Bochen Zhou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Bochen Zhou has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Geshuang Li
Henan College of Surveying and Mapping, Zhengzhou, China
2 shared publications - Hui Liu
Advanced Research Institute for Digital-Twin Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, China
2 shared publications - Mengyuan Zhu
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
2 shared publications - Wenfei Zhao
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
2 shared publications - Zechao Bai
North China University of Technology
2 shared publications - Ke Zheng
College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
1 shared publication
Latest Publications
- Open Access
- 31 August 2023
- Published by MDPI AG in Remote Sensing
- Vol. 15 (17) , 4293
Soil and Rockfill Dams Safety Assessment for Henan Province: Monitoring, Analysis and Prediction
It is of great significance to explore the spatial and temporal evolution of soil and rockfill dam deformation, ensuring the safety of people’s lives and healthy economic development. The spatial and temporal evolution patterns of deformation of 17 large soil and rockfill dams in Henan Province were analyzed by using the PS-InSAR technique and 55 Sentinel-1A images from March 2017 to September 2021. Based on factors such as reservoir water level and rainfall, a series of analyses were conducted on the Xiaolangdi soil and rockfill dam, which has the highest dam height and the most prominent deformation problem. The monitoring results show that all the soil and rockfill dams in Henan Province have different degrees of deformation, and there is a close relationship between dam height and deformation. In addition, the deformation rate of the Xiaolangdi soil and rockfill dam in the past five years presents a “Stepped Shape” deformation trend from the top to the bottom of the dam. The deformation of the upper, middle, and lower parts of the dam body reaches 80 mm, 40 mm, and 20 mm, respectively, among which the middle part of the dam crest has the largest deformation. Furthermore, the time series prediction model for sparrow search algorithm Long Short-Term Memory considering the moving average filter (MAF-SSA-LSTM) is proposed to predict and accurately analyze the future deformation of Xiaolangdi soil and rockfill dam with RMSE of 1.526 mm, MAE of 1.447 mm, and MAPE of 2.22%, which proved that the model has high prediction accuracy. It can truly reflect the overall deformation trend of the dam body. The results provide a theoretical basis and decision basis for the census of reservoir safety conditions and deformation history retrieval in Henan Province.
- 31 August 2023
- Published by MDPI AG in Remote Sensing
- Vol. 15 (17) , 4293
Open AccessSoil and Rockfill Dams Safety Assessment for Henan Province: Monitoring, Analysis and Prediction
It is of great significance to explore the spatial and temporal evolution of soil and rockfill dam deformation, ensuring the safety of people’s lives and healthy economic development. The spatial and temporal evolution patterns of deformation of 17 large soil and rockfill dams in Henan Province were analyzed by using the PS-InSAR technique and 55 Sentinel-1A images from March 2017 to September 2021. Based on factors such as reservoir water level and rainfall, a series of analyses were conducted on the Xiaolangdi soil and rockfill dam, which has the highest dam height and the most prominent deformation problem. The monitoring results show that all the soil and rockfill dams in Henan Province have different degrees of deformation, and there is a close relationship between dam height and deformation. In addition, the deformation rate of the Xiaolangdi soil and rockfill dam in the past five years presents a “Stepped Shape” deformation trend from the top to the bottom of the dam. The deformation of the upper, middle, and lower parts of the dam body reaches 80 mm, 40 mm, and 20 mm, respectively, among which the middle part of the dam crest has the largest deformation. Furthermore, the time series prediction model for sparrow search algorithm Long Short-Term Memory considering the moving average filter (MAF-SSA-LSTM) is proposed to predict and accurately analyze the future deformation of Xiaolangdi soil and rockfill dam with RMSE of 1.526 mm, MAE of 1.447 mm, and MAPE of 2.22%, which proved that the model has high prediction accuracy. It can truly reflect the overall deformation trend of the dam body. The results provide a theoretical basis and decision basis for the census of reservoir safety conditions and deformation history retrieval in Henan Province.
- Open Access
Applicability Assessment of Multi-Source DEM-Assisted InSAR Deformation Monitoring Considering Two Topographical Features
The high-precision digital elevation model (DEM) is of great significance for improving the accuracy of InSAR deformation monitoring. In today’s free opening of multi-source DEM, there is no consensus on how to select suitable DEMs to assist InSAR in deformation monitoring for different landforms. This article introduces five types of DEMs: ALOS12.5, SRTM-1, ASTER V3, AW3D30, and Copernicus 30, and uses SBAS-InSAR technology to analyze the applicability of deformation monitoring in the Qinghai Tibet Plateau and Central China Plain regions. The coverage, average value, standard deviation, and unwrapping efficiency of the phase unwrapping results, the temporal deformation rate curves of six random deformation points in the key deformation area, as well as the consistency with the second-level data and the comparative analysis of RMSE of all deformation points, show that in the Qinghai Tibet Plateau region, Copernicus 30 is the best, followed by ASTER V3, AW3D30, and SRTM-1 having low accuracy, and ALOS12.5 is the worst. In the Central China Plain region, AW3D30 is the best, followed by Copernicus 30, SRTM-1, and ASTER V3 having low accuracy, and ALOS12.5 is still the worst. Although ALOS12.5 has the highest resolution, it is not recommended for deformation monitoring based on its worst performance in plateau and plain areas. It is recommended to use Copernicus 30 in plateau areas and AW3D30 for deformation monitoring in plain areas.
Open AccessApplicability Assessment of Multi-Source DEM-Assisted InSAR Deformation Monitoring Considering Two Topographical Features
The high-precision digital elevation model (DEM) is of great significance for improving the accuracy of InSAR deformation monitoring. In today’s free opening of multi-source DEM, there is no consensus on how to select suitable DEMs to assist InSAR in deformation monitoring for different landforms. This article introduces five types of DEMs: ALOS12.5, SRTM-1, ASTER V3, AW3D30, and Copernicus 30, and uses SBAS-InSAR technology to analyze the applicability of deformation monitoring in the Qinghai Tibet Plateau and Central China Plain regions. The coverage, average value, standard deviation, and unwrapping efficiency of the phase unwrapping results, the temporal deformation rate curves of six random deformation points in the key deformation area, as well as the consistency with the second-level data and the comparative analysis of RMSE of all deformation points, show that in the Qinghai Tibet Plateau region, Copernicus 30 is the best, followed by ASTER V3, AW3D30, and SRTM-1 having low accuracy, and ALOS12.5 is the worst. In the Central China Plain region, AW3D30 is the best, followed by Copernicus 30, SRTM-1, and ASTER V3 having low accuracy, and ALOS12.5 is still the worst. Although ALOS12.5 has the highest resolution, it is not recommended for deformation monitoring based on its worst performance in plateau and plain areas. It is recommended to use Copernicus 30 in plateau areas and AW3D30 for deformation monitoring in plain areas.