Obtaining accurate satellite precipitation data is crucial for monitoring flood and flood disasters and analysing climate change. As a new generation of satellite precipitation product, global rainfall observation program GPM is integrated with advanced microwave detection technology and data correction algorithm, providing more choices for studying precipitation in global regions. The main purpose of this paper is to evaluate the adaptability of GPM three-stage precipitation product IMERG (Final Run mode) at different temporal resolutions in the Beijing-Tianjin-Hebei region. After screening, the precipitation data of 107 national meteorological stations in the Beijing-Tianjin-Hebei region was used as the verification data, and the detection capability of GPM satellite precipitation data in different time scales of day, month and season as well as extreme precipitation events was analysed. The following conclusions were obtained: (1) Compared with the IMERG products with half -hourly and daily temporal resolution, the IMERG satellite precipitation data with 1month temporal resolution has a strong correlation, reaching 0.90. It can reflect the precipitation event accurately in the Beijing-Tianjin-Hebei region. The poor performance of IMERG satellite is concentrated in the north-western and south-eastern edges of the Beijing-Tianjin-Hebei region.(2) The performance of IMERG precipitation data in the humid season on the monthly scale is better than that in the dry season, and GPM satellite precipitation data are generally overestimated.(3) In the process of extreme precipitation event detection using 0.5h temporal resolution data, the tendency of IMERG satellite precipitation data to accumulate precipitation is roughly consistent with that of the station, but the phenomenon of overestimation still exists, especially in places with large precipitation, overestimation is more obvious. In view of this precipitation event, satellite precipitation data covers almost the entire precipitation process, and some values are still high. Although the data has good detection capability for extreme precipitation events, the monitoring of precipitation peak is not accurate enough. According to the comprehensive analysis, its Final GPM product has a strong ability to detect rainfall events, which can provide data support for the long time series analysis in the Beijing-Tianjin-Hebei region.
The ground subsidence phenomenon is more serious in Beijing, large-scale land subsidence seriously threats to urban planning and construction and the safety of residents. In order to study the subsidence condition, it is necessary to monitor land subsidence. Choosing 28 scenes Envisat ASAR images covering Beijing city from December 2003 to March 2009, permanent scatterer SAR interferometry (PSI) technique was applied to obtained time series land subsidence information. Then the trend characteristics and factors of subsidence were analyzed, comparing land subsidence result with the groundwater data and geological structure data. Comparison between the PSI-derived subsidence rates and leveling data obtained shows that the result of PSI is agreed with the leveling data. The results indicate that the PSI technique is capable of providing high-level accuracy subsidence information. The results show that:(1) The deformation rates derived PSI ranging from -45.80 to 4.36mm/a;(2) In the study area, the serious subsidence areas distribute in Chaoyang District, Shunyi District, Tongzhou District and Pinggu District;(3) The subsidence tends to become more and more concentrated in 6 years from 2003 to 2009.
Aiming at spatial characteristics and echo information of the LiDAR point cloud data, design a regional segmentation and decision tree combined lidar point data classification method. First, based on the continuity of the LiDAR point cloud to finish the experiment area's region segmentation. Then, statistics each area boundaries and internal the number of dihedral angle cosine, to draw a line chart. Using the intersection's cosine of line chart , and region segmentation's minimum height as threshold to determine the ground point and the non-ground points. Finally, statistics separately all LiDAR point data set's dihedral angle, echo times, echo intensity, mean elevation, four constraint information to build a decision tree to determine which type of feature vesting each divided region. Using classification confusion matrix to assess the classification's accuracy, overall accuracy is higher than 94%. Experimental results show that this method can effectively separate roads, trees, buildings and terrain.
Differential synthetic aperture radar interferometry (InSAR) has already proven its potential for ground subsidence
monitoring. In recent years Multi-Temporal InSAR technology has been rapid development. Coherence of interferogram is
an important indicator to measure the interferometric phase in the Multi-Temporal InSAR system. This paper study the
effect of the Spatial-Temporal baseline on coherence for SAR images in Multi-Temporal InSAR processing base on the
aspect of statistics. on the basis of a large amount of data, a formula for calculating coherence for SAR images was
deduced which it correspond to the relationship between Spatial-Temporal baseline and the coherence of interferogram.
This formula can optimize the selection of interference image pairs during processing Multi-Temporal InSAR. To
determine whether this formula is useful, two methods of interference image pairs selection was used, one is the formula to
optimize the selection, another is the traditional fixed threshold method. The author compared the coherence of
Interferogram to judge the merits of the two methods. The results indicate that the formula not only select more
interferogram from interferogram stack, but also increase the number of highly coherent points. And use SBAS-InSAR
technique to obtain the 2010-2013 Beijing urban land subsidence information, verification monitoring accuracy by
comparing level monitoring result.
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