The permafrost development in the Qinghai-Tibet Engineering Corridor(QTEC)is affected by natural environment changes and human engineering activities.Human engineering activities may damage the permafrost growing envi...The permafrost development in the Qinghai-Tibet Engineering Corridor(QTEC)is affected by natural environment changes and human engineering activities.Human engineering activities may damage the permafrost growing environment,which in turn impact these engineering activities.Thus high spatial-temporal resolution monitoring over the QTEC in the permafrost region is very necessary.This paper presents a method for monitoring the frozen soil area using the intermittent coherencebased small baseline subset(ICSBAS).The method can improve the point density of the results and enhance the interpretability of deformation results by identifying the discontinuous coherent points according to the coherent value of time series.Using the periodic function that models the seasonal variation of permafrost,we separate the long wavelength atmospheric delay and establish an estimation model for the frozen soil deformation.Doing this can raise the monitoring accuracy and improve the understanding of the surface deformation of the frozen soil.In this study,we process 21 PALSAR data acquired by the Alos satellite with the proposed ICSBAS technique.The results show that the frozen soil far from the QTR in the study area experiences frost heave and thaw settlement(4.7 cm to8.4 cm)alternatively,while the maximum settlement along the QTR reaches 12 cm.The interferomatric syntnetic aperture radar(InSAR)-derived results are validated using the ground leveling data nearby the Beiluhe basin.The validation results show the InSAR results have good consistency with the leveling data in displacement rates as well as time series.We also find that the deformation in the permafrost area is correlated with temperature,human activities and topography.Based on the interfering degree of human engineering activities on the permafrost environment,we divide the QTEC along the Qinghai-Tibet Railway into engineering damage zone,transition zone and natural permafrost.展开更多
The vertical structure of water vapor in atmosphere is one of the initial information of numerical weather forecast model. Because of the strong variation of water vapor in atmosphere and limited spatio-temporal solut...The vertical structure of water vapor in atmosphere is one of the initial information of numerical weather forecast model. Because of the strong variation of water vapor in atmosphere and limited spatio-temporal solutions of traditional ob- servation technique, the initial water vapor field of numerical weather forecast model can not accurately be described. At present, using GPS slant observa- tions to study water vapor profile is very popular in the world. Using slant water vapor(SWV) observa- tions from Shanghai GPS network,we diagnose the three-dimensional(3D) water vapor structure over Shanghai area firstly in China. In water vapor tomo- graphy, Gauss weighted function is used as horizon- tal constraint, the output of numerical forecast is used as apriori information, and boundary condition is also considered. For the problem without exact apriori weights for observations, estimation of variance components is introduced firstly in water vapor to- mography to determine posteriori weights. Robust estimation is chosen for reducing the effect of blun- ders on solutions. For the descending characteristic of water vapor with height increasing, non-equal weights are used along vertical direction. Compari- sons between tomography results and the profile provided by numerical model (MM5) show that the forecasted moisture fields of MM5 can be improved obviously by GPS slant water vapor. Using GPS slant observations to study 3D structure of atmosphere in near real-time is very important for improving initialwater vapor field of short-term weather forecast and enhancing the accuracy of numerical weather fore- cast.展开更多
The use of a general EM(expectation-maximization) algorithm in multi-spectral image classification is known to cause two problems:singularity of the variance-covariance matrix and sensitivity of randomly selected init...The use of a general EM(expectation-maximization) algorithm in multi-spectral image classification is known to cause two problems:singularity of the variance-covariance matrix and sensitivity of randomly selected initial values.The former causes computation failure;the latter produces unstable classification results.This paper proposes a modified approach to resolve these defects.First,a modification is proposed to determine reliable parameters for the EM algorithm based on a k-means algorithm with initial centers obtained from the density function of the first principal component,which avoids the selection of initial centers at random.A second modification uses the principal component transformation of the image to obtain a set of uncorrelated data.The number of principal components as the input of the EM algorithm is determined by the principal contribution rate.In this way,the modification can not only remove singularity but also weaken noise.Experimental results obtained from two sets of remote sensing images acquired by two different sensors confirm the validity of the proposed approach.展开更多
In the application of 3D Geoscience Modeling,we often need to generate the volumetric representations of geological bodies from their surface representations.Linear octree,as an efficient and easily operated volumetri...In the application of 3D Geoscience Modeling,we often need to generate the volumetric representations of geological bodies from their surface representations.Linear octree,as an efficient and easily operated volumetric model,is widely used in 3D Geoscience Modeling.This paper proposes an algorithm for fast and dynamic generation of linear octrees of geological bodies from their surface models under hardware acceleration.The Z-buffers are used to determine the attributes of octants and voxels in a fast way,and a divide-and-conquer strategy is adopted.A stack structure is exploited to record the subdivision,which allows generating linear octrees dynamically.The algorithm avoids large-scale sorting process and bypasses the compression in linear octrees generation.Experimental results indicate its high efficiency in generating linear octrees for large-scale geologic bodies.展开更多
