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Jiyuan Hu
Henan Industrial Technology Academy of Spatio-Temporal Big Data, Henan University, Zhengzhou 450000, China

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Journal article
Published: 27 May 2021 in Land
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The study of the temporal and spatial evolution of wetland landscapes and its driving factors is an important reference for wetland ecological restoration and protection. This article utilized seven periods of land use data in Henan Province from 1980 to 2015 to extract the spatial distribution characteristics of wetlands and analyze the temporal and spatial changes of wetlands in Henan Province. Transfer matrix, landscape metrics, correlation analysis, and redundancy analysis were applied to calculate and analyze the transformation types and area of wetland resources between all consecutive periods, and then the main driving factors of wetland expansion/contraction were explored. First, the total wetland area in Henan Province increased by 28% from 1980 to 2015, and the increased wetland area was mainly constructed wetlands, including paddy field, reservoir and pond, and canal. Natural wetlands such as marsh, lake, and floodplain decreased by 74%. Marsh area declined the most during 1990–1995, and was mainly transformed into floodplain and “Others” because of agricultural reclamation, low precipitation, and low Yellow River runoff. The floodplain area dropped the most from 2005 to 2010, mainly converted to canals and “Others” because of reclamation, exploitation of groundwater, the construction of the South–to–North Water Transfer Project, and recreational land development. Second, the results of correlation analysis and redundancy analysis indicated that economic factors were positively correlated with the area of some constructed wetlands and negatively correlated with the area of some natural wetlands. Socioeconomic development was the main driving factors for changes in wetland types. The proportion of wetland habitat in Henan Province in 2015 was only 0.3%, which is low compared to the Chinese average of 2.7%. The government should pay more attention to the restoration of natural wetlands in Henan Province.

ACS Style

Heying Li; Jiayao Wang; Jianchen Zhang; Fen Qin; Jiyuan Hu; Zheng Zhou. Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015. Land 2021, 10, 564 .

AMA Style

Heying Li, Jiayao Wang, Jianchen Zhang, Fen Qin, Jiyuan Hu, Zheng Zhou. Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015. Land. 2021; 10 (6):564.

Chicago/Turabian Style

Heying Li; Jiayao Wang; Jianchen Zhang; Fen Qin; Jiyuan Hu; Zheng Zhou. 2021. "Analysis of Characteristics and Driving Factors of Wetland Landscape Pattern Change in Henan Province from 1980 to 2015." Land 10, no. 6: 564.

Journal article
Published: 04 December 2019 in Remote Sensing
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Ground-based radar interferometry, which can be specifically classified as ground-based synthetic aperture radar (GB-SAR) and ground-based real aperture radar (GB-RAR), was applied to monitor the Liusha Peninsula landslide and Baishazhou Yangtze River Bridge. The GB-SAR technique enabled us to obtain the daily displacement evolution of the landslide, with a maximum cumulative displacement of 20 mm in the 13-day observation period. The virtual reality-based panoramic technology (VRP) was introduced to illustrate the displacement evolutions intuitively and facilitate the following web-based panoramic image browsing. We applied GB-RAR to extract the operational modes of the large bridge and compared them with the global positioning system (GPS) measurement. Through full-scale test and time-frequency result analysis from two totally different monitoring methods, this paper emphasized the 3-D display potentiality by combining the GB-SAR results with VRP, and focused on the detection of multi-order resonance frequencies, as well as the configure improvement of ground-based radars in bridge health monitoring.

ACS Style

Jiyuan Hu; Jiming Guo; Yi Xu; Lv Zhou; Shuai Zhang; Kunfei Fan. Differential Ground-Based Radar Interferometry for Slope and Civil Structures Monitoring: Two Case Studies of Landslide and Bridge. Remote Sensing 2019, 11, 2887 .

AMA Style

Jiyuan Hu, Jiming Guo, Yi Xu, Lv Zhou, Shuai Zhang, Kunfei Fan. Differential Ground-Based Radar Interferometry for Slope and Civil Structures Monitoring: Two Case Studies of Landslide and Bridge. Remote Sensing. 2019; 11 (24):2887.

Chicago/Turabian Style

Jiyuan Hu; Jiming Guo; Yi Xu; Lv Zhou; Shuai Zhang; Kunfei Fan. 2019. "Differential Ground-Based Radar Interferometry for Slope and Civil Structures Monitoring: Two Case Studies of Landslide and Bridge." Remote Sensing 11, no. 24: 2887.

