Chao fan Zhou

Dr. Chao fan Zhou


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

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

Representative Publications

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31 October 2020 in Remote Sensing
Verified
Journal Article
Open access
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MSMin Shi
Min Shi
HGHuili Gong
Huili Gong
Mingliang GaoMingliang Gao
Mingliang Gao
BCBeibei Chen
Beibei Chen
SZShunkang Zhang
Shunkang Zhang
CZChao fan Zhou
Chao fan Zhou
Groundwater resources have been exploited and utilized on a large scale in the North China Plain (NCP) since the 1970s. As a result of extensive groundwater depletion, the NCP has experienced significant land subsidence, which threatens geological stability and infrastructure health and exacerbates the risks of other geohazards. In this study, we employed multi-track Synthetic Aperture Radar (SAR) datasets acquired by the Sentinel-1A (S1A) satellite to detect spatial and temporal distributions of surface deformation in the NCP from 2016 to 2018 based on multi-temporal interferometric synthetic aperture radar (MT-InSAR). The results show that the overall ground displacement ranged from −165.4 mm/yr (subsidence) to 9.9 mm/yr (uplift) with a standard variance of 28.8 mm/yr. During the InSAR monitoring period, the temporal pattern of land subsidence was dominated by a decreasing tendency and the spatial pattern of land subsidence in the coastal plain exhibited an expansion trend. Validation results show that the S1A datasets agree well with levelling data, indicating the reliability of the InSAR results. With groundwater level data, we found that the distribution of subsidence in the NCP is spatially consistent with that of deep groundwater depression cones. A comparison with land use data shows that the agricultural usage of groundwater is the dominant mechanism responsible for land subsidence in the whole study area. Through an integrated analysis of land subsidence distribution characteristics, geological data, and previous research results, we found that other triggering factors, such as active faults, precipitation recharge, urbanization, and oil/gas extraction, have also impacted land subsidence in the NCP to different degrees.

17 February 2022 in Remote Sensing
Verified
Journal Article
Open access
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XZXin Zhang
Xin Zhang
BCBeibei Chen
Beibei Chen
HGHuili Gong
Huili Gong
KLKunchao Lei
Kunchao Lei
CZChao fan Zhou
Chao fan Zhou
DZDanni Zhao
Danni Zhao
The long-term over-exploitation of groundwater has not only caused the compaction of aquifer thickness and surface deformation but has also further aggravated the loss of groundwater storage (GWS) in Beijing plain. The South-to-North Water Diversion Project (SNWDP) furnishes a new source of water for Beijing. By reviewing related studies, it was found that there are few studies on the realization of GWS estimation based on InSAR technology considering the lag effect. Therefore, in this study, firstly, the long-time series deformation characteristics of Beijing plain were obtained from 46 RadarSat-2 images using small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology. Secondly, the seasonal components of surface deformation and hydraulic head change were extracted by means of multichannel singular spectrum analysis (MSSA), verifying the separation accuracy by means of Monto Carlo-SSA (MC-SSA). Finally, for the hydrodynamic delay (aquifer water supply/drainage) of the complex aquifer system, we introduced the time lag cross-correlation (TLCC) approach to correct the hysteresis response of seasonal deformation relative to the variation of the aquifer system head, so as to realize the estimation of aquifer storage properties and GWS loss, even unrecoverable GWS (UGWS). The results showed that the average annual variation of total GWS (TGWS) in Beijing plain was −6.702 × 107 m3, of which the depletion volume of UGWS was −6.168 × 107 m3, accounting for 92.03% of the TGWS. On a temporal scale, the depletion of UGWS lagged behind the total head change, with about one year of lag time. On a spatial scale, in contrast to the north of Beijing plain, the depletion of UGWS in the south only recovered briefly after 2015 and then continued to decline. This further indicated that the process of the decline of middle-deep confined head and long-term GWS loss caused by over-exploitation of groundwater was irreversible. These findings are of great significance to optimize the allocation of groundwater resources, reduce the harm of land subsidence and protect groundwater resources.

19 September 2023 in Remote Sensing
Verified
Journal Article
Open access
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LWLin Wang
Lin Wang
CZChao fan Zhou
Chao fan Zhou
HGHuili Gong
Huili Gong
BCBeibei Chen
Beibei Chen
XXXinyue Xu
Xinyue Xu
High-speed railways in the Beijing–Tianjin–Hebei (BTH) Plain are gradually becoming more widespread, covering a greater area. The operational safety of high-speed railways is influenced by the continuous development of land subsidence. It is necessary to predict the subsidence along the high-speed railways; thus, this work is of critical importance to the safety of high-speed railway operation. In this study, we processed Sentinel-1A data using the Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to acquire the land subsidence in the typical BTH area. Then, we combined the Empirical Mode Decomposition (EMD) and Gradient Boosting Decision Tree (GBDT) methods (EMD-GBDT) to forecast land subsidence along high-speed railways. The results revealed that some parts of the high-speed railways in the BTH plain had passed through or approached the land subsidence area; the maximum cumulative subsidence of the Beijing–Shanghai, Tianjin–Baoding and Shijiazhuang–Jinan high-speed railways reached 326 mm, 384 mm and 350 mm, respectively. The forecasting accuracy for land subsidence along high-speed railways was enhanced by the EMD-GBDT model. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) were 0.38 mm to 0.56 mm and 0.23 mm to 0.38 mm, respectively.

