Hongdong Fan

Dr. Hongdong Fan


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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17 July 2015 in Remote Sensing
Verified
Journal Article
Open access
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HFHongdong Fan
Hongdong Fan
XGXiaoxiong Gao
Xiaoxiong Gao
JYJunkai Yang
Junkai Yang
KDKa-zhong Deng
Ka-zhong Deng
YYYang Yu
Yang Yu
An approach to study the mechanism of mining-induced subsidence, using a combination of phase-stacking and sub-pixel offset-tracking methods, is reported. In this method, land subsidence with a small deformation gradient was calculated using time-series differential interferometric synthetic aperture radar (D-InSAR) data, whereas areas with greater subsidence were calculated by a sub-pixel offset-tracking method. With this approach, time-series data for mining subsidence were derived in Yulin area using 11 TerraSAR-X (TSX) scenes from 13 December 2012 to 2 April 2013. The maximum mining subsidence and velocity values were 4.478 m and 40 mm/day, respectively, which were beyond the monitoring capabilities of D-InSAR and advanced InSAR. The results were compared with the GPS field survey data, and the root mean square errors (RMSE) of the results in the strike and dip directions were 0.16 m and 0.11 m, respectively. Four important results were obtained from the time-series subsidence in this mining area: (1) the mining-induced subsidence entered the residual deformation stage within about 44 days; (2) the advance angle of influence changed from 75.6° to 80.7°; (3) the prediction parameters of mining subsidence; (4) three-dimensional deformation. This method could be used to predict the occurrence of mining accidents and to help in the restoration of the ecological environment after mining activities have ended.

9 July 2022 in Remote Sensing
Verified
Journal Article
Open access
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YXYaozong Xu
Yaozong Xu
TLTao Li
Tao Li
Xinming TangXinming Tang
Xinming Tang
XZXiang Zhang
Xiang Zhang
HFHongdong Fan
Hongdong Fan
YWYuewen Wang
Yuewen Wang
Intensive and large-scale underground coal mining has caused geological disasters such as local ground subsidence, cracks and collapse in the Datong coalfield, China, inducing serious threats to local residents. Interferometric synthetic aperture radar (InSAR) has the capability of surface deformation detection with high precision in vast mountainous areas. DInSAR, stacking-InSAR and SBAS-InSAR are commonly used InSAR-related deformation analysis methods. They can provide effective support for mine ecological security monitoring and prevent disasters. We use the three methods to conduct the deformation observation experiments in the Datong coalfield. Sentinel-1A data from November 2020 to October 2021 are used. As a result, a total of 256 deformations in the Datong coalfield were successfully detected by the three methods, of which 218 are mining deformations, accounting for 85% of the total deformations. By comparing the results of the three methods, we found that DInSAR, stacking-InSAR, and SBAS-InSAR detected 130, 256, and 226 deformations in the Datong coalfield, respectively, while the deformations caused by coal mining were 128, 218, and 190. DInSAR results with long spatiotemporal baselines are seriously incoherent. SBAS-InSAR results of displacement rate are more precise than stacking-InSAR, and the mean standard deviation is 1.0 mm/a. However, for areas with lush vegetation or low coherence, SBAS-InSAR has poor performance. The detection deformation area results of DInSAR and SBAS-InSAR are subsets of stacking-InSAR. The displacement rates obtained by stacking-InSAR and SBAS-InSAR are consistent; the mean difference in the displacement rate between the two methods is 2.7 mm/a, and the standard deviation is 5.1 mm/a. The mining deformation locations and their shapes in the study area can be identified with high efficiency and power by stacking-InSAR. Therefore, with a comprehensive understanding of the advantages and limitations of the three methods, stacking-InSAR can be an effective and fast method to identify the level, location and range of mining deformation in lush mountainous areas.

