苏联的步行机器人研究——赴苏访问归来一席谈

1 前言1986年中国科学院与苏联科学院签订协议,每年双方各派学者向对方访问50人周,我这次赴苏访问是我院履行此协议的第一组(另有兰州冰川冻土所的两名学者)。我们于7月2日启程,7月16日回国,在这两周内先后访问了苏联科学院机械学研究所、苏联科学院     

荷兰的控制理论和应用研究

笔者于1982年10月6日至10月20日应荷兰埃特候温技术大学艾克霍夫教授(P.Eykhoff)的邀请,访问了埃特候温、台尔夫特和却文特等三所荷兰的技术大学,以及飞利浦公司等有关工厂,与荷兰控制工程界的学者和专家进行了接触和交谈。下面就了解到的控制理论和应用研究情况,作扼要的介绍。     

荷兰女王访问苏州飞利浦

日前在中国访问的荷兰女王贝娅特丽克丝殿下及随行代表团访问了苏州飞利浦显示器厂。此次女王殿下访华行     

瑞典、丹麦自动控制理论的科学研究与教学

中国科学院应用数学代表团于1978年11月28日至12月20日访问了瑞典、丹麦两国。本文只介绍我们在两国所了解到的有关自动控制理论科学研究与高等教育的情况。     

华为承建荷兰全国WCDMA网络

2004年12月8日晚．中国政府总理温家宝和荷兰政府首相巴尔克嫩德．双双出席了荷兰移动运营商Telrort与华为公司的WCDMA3G项目合同签字仪式．共同见证了中荷在电信领域的首次合作。这是中国基于WCDMA制式设备对GSM、WCDMA发源地欧洲的突破．也是华为公司多年来致力于3G投入的回报。该合同包括目前业界领先的基于R4软交换架构的WCDMA核心网、基站系统及覆盖荷兰全国3G网络的相关工程和服务。     

瑞典、丹麦自动控制理论的科学研究与教学

中国科学院应用数学代表团于1978年11月28日至12月20日访问了瑞典、丹麦两国。本文只介绍我们在两国所了解到的有关自动控制理论科学研究与高等教育的情况。所访问的有关单位是:北瑞 Lulea 的瑞典钢厂、Uppsala 大学自动控制与系统分析系、ASEA公司、Link(?)pung 大学自动控制系、Philips 公司,Ringhals 原子核发电站、Volvo 汽     

网络连接无限——3Com总裁来华讲说“统一网络”与知识经济

7月25日至28日,3Com公司董事会主席、总裁兼首席执行官EricBenhamou先生对中国进行了为期4天的访问,这是Eric暨4年前访华后的第二次中国之旅,4天中,Eric与国务院副总理吴邦国、信息产业部官员以及国内IT界的知名学者就知识经济与网络的未来广泛交换了意见。这4天,Eric使用频率最高的两个词就是“统一网络”与“知识经济”。     

第九届世界计算机大会概况

1983年9月19日至23日,在巴黎举行了IFIP(THE INTERNATIONAL FEDERATION FOR INFORMATION PROCESSING)大会,这是一次规模较大的学术会议,共有来自48个国家的约5000人参加。我国派出了一个由23人组成的代表团出席。会后,我们还访问了法国的两个软件开发中心以及计算机辅助设计公司,参观了法国电子产品展览会。     

西德气象和海洋遥感专家来华访问

应国家海洋局第二海洋研究所(以下简称海洋二所)邀请,德意志联邦共和国柏林费里(FREIE)大学地球物理系沃宁克(G·Warnecke)教授和杰克(Christian·Zick)博士于1988年12月2日至14日来我国进行访问,先后在中科院上海技术物理所、海洋局二所及海洋气象预报中心进行讲学活动。 12月3日至8日在海洋二所期间,两位学者作了“遥感动画片技术及方法研究”、“云发展过程、海面温度场和海冰场的动态变化演示及分析”、“大气尺度及准大气尺度涡流的遥感资料的定量提取”等学术报告,     

