Article
Environmental Sciences
Jinhua Zhang, Changqing Ke, Xiaoyi Shen, Jinxin Lin, Ru Wang
Summary: Shanghai has experienced microscale land subsidence in recent years, affecting the operational safety of subways and other infrastructures. Using high-resolution TerraSAR-X images and the PS-InSAR method, the land subsidence along the subways in Shanghai was analyzed. The results showed overall stability in land subsidence along the subway lines, with significant deformation mainly occurring along suburban subways that were newly open to traffic. Factors such as human-induced ground loads, foundation pit constructions, and road constructions were identified as the main causes of local land subsidence. The rise in groundwater level was found to be closely related to the deceleration in land subsidence after the subway lines were open to traffic.
Article
Environmental Sciences
Marco Anzidei, Giovanni Scicchitano, Giovanni Scardino, Christian Bignami, Cristiano Tolomei, Antonio Vecchio, Enrico Serpelloni, Vincenzo De Santis, Carmelo Monaco, Maurilio Milella, Arcangelo Piscitelli, Giuseppe Mastronuzzi
Summary: The study reveals the combined effects of land subsidence and sea-level rise on the coastal areas in southern Italy, focusing on potential flooding scenarios in the coming decades. The results show significant land subsidence in some areas, leading to a high risk of extensive land flooding in the next few decades.
Article
Environmental Sciences
Osman Orhan
Summary: Konya, located in the Konya Closed Basin, is the most important agricultural production region in Turkey, but faces threats to agriculture due to declining groundwater levels and unsuitable agricultural activities for the climate conditions. Through the use of InSAR technique and auxiliary data, the causes of land subsidence in the region were investigated, revealing a strong correlation between land subsidence and groundwater level changes. Regional patterns of cultivated area and urbanization, major factors in groundwater consumption, were also identified through optic data analysis.
ENVIRONMENTAL MONITORING AND ASSESSMENT
(2021)
Article
Geochemistry & Geophysics
Zhongling Huang, Corneliu Octavian Dumitru, Zongxu Pan, Bin Lei, Mihai Datcu
Summary: This study addresses the challenges in large-scale high-resolution SAR image classification with imbalanced classes, geographic diversity, and label noise through deep transfer learning and a specific loss function. The proposed method optimizes performance while reducing the risk of overfitting, and demonstrates good generalization in tasks such as MSTAR target recognition.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Engineering, Geological
Zhenkai Zhou, Xin Yao, Kaiyu Ren, Hongyan Liu
Summary: In this study, InSAR technology was used to obtain fine-scale surface deformation at Beijing Capital International Airport and investigate the formation mechanism of a ground fissure.
ENGINEERING GEOLOGY
(2022)
Article
Chemistry, Analytical
Emil Bayramov, Giulia Tessari, Martin Kada
Summary: This study compared vertical and horizontal surface displacements derived from different satellite missions to detect oil extraction-induced subsidence in the Tengiz oilfield. The results showed consistent ground motion patterns for vertical displacement velocities and larger variations and deviations for horizontal displacement velocities. Spatial analysis indicated that subsidence processes in the oilfield are influenced by factors such as seismic faults and terrain characteristics, in addition to oil production activities.
Article
Remote Sensing
Qiuxiang Tao, Fengyun Wang, Zaijie Guo, Leyin Hu, Chen Yang, Tongwen Liu
Summary: This study found that increasing the number of interferograms and lowering the coherence threshold can improve the accuracy of SBAS InSAR results, better reflecting the spatial distribution and variation trend of mining subsidence. However, excessive interferograms and overly low coherence thresholds can increase data processing difficulties and the differences between SBAS InSAR and leveling-monitored results.
EUROPEAN JOURNAL OF REMOTE SENSING
(2021)
Article
Engineering, Ocean
Yi Zhang, Yafei Luo, Haijun Huang, Yanxia Liu, Haibo Bi, Xinyuan Zhang, Zehua Zhang, Kuifeng Wang, Zechao Bai, Xinghua Zhou
Summary: In recent years, noticeable subsidence depressions have occurred along the coastal zone of the Yellow River Delta. By using satellite imagery and technology, a typical subsidence bowl was discovered, and the relationship between settlement and water content was established, providing guidance for future mining.