1 September 2018 in Remote Sensing
Verified
Journal Article
Open access
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MZmeinan zheng
meinan zheng
KDKa-zhong Deng
Ka-zhong Deng
HFHongdong Fan
Hongdong Fan
Sen DuSen Du
Sen Du
To determine the relationship between underground mining, groundwater storage change, and surface deformation, we first used two sets of ENVISAT data and one set of Sentinel-1A data to obtain surface deformation in eastern Xuzhou coalfield based on the temporarily coherent point interferometric synthetic aperture radar (TCPInSAR) technique. By comparison with underground mining activities, it indicated that the surface subsidence is mainly related to mine exploitation and residual subsidence in the goaf, while the surface uplift is mainly related to restoration of the groundwater level. The average groundwater storage change in the eastern Xuzhou coalfield from January 2005 to June 2017 was obtained through the Gravity Recovery and Climate Experiment (GRACE) data, and the results indicated that the groundwater storage changed nonlinearly with time. The reliability of the groundwater monitoring results was qualitatively validated by using measured well data from April 2009 to April 2010. Combining with time of mining and mine closing analysis, groundwater storage change within the research area had a strong correlation with drainage activity of underground mining. An analysis was finally conducted on the surface deformation and the groundwater storage change within the corresponding time. The results indicated that the groundwater storage variation in the research area has a great influence on the surface deformation after the mine closed.

10 September 2018 in Remote Sensing
Verified
Journal Article
Open access
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HFHongdong Fan
Hongdong Fan
LLLu Lu
Lu Lu
YYYahui Yao
Yahui Yao
Time Series Interferometric Synthetic Aperture Radar (TS-InSAR) has high accuracy for monitoring slow surface subsidence. However, in the case of a large-scale mining subsidence areas, the monitoring capabilities of TS-InSAR are poor, owing to temporal and spatial decorrelation. To monitor mining subsidence effectively, a method known as Probability Integration Model Small Baseline Set (PIM-SBAS) was applied. In this method, mining subsidence with a large deformation gradient was simulated by a PIM. After simulated deformation was transformed into a wrapped phase, the residual wrapped phase was obtained by subtracting the simulated wrapped phase from the actual wrapped phase. SBAS was used to calculate the residual subsidence. Finally, the mining subsidence was determined by adding the simulated deformation to the residual subsidence. The time series subsidence of the Nantun mining area was derived from 10 TerraSAR-X (TSX) images for the period 25 December 2011 to 2 April 2012. The Zouji highway above the 9308 workface was the target for study. The calculated maximum mining subsidence was 860 mm. The maximum subsidence for the Zouji highway was about 145 mm. Compared with the SBAS method, PIM-SBAS alleviates the difficulty of phase unwrapping, and may be used to monitor large-scale mining subsidence.

19 July 2020 in Bulletin of Engineering Geology and the Environment
Verified
Journal Article
Closed access
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YLYoufeng Liu
Youfeng Liu
HFHongdong Fan
Hongdong Fan
LWLiang Wang
Liang Wang
HZHuifu Zhuang
Huifu Zhuang

23 December 2015 in Remote Sensing
Verified
Journal Article
Open access
PDF file
XZXiang Zhang
Xiang Zhang
Baozhang ChenBaozhang Chen
Baozhang Chen
HFHongdong Fan
Hongdong Fan
JHJilei Huang
Jilei Huang
HZHui Zhao
Hui Zhao
The potential use of TerraSAR-X and Radarsat-2 data for soil moisture retrieval over bare agricultural areas was investigated using both empirical and semi-empirical approaches. For the empirical approach, the Support Vector Regression (SVR) model was used with two cases: (1) using only one C-band or X-band image; and (2) using a pair of C-band and X-band images jointly. For the semi-empirical approach, the modified Dubois model based on C-band and X-band SAR data was developed to estimate soil moisture content. The experiments were implemented over two bare agricultural areas, and in-situ measurements were carried out to assess the methods. The results showed that the TerraSAR-X and Radarsat-2 are suitable remote sensing tools for the estimation of surface soil moisture, with an accuracy of about 3 vol % (root mean square error, RMSE) over bare agricultural areas. Compared with the results obtained by Radarsat-2 data, TerraSAR-X data gives a slight improvement in estimating soil moisture. The accuracy of the soil moisture estimation was improved further when the two bands SAR data were used (RMSE of about 2.2 vol %) instead of only one. Moreover, the modified Dubois model showed comparable accuracy to the empirical model independent of the surface roughness.