随之加剧。本文就2012年发生在上海海域吴淞口和九段沙附近的2起重大溢油事故,基于美国NASA(National Aeronautics and Space Administration)中等分辨率MODIS(Moderate-resolution Imaging Spectroradiometer)与国产"环境一号"卫星HJ-1的多源卫星数据,对溢油信息进行对比,通过对油水敏感通道进行波段比值运算,突出油膜与背景海水的光谱反射率差异,再结合重柴油光谱特征,利用图像分割的阈值确定法,从疑似溢油区域中有效提取溢油信息,实现溢油区域定位、溢油面积和溢油量的诊断,为事发后海域应急响应工作提供基础性分析依据。
文摘China has a vast territory with abundant crops,and how to collect crop information in China timely,objectively and accurately,is of great significance to the scientific guidance of agricultural development.In this paper,by selecting moderateresolution imaging spectroradiometer(MODIS)data as the main information source,on the basis of spectral and biological characteristics mechanism of the crop,and using the freely available advantage of hyperspectral temporal MODIS data,conduct large scale agricultural remote sensing monitoring research,develop applicable model and algorithm,which can achieve large scale remote sensing extraction and yield estimation of major crop type information,and improve the accuracy of crop quantitative remote sensing.Moreover,the present situation of global crop remote sensing monitoring based on MODIS data is analyzed.Meanwhile,the climate and environment grid agriculture information system using large-scale agricultural condition remote sensing monitoring has been attempted preliminary.
基金Under the auspices of National Key Research and Development Program(No.2016YFC0500203)National Natural Science Foundation of China(No.41571427)
文摘Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.
