Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquak...Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.展开更多
Analyzing the aftershock sequence of the 2008 Wenchuan earthquake,we considered 26 micro-earthquakes "just underneath" seismic stations.Making use of such special station-event configurations to determine th...Analyzing the aftershock sequence of the 2008 Wenchuan earthquake,we considered 26 micro-earthquakes "just underneath" seismic stations.Making use of such special station-event configurations to determine the depth of these micro-earthquakes provided accurate relocation of aftershocks with a reference set of "ground truth(GT)events".展开更多
Generating ground truth data for developing object detection algorithms of intelligent surveillance systems is a considerably important yet time-consuming task; therefore, a user-friendly tool to annotate videos effic...Generating ground truth data for developing object detection algorithms of intelligent surveillance systems is a considerably important yet time-consuming task; therefore, a user-friendly tool to annotate videos efficiently and accurately is required. In this paper, the development of a semi-automatic video annotation tool is described. For efficiency, the developed tool can automatically generate the initial annotation data for the input videos utilizing automatic object detection modules, which are developed independently and registered in the tool. To guarantee the accuracy of the ground truth data, the system also has several user-friendly functions to help users check and edit the initial annotation data generated by the automatic object detection modules. According to the experiment＇s results, employing the developed annotation tool is considerably beneficial for reducing annotation time; when compared to manual annotation schemes, using the tool resulted in an annotation time reduction of up to 2.3 times.展开更多
Soil moisture(SM)content is one of the most important environmental variables in relation to land surface climatology,hydrology,and ecology.Long-term SM data-sets on a regional scale provide reasonable information abo...Soil moisture(SM)content is one of the most important environmental variables in relation to land surface climatology,hydrology,and ecology.Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions.The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data.The study area is Tuv(48°40′30″N and 106°15′55″E)province in the forest steppe zones in Mongolia.In addition to this,land surface temperature(LST)and normalized difference vegetation index(NDVI)from Landsat satellite images were integrated for the assessment.Furthermore,we used a digital elevation model(DEM)from ASTER satellite image with 30-m resolution.Aspect and slope maps were derived from this DEM.The soil moisture index(SMI)was obtained using spectral information from Landsat satellite data.We used regression analysis to develop the model.The model shows how SMI from satellite depends on LST,NDVI,DEM,Slope,and Aspect in the agricultural area.The results of the model were correlated with the ground SM data in Tuv province.The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area.Further research is focused on moisture mapping for different natural zones in Mongolia.The innovative part of this research is to estimate SM using drivers which are vegetation,land surface temperature,elevation,aspect,and slope in the forested steppe area.This integrative methodology can be applied for different regions with forest and desert steppe zones.展开更多
It is common knowledge that continental retrieval especially for Qinghai-Xizang Plateau has not been solved todate. In order to explore applicable inverse model and method for continent including the plateau, in this ...It is common knowledge that continental retrieval especially for Qinghai-Xizang Plateau has not been solved todate. In order to explore applicable inverse model and method for continent including the plateau, in this study authors use an improved simultaneous physical retrieval method hereafter referred to as the ISPRM, for computing meteorological parameters from NOAA-10 satellite TOVS data. The retrieval results verified by nearby radiosondesshow that the ISPRM is more applicable for the continental plateau.展开更多
Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this problem.TL system captures all user socke...Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this problem.TL system captures all user socket calls and their corresponding application process information in the user mode on a Windows host.Once a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel mode.Then the intermediate driver writes application type information on TOS field of the IP packets which match the 5-tuple.In this way,each IP packet sent from the Windows host carries their application information.Therefore,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models.展开更多
With the rocketing progress of the Internet, it is easier for people to get information about the objects that they are interested in. However, this information usually has conflicts. In order to resolve conflicts and...With the rocketing progress of the Internet, it is easier for people to get information about the objects that they are interested in. However, this information usually has conflicts. In order to resolve conflicts and get the true information, truth discovery has been proposed and received widespread attention. Many algorithms have been proposed to adapt to different scenarios. This paper aims to investigate these algorithms and summarize them from the perspective of algorithm models and specific concepts. Some classic datasets and evaluation metrics are given in this paper. Some future directions for readers are also provided to better understand the field of truth discovery.展开更多
