Article
Geosciences, Multidisciplinary
Noha Ismail Medhat, Masa-yuki Yamamoto, Cristiano Tolomei, Assia Harbi, Said Maouche
Summary: This study used satellite observation techniques to monitor ground displacement and landslides in the Mila Basin, Algeria. The findings suggest that the ground movements in the area are slow and influenced by factors such as earthquakes, precipitation, terrain topography, and soil moisture. This study is significant for landslide hazard identification and risk assessment in the region.
Article
Environmental Sciences
Farid Nur Bahti, Chih-Chung Chung, Chun-Chen Lin
Summary: This paper conducted a parametric test to optimize the settings of Sentinel 1A PS-InSAR and SBAS-InSAR and confirmed the recommended settings through verification with GNSS in landslide cases. The results indicate that SBAS is feasible for practical landslide monitoring.
Article
Environmental Sciences
Horst Hammer, Silvia Kuny, Antje Thiele
Summary: This paper introduces an algorithm for enhancing coherence contrast by combining careful filtering of amplitude and interferometric phase images. Applied to an airborne interferometric SAR image pair recorded by Hensoldt Sensors GmbH's SmartRadar experimental sensor, the algorithm aims to automatically detect vehicle tracks. The enhancement scheme proposed in this paper shows that the mean gray-level difference between low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%, demonstrating its effectiveness in detecting tracks more completely.
Article
Environmental Sciences
Bin Pan, Xianjian Shi
Summary: Conducting landslide recognition research is of notable practical significance for disaster management. This study presents a dual-polarization SAR image landslide recognition approach that combines ascending and descending time-series information while considering polarization channel details, achieving significant improvements in recognition accuracy.
Article
Engineering, Electrical & Electronic
Carlos Villamil Lopez, Uwe Stilla
Summary: This article introduces a new method for automatically estimating all relevant parameters of oil storage tanks using high-resolution synthetic aperture radar (SAR) images, including capacity, roof type, and stored oil volume. By utilizing temporal information from SAR time series, more accurate and robust estimates can be obtained.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Environmental Sciences
Wenjie He, Jianjun Zhu, Juan M. Lopez-Sanchez, Cristina Gomez, Haiqiang Fu, Qinghua Xie
Summary: This study evaluates the capacity of TanDEM-X interferometric synthetic aperture radar (InSAR) data assisted by an external digital terrain model (DTM) to estimate forest canopy height. A ground-to-volume ratio estimation model is proposed for precise estimation of canopy height. The results show that the proposed method has high accuracy and performance in forest height estimation, compared with existing methods and LiDAR data.
Article
Geography, Physical
Luigi Guerriero, Ernesto P. Prinzi, Domenico Calcaterra, Sabatino Ciarcia, Diego Di Martire, Francesco M. Guadagno, Giuseppe Ruzza, Paola Revellino
Summary: Deep-seated landslides play a significant role in relief shaping and human settlements, with the Buonalbergo landslide showing a nearly constant rate of movement for the past three decades and potential geological factors influencing its future evolution.
Article
Engineering, Electrical & Electronic
Carlos Villamil Lopez, Uwe Stilla
Summary: In this article, a novel SAR change detection method is proposed for the monitoring of man-made objects. The method detects changes by identifying the appearance and disappearance of strong scatterers, ignoring changes to natural targets. Additionally, an object-based change analysis step is introduced.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Jun Hu, Wenqing Wu, Rong Gui, Zhiwei Li, Jianjun Zhu
Summary: This article proposes a method for the selection of homogeneous pixels using a stacked autoencoder (SAE) network. Based on deep learning image classification, this method shows good performance in the application of multitemporal synthetic aperture radar interferometry (InSAR).
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Geological
Xiaojie Liu, Chaoying Zhao, Qin Zhang, Zhong Lu, Zhenhong Li, Chengsheng Yang, Wu Zhu, Jing Liu-Zeng, Liquan Chen, Chuanjin Liu
Summary: Active landslides along the Jinsha River corridor pose serious threats and attract widespread attention due to their large scale, number, and potential disaster chain characteristics. Conventional InSAR-based methods face challenges in mapping landslides efficiently in this region, leading to the development of a new procedure integrating surface deformation and geomorphological features for large-area landslide mapping.