Journal article
Published: 09 October 2018 in Applied Sciences
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We investigated the effect of mass loading (atmospheric, oceanic and hydrological loading (AOH)) on Global Positioning System (GPS) height time series from 30 GPS stations in the Eurasian plate. Wavelet coherence (WTC) was employed to inspect the correlation and the time-variable relative phase between the two signals in the time–frequency domain. The results of the WTC-based semblance analysis indicated that the annual fluctuations in the two signals for most sites are physically related. The phase asynchrony at the annual time scale between GPS heights and AOH displacements indicated that the annual oscillation in GPS heights is due to a combination of mass loading signals and systematic errors (AOH modelling errors, geophysical effects and/or GPS system errors). Moreover, we discuss the impacts of AOH corrections on GPS noise estimation. The results showed that not all sites have an improved velocity uncertainty due to the increased amplitude of noise and/or the decreased spectral index after AOH corrections. Therefore, the posterior mass loading model correction is potentially feasible but not sufficient.

ACS Style

Zhen Li; Jianping Yue; Jiyuan Hu; Yunfei Xiang; Jian Chen; Yankai Bian. Effect of Surface Mass Loading on Geodetic GPS Observations. Applied Sciences 2018, 8, 1851 .

AMA Style

Zhen Li, Jianping Yue, Jiyuan Hu, Yunfei Xiang, Jian Chen, Yankai Bian. Effect of Surface Mass Loading on Geodetic GPS Observations. Applied Sciences. 2018; 8 (10):1851.

Chicago/Turabian Style

Zhen Li; Jianping Yue; Jiyuan Hu; Yunfei Xiang; Jian Chen; Yankai Bian. 2018. "Effect of Surface Mass Loading on Geodetic GPS Observations." Applied Sciences 8, no. 10: 1851.

Journal article
Published: 16 June 2018 in Applied Sciences
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In this study, we proposed a novel method for global navigation satellite system (GNSS) ambiguity resolution (AR). The proposed method utilizes an improved particle swarm optimization (IPSO) algorithm to obtain the GNSS integer ambiguity with the double differenced (DD) float resolution and its corresponding covariance matrix. First, we introduced population maturity to the standard PSO (SPSO) algorithm for the adaptive adjustment of inertia weight. Next, to improve the global convergence and robustness of the SPSO algorithm, we adopted population classification and constructed a Gauss mutation for the particle evolution process of the optimal population. Then, we applied the IPSO algorithm in the field of GNSS AR, called IPSO–AR. Finally, we evaluated the performance of the IPSO–AR algorithm under different DD ambiguity float resolutions with various dimensions and precisions. Numerical results showed that compared with the SPSO–AR algorithm, the IPSO–AR algorithm has a superior correct rate, but low efficiency. Under the appropriate parameter settings, the efficiency of the IPSO–AR algorithm is mainly dependent on the dimensions of DD ambiguity, whereas the correct rate of the IPSO–AR algorithm is mainly dependent on the precision of DD ambiguity. The proposed IPSO–AR algorithm has potential applications under the conditions of few visible satellites or constrained baseline length.

ACS Style

Xin Li; Jiming Guo; Jiyuan Hu. An Improved PSO Algorithm and Its Application in GNSS Ambiguity Resolution. Applied Sciences 2018, 8, 990 .

AMA Style

Xin Li, Jiming Guo, Jiyuan Hu. An Improved PSO Algorithm and Its Application in GNSS Ambiguity Resolution. Applied Sciences. 2018; 8 (6):990.

Chicago/Turabian Style

Xin Li; Jiming Guo; Jiyuan Hu. 2018. "An Improved PSO Algorithm and Its Application in GNSS Ambiguity Resolution." Applied Sciences 8, no. 6: 990.

