Article
Geosciences, Multidisciplinary
Shih-Yuan Lin
Summary: Widespread land subsidence in urban areas is a growing problem worldwide, primarily caused by climate change, urbanization, and unbalanced groundwater extraction. This study focuses on Taipei City, which has faced challenges of ground subsidence. Through the analysis of Sentinel-1 remote sensing data, it is found that certain areas in the city experience significant surface subsidence, particularly in former river and lake beds. The combination of precipitation and groundwater level data reveals spatio-temporal heterogeneity of deformation. The study demonstrates the feasibility of using remote sensing data for widespread monitoring of subsidence hazards in urban planning and development.
GEOMATICS NATURAL HAZARDS & RISK
(2022)
Article
Environmental Sciences
Francesca Cigna, Deodato Tapete
Summary: This paper uses an integrated urban and satellite Interferometric Synthetic Aperture Radar (InSAR) approach to investigate land subsidence, urban growth, and population trends in the Metropolitan Area of Morelia in Mexico, revealing a predominant edge-expansion growth model and a doubling population over the last 30 years. The study also shows that subsidence is structurally-controlled by main normal faults and non-linearly deforming subsidence bowls develop at extraction wells in both old and newly urbanized sectors.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Juan S. Tamayo Duque, Antonio Miguel Ruiz-Armenteros, Guillermo E. Avila Alvarez, Gustavo Matiz, Joaquim J. Sousa
Summary: This study investigates the subsidence phenomenon in Bogota, Colombia, including both urban and rural areas. The analysis results indicate that the outer regions of the city experience the most significant subsidence, with velocities reaching approximately 5-6 cm/year.
Article
Chemistry, Multidisciplinary
Shasha Zhu, Xiaoqing Zuo, Ke Shi, Yongfa Li, Shipeng Guo, Chen Li
Summary: This study used InSAR and GNSS data to monitor surface subsidence in Kunming city, verifying the effectiveness of InSAR data and analyzing the extent and impact of subsidence. The results showed varying degrees of subsidence in different areas.
APPLIED SCIENCES-BASEL
(2022)
Article
Environmental Sciences
Kendall Wnuk, Wendy Zhou, Marte Gutierrez
Summary: The study used Interferometric Synthetic Aperture Radar (InSAR) time-series analysis to monitor and research surface deformations induced by the excavation of a subway station and rail crossover cavern in downtown Los Angeles, revealing previously unidentified deformations.
Article
Environmental Sciences
Haonan Jiang, Timo Balz, Jianan Li, Vishal Mishra
Summary: This article describes a short-term rapid subsidence event in the Bi Guiyuan community in Balitai Town, Tianjin City, and the use of InSAR technology to monitor the subsidence. Through the integration of findings from an InSAR analysis and geological studies, it is speculated that the event is related to the extraction of geothermal resources.
Article
Geochemistry & Geophysics
E. Chaussard, E. Havazli, H. Fattahi, E. Cabral-Cano, D. Solano-Rojas
Summary: Subsidence rates in Mexico City have been relatively constant since 1950, reaching up to 50 cm/year. There is no direct relationship between groundwater level fluctuations and pumping rates with subsidence rates, but a strong positive linear relationship exists between subsidence rates and the thickness of the upper aquitard. It is forecasted that total compaction of the upper aquitard may take around 150 years, leading to potential additional subsidence up to 30 m.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2021)
Article
Environmental Sciences
Meer Muhammad Sajjad, Juanle Wang, Zeeshan Afzal, Sajid Hussain, Aboubakar Siddique, Rehan Khan, Muhammad Ali, Javed Iqbal
Summary: This study used PS-InSAR techniques to monitor land surface deformation and groundwater levels in Lahore, Pakistan, and found that both land subsidence and groundwater levels are increasing, especially in the city center. The declining groundwater levels exacerbate land subsidence, and there is a significant positive correlation between groundwater levels and land subsidence.
Article
Environmental Sciences
Muhammad Afaq Hussain, Zhanlong Chen, Ying Zheng, Muhammad Shoaib, Junwei Ma, Ijaz Ahmad, Aamir Asghar, Junaid Khan
Summary: Groundwater dynamics driven by extraction and recharge are major factors contributing to subsidence in urban areas, particularly in rapidly expanding cities like Lahore. The use of PS-InSAR techniques based on Sentinel-1 data from January 2020 to December 2021 has proven to be effective in monitoring and analyzing land subsidence, providing valuable insights for urban planning, infrastructure development, and risk assessment related to subsidence issues. Areas with high groundwater discharge are prone to significant subsidence, while surrounding areas may show uplift during the study period.