The power generation of bifacial photovoltaic modules is greatly related to the diffuse solar radiation component received by the rear side,but radiation component data are scarce in China,where bifacial solar market ...The power generation of bifacial photovoltaic modules is greatly related to the diffuse solar radiation component received by the rear side,but radiation component data are scarce in China,where bifacial solar market is large.Radiation components can be estimated from satellite data,but sufficient ground truth data are needed for calibrating empirical methods or training machine learning methods.In this work,a data-augmented machine learning method was proposed to estimate radiation components.Instead of using observed ground truth,far more abundant radiation component data derived from sunshine duration measured at 2,453 routine weather stations in China were used to augment samples for training a machine-learning-based model.The inputs of the model include solar radiation(either from ground observation or satellite remote sensing)and surface meteorological data.Independent validation of the model at Chinese stations and globally distributed stations demonstrates its effectiveness and generality.Using a state-of-the-art satellite product of solar radiation as input,the model is applied to construct a satellite-based radiation component dataset over China.The new dataset not only outperforms mainstream radiation component datasets,but also has significantly higher accuracy than satellite-based datasets derived from other machine learning methods trained with limited observations,indicating the superiority of our data-augmented method.In principle,this model can be applied on the global scale without additional training with local data.展开更多
In order to improve the interpretation of the earth system microwave remote sensing, the research of microwave spectrum characteristics of the ground truth (earth objects) was carried out in laboratory. A laboratory f...In order to improve the interpretation of the earth system microwave remote sensing, the research of microwave spectrum characteristics of the ground truth (earth objects) was carried out in laboratory. A laboratory for microwave remote sensing of the earth objects has been constructed to improve the remote sensing level, the laboratory consists of four parts: the measuring system of dielectric constants, the microwave emissivity meter, the microwave reflectometer and the microwave remote sensing simulation experiment in field. In this paper, the principle of measurement, the correction of near field process, the structure of instrument, the calibration method and the measurement of the earth substances, including soil, water and oil, are discussed. The labora- tory may supply the condition for measuring the parameters of thc earth substance remote sensing and help to interpret the remote sensing data.展开更多
基金supported by Chinese Acadmy of Sciences Fund(No.KCZX-YW-116-1)Joint Seismological Science Fundation of China (Nos.20080878 and 200708035)
文摘Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.
文摘Analyzing the aftershock sequence of the 2008 Wenchuan earthquake,we considered 26 micro-earthquakes "just underneath" seismic stations.Making use of such special station-event configurations to determine the depth of these micro-earthquakes provided accurate relocation of aftershocks with a reference set of "ground truth(GT)events".
文摘Generating ground truth data for developing object detection algorithms of intelligent surveillance systems is a considerably important yet time-consuming task; therefore, a user-friendly tool to annotate videos efficiently and accurately is required. In this paper, the development of a semi-automatic video annotation tool is described. For efficiency, the developed tool can automatically generate the initial annotation data for the input videos utilizing automatic object detection modules, which are developed independently and registered in the tool. To guarantee the accuracy of the ground truth data, the system also has several user-friendly functions to help users check and edit the initial annotation data generated by the automatic object detection modules. According to the experiment＇s results, employing the developed annotation tool is considerably beneficial for reducing annotation time; when compared to manual annotation schemes, using the tool resulted in an annotation time reduction of up to 2.3 times.
文摘Soil moisture(SM)content is one of the most important environmental variables in relation to land surface climatology,hydrology,and ecology.Long-term SM data-sets on a regional scale provide reasonable information about climate change and global warming specific regions.The aim of this research work is to develop an integrated methodology for SM of kastanozems soils using multispectral satellite data.The study area is Tuv(48°40′30″N and 106°15′55″E)province in the forest steppe zones in Mongolia.In addition to this,land surface temperature(LST)and normalized difference vegetation index(NDVI)from Landsat satellite images were integrated for the assessment.Furthermore,we used a digital elevation model(DEM)from ASTER satellite image with 30-m resolution.Aspect and slope maps were derived from this DEM.The soil moisture index(SMI)was obtained using spectral information from Landsat satellite data.We used regression analysis to develop the model.The model shows how SMI from satellite depends on LST,NDVI,DEM,Slope,and Aspect in the agricultural area.The results of the model were correlated with the ground SM data in Tuv province.The results indicate that there is a good agreement between output SM and SM of ground truth for agricultural area.Further research is focused on moisture mapping for different natural zones in Mongolia.The innovative part of this research is to estimate SM using drivers which are vegetation,land surface temperature,elevation,aspect,and slope in the forested steppe area.This integrative methodology can be applied for different regions with forest and desert steppe zones.
