Article
Environmental Sciences
Shiyao Li, Run Wang, Lei Wang, Shaoyu Liu, Jiang Ye, Hang Xu, Ruiqing Niu
Summary: This paper proposes a remote sensing monitoring approach of mining activities based on deep learning and integrated interferometric synthetic aperture radar technique. The approach accurately identifies and extracts the spatial location of mine patches and analyzes mining activities in the study area. The proposed approach achieves high recognition accuracy and shows promising prospects for engineering applications.
Article
Remote Sensing
Qingyu Li, Hannes Taubenboeck, Yilei Shi, Stefan Auer, Robert Roschlaub, Clemens Glock, Anna Kruspe, Xiao Xiang Zhu
Summary: This study explores the detection of undocumented buildings using remote sensing techniques, extracting morphological parameters and landscape metrics to understand their distribution in Bavaria, Germany. The results reveal that most undocumented buildings are located in low-density regions, indicating a potentially greater fragmentation of the landscape by buildings than currently documented.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Plant Sciences
Weiwei Sun, Qijin He, Jiahong Liu, Xiao Xiao, Yaxin Wu, Sijia Zhou, Selimai Ma, Rongwan Wang
Summary: This study established a scalable annual and inter-annual quality prediction model for summer maize in different growth periods using hierarchical linear modeling (HLM) combined with hyperspectral and meteorological data. Compared to the multiple linear regression (MLR) using vegetation indices (VIs), the HLM showed improved prediction accuracy. The results demonstrated that meteorological factors, especially precipitation, had a significant influence on grain quality.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Zhaoxu Zhang, Wei Xu, Zhenwei Shi, Qiming Qin
Summary: The study focused on the complexity of drought occurrence and integrated multiple factors to create a Comprehensive Drought Monitoring Index (CDMI). It was found that CDMI had negative correlations with areas covered by drought and positive correlations with relative soil moisture and crop yield. The application of CDMI in Henan Province during the summer maize growing season proved its reliability for monitoring and assessing agricultural drought.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Foyez Ahmed Prodhan, Jiahua Zhang, Fengmei Yao, Lamei Shi, Til Prasad Pangali Sharma, Da Zhang, Dan Cao, Minxuan Zheng, Naveed Ahmed, Hasiba Pervin Mohana
Summary: The study aims to monitor drought in South Asia using deep learning approach, showing that the DFNN model outperformed others for SMDI prediction and captured high spatial variability of drought patterns. The model also displayed good stability and high correlation coefficients with in-situ SPEI, indicating its applicability for comprehensive drought monitoring.
Article
Environmental Sciences
Teerawong Laosuwan, Yannawut Uttaruk, Tanutdech Rotjanakusol
Summary: This study uses satellite remote sensing to monitor Thailand's atmospheric environment, focusing on carbon dioxide (CO2) levels from 2017 to 2021. The results show that CO2 concentrations fluctuate with seasons, with higher concentrations in winter and summer correlating with temperature changes, and decreased concentrations during the rainy season due to increased plant photosynthesis.
POLISH JOURNAL OF ENVIRONMENTAL STUDIES
(2023)
Article
Computer Science, Hardware & Architecture
Xiangyong Zhang
Summary: In the modern era, the remote sensing capabilities of wireless sensor networks have been utilized to protect and restore river ecosystems. Remote sensing technology can detect changes in river ecosystems, identify vulnerable areas, and measure the effectiveness of restoration efforts over time. This technology significantly improves our ability to protect and restore river ecosystems, leading to improved sustainability and biodiversity conservation.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Environmental Sciences
Wei Wei, Jing Zhang, Liang Zhou, Binbin Xie, Junju Zhou, Chuanhua Li
Summary: This study evaluated the applicability of different drought indices for monitoring drought events in China. It found that VCI and TCI are better for monitoring long-term drought conditions, while SPI-1 has a higher correlation with PCI for short-term drought monitoring. SMCI has better correlation with short-term in situ drought index. Correlations with combined drought indices were better than with single drought indices.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Liang Chen, Zhiqiang Lan, Shuo Qian, Xiaojuan Hou, Le Zhang, Jian He, Xiujian Chou
Summary: This study proposed an adaptive real-time sensing method for microseismic monitoring from the perspective of systematic design. It first constructed an over-complete learning dictionary by analyzing noise and signal structure characteristics. Then, it analyzed the key performance factors of random projection through comparison between different matrices according to the learned dictionary. It also explored the relationship between signal sparsity and residual energy decay during data recovery with greedy pursuit algorithms and presented an energy-ratio-based sparsity adaptive matching algorithm. Finally, the performance evaluation of the proposed method was conducted using synthetic signals and field monitoring data.
