The Qinghai-Tibet Plateau plays a very important role in studying severe weather in China and around the globe because of its unique characteristics. Moreover, the surface emissivities of the Qinghai-Tibet Plateau are...The Qinghai-Tibet Plateau plays a very important role in studying severe weather in China and around the globe because of its unique characteristics. Moreover, the surface emissivities of the Qinghai-Tibet Plateau are also important for retrieving surface and atmospheric parameters. In the current study, a retrieval algorithm was developed to retrieve the surface emissivities of the Qinghai-Tibet Plateau. The developed algorithm was derived from the radiative transfer model and was first validated using simulated data from a one-dimensional microwave simulator. The simulated results show good precision. Then, the surface emissivities of the Qinghai-Tibet Plateau were retrieved using brightness temperatures from the advanced microwave-scanning radiometer and atmospheric profile data from the moderate resolution imaging spectroradiometer. Finally, the features of the time and space distribution of the retrieved results were analyzed. In terms of spatial characteristics, a spatial distribution con- sistency was found between the retrieved results and surface coverage types of the Qinghai-Tibet Plateau. In terms of time characteristics, the changes in emissivity, which were within 0.01 for every day, were not evident within a one-month time scale. In addition, surface emissivities are sensitive to rainfall. The reasonability of the retrieved results indicates that the algorithm is feasible. A time-series surface emissivity database on the Qinghai-Tibet Plateau can be built using the developed algorithm, and then other surface or atmospheric parameters would have high retrieval precision to support related geological re- search on the Qinghai-Tibet Plateau.展开更多
Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging s...Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users' experience,but also restrict resources' retrieval efficiency.Tag clustering can aggregate tags with similar semantics together,and help mitigate the above problems.In this paper,we first present a common co-occurrence group similarity based approach,which employs the ternary relation among users,resources,and tags to measure the semantic relevance between tags.Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data.Finally,experimental results show that the proposed method is useful and efficient.展开更多
基金supported by National Natural Science Foundation of China(Grant Nos. 41101314 and 40930530)State Key Laboratory of Remote Sensing Open Fund (Grant No. OFSLRSS201104)+2 种基金Institute of Plateau Meteorology Open Fund (Grant No. LPM2011018)Digital Earth Key Laboratory of CAS Open Fund (Grant No. 2010LDE008)Chinese Academy of Meteorological Science Special Fund (Grant No. 2008Z003)
文摘The Qinghai-Tibet Plateau plays a very important role in studying severe weather in China and around the globe because of its unique characteristics. Moreover, the surface emissivities of the Qinghai-Tibet Plateau are also important for retrieving surface and atmospheric parameters. In the current study, a retrieval algorithm was developed to retrieve the surface emissivities of the Qinghai-Tibet Plateau. The developed algorithm was derived from the radiative transfer model and was first validated using simulated data from a one-dimensional microwave simulator. The simulated results show good precision. Then, the surface emissivities of the Qinghai-Tibet Plateau were retrieved using brightness temperatures from the advanced microwave-scanning radiometer and atmospheric profile data from the moderate resolution imaging spectroradiometer. Finally, the features of the time and space distribution of the retrieved results were analyzed. In terms of spatial characteristics, a spatial distribution con- sistency was found between the retrieved results and surface coverage types of the Qinghai-Tibet Plateau. In terms of time characteristics, the changes in emissivity, which were within 0.01 for every day, were not evident within a one-month time scale. In addition, surface emissivities are sensitive to rainfall. The reasonability of the retrieved results indicates that the algorithm is feasible. A time-series surface emissivity database on the Qinghai-Tibet Plateau can be built using the developed algorithm, and then other surface or atmospheric parameters would have high retrieval precision to support related geological re- search on the Qinghai-Tibet Plateau.
基金supported by the National Natural Science Foundation of China(Nos.61273292,61303131,51474007,and 51374114)the MOE Humanities and Social Science Research on Youth Foundation of China(No.13YJCZH077)
文摘Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users' experience,but also restrict resources' retrieval efficiency.Tag clustering can aggregate tags with similar semantics together,and help mitigate the above problems.In this paper,we first present a common co-occurrence group similarity based approach,which employs the ternary relation among users,resources,and tags to measure the semantic relevance between tags.Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data.Finally,experimental results show that the proposed method is useful and efficient.