文摘It is common knowledge that continental retrieval especially for Qinghai-Xizang Plateau has not been solved todate. In order to explore applicable inverse model and method for continent including the plateau, in this study authors use an improved simultaneous physical retrieval method hereafter referred to as the ISPRM, for computing meteorological parameters from NOAA-10 satellite TOVS data. The retrieval results verified by nearby radiosondesshow that the ISPRM is more applicable for the continental plateau.
基金ACKNOWLEDGEMENT This research was partially supported by the National Basic Research Program of China （973 Program） under Grant No. 2011CB30- 2605 the National High Technology Research and Development Program of China （863 Pro- gram） under Grant No. 2012AA012502+3 种基金 the National Key Technology Research and Dev- elopment Program of China under Grant No. 2012BAH37B00 the Program for New Cen- tury Excellent Talents in University under Gr- ant No. NCET-10-0863 the National Natural Science Foundation of China under Grants No 61173078, No. 61203105, No. 61173079, No. 61070130, No. 60903176 and the Provincial Natural Science Foundation of Shandong under Grants No. ZR2012FM010, No. ZR2011FZ001, No. ZR2010FM047, No. ZR2010FQ028, No. ZR2012FQ016.
文摘Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this problem.TL system captures all user socket calls and their corresponding application process information in the user mode on a Windows host.Once a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel mode.Then the intermediate driver writes application type information on TOS field of the IP packets which match the 5-tuple.In this way,each IP packet sent from the Windows host carries their application information.Therefore,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models.
基金Fundamental Research Funds for the Central Universities,China (No. 22D111207)。
文摘With the rocketing progress of the Internet, it is easier for people to get information about the objects that they are interested in. However, this information usually has conflicts. In order to resolve conflicts and get the true information, truth discovery has been proposed and received widespread attention. Many algorithms have been proposed to adapt to different scenarios. This paper aims to investigate these algorithms and summarize them from the perspective of algorithm models and specific concepts. Some classic datasets and evaluation metrics are given in this paper. Some future directions for readers are also provided to better understand the field of truth discovery.
基金supported by the Sustainable Development International Cooperation Program of National Science Found-ation of China(Grant No.42361144875)the National Natural Science Foundation of China(Grant No.42171360).
文摘The power generation of bifacial photovoltaic modules is greatly related to the diffuse solar radiation component received by the rear side,but radiation component data are scarce in China,where bifacial solar market is large.Radiation components can be estimated from satellite data,but sufficient ground truth data are needed for calibrating empirical methods or training machine learning methods.In this work,a data-augmented machine learning method was proposed to estimate radiation components.Instead of using observed ground truth,far more abundant radiation component data derived from sunshine duration measured at 2,453 routine weather stations in China were used to augment samples for training a machine-learning-based model.The inputs of the model include solar radiation(either from ground observation or satellite remote sensing)and surface meteorological data.Independent validation of the model at Chinese stations and globally distributed stations demonstrates its effectiveness and generality.Using a state-of-the-art satellite product of solar radiation as input,the model is applied to construct a satellite-based radiation component dataset over China.The new dataset not only outperforms mainstream radiation component datasets,but also has significantly higher accuracy than satellite-based datasets derived from other machine learning methods trained with limited observations,indicating the superiority of our data-augmented method.In principle,this model can be applied on the global scale without additional training with local data.
基金Supported by National Natural Science Foundation of China
文摘In order to improve the interpretation of the earth system microwave remote sensing, the research of microwave spectrum characteristics of the ground truth (earth objects) was carried out in laboratory. A laboratory for microwave remote sensing of the earth objects has been constructed to improve the remote sensing level, the laboratory consists of four parts: the measuring system of dielectric constants, the microwave emissivity meter, the microwave reflectometer and the microwave remote sensing simulation experiment in field. In this paper, the principle of measurement, the correction of near field process, the structure of instrument, the calibration method and the measurement of the earth substances, including soil, water and oil, are discussed. The labora- tory may supply the condition for measuring the parameters of thc earth substance remote sensing and help to interpret the remote sensing data.
