The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared...The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.展开更多
随着航天航空遥感技术的飞速发展,立体式、多层次、多视角、全方位和全天候对地观测的时代已然到来。如何激活数据价值,更好地服务行业应用,满足快速增长的遥感应用需求,成为遥感企业面临的迫切课题。遥感图像处理软件作为遥感数据与行...随着航天航空遥感技术的飞速发展,立体式、多层次、多视角、全方位和全天候对地观测的时代已然到来。如何激活数据价值,更好地服务行业应用,满足快速增长的遥感应用需求,成为遥感企业面临的迫切课题。遥感图像处理软件作为遥感数据与行业应用的桥梁,在遥感产业化过程中发挥着不可替代的作用。本文概述了国内外遥感卫星数据和遥感软件发展历程,通过中国国产遥感图像处理软件——像素专家(pixel information expert,PIE)阐述了国产遥感软件的研制进展、典型应用和未来技术发展方向。PIE软件具有多源遥感载荷全方位支持、全谱段要素信息智能提取、多行业全业务链深度融合、海量遥感数据快速处理和自主产权程序完全可控等5大核心能力。未来将加强与大数据、云计算和人工智能等技术前沿领域的交叉融合,提升遥感数据分析处理、知识挖掘与决策支持能力,实现遥感数据的按需获取快速传输和专题信息聚焦服务。展开更多
This paper discusses a methodology to collect building inventory data by combining image processing techniques,field work or tools such as Google Street View and applying statistical inferences.Following the methodolo...This paper discusses a methodology to collect building inventory data by combining image processing techniques,field work or tools such as Google Street View and applying statistical inferences.Following the methodology outlined in Marinescu(2002),a family of Gabor filters are first constructed,which are then applied to an optical high-resolution image.The output from the processed image is segmented using Self-Organising Maps.This paper examines the relationship between the segmented areas in the image and the building type distribution within each segmented area,by deriving the distribution from field data.The relationship between the average number of buildings in these cells against the number of grid cells allocated to each segmentation cluster is also investigated.Finally,using these results,the overall building inventory distribution for the whole of the case study site of Pylos is presented.展开更多
基金supported by the National Natural Science Foundation of China[grant numbers 41421004 and 41210007]the International Innovation Team project of the Chinese Academy of Sciences entitled ‘High Resolution Numerical Simulation of Regional Environment’
文摘The data of several rainfall products, including those estimated from satellite measurements and those forecasted via numerical weather modeling, for a severe debris-flow event in Zhouqu, Northwest China, are compared and analyzed in this paper. The satellite products, including CPC MORPHing technique（CMORPH）, TMPA-RT, and PERSIANN are all near-real-time retrieved with high temporal and spatial resolutions. The numerical weather model used in this paper for precipitation forecasting is WRF. The results show that all three satellite products can basically reproduce the rainfall pattern, distribution, timing, scale, and extreme values of the event, compared with gauge data. Their temporal and spatial correlation coefficients with gauge data are as high as about 0.6, which is statistically significant at 0.01 level. The performance of the forecasted results modeled with different spatial resolutions are not as good as the satellite-estimated results, although their correlation coefficients are still statistically significant at 0.05 level. From the total rainfall and extreme value time series for the domain, it is clear that, from the grid-to-grid perspective, the passive microwave-based CMORPH and TRMM products are more accurate than the infrared-based PERSIANN, while PERSIANN performs very well from the general point of view, especially when considering the whole domain or the whole convective precipitation system. The forecasted data — especially the highest resolution model domain data — are able to represent the total or mean precipitation very well in the research domain, while for extreme values the errors are large. This study suggests that satellite-retrieved and model-forecasted rainfall data are a useful complement to gauge data, especially for areas without gauge stations and areas not covered by weather radars.
文摘随着航天航空遥感技术的飞速发展,立体式、多层次、多视角、全方位和全天候对地观测的时代已然到来。如何激活数据价值,更好地服务行业应用,满足快速增长的遥感应用需求,成为遥感企业面临的迫切课题。遥感图像处理软件作为遥感数据与行业应用的桥梁,在遥感产业化过程中发挥着不可替代的作用。本文概述了国内外遥感卫星数据和遥感软件发展历程,通过中国国产遥感图像处理软件——像素专家(pixel information expert,PIE)阐述了国产遥感软件的研制进展、典型应用和未来技术发展方向。PIE软件具有多源遥感载荷全方位支持、全谱段要素信息智能提取、多行业全业务链深度融合、海量遥感数据快速处理和自主产权程序完全可控等5大核心能力。未来将加强与大数据、云计算和人工智能等技术前沿领域的交叉融合,提升遥感数据分析处理、知识挖掘与决策支持能力,实现遥感数据的按需获取快速传输和专题信息聚焦服务。
文摘This paper discusses a methodology to collect building inventory data by combining image processing techniques,field work or tools such as Google Street View and applying statistical inferences.Following the methodology outlined in Marinescu(2002),a family of Gabor filters are first constructed,which are then applied to an optical high-resolution image.The output from the processed image is segmented using Self-Organising Maps.This paper examines the relationship between the segmented areas in the image and the building type distribution within each segmented area,by deriving the distribution from field data.The relationship between the average number of buildings in these cells against the number of grid cells allocated to each segmentation cluster is also investigated.Finally,using these results,the overall building inventory distribution for the whole of the case study site of Pylos is presented.