光存储技术领域的一次盛会 ISOS’2005会议报道

2005年4月2日至6日,第七届国际光存储会议 (ISOS’2005)在广东省湛江市举行。此次会议由中国 科学院上海光学精密机械研究所主办,湛江华丽金音 影碟有限公司协办,干福熹院士任大会主席。来自荷 兰、韩国、日本、美国、德国、奥地利、新加坡等国 家以及中国海峡两岸与香港地区的专家、学者共120余 人参加了本届大会。     

SMOS与SMAP过境时段表层土壤水分的稳定性研究

SMOS和SMAP都是为获取全球土壤水分信息而设计的专题卫星,均搭载了L波段辐射计。进行二者的横向对比是构建具有一致性的全球土壤水分数据集的关键基础。虽然SMAP、SMOS名义上的过境时刻是固定的,但二者的实际过境时刻随时间和空间发生变化,它们与地面实测数据三者之间难以匹配形成时序上严格统一的样本对,从而给土壤水分反演结果的精度评定带来困难。针对这一问题,以美国大陆地区为研究区,首先对2016~2017年SMOS、SMAP土壤水分数据的时间戳进行统计,判定二者过境的交叠时段;进而利用高观测频率、大空间尺度的实测数据,研究表层土壤水分在此时段内的自然变化特征。结果显示,按照全部、无降水、有降水3种条件,在样本量分别为98.14%、99.51%和88.49%的绝大多数情况下,表层土壤水分的变化量为0.007 m3/m3、0.007 m3/m3和0.012 m3/m3, 远小于SMOS、SMAP的目标精度（0.04 m3/m3）。初步证实： ①SMOS与SMAP的土壤水分反演结果（L2数据）可进行直接比对;②过境时刻差异对验证误差的影响可不计。     

Pixel-scalesoil Moisture Monitoring Network and Its Preliminary Validation of L-band Soil Moisture Products

Soil moisture is a key variable in the process of crop growth,ground-air water heat exchange and global water cycle,which plays an important role in drought monitoring,hydrological land surface processes and climate change.Passive microwave remote sensing has become the main means of monitoring soil moisture with the sensitivity to soil moisture.In this study,the authenticity test of SMAP（Soil Moisture and Active and Passive） and SMOS（Soil Moisture and Ocean Salinity）passive microwave soil moisture products using the soil moisture sensor network monitoring data carried out against the underlying surface of farmlands in Jilin Province was carried out.The following conclusions were obtained：（1）Compared with the in situ measured data,SMOS L3(ascending and descending overpasses) and SMAP L3 passive microwave soil moisture products generally underestimated the ground data,but With the occurrence of rainfall events,there will be the phenomenon which is the value of soil moisture products is higher than the in situ data; although the unbiased root mean square error (unRMSE) of the two soil moisture products was greater than 0.07 m3/m3,the unRMSE of SMAP passive microwave soil moisture product data which was 0.078 m3/m3 was slightly lower;（2）Since the depth of induction of the L-band is lighter than the depth of detection of the sensor(5cm),and the dryness of the soil surface after rainfall causes the vertical inhomogeneity of soil moisture,which is one of the reasons why SMOS and SMAP passive microwave soil moisture products underestimate soil moisture; （3）SMOS has a higher value than the range of SMAP brightness temperature,which may be caused by radio frequency interference (RFI),which makes the error of soil moisture Retrieval and affects the validation accuracy.The comparison of bright temperature distribution of SMOS and SMAP shows that the effect of RFI on SMOS is more serious due to the influence of electromagnetic radio frequency interference (RFI),which may be the reason why the RMSE of soil moisture product of SMOS is higher than that of passive microwave soil moisture product of SMAP.     