Journal article
Published: 22 September 2017 in Remote Sensing
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The Terrain Observation with Progressive Scans (TOPS) acquisition mode of Sentinel-1A provides a wide coverage per acquisition and features a repeat cycle of 12 days, making this acquisition mode attractive for surface subsidence monitoring. A few studies have analyzed wide-coverage surface subsidence of Wuhan based on Sentinel-1A data. In this study, we investigated wide-area surface subsidence characteristics in Wuhan using 15 Sentinel-1A TOPS Synthetic Aperture Radar (SAR) images acquired from 11 April 2015 to 29 April 2016 with the Small Baseline Subset Interferometric SAR (SBAS InSAR) technique. The Sentinel-1A SBAS InSAR results were validated by 110 leveling points at an accuracy of 6 mm/year. Based on the verified SBAS InSAR results, prominent uneven subsidence patterns were identified in Wuhan. Specifically, annual average subsidence rates ranged from −82 mm/year to 18 mm/year in Wuhan, and maximum subsidence rate was detected in Houhu areas. Surface subsidence time series presented nonlinear subsidence with pronounced seasonal variations. Comparative analysis of surface subsidence and influencing factors (i.e., urban construction, precipitation, industrial development, carbonate karstification and water level changes in Yangtze River) indicated a relatively high spatial correlation between locations of subsidence bowl and those of engineering construction and industrial areas. Seasonal variations in subsidence were correlated with water level changes and precipitation. Surface subsidence in Wuhan was mainly attributed to anthropogenic activities, compressibility of soil layer, carbonate karstification, and groundwater overexploitation. Finally, the spatial-temporal characteristics of wide-area surface subsidence and the relationship between surface subsidence and influencing factors in Wuhan were determined.

ACS Style

Lv Zhou; Jiming Guo; Jiyuan Hu; Jiangwei Li; Yongfeng Xu; Yuanjin Pan; Miao Shi. Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR. Remote Sensing 2017, 9, 982 .

AMA Style

Lv Zhou, Jiming Guo, Jiyuan Hu, Jiangwei Li, Yongfeng Xu, Yuanjin Pan, Miao Shi. Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR. Remote Sensing. 2017; 9 (10):982.

Chicago/Turabian Style

Lv Zhou; Jiming Guo; Jiyuan Hu; Jiangwei Li; Yongfeng Xu; Yuanjin Pan; Miao Shi. 2017. "Wuhan Surface Subsidence Analysis in 2015–2016 Based on Sentinel-1A Data by SBAS-InSAR." Remote Sensing 9, no. 10: 982.

Journal article
Published: 14 September 2016 in Sensors
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The aim of this study was to investigate the relationship between surface subsidence and groundwater changes. To investigate this relationship, we first analyzed surface subsidence. This paper presents the results of a case study of surface subsidence in Beijing from 1 August 2007 to 29 September 2010. The Multi-temporal Interferometric Synthetic Aperture Radar (multi-temporal InSAR) technique, which can simultaneously detect point-like stable reflectors (PSs) and distributed scatterers (DSs), was used to retrieve the subsidence magnitude and distribution in Beijing using 18 ENVISAT ASAR images. The multi-temporal InSAR-derived subsidence was verified by leveling at an accuracy better than 5 mm/year. Based on the verified multi-temporal InSAR results, a prominent uneven subsidence was identified in Beijing. Specifically, most of the subsidence velocities in the downtown area were within 10 mm/year, and the largest subsidence was detected in Tongzhou, with velocities exceeding 140 mm/year. Furthermore, Gravity Recovery and Climate Experiment (GRACE) data were used to derive the groundwater change series and trend. By comparison with the multi-temporal InSAR-derived subsidence results, the long-term decreasing trend between groundwater changes and surface subsidence showed a relatively high consistency, and a significant impact of groundwater changes on the surface subsidence was identified. Additionally, the spatial distribution of the subsidence funnel was partially consistent with that of groundwater depression, i.e., the former possessed a wider range than the latter. Finally, the relationship between surface subsidence and groundwater changes was determined.

ACS Style

Jiming Guo; Lv Zhou; Chaolong Yao; Jiyuan Hu. Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing. Sensors 2016, 16, 1495 .

AMA Style

Jiming Guo, Lv Zhou, Chaolong Yao, Jiyuan Hu. Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing. Sensors. 2016; 16 (9):1495.

Chicago/Turabian Style

Jiming Guo; Lv Zhou; Chaolong Yao; Jiyuan Hu. 2016. "Surface Subsidence Analysis by Multi-Temporal InSAR and GRACE: A Case Study in Beijing." Sensors 16, no. 9: 1495.