Article
Environmental Sciences
Kim de Wit, Bente R. Lexmond, Esther Stouthamer, Olaf Neussner, Nils Doerr, Andreas Schenk, Philip S. J. Minderhoud
Summary: The Mekong delta, like many deltas around the world, is experiencing high rates of subsidence primarily due to natural compaction and groundwater overexploitation, which is damaging buildings and infrastructure in urbanized areas. Most buildings with piled foundations have lower subsidence rates and stability, with shallow compaction processes contributing up to 30 mm/year of differential subsidence. Piling depths can be used to quantify depth-dependent subsidence rates and local factors such as previous land use and variation in piling depth are proposed as important factors determining urban differential subsidence.
Article
Environmental Sciences
Yufang He, Guochang Xu, Hermann Kaufmann, Jingtao Wang, Hua Ma, Tong Liu
Summary: This paper proposes the integration of InSAR and LiDAR technologies to analyze urban surface micro slow subsidence and assess hazards for buildings. By using LiDAR data, the geolocation quality of InSAR and building contour extraction can be improved. The study reveals certain spatial patterns in land subsidence rates in the Shenzhen District.
Article
Green & Sustainable Science & Technology
Yong Han, Guangchun Liu, Jie Liu, Jun Yang, Xiangcheng Xie, Weitao Yan, Wenzhi Zhang
Summary: Jiaozuo, located in northwest Henan Province, is one of China's major anthracite production bases. Due to mining history, urbanization, and human activities, the area is prone to land subsidence, posing a threat to urban infrastructure and people's lives. Traditional leveling techniques are insufficient for monitoring large areas of land subsidence, and conventional methods may not provide timely results.
Article
Multidisciplinary Sciences
Yarong Yang, Jie Ma, Hong Liu, Lili Song, Wei Cao, Yifan Ren
Summary: Understanding the spatial distribution of urban forest ecosystem services is crucial for urban planning and sustainable development. This study used the i-Tree Eco model and kriging interpolation to quantify and map the services in Zhengzhou, China. The results showed significant spatial heterogeneity, with higher ecosystem services in watershed and woodland areas. This study provides a basis for future urban construction and management, contributing to improved ecosystem services and the health of urban residents.
Article
Environmental Sciences
Yuanmao Xu, Zhen Wu, Huiwen Zhang, Jie Liu, Zhaohua Jing
Summary: This article uses Interferometric Synthetic Aperture Radar (InSAR) to monitor land subsidence in the main urban area of Lanzhou, China, from October 26, 2014, to December 12, 2021. The results show that Lanzhou has a high risk of future subsidence, with linear subsidence dominating most areas along the Yellow River, railway lines, and villages and towns on the edges of urban areas. Factors influencing subsidence include precipitation, fault distribution, lithology of strata, high-rise buildings, and proximity to the river and railway. This poses a threat to the lives and properties of the population.
Article
Environmental Sciences
Huimin Sun, Hongxia Peng, Min Zeng, Simiao Wang, Yujie Pan, Pengcheng Pi, Zixuan Xue, Xinwen Zhao, Ao Zhang, Fengmei Liu
Summary: The superimposed effects of sea level rise caused by global warming and land subsidence seriously threaten the sustainable development of coastal cities. A study using the SBAS-InSAR technique to monitor land subsidence in the coastal city of Zhuhai in China revealed extensive subsidence and identified factors triggering the subsidence. The research also assessed the vulnerability of certain communities and roads in Zhuhai to subsidence using comprehensive index method and the analytic hierarchy process.
Article
Biology
Chao Wang, Quan Zou
Summary: A novel tool, DeepSoluE, was developed to predict protein solubility using a long-short-term memory (LSTM) network with hybrid features composed of physicochemical patterns and distributed representation of amino acids. The proposed model achieved more accurate and balanced performance than existing tools, serving as a bioinformatics tool for prescreening of potentially soluble targets to reduce the cost of wet-experimental studies.