基金supported by the National Natural Science Foundation of China(42174026)the National Key Research and Development Program of China(2021YFE011004)。
文摘The permafrost development in the Qinghai-Tibet Engineering Corridor(QTEC)is affected by natural environment changes and human engineering activities.Human engineering activities may damage the permafrost growing environment,which in turn impact these engineering activities.Thus high spatial-temporal resolution monitoring over the QTEC in the permafrost region is very necessary.This paper presents a method for monitoring the frozen soil area using the intermittent coherencebased small baseline subset(ICSBAS).The method can improve the point density of the results and enhance the interpretability of deformation results by identifying the discontinuous coherent points according to the coherent value of time series.Using the periodic function that models the seasonal variation of permafrost,we separate the long wavelength atmospheric delay and establish an estimation model for the frozen soil deformation.Doing this can raise the monitoring accuracy and improve the understanding of the surface deformation of the frozen soil.In this study,we process 21 PALSAR data acquired by the Alos satellite with the proposed ICSBAS technique.The results show that the frozen soil far from the QTR in the study area experiences frost heave and thaw settlement(4.7 cm to8.4 cm)alternatively,while the maximum settlement along the QTR reaches 12 cm.The interferomatric syntnetic aperture radar(InSAR)-derived results are validated using the ground leveling data nearby the Beiluhe basin.The validation results show the InSAR results have good consistency with the leveling data in displacement rates as well as time series.We also find that the deformation in the permafrost area is correlated with temperature,human activities and topography.Based on the interfering degree of human engineering activities on the permafrost environment,we divide the QTEC along the Qinghai-Tibet Railway into engineering damage zone,transition zone and natural permafrost.
文摘The vertical structure of water vapor in atmosphere is one of the initial information of numerical weather forecast model. Because of the strong variation of water vapor in atmosphere and limited spatio-temporal solutions of traditional ob- servation technique, the initial water vapor field of numerical weather forecast model can not accurately be described. At present, using GPS slant observa- tions to study water vapor profile is very popular in the world. Using slant water vapor(SWV) observa- tions from Shanghai GPS network,we diagnose the three-dimensional(3D) water vapor structure over Shanghai area firstly in China. In water vapor tomo- graphy, Gauss weighted function is used as horizon- tal constraint, the output of numerical forecast is used as apriori information, and boundary condition is also considered. For the problem without exact apriori weights for observations, estimation of variance components is introduced firstly in water vapor to- mography to determine posteriori weights. Robust estimation is chosen for reducing the effect of blun- ders on solutions. For the descending characteristic of water vapor with height increasing, non-equal weights are used along vertical direction. Compari- sons between tomography results and the profile provided by numerical model (MM5) show that the forecasted moisture fields of MM5 can be improved obviously by GPS slant water vapor. Using GPS slant observations to study 3D structure of atmosphere in near real-time is very important for improving initialwater vapor field of short-term weather forecast and enhancing the accuracy of numerical weather fore- cast.
基金supported by the National High-tech R&D Program of China(2007AA12Z226 and SS2012AA120804)the National Natural Science Foundation of China(40674015 and 41074009)+2 种基金the Doctoral Fund of Ministry of Education of China(20100022110008)the Fundamental Research Funds for the Central Universities(2-9-2011-227)the Open Research Fund of Key Laboratory of Digital Earth Science,Center for Earth Observation and Digital Earth,Chinese Academy of Sciences (2010LDE002)
文摘The use of a general EM(expectation-maximization) algorithm in multi-spectral image classification is known to cause two problems:singularity of the variance-covariance matrix and sensitivity of randomly selected initial values.The former causes computation failure;the latter produces unstable classification results.This paper proposes a modified approach to resolve these defects.First,a modification is proposed to determine reliable parameters for the EM algorithm based on a k-means algorithm with initial centers obtained from the density function of the first principal component,which avoids the selection of initial centers at random.A second modification uses the principal component transformation of the image to obtain a set of uncorrelated data.The number of principal components as the input of the EM algorithm is determined by the principal contribution rate.In this way,the modification can not only remove singularity but also weaken noise.Experimental results obtained from two sets of remote sensing images acquired by two different sensors confirm the validity of the proposed approach.
基金supported by National Natural Science Foundation of China (Grant No.60502008)Hi-tech Research and Development Program of China (Grant Nos.2006AA12Z220 and 2007AA12Z226)Program for New Century Excellent Talents in University (Grant No.NCET-07-0099)
文摘In the application of 3D Geoscience Modeling,we often need to generate the volumetric representations of geological bodies from their surface representations.Linear octree,as an efficient and easily operated volumetric model,is widely used in 3D Geoscience Modeling.This paper proposes an algorithm for fast and dynamic generation of linear octrees of geological bodies from their surface models under hardware acceleration.The Z-buffers are used to determine the attributes of octants and voxels in a fast way,and a divide-and-conquer strategy is adopted.A stack structure is exploited to record the subdivision,which allows generating linear octrees dynamically.The algorithm avoids large-scale sorting process and bypasses the compression in linear octrees generation.Experimental results indicate its high efficiency in generating linear octrees for large-scale geologic bodies.