28 November 2023 in Land
Verified
Journal Article
Open access
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XXXinyue Xu
Xinyue Xu
CZChao fan Zhou
Chao fan Zhou
HGHuili Gong
Huili Gong
BCBeibei Chen
Beibei Chen
LWLin Wang
Lin Wang
Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this area is significant. In this paper, we used the Small Baseline Subsets Interferometric Point Target Analysis (SBAS-IPTA) technique to process the Envisat-ASAR, Radarsat-2, and Sentinel-1A data and obtained the land subsidence of Cangzhou from 2004 to 2020. Additionally, we obtained winter wheat distribution information in Cangzhou using the Pixel Information Expert Engine (PIE-Engine) remote sensing cloud platform. On this basis, we analyzed the relationship between ground water level, winter wheat planting area, and the response of land subsidence according to the land use type and groundwater level monitoring data near the winter wheat growing area. The results show that during 2004–2020, the average annual subsidence rate of many places in Cangzhou was higher than 30 mm/year, and the maximum subsidence rate was 115 mm/year in 2012. From 2004 to 2020, the area of the subsidence funnel showed a trend of first increasing and then decreasing. In 2020, the subsidence funnel area reached 6.9 × 103 km2. The winter wheat planting area in the urban area showed a trend of first decreasing, then increasing and then decreasing, and it accounted for a large proportion in the funnel area. At the same time, we studied the relationship between the land subsidence rate and the water level at different burial depths and the response of winter wheat planting area. The results showed that the change of confined water level had a stronger response with the other two variables.

17 July 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SZShunkang Zhang
Shunkang Zhang
BCBeibei Chen
Beibei Chen
HGHuili Gong
Huili Gong
KLKunchao Lei
Kunchao Lei
MSMin Shi
Min Shi
CZChao fan Zhou
Chao fan Zhou
Surface displacement is an common environmental geological phenomenon in the Beijing Plain. Research on surface displacement in the Beijing Plain has mainly focused on vertical surface displacement, whereas the horizontal displacement has scarcely been studied. To investigate the 3-D surface displacement in the Beijing Plain, we construct a leveling-constrained multidirectional PS-InSAR 3-D surface displacement estimation method to obtain the 3-D surface displacement information. The results show that the surface displacement in the study area during 2016–2018 was mainly vertical displacement with two main northern and southern subsidence centers; the vertical displacement ranged from −150 mm/year (down) to 5 mm/year (up), and the east–west horizontal displacement ranged from 20 mm/year (east) to 22 mm/year (west). Validation results show that the 3-D surface displacement estimation results agree well with leveling data and GPS data, indicating the reliability of the 3-D surface displacement datasets. The 3-D surface displacement results show that horizontal displacement is obvious in the areas with a large vertical displacement in the eastern Beijing Plain. Additionally, the horizontal displacement is directed toward the center of vertical displacement. The compressive strain is observed close to the centers of vertical displacement, whereas tensile strain occurs far from the centers of vertical displacement. The main cause of the 3-D surface displacement in the study area is the long-term groundwater overexploitation, especially deep groundwater exploitation. The spatial and temporal extents of displacement do not exactly match the locations of the groundwater sinks in different aquifers; instead, geological structures and stratigraphic/lithological conditions may have a combined effect. Moreover, the spatial and temporal distributions of surface displacement are closely related to ground fissure activity, and both influence each other.

11 October 2023 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Verified
Journal Article
Open access
DZDanni Zhao
Danni Zhao
BCBeibei Chen
Beibei Chen
HGHuili Gong
Huili Gong
KLKunchao Lei
Kunchao Lei
CZChao fan Zhou
Chao fan Zhou
JHJinming Hu
Jinming Hu
Land subsidence is an environmental geological phenomenon mainly caused by groundwater overexploitation. Long-term overexploitation of groundwater not only causes compaction of aquifer thickness and surface deformation but also leads to the loss of aquifer water storage capacity. The skeleton water storage coefficient (Sk) is an important parameter for evaluating the water storage capacity of aquifer groups. This paper proposes a new research framework for obtaining the Sk of different aquifer groups: combining Permanent Scatter for SAR Interferometry (PS-InSAR) technology and a Multiscale Geographic Weighted Regression (MGWR) model to obtain subsidence information for different aquifer groups, inverting the Sk of different aquifer groups from the spatial scale, and discussing the deformation characteristics of soil layers under different water head change modes to evaluate the deformation and water storage characteristics of different aquifer groups. This framework is applied to the land subsidence region of the Beijing Plain. We calculated that the settlement proportions of different compression layer groups were 14.75%, 23.65%, 33.44% and 28.16%. Due to the different lithological compositions and groundwater exploitation of different aquifers, the Sk values exhibit different spatial distribution characteristics. With the continuous development of subsidence, the water storage performance of the aquifer group is continuously declining. These findings contribute to managing the sustainable use of groundwater resources and controlling subsidence. It is demonstrated that the research framework proposed in this article can serve as an effective tool for obtaining settlement information and the Sk of different aquifer groups.