反演策略对SMOS土壤水分反演算法的影响研究

为降低SMOS土壤水分反演算法的复杂度、提高土壤水分反演精度,对SMOS土壤水分反演策略进行调整：将多参数反演改为单参数反演以简化观测与模拟亮温的代价函数,以固定步长（0.001 m3/m3）代替不定步长从而避免复杂的矩阵运算,将围绕土壤水分先验值的少量局部搜索调整为全土壤水分区间（0~0.05 m³/m³）的密集全局搜索。利用美国USCRN 44个站点实测土壤水分分别与SMOS官方反演的土壤水分和SMOS调整算法反演的土壤水分进行对比分析。结果表明：与SMOS相比,算法调整后土壤水分的平均绝对偏差MAD、均方根误差RMSE和无偏均方根误差ubRMSE分别降低了0.012、0.018和0.020 m3/m3。     

Impact of surface heterogeneity on surface soil moisture retrievals from passive microwave data at the regional scale: The Upper Danube case

Water and energy fluxes at the interface between the land surface and atmosphere are strongly depending on the surface soil moisture content which is highly variable in space and time. The sensitivity of active and passive microwave remote sensing data to surface soil moisture content has been investigated in numerous studies. Recent satellite borne mission concepts, as e.g. the SMOS mission, are dedicated to provide global soil moisture information with a temporal frequency of 1-3 days to capture it's high temporal dynamics. Passive satellite microwave sensors have spatial resolutions in the order of tens of kilometres. The retrieved soil moisture fields from that sensors therefore represent surface information which is integrated over large areas. It has been shown that the heterogeneity within an image pixel might have considerable impact on the accuracy of soil moisture retrievals from passive microwave data.The paper investigates the impact of land surface heterogeneity on soil moisture retrievals from L-band passive microwave data at different spatial scales between 1 km and 40 km. The impact of sensor noise and quality of ancillary information is explicitly considered. A synthetic study is conducted where brightness temperature observations are generated using simulated land surface conditions. Soil moisture information is retrieved from these simulated observations using an iterative approach based on multiangular observations of brightness temperature. The soil moisture retrieval uncertainties resulting from the heterogeneity within the image pixels as well as the uncertainties in the a priori knowledge of surface temperature data and due to sensor noise, is investigated at different spatial scales. The investigations are made for a heterogeneous hydrological catchment in Southern Germany (Upper Danube) which is dedicated to serve as a calibration and validation site for the SMOS mission.     

国地球资源遥感卫星的工作状况和研制动态

In order to reduce the complexity of SMOS official soil moisture retrieval algorithm and improve the accuracy of soil moisture retrievals, a new retrieval strategy on SMOS soil moisture retrieval algorithm was developed. In the new retrieval strategy on SMOS soil moisture retrieval algorithm, the fixed step size (0.001 m3/m3) was used to replace the flexible step size obtained by the SMOS matrix operation. The multi-parameter was changed to a single-parameter in the cost function. The data from 44 USCRN sites in the United States were compared with the soil moisture retrieved from SMOS official algorithm as well as the adjustment of SMOS algorithm. The results show that compared with the SMOS official algorithm, the average absolute deviation, root mean square error,and unbiased root mean square error of the adjustment of SMOS algorithm are reduced by 0.012 m3/m3, 0.018 m3/m3,and 0.020 m3/m3,respectively.     

基于Triple-Collocation方法的微波遥感土壤水分产品不确定性分析及数据融合

微波遥感可以获取大范围的地表土壤水分信息，以及由此得到全球尺度的土壤水分产品。但由于传感器观测配置和反演方法等诸多因素的影响，使得不同的土壤水分产品在精度和可靠性方面存在差异。基于Triple-Collocation（TC）方法，在青藏高原那曲地区的0.25°×0.25°和1.0°×1.0°两个空间尺度上对AMSR2、SMAP和SMOS 3种土壤水分遥感产品进行不确定性分析，开展基于随机误差的数据融合算法研究。研究结果表明:不同遥感产品间的随机误差在空间分布上存在显著的不一致性，使得应用传统的算术平均方法进行数据融合不具有普适性。基于此不确定性，对3种产品配赋相应的权重进行融合，相比于3种土壤水分原始数据集，融合产品不仅具有更丰富的数据量，也会对数据精度有所改善。当遥感产品间的随机误差接近时，等权重和优化权重的融合结果非常接近；当遥感产品间的随机误差差异较大时，基于不确定性的数据融合方法相比等权重方法可以明显的提高融合数据的精度。     

