Remote Sensing image fusion is an effective way to use the large volume ofdata from multi-source images. This paper introduces a new method of remote sensing image fusionbased on support vector machine (SVM), using hi...Remote Sensing image fusion is an effective way to use the large volume ofdata from multi-source images. This paper introduces a new method of remote sensing image fusionbased on support vector machine (SVM), using high spatial resolution data SPIN-2 and multi-spectralremote sensing data SPOT-4. Firstly, the new method is established by building a model of remotesensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classificationfusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1) Fromsubjectivity assessment, the spatial resolution of the fused image is improved compared to theSPOT-4. And it is clearly that the texture of the fused image is distinctive. 2) From quantitativeanalysis, the effect of classification fusion is better. As a whole, the re-suit shows that theaccuracy of image fusion based on SVM is high and the SVM algorithm can be recommended forapplication in remote sensing image fusion processes.展开更多
High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrologi...High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrological disaster prevention and mitigation.In this study,high-density rain gauge data are used to evaluate the fusion accuracy of the China Meteorological Administration Multisource Precipitation Analysis System(CMPAS),and four CMPAS products with different spatial and temporal resolution and different data sources are compared,to derive the applicability of CMPAS.Results show that all the CMPAS products show high accuracy in the Sichuan Basin,followed by Panxi Area and the western Sichuan Plateau.The errors of the four products all rise with the increase in precipitation.CMPAS overestimates precipitation in summer and autumn and underestimates it in spring and winter.Overall,the applicability of these fused data in the Sichuan Basin is quite good.Due to the lack of observations and the influence of the terrain and meteorological conditions,the evaluation of CMPAS in the plateau area needs further analysis.展开更多
In order to realize information construction on settlement of pile-group foundation of Sutong Bridge, the monitoring instruments of high-precision micro-pressure sensor and hydrostatic leveling and settlement profiler...In order to realize information construction on settlement of pile-group foundation of Sutong Bridge, the monitoring instruments of high-precision micro-pressure sensor and hydrostatic leveling and settlement profiler were integrated synthetically. A set of practical multi-scale monitoring system on settlement of super-large pile-group foundation in deep water was put forward. The reliable settlement results are obtained by means of multi-sensor data fusion. Finite element model of pile-group foundation is established. By analysis of finite element simulated calculation of pile-group foundation, rules of settlement and uneven settlement obtained by monitoring and calculation results are coincident and the absolute error of settlement between them is 4.7 mm. The research shows that it is reasonable and feasible to monitor settlement of pile-group foundation with the system, and it can provide a method for the same type pile-group foundation in deep water.展开更多
文摘Remote Sensing image fusion is an effective way to use the large volume ofdata from multi-source images. This paper introduces a new method of remote sensing image fusionbased on support vector machine (SVM), using high spatial resolution data SPIN-2 and multi-spectralremote sensing data SPOT-4. Firstly, the new method is established by building a model of remotesensing image fusion based on SVM. Then by using SPIN-2 data and SPOT-4 data, image classificationfusion is tested. Finally, an evaluation of the fusion result is made in two ways. 1) Fromsubjectivity assessment, the spatial resolution of the fused image is improved compared to theSPOT-4. And it is clearly that the texture of the fused image is distinctive. 2) From quantitativeanalysis, the effect of classification fusion is better. As a whole, the re-suit shows that theaccuracy of image fusion based on SVM is high and the SVM algorithm can be recommended forapplication in remote sensing image fusion processes.
基金supported by the Sichuan Meteorological Bureau,the Sichuan Meteorological Observation and Data Centerthe Heavy Rain and Drought-Flood Disasters in Plateau and Basin Key Laboratory of Sichuan Province[grant number SCQXKJQN202121]+1 种基金the Key Technology Development Project of Weather Forecasting[grant number YBGJXM(2020)1A-08]the Innovative Development Project of the China Meteorological Administration[grant number CXFZ2021Z007]。
文摘High-quality and high-resolution precipitation data are the basis for mesoscale numerical weather forecasting,model verification,and hydrological monitoring,which play an important role in meteorological and hydrological disaster prevention and mitigation.In this study,high-density rain gauge data are used to evaluate the fusion accuracy of the China Meteorological Administration Multisource Precipitation Analysis System(CMPAS),and four CMPAS products with different spatial and temporal resolution and different data sources are compared,to derive the applicability of CMPAS.Results show that all the CMPAS products show high accuracy in the Sichuan Basin,followed by Panxi Area and the western Sichuan Plateau.The errors of the four products all rise with the increase in precipitation.CMPAS overestimates precipitation in summer and autumn and underestimates it in spring and winter.Overall,the applicability of these fused data in the Sichuan Basin is quite good.Due to the lack of observations and the influence of the terrain and meteorological conditions,the evaluation of CMPAS in the plateau area needs further analysis.
基金Project(2002CB412707) supported by the National Basic Research Program of ChinaProject(2006BAG04B05) supported by the National Science and Technology Pillar Program during the 11th Five-Year Plan of ChinaProject(2010B14414) supported by the Scientific Research Program of Center University in China
文摘In order to realize information construction on settlement of pile-group foundation of Sutong Bridge, the monitoring instruments of high-precision micro-pressure sensor and hydrostatic leveling and settlement profiler were integrated synthetically. A set of practical multi-scale monitoring system on settlement of super-large pile-group foundation in deep water was put forward. The reliable settlement results are obtained by means of multi-sensor data fusion. Finite element model of pile-group foundation is established. By analysis of finite element simulated calculation of pile-group foundation, rules of settlement and uneven settlement obtained by monitoring and calculation results are coincident and the absolute error of settlement between them is 4.7 mm. The research shows that it is reasonable and feasible to monitor settlement of pile-group foundation with the system, and it can provide a method for the same type pile-group foundation in deep water.