ENGINEERING GEOLOGY
(2021)
Article
Environmental Sciences
Yunkai Deng, Weiming Tian, Ting Xiao, Cheng Hu, Hong Yang
Summary: This paper proposes an improved method for selecting high-quality pixels in natural scenes for GB-SAR interferometry, including PS, QPS, and DS, using ADI and TPC methods. Experimental results show that the number of HQPs can be significantly increased while slightly sacrificing phase quality.
Article
Environmental Sciences
Alexander Zakharov, Liudmila Zakharova
Summary: This study presents the results of interferometric processing and analysis of SAR data over a landslide territory. The analysis reveals the characteristics and possible triggering factors of the landslide movement. The study shows that the landslide developed within a depression, triggered by reservoir filling and subsequent water level fluctuations. Increased precipitation also accelerated the landslide movement rate.
Article
Multidisciplinary Sciences
Flora Giudicepietro, Sonia Calvari, Walter De Cesare, Bellina Di Lieto, Federico Di Traglia, Antonietta M. Esposito, Massimo Orazi, Pierdomenico Romano, Anna Tramelli, Teresa Nolesini, Nicola Casagli, Pierfrancesco Calabria, Giovanni Macedonio
Summary: In this study, we have identified precursors of the October-November 2022 effusive crisis at Stromboli through seismic and thermal camera measurements. The seismic precursors, caused by an escalating degassing process, were observed before the lava overflows on October 9 and November 16. The analysis of seismic and thermal data also showed inflation of the crater area, especially evident in the October 9 episode, indicating the importance of these findings for understanding Stromboli's eruptive mechanisms and early warning of potentially dangerous phenomena.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Nicusor Necula, Mihai Niculita, Simone Fiaschi, Rinaldo Genevois, Paolo Riccardi, Mario Floris
Summary: Landslides pose an increasing threat to urbanized areas and affected communities, prompting the need for advanced techniques like MT-InSAR for landslide investigation and monitoring. The study in Eastern Romania demonstrates the effectiveness of using SAR images and numerical modeling to identify active landslides and understand their mechanisms.
Article
Environmental Sciences
Fabio Bovenga, Ilenia Argentiero, Alberto Refice, Raffaele Nutricato, Davide O. Nitti, Guido Pasquariello, Giuseppe Spilotro
Summary: This study uses MTInSAR to investigate the ground stability of two hilly villages in Italy and finds evidence of nonlinear displacements in key infrastructures.
Article
Computer Science, Interdisciplinary Applications
Francesco Marchese, Nicola Genzano, Michael Nolde, Alfredo Falconieri, Nicola Pergola, Simon Plank
Summary: A new eruption started at Kilauea volcano in Hawaii on December 20, 2020, resulting in the formation of a new lava lake. This study used the Normalized Hot Spot Indices algorithm to investigate the lava lake and found that it provided accurate information about the lake and its variations. By correcting for the influence of solar irradiation, the study estimated the radiant flux from the hottest pixels.
ENVIRONMENTAL MODELLING & SOFTWARE
(2022)
Article
Engineering, Electrical & Electronic
Max Helleis, Marc Wieland, Christian Krullikowski, Sandro Martinis, Simon Plank
Summary: This study compared the effectiveness of various convolutional neural network architectures in water and flood mapping using Sentinel-1 amplitude data, evaluating their performance globally and enhancing their generalization capacity through model training for flood events. The models trained on data without distinct inundation showed excellent performance in mapping water extent during flood events and performed well on the Sen1Floods11 dataset.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Feng Zhao, Jordi J. Mallorqui, Juan M. Lopez-Sanchez
Summary: Polarimetric persistent scatterer interferometry (PolPSI) enhances the phase quality of interferograms by using polarimetric optimization algorithms. This research investigates the impact of image resolution on the performance of PolPSI. The results show that the ability to select high-quality pixels decreases and the polarimetric optimization improves the density and quality of persistent scatterers, especially as the image resolution degrades.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Moritz Roesch, Simon Plank
Summary: This study introduces a novel object-oriented classification approach for mapping lava flows in unvegetated areas of active volcanoes using high-resolution satellite data. The results show that the developed method produces good results for monitoring volcanic hazards.