IEEE SENSORS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Runyu Fan, Ruyi Feng, Wei Han, Lizhe Wang
Summary: The study proposed a UFZ mapping method using OpenStreetMap-based sample generation and a bi-branch neural network (BibNet) to comprehensively utilize remote sensing images and social sensing data. Experiments conducted in Shenzhen City and Hong Kong City showed high overall accuracy, indicating the effectiveness of the proposed method in mapping UFZs.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Engineering, Electrical & Electronic
Yao Xiao, Chang-Qing Ke, Yu Cai, Xiaoyi Shen, Zifei Wang, Vahid Nourani, Drolma Lhakpa
Summary: This study accurately identified glacier changes in the southeastern Tibetan Plateau using a combination of photogrammetry, optical remote sensing, and synthetic aperture radar datasets. The results showed that the glacier area decreased from the 1970s to 2020, with a total degradation of approximately 2759.14 km(2). Rising summer temperatures may be the driving force behind this continuous decline. The findings of this study provide accurate glacier information for glacier monitoring and modeling studies.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2023)
Article
Geosciences, Multidisciplinary
Zhicheng Wang, Zhiqiang Gao
Summary: This study presents an approach for high-frequency dynamic monitoring of flood disaster using a remote sensing data cube. By removing clouds and fusing data, high spatiotemporal resolution monitoring is achieved.
Article
Thermodynamics
Baohua Wen, Fan Peng, Qingxin Yang, Ting Lu, Beifang Bai, Shihai Wu, Feng Xu
Summary: Computer vision technology and high-resolution remote sensing images provide opportunities for accurately measuring the evolution of natural and artificial environments on Earth. This study focuses on the green evolution of courtyard buildings with roofed courtyards, and identifies the adoption and evolution patterns of different technologies in different villages.
BUILDING SIMULATION
(2023)
Article
Geochemistry & Geophysics
Xiangli Nie, Ruofei Gao, Rui Wang, Deliang Xiang
Summary: A novel online multiview deep forest architecture is proposed in this study, which processes data from different views through a cascade structure and multiple layers of ensemble, resulting in learning a deep forest model in an online manner from a stream of multiview data.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2021)
Article
Environmental Sciences
Liya Zhao, Qi Yang, Qiang Zhao, Jingwei Wu
Summary: By utilizing time-series remote sensing data, this study successfully detected the dynamics of abandoned salinized farmland in the Hetao region. The results show that cropland area has been expanding in recent decades with significant desalinization progress, mainly attributed to the popularization of water-saving irrigation technology, the construction of artificial drainage facilities, and a shift in cropping patterns. This study demonstrates the promising possibility of reutilizing abandoned salinized farmland through a leaching campaign.
Article
Engineering, Geological
Mariano Di Napoli, Francesco Carotenuto, Andrea Cevasco, Pierluigi Confuorto, Diego Di Martire, Marco Firpo, Giacomo Pepe, Emanuele Raso, Domenico Calcaterra
Review
Environmental Sciences
Lorenzo Solari, Matteo Del Soldato, Federico Raspini, Anna Barra, Silvia Bianchini, Pierluigi Confuorto, Nicola Casagli, Michele Crosetto
Article
Environmental Sciences
Qingkai Meng, Pierluigi Confuorto, Ying Peng, Federico Raspini, Silvia Bianchini, Shuai Han, Haocheng Liu, Nicola Casagli
Article
Environmental Sciences
Mariano Di Napoli, Diego Di Martire, Giuseppe Bausilio, Domenico Calcaterra, Pierluigi Confuorto, Marco Firpo, Giacomo Pepe, Andrea Cevasco
Summary: This study utilized a combined approach, including Machine Learning techniques and GIS, to assess shallow landslide susceptibility in the Cinque Terre area. It provided a susceptibility map describing detachment, transit, and runout, which can be used for land planning and risk management purposes.
Review
Environmental Sciences
Matteo Del Soldato, Pierluigi Confuorto, Silvia Bianchini, Paolo Sbarra, Nicola Casagli
Summary: The combination of GNSS and InSAR techniques has shown to be useful for studying ground deformation and water vapor measurements, and has been widely applied. Research indicates that combining these two techniques can improve knowledge within the scientific community and foster the development of new approaches.