MARINE GEORESOURCES & GEOTECHNOLOGY
(2023)
Article
Engineering, Geological
Fumeng Zhao, Wenping Gong, Huiming Tang, Shiva P. Pudasaini, Tianhe Ren, Zhan Cheng
Summary: Land subsidence caused by over-exploitation of groundwater resources poses a significant hazard in many large cities globally. Assessing infrastructure risks under the threat of land subsidence is crucial for urban planning and design. This study proposes an integrated approach combining land subsidence, ground fissures, and elements at risk. Time-series Interferometric Synthetic Aperture Radar (InSAR) is used to study ground surface deformation, and differential settlement is assessed using an angular distortion index. Land use classification analysis is conducted to identify potentially affected elements using optical and radar images with an object-based approach. Finally, a risk matrix integrating differential settlement, ground fissures, and land use classification results is employed to assess land subsidence risk. The effectiveness of the proposed method is demonstrated through a risk assessment of land subsidence in Xi'an, China, and the advantages of synergetic land use classification over pixel-based classification are illustrated.
ENGINEERING GEOLOGY
(2023)
Article
Environmental Sciences
Baolong Wu, Haonan Wang, Jianlai Chen
Summary: This paper presents a method for power transmission tower detection in mountainous areas using single-baseline and multi-baseline SAR interferometry coherence images, which show better feature enhancement effectiveness compared to SAR amplitude images. It also proposes a novel feature enhancement method using multi-baseline SAR interferometry-correlated synthesis images. Experimental results demonstrate that the detection performance using multi-baseline SAR interferometry-correlated synthesis images improves by more than 43.6% compared to using SAR amplitude images when benchmark deep learning-based detectors are used.
Article
Green & Sustainable Science & Technology
Huizhi Duan, Yongsheng Li, Bingquan Li, Hao Li
Summary: Ground deformation plays a crucial role in delta sustainability. This study presents a fast InSAR time-series processing approach for Sentinel-1 TOPS images, demonstrating its effectiveness in mapping surface deformation over the Yellow River Delta. The findings highlight several significant subsidence events in the study area, attributed to geological factors, underground brine and hydrocarbon extraction, as well as sediment consolidation and compaction.
Article
Geography, Physical
Bin Zhang, Ling Chang, Alfred Stein
Summary: This research focuses on addressing two challenges in InSAR technology: identifying common ground targets from different SAR datasets in space and concatenating time series when dealing with temporal dynamics. The study achieved dynamic extraction of ground features from multiple SAR datasets by describing geolocation uncertainty and calculating cross volumes using Monte Carlo methods.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Corneliu Octavian Dumitru, Gottfried Schwarz, Mihai Datcu
Summary: The article explores the automated analysis of SAR and multispectral images, proposing an advanced SAR image analysis system design that can generate semantically annotated classification results and refine classification results by incorporating expert knowledge and additional knowledge extracted from public databases.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Review
Geography, Physical
Peichao Gao, Zhilin Li, Zhe Qin
JOURNAL OF SPATIAL SCIENCE
(2019)
Article
Computer Science, Information Systems
Jun Chen, Shu Peng, Hao Chen, Xuesheng Zhao, Yuejing Ge, Zhilin Li
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2020)
Article
Computer Science, Information Systems
Jianting Yang, Kongyang Zhao, Muzi Li, Zhu Xu, Zhilin Li
Summary: Automated generalization of road network data is challenging due to the complexity of identifying complex junctions, which do not have regular geometric boundaries and are scale-dependent. Existing methods using geometric and topological statistics to characterize and identify complex junctions are error-prone, scale-dependent, and lack generality. This study overcomes these challenges by clarifying the topological boundaries of complex junctions, leading to a more accurate identification method that ensures the integrity of the junctions and simplifies them effectively.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Article
Chemistry, Multidisciplinary
Xinghua Cheng, Zhilin Li
Summary: This study suggests that configurational entropy capturing both compositional and configurational information can optimize DEM encryption, and proposes an encryption algorithm based on the integration of chaos system and linear prediction, which is validated through experiments.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Information Systems
Qian Peng, Zhilin Li, Jun Chen, Wanzeng Liu
Summary: This project introduces a complexity-based method to achieve a good matching between image resolution and map scale, ensuring both accuracy and user preference.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2021)
Article
Environmental Sciences
Bo Zhang, Guoxiang Liu, Rui Zhang, Yin Fu, Qiao Liu, Jialun Cai, Xiaowen Wang, Zhilin Li
Summary: The paper introduces an improved neighborhood-based ratio method to identify the boundaries and track the spatiotemporal changes of glacial lakes using a series of SAR images. Through monitoring two glacial lakes, the method demonstrates reliability and accuracy in detecting these changes.