基于Triple-Collocation方法的微波遥感土壤水分产品不确定性分析及数据融合

微波遥感可以获取大范围的地表土壤水分信息,以及由此得到全球尺度的土壤水分产品。但由于传感器观测配置和反演方法等诸多因素的影响,使得不同的土壤水分产品在精度和可靠性方面存在差异。基于Triple-Collocation（TC）方法,在青藏高原那曲地区的0.25°×0.25°和1.0°×1.0°两个空间尺度上对AMSR2、SMAP和SMOS 3种土壤水分遥感产品进行不确定性分析,开展基于随机误差的数据融合算法研究。研究结果表明:不同遥感产品间的随机误差在空间分布上存在显著的不一致性,使得应用传统的算术平均方法进行数据融合不具有普适性。基于此不确定性,对3种产品配赋相应的权重进行融合,相比于3种土壤水分原始数据集,融合产品不仅具有更丰富的数据量,也会对数据精度有所改善。当遥感产品间的随机误差接近时,等权重和优化权重的融合结果非常接近;当遥感产品间的随机误差差异较大时,基于不确定性的数据融合方法相比等权重方法可以明显的提高融合数据的精度。     

Validation of SMOS Soil Moisture Products on Different Vegetation Types in Qilian Mountain

Observation data of 34 in-situ stations located in seven main vegetation types were used to evaluate the performance of SMOS soil moisture products in Qilian Mountain,Northwest China.SMOS data were processed to correspond to the observation data,and three indices：R、Biasand RMSE were calculated at both annual and seasonal scales for each observation station.Results show that SMOS products were credible in the study area,but underestimated soil moisture in Qilian Mountain,and failed to achieve the intended accuracy target of 0.04 m3/m3.SMOS performed better in estimating vegetation emission than soil emission,leading to its better performance in areas with higher vegetation coverage.Similarly,SMOS performed better in the humid condition than the arid condition,and also better in areas with smaller soil moisture variability than those with large soil moisture variability.At seasonal scale,SMOS products fitted the observations better in the summer and autumn than the spring.     

Error Characteristics of Microwave Soil Moisture Products based on Triple Collocation and Its Spatial-temporal Pattern

Soil moisture is an important state variable connecting the land surface-atmosphere system, and its information can be efficiently acquired by the new technique of microwave remote sensing. Accurate interpretation of the microwave soil moisture products qualities and in-depth understanding of their temporal and spatial distributions are important prerequisites for their successful application in earth science through data assimilation. In this study, three microwave soil moisture products, FengYun-3C(FY-3C), Soil Moisture Active Passive (SMAP) and Advanced Scatterometer(ASCAT), were evaluated over China based on the triple collocation (TC) method. The abilities of three products to obtain temporal and spatial variations of soil moisture were illustrated by Hovm?ller diagram. The results show that: (1) SMAP generally outperforms ASCAT and FY-3C, with highest TC-based signal-to-noise ratio(SNR) under different land use types. The TC-based SNRs are 1.668dB, -0.316dB and -2.182dB for SMAP, ASCAT and FY-3C respectively; and their correlation coefficients with ground observations are 0.514, 0.501 and 0.209, respectively. (2) The accuracies of FY-3C and ASCAT in Northwest China are overall higher than those in the southern China. All three products can capture the latitudinal and longitudinal gradients of soil moisture, whereas their seasonal fluctuations are higher than those of in-situ measurements. Among three products, FY-3C shows highest spatial gradient and strongest seasonal fluctuations. (3) FY-3C product performance is more susceptible to vegetation coverage than ASCAT and SMAP, but it outperforms ASCAT in barren areas. The results of our study could provide useful insights for assimilating microwave soil moisture products into land surface models to improve hydrological prediction.