Article
Engineering, Electrical & Electronic
Mengmeng Wang, Miao Li, Zhengjia Zhang, Tian Hu, Guojin He, Zhaoming Zhang, Guizhou Wang, Hua Li, Junlei Tan, Xiuguo Liu
Summary: This article proposed a radiance based split window (RBSW) algorithm for retrieving land surface temperature (LST) from Landsat 9 TIRS-2 data and improved the split-window covariance-variance ratio (SWCVR) algorithm for estimating atmospheric water vapor (AWV). The performance of the proposed method was assessed using simulation data and satellite observations, showing good accuracy in LST retrieval. The proposed algorithm has the potential to be a reliable method for LST generation from Landsat 9 TIRS-2 data without dependence on external atmospheric data.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Biology
Chao Wang, Qiang Yang
Summary: This paper presents ScerePhoSite, a machine learning method for fungal phosphorylation site identification. The method utilizes hybrid physicochemical features to represent sequence fragments, and combines LGB-based feature importance with sequential forward search to select the optimal feature subset. ScerePhoSite outperforms current available tools and shows a more robust and balanced performance. Furthermore, the impact and contribution of specific features on the model performance were investigated using SHAP values. ScerePhoSite is expected to be a useful bioinformatics tool for pre-screening possible phosphorylation sites in fungi and facilitating functional understanding of phosphorylation modification.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Biochemical Research Methods
Chao Wang, Quan Zou, Ying Ju, Hua Shi
Summary: A two-layer predictor called Enhancer-FRL was proposed for identifying enhancers and predicting their activities. The model utilized feature representation learning scheme and integrated multiview probabilistic features to achieve better performance and model robustness, outperforming state-of-the-art available toolkits on independent test dataset.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Environmental Sciences
Ji Ge, Hong Zhang, Lu Xu, Chunling Sun, Haoxuan Duan, Zihuan Guo, Chao Wang
Summary: A SHAP value-guided explanation model was proposed to improve the physical interpretability of SAR rice field extraction. Physical characteristics were extracted and combined with LSTM model and SHAP values for physical interpretation and weight fusion. Additionally, a spatial interpretation network was constructed for spatial refinement of the extraction results. The method demonstrated high interpretability and practical value compared to other methods.
Article
Environmental Sciences
Xiaohan Zheng, Chao Wang, Yixian Tang, Hong Zhang, Tianyang Li, Lichuan Zou, Shaoyang Guan
Summary: An adaptive high coherence temporal subsets (HCTSs) small baseline subset (SBAS)-InSAR method is proposed in this paper to monitor the degradation of peatlands in Southeast Asia. By capturing the high coherence time range and applying a time-weighted strategy, this method can calculate the deformation results of peatlands more accurately and observe the dynamic changes in deformation rate. The number of measurement points observed by this method is also significantly higher than the traditional SBAS-InSAR method.
Article
Environmental Sciences
Jing Wang, Sirui Tian, Xiaolin Feng, Bo Zhang, Fan Wu, Hong Zhang, Chao Wang
Summary: This paper proposes a novel framework called LPPCL for SAR automatic target recognition with limited labeled data, which not only learns informative feature representations but also preserves the local similarity property in the latent feature space. By embedding the local similarity of the original data as pseudo labels and using a multi-branch structure to improve the model's robustness, as well as replacing the global average pooling layer with a self-attentive pooling module, this framework significantly improves the performance of the model.
Article
Geochemistry & Geophysics
Tianyang Li, Chao Wang, Hong Zhang, Fan Wu, Xiaohan Zheng
Summary: This letter proposes a dual-domain transformer (DDFormer) semantic segmentation model for damaged buildings detection using a single post-earthquake high-resolution SAR image. The DDFormer achieves optimal detection accuracy with mean intersection over union (mIoU) and F-Score of 81.81% and 90%, respectively. In addition, the results are highly consistent with the Turkey Earthquake Report published by Microsoft with a correlation coefficient of 0.626, demonstrating the robustness and effectiveness of DDFormer.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Zhiyong Xu, Xiaolin Feng, Sirui Tian, Xiang-Jun Shen, Hong Zhang, Chao Wang
Summary: In this article, a novel edge preserved SAR despeckling method named EP-LRSID is proposed, which can reduce speckle noise while preserving rich edge details. By obtaining structural edge information from residuals, the low-rank model is applied to the despeckling process to better preserve structural information. Extensive experiments demonstrate that EP-LRSID achieves the highest despeckling performance with edge preservation compared to other state-of-the-art algorithms.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Engineering, Electrical & Electronic
Xin Zhao, Chao Wang, Jiankun He, Lianhui Liang, Yixian Tang, Hong Zhang
Summary: The use of InSAR data helps to explore the tectonic movement, fault slip rates, and strain distribution in the western Tibetan Plateau. The study reveals a high slip rate fault along the northern edge of the plateau, while the fault slip rates inside the plateau are much lower. Additionally, the strain rate is concentrated near the plateau margins and there is a low-strain region within the plateau.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Ji Ge, Hong Zhang, Lu Xu, Chun-Ling Sun, Chao Wang
Summary: A interpretable deep learning SAR rice area mapping method is proposed in this letter to improve accuracy and suppress wetland interference by extracting interpretable temporal features.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)