Article
Environmental Sciences
Lorenzo Ammirati, Rita Chirico, Diego Di Martire, Nicola Mondillo
Summary: The study uses multispectral satellite images to map the land area affected by the flood caused by the tailing dam collapse in Brasil. The analysis shows drastic changes in vegetation rate, soil, and water after the disaster. This technique provides a tool for quickly classifying flood areas and monitoring and planning reclamation and restoration activities.
Article
Environmental Sciences
Krisztina Kelevitz, Alessandro Novellino, Arnaud Watlet, James Boyd, James Whiteley, Jonathan Chambers, Colm Jordan, Tim Wright, Andrew Hooper, Juliet Biggs
Summary: This paper presents a case study of using ESA's Sentinel-1 InSAR data to study the behavior and seasonal variations of the Hollin Hill landslide in the UK. The study shows that InSAR data provides valuable information about landslide movement and behavior. The installation of corner reflectors improves the accuracy of InSAR measurements and allows tracking of the most recent landslide movement.
Article
Geochemistry & Geophysics
M. Angarita, R. Grapenthin, S. Plank, F. J. Meyer, H. Dietterich
Summary: Morphological processes induce meter-scale elevation changes, which can provide insights into volcanic eruptive activity and related hazards. Synthetic aperture radar (SAR) is a useful tool for observing surface changes during inclement weather and at night. In this study, a new method is developed to estimate meter-scale vertical morphological changes using SAR amplitude images and a high-quality DEM. The method is validated through simulations and applied to real data from volcanic eruptions.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
(2022)
Article
Chemistry, Analytical
Alejandro Mestre-Quereda, Juan M. Lopez-Sanchez, Jordi J. Mallorqui
Summary: Geometrical decorrelation is one of the sources of noise in Synthetic Aperture Radar (SAR) interferograms, and it can be compensated by range filtering. Multiple range filtering methods have been proposed, and this manuscript analyzes their advantages and limitations. A new adaptive filtering approach is also proposed, which improves filtering accuracy, especially in steep areas and vegetation-covered regions.
Article
Environmental Sciences
Mohammad Amin Khalili, Behzad Voosoghi, Luigi Guerriero, Saeid Haji-Aghajany, Domenico Calcaterra, Diego Di Martire
Summary: This paper aims to determine the best interval for interpreting long-term deformation processes and identifying displacement patterns by using three unsupervised clustering algorithms and implementing the advanced integration method for atmospheric phase screen correction. Through the comparison of signals corrected by the AIM and the GPS station, as well as similarity measures and Davies-Bouldin index scores, the SBAS technique with the unsupervised K-medians method has been chosen as the accurate and reliable interval.
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
Chemistry, Multidisciplinary
Mohammad Amin Khalili, Giuseppe Bausilio, Chiara Di Muro, Sebastiano Perriello Zampelli, Diego Di Martire
Summary: This study investigates landslide risks in Southern Italy using DInSAR analysis on radar imagery. The findings reveal active slope movements and the threat to the San Marco dei Cavoti hamlet. This research contributes to a better understanding of landslide dynamics and highlights the need for further investigation or intervention measures.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Michelle Rygus, Alessandro Novellino, Ekbal Hussain, Fifik Syafiudin, Heri Andreas, Claudia Meisina
Summary: InSAR time series measurements are difficult to interpret due to the large volume of data generated. We propose a novel framework to interpret the data using dimensionality reduction, clustering, and change detection methods. This approach provides an objective way to monitor and understand ground movements in large deforming areas.
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
Remote Sensing
Sen Du, Jordi J. Mallorqui, Feng Zhao
Summary: This paper proposes a method called Patch Like Reduction (PLR) to reduce patch-like errors in SAR Offset Tracking (OT). The method finds a sensor and scene independent threshold to remove high amplitude pixels that are prone to cause patch-like errors. Experimental results demonstrate that the proposed method can effectively reduce patch-like errors.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Geosciences, Multidisciplinary
Stefan Schlaffer, Marco Chini, Wouter Dorigo, Simon Plank
Summary: The North American Prairie Pothole Region (PPR) is a significant wetland system that plays a crucial role in biodiversity, water storage, and flood management. This study developed a robust approach using Sentinel-1 data and high-resolution topographical information to classify and monitor the open water extent in the prairie wetlands. The results demonstrate the potential of Sentinel-1 data for high-resolution monitoring of prairie wetlands.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2022)
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)
