Conventional singe baseline InSAR is easily affected by atmospheric artifacts, making it difficult to generate highprecision DEM. To solve this problem, in this paper, a multi-baseline interferometric phase accumulation method with weights fixed by coherence is proposed to generate higher accuracy DEM. The mountainous area in Kunming, Yunnan Province, China is selected as study area, which is characterized by cloudy weather, rugged terrain and dense vegetation. The multi-baseline InSAR experiments are carried out by use of four ALOS-2 PALSAR-2 images. The generated DEM is evaluated by Chinese Digital Products of Fundamental Geographic Information 1:50000 DEM. The results demonstrate that: 1) the proposed method can reduce atmospheric artifacts significantly; 2) the accuracy of InSAR DEM generated by six interferograms satisfies the standard of 1:50000 DEM Level Three and American DTED-1.
Affected by over-exploration of groundwater for a long time, the Hangjiahu Plain in Zhejiang province, southeast of China, has suffering serious ground subsidence during the past several decades. In this paper, we investigate the time series InSAR technique for the generation of subsidence maps over this plain. 25 Radarsat-2 images acquired from Jan 2012 to Nov 2014 are used. The results show that serious subsidence has taken place in the north and southeast of Jiaxing, the east and north of Huzhou, and the north of Hangzhou. Meanwhile some rebound occurs in the east of Jiaxing and the southeast of Huzhou. The results are compared with 35 levelling measurements. The standard deviation of the error between the two data is 3.01mm, which demonstrate that time series InSAR technique has good accuracy for subsidence monitoring.
Due to long term over-exploring groundwater, ground subsidence has taken place in Urumqi city for many years.
Traditional ways of monitoring ground deformation utilize levelling and global positioning system (GPS) measurement.
They have the advantage of high accuracy. However, they are very costly and cannot achieve enough spatial sampling
density. Recently, space-born synthetic aperture radar interferometry (InSAR) is playing an important role in monitoring
ground deformation. In this paper, 11 ALOS PALSAR images from 2007 to 2010 have been acquired to monitor the
Urumqi City using small baseline time series InSAR technique. Results show that the subsidence is mainly taken place in
Qidaowan Industry Park, Urumqi Development Zone and North Industry Park. The maximum subsidence velocity can
reach to -64.6mm/year.
Because the terrain of mountain glacier is usually very rugged, it is hard to measure glaciers and estimated their changes
in larger area by conventional measuring method. With fast development of remote sensing technique, synthetic aperture
radar (SAR) interferometry is used for glacier monitoring with the ability of all-time and all-weather. Although
interferometric coherence is a very good index to glacier, it is difficult to distinguish glacier area from non-glacier area
when their coherence is similar. In this case, interferometric phase can play an important role to identify glacier. In this
paper, phase texture analysis method is proposed to extract glacier. 8 texture features were analyzed based on co-occurrence
matrix (COM), including mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and
correlation. Among them, variance, contrast and dissimilarity can distinguish glacier from non-glacier clearly most, so
they are chosen for RGB combination. Then the RGB combination image is classified into several land covers by
maximum likelihood classification (MLC). With post-classification processing, glacier area can be extracted accurately.
Landsat TM images validate the proposed method.
To overcome the shortage of conventional least squares (LS) DInSAR technique which can only obtain the optimal
deformation under ideal condition, we propose an advanced LS algorithm to retrieve ground deformation over large
areas. In this algorithm, two extensions are derived. First, the atmospheric phase screen (APS) is removed from the
differential interferometric phases by temporal low-pass filtering. Second, topographic errors are considered in the linear
model to be separated from deformation. The proposed algorithm has been tested with an ALOS PALSAR data set
relative to southern Jiangsu Province, covering the cities of Suzhou and Wuxi, East China. Finally, leveling data validate
The devastating Wenchuan Earthquake occurred in Sichuan Province, Southwestern China, with a magnitude of 8.0 on May 12, 2008. Most buildings along the seismic zone were ruined, resulting in infrastructure damage to factories, traffic facilities and power supplies. The earthquake also triggered geological disasters, such as landslides, debris flow, landslide lakes, etc. During the rescue campaign the remote sensing aircrafts of the Chinese Academy of Sciences (CAS), equipped with synthetic aperture radar (SAR) and optical sensors, flew over the disaster area and acquired many high resolution airborne SAR images. We first describe the basic characteristics of SAR imagery. The SAR images of buildings are simulated, and the backscattering mechanism of the buildings is analyzed. Finally, the various disaster phenomena are described and analyzed in the high resolution airborne SAR images. It is shown that certain phenomena of ruins could be identified clearly in high resolution SAR images in proper imaging conditions, while the functional destruction is quite difficult to detect. With calibrated data, the polarmetric SAR interferometry could be used to analyze the scattering mechanism and 3D distribution of the scattering center, which are redound to earthquake damage assessment.
This paper aims at improving the retrieval accuracy of urban residential areas in arid region where barrens are distributed
widely by fusing multi-spectral image and SAR image based on HIS transformation. Unlike traditional supervised
classification, 2-class classification is used to obtain urban residential areas and non-residential areas. Comparison
between this method and traditional supervised maximum likelihood classification (MLC) method is performed. It is
found that the retrieval of urban residential areas from the fused image is more accurate than that from TM image by
using MLC, with accuracy of 84.21% and 71.79% respectively. The result validates the efficiency of our method.