Article
Geosciences, Multidisciplinary
P. Confuorto, C. Sepe, C. Del Gaudio, D. Di Martire, G. M. Verderame, D. Calcaterra
Summary: The Municipality Emergency Plan of Palma Campania in Southern Italy is a fundamental tool to face natural and anthropogenic risks, providing a detailed risk assessment and tailored intervention model for population safety during calamities. The plan aims at long-term prevention and risk awareness, serving as a valuable approach for municipalities affected by multiple risks to define the best strategies for risk reduction.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2021)
Article
Remote Sensing
Pierluigi Confuorto, Matteo Del Soldato, Lorenzo Solari, Davide Festa, Silvia Bianchini, Federico Raspini, Nicola Casagli
Summary: This study depicts three different operational continuous monitoring experiences based on Sentinel-1 data in Italy and analyzes the results obtained in one year. The results show distinct distributions of anomalies in different regions, suggesting further improvements and applications are needed.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Environmental Sciences
Pierluigi Confuorto, Camilla Medici, Silvia Bianchini, Matteo Del Soldato, Ascanio Rosi, Samuele Segoni, Nicola Casagli
Summary: Continuous monitoring of Earth surface displacements using MTInSAR data enables the identification of movement anomalies caused by slope instability and subsidence. A Machine Learning algorithm, such as Random Forest, was used to assess the probability of these anomalies occurring and generate maps. These maps provide useful indications for geohazard prevention and need to be periodically updated and refined.
Article
Geography, Physical
Davide Festa, Manuela Bonano, Nicola Casagli, Pierluigi Confuorto, Claudio De Luca, Matteo Del Soldato, Riccardo Lanari, Ping Lu, Michele Manunta, Mariarosaria Manzo, Giovanni Onorato, Federico Raspini, Ivana Zinno, Francesco Casu
Summary: This study utilizes satellite-based multi-temporal interferometric datasets to investigate terrain changes in Italy, and classifies triggering factors, showing that landslides and subsidence events are the main causes of terrain deformation.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Review
Geosciences, Multidisciplinary
Federico Raspini, Francesco Caleca, Matteo Del Soldato, Davide Festa, Pierluigi Confuorto, Silvia Bianchini
Summary: This paper presents a critical review of the existing literature on the use of satellite SAR imagery for subsidence analysis. The review highlights the growth in scientific production and the increasing interest in subsidence studies. It also emphasizes the role of satellite InSAR as an operative tool in subsidence research, while acknowledging the remaining technical and operational challenges.
EARTH-SCIENCE REVIEWS
(2022)
Article
Geography, Physical
Davide Festa, Nicola Casagli, Francesco Casu, Pierluigi Confuorto, Claudio De Luca, Matteo Del Soldato, Riccardo Lanari, Michele Manunta, Mariarosaria Manzo, Federico Raspini
Summary: By applying machine learning techniques to integrate and analyze large-scale interferometric datasets, it can effectively detect high-displacement areas and classify ground motion sources, showing promising performance especially in northern Italy.
GISCIENCE & REMOTE SENSING
(2022)
Article
Environmental Sciences
Silvia Bianchini, Pierluigi Confuorto, Emanuele Intrieri, Paolo Sbarra, Diego Di Martire, Domenico Calcaterra, Riccardo Fanti
Summary: This study presents a sinkhole susceptibility and risk assessment in Guidonia-Bagni di Tivoli plain, Italy, using a machine learning model. The results show that lithology, travertine thickness, groundwater, and land use are the main factors affecting sinkhole formation. The risk map indicates that 2% of the study area is at higher risk, especially in the main urban fabric. The study demonstrates the potential of machine learning models in predicting sinkhole areas and providing useful information for urban planning and geohazard risk management.
GEOCARTO INTERNATIONAL
(2022)
Article
Engineering, Geological
Pierluigi Confuorto, Nicola Casagli, Francesco Casu, Claudio De Luca, Matteo Del Soldato, Davide Festa, Riccardo Lanari, Mariarosaria Manzo, Giovanni Onorato, Federico Raspini
Summary: The use of synthetic aperture radar imagery for landslide inventory updates is essential for risk management and territorial planning. The application of automatic SAR data processing has been used to update the Italian national landslide database. The study demonstrates that the nationwide use of Sentinel-1 MTInSAR data could provide fundamental support for landslide inventory updates.
Article
Remote Sensing
Davide Festa, Alessandro Novellino, Ekbal Hussain, Luke Bateson, Nicola Casagli, Pierluigi Confuorto, Matteo Del Soldato, Federico Raspini
Summary: In this paper, an unsupervised and automated approach based on Principal Component Analysis (PCA) and K-means clustering is presented to detect patterns of ground deformation from Interferometric Synthetic Aperture Radar (InSAR) Time Series. The approach combines PCA for data dimensionality reduction and feature extraction with K-means clustering to identify spatially and temporally coherent displacement phenomena. The results demonstrate the potential applicability of this approach to automated ground motion analysis.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Geography
E. Raso, A. Mandarino, G. Pepe, D. Calcaterra, Andrea Cevasco, P. Confuorto, M. Di Napoli, M. Firpo
Summary: This study presents the geomorphological investigation and mapping within Cinque Terre National Park, showcasing the impact of human modification on the landscape. A new geomorphological map at 1:18,000 scale outlines the various landforms and deposits, highlighting the vulnerability of terraced slopes due to farmland abandonment. The map serves as a crucial tool for future hazard assessment, zoning, and land management strategies.
