Article
Environmental Sciences
Aida Alvera-Azcarate, Dimitry Van der Zande, Alexander Barth, Joao Felipe Cardoso dos Santos, Charles Troupin, Jean-Marie Beckers
Summary: This method proposes a way to detect cloud shadows over the ocean by applying a series of tests. It is not dependent on the wavebands measured by a specific satellite sensor, and works with cloud shadows of all sizes, including very small object shadows.
REMOTE SENSING OF ENVIRONMENT
(2021)
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
Chemistry, Multidisciplinary
Hakan Erten, Erkan Bostanci, Koray Acici, Mehmet Serdar Guzel, Tunc Asuroglu, Ayhan Aydin
Summary: The Synthetic Aperture Radar (SAR) system provides high-resolution images, and semantic SAR image segmentation offers a computer-based solution to simplify segmentation tasks. We propose a novel approach for labeling Sentinel-1 SAR radar images provided by the European Space Agency (ESA). Our approach involves denoising the images and using deep neural networks to enhance the results of semantic segmentation. By comparing our newly created dataset with speckled noise and noise-free versions, we achieved a mean intersection over union (mIoU) of 70.60% and overall pixel accuracy (PA) of 92.23 with the HRNet model. The combination of our pipeline with deep neural networks showed significant improvements in challenging semantic segmentation accuracy and mIoU values on the newly created Sentinel-1 dataset, as assessed by the McNemar test.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Xiaolin Sun, Xi Chen, Liao Yang, Weisheng Wang, Xixuan Zhou, Lili Wang, Yuan Yao
Summary: This paper uses Synthetic Aperture Radar (SAR) technology to rapidly assess post-earthquake building damage and proposes a simple and fast method. The experiment proves that the method can accurately identify damaged and undamaged areas, providing important reference for post-earthquake building damage assessment.
Article
Construction & Building Technology
J. A. Avila-Haro, R. Gonzalez-Drigo, Y. F. Vargas-Alzate, L. Pujades, A. Barbat
Summary: The research aims to quantify the uncertainties related to the mechanical properties of unreinforced masonry (URM) and analyze their influence on the seismic performance of a representative building model in Barcelona, Spain. A probabilistic approach is illustrated with a case study on an existing seven-story URM building, showing that material property variability generates significant uncertainties in the seismic response of URM buildings.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Forestry
Philipp Kaiser, Henning Buddenbaum, Sascha Nink, Joachim Hill
Summary: This paper presents the use of multitemporal Sentinel-1 synthetic aperture radar (SAR) data to detect drought-affected and fire-endangered forest stands with high spatial and temporal resolution. The authors developed a novel Sentinel-1 Radar Drought Index (RDI) to reduce speckle noise and created a spatially explicit detection map of drought-affected forest stands in the Donnersberg study area in Germany. The results showed a significant correlation between RDI values and monthly mean temperatures, indicating the potential of Sentinel-1 data for timely detection of drought-affected and fire-prone forest areas.
Article
Environmental Sciences
Boyang Jiang, Xiaohuan Dong, Mingjun Deng, Fangqi Wan, Taoyang Wang, Xin Li, Guo Zhang, Qian Cheng, Shuying Lv
Summary: By establishing a validation field in Xianning, China, the geometric performance of ALOS, TerraSAR-X, Cosmo-SkyMed, RadarSat-2, and Chinese YG-3 SAR satellites was analyzed using the rational function model (RFM). The study found that each image could achieve sub-pixel positioning accuracy in range and azimuth direction when four ground control points (GCPs) were placed in the corners, resulting in a root mean square error (RMSE) of 1.5 pixels. The study also highlighted the effectiveness of an automated GCP-matching approach and showed that all five SAR satellite images can achieve sub-pixel positioning accuracy in range and azimuth direction when four GCPs are used.
Article
Geosciences, Multidisciplinary
Haojie Wang, Limin Zhang, Lin Wang, Ruilin Fan, Shengyang Zhou, Yejia Qiang, Ming Peng
Summary: This paper presents an integrated machine learning method for co-seismic landslide detection, combining multi-source data, pixel-based and object-based treatments, and ML techniques. Two case studies in China demonstrate the outstanding performance and generic nature of the proposed method in high-resolution co-seismic landslide detection.
Article
Computer Science, Artificial Intelligence
Zhi-Ze Wu, Xiao-Feng Wang, Le Zou, Li-Xiang Xu, Xin-Lu Li, Thomas Weise
Summary: Object detection from satellite images is challenging due to large coverage areas and objects of different scales. A hierarchical framework with deep feature extraction and inclined bounding box mechanism is proposed to improve efficiency. Experimental results demonstrate the superior performance of the proposed method compared to standalone state-of-the-art object detectors.
APPLIED SOFT COMPUTING
(2021)
Article
Environmental Sciences
Nabil Bachagha, Wenbin Xu, Xingjun Luo, Nicola Masini, Mondher Brahmi, Xinyuan Wang, Fatma Souei, Rosa Lasaponora
Summary: The availability of high-resolution satellite synthetic aperture radar (SAR) data has attracted the attention of scientists and archeologists. This research explores the potential of using a novel method (nonlocal-SAR) to detect buried archeological remains in steep terrain. The study confirms the capability of SAR data to reveal unknown archeological sites.
Article
Environmental Sciences
Yuliang Nie, Qiming Zeng, Haizhen Zhang, Qing Wang
Summary: This study proposed a new method to detect completely collapsed buildings using a single post-event full polarization SAR image, with two improvements made to building damage detection: providing a more effective solution for non-building area removal and significantly improving the classification performance of collapsed and standing buildings.
Article
Geochemistry & Geophysics
Xingliang Huang, Kaiqiang Chen, Deke Tang, Chenglong Liu, Libo Ren, Zheng Sun, Ronny Hansch, Michael Schmitt, Xian Sun, Hai Huang, Helmut Mayer
Summary: This study proposes a benchmark for building detection and fine-grained classification from high-resolution satellite imagery. The dataset includes extensive annotations of building instances, roof types, and building functions from cities worldwide. Additionally, finely aligned synthetic aperture radar images are provided for the development and evaluation of multimodal image approaches.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
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)
Article
Engineering, Industrial
Mohamadreza Sheibani, Ge Ou
Summary: The article proposes an adaptive local kernels method to improve the computational complexity of the standard MI algorithm, demonstrating its advantages in the post-earthquake regional building damage assessment.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Geochemistry & Geophysics
T. Manninen, E. Jaaskelainen, E. Tomppo
Summary: This study presents a new nonlocal averaging approach (STAl'SAR) to reduce speckle in high-resolution SAR images and improve the resolution of statistical parameters. The approach analyzes the similarity of SAR pixels based on statistical data and applies K-means clustering for image segmentation. Nonlocal averaging