Article
Computer Science, Information Systems
Hong Zhang, Tian Lan, Zhilin Li
Summary: By studying the street networks in Hong Kong from 1971 to 2018, it was found that cities evolve in a fractal manner, with the dimensions of geometric fractal, topological fractal, and hierarchical fractal increasing over time. This indicates a more mature and complex street network structure with a core-periphery pattern and progressively optimized structural elements. The findings contribute to a deeper understanding of urban development.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2022)
Article
Geography, Physical
Sawaid Abbas, Qian Peng, Man Sing Wong, Zhilin Li, Jicheng Wang, Kathy Tze Kwun Ng, Coco Yin Tung Kwok, Karena Ka Wai Hui
Summary: This study established a hyperspectral library for urban tree species in Hong Kong, developed a Deep Neural Network classification model for accurate identification of tree species, and analyzed the seasonal patterns of urban tree species using hyperspectral imaging. The research provides a unique baseline for understanding hyperspectral characteristics and seasonality of urban tree species.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Geography, Physical
Bai Zhu, Yuanxin Ye, Liang Zhou, Zhilin Li, Gaofei Yin
Summary: A robust and effective method for co-registration of aerial imagery and LiDAR data is proposed, conducted in two stages including coarse registration and fine registration. The method demonstrates robustness to geometric distortions and radiometric changes in experiments, achieving registration accuracy of less than 2 pixels for all cases, outperforming current four state-of-the-art methods.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Geography, Physical
Jiaqi Tian, Xiaolin Zhu, Jin Chen, Cong Wang, Miaogen Shen, Wei Yang, Xiaoyue Tan, Shuai Xu, Zhilin Li
Summary: This study conducted two simulation experiments and found that optimal parameters for MVC and smoothing filters can improve the accuracy of vegetation phenology detection, especially in reducing the impact on SOS extraction accuracy. Additionally, significant spatial heterogeneity was observed in the optimal parameters for both the MVC and smoothing filters.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2021)
Article
Computer Science, Information Systems
Peng Ti, Tao Xiong, Yuhong Qiu, Liying Wang, Zhilin Li
Summary: Landmark buildings play a significant role in spatial cognition on maps. This study proposes an automatic method for generating representations of landmark building outlines, which involves extracting and simplifying the outlines from street-view photographs and symbolizing them in 3D. The experimental results show that the method successfully facilitates the recognition and perception of landmark buildings on maps.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2023)
Article
Environmental Sciences
Jicheng Wang, Xin Yan, Li Shen, Tian Lan, Xunqiang Gong, Zhilin Li
Summary: Weakly supervised semantic segmentation methods using only image-level annotations are gaining popularity in automated building extraction. Class activation maps (CAMs) are crucial for these methods but often result in inaccurate and incomplete results. We propose a scale-invariant multi-level context aggregation network to improve the quality of CAMs, achieving state-of-the-art results on building extraction with high completeness.
Article
Geography
Tian Lan, Zhilin Li, Qian Peng, Xinyu Gong
TRANSACTIONS IN GIS
(2020)
Article
Environmental Sciences
LI Zhilin, Xinyu Gong, Jun Chen, Jon Mills, LI Songnian, Xu Zhu, Ti Peng, Wu Hao
JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS
(2020)
Article
Geography
Tian Lan, Zhilin Li, Hong Zhang
ANNALS OF THE AMERICAN ASSOCIATION OF GEOGRAPHERS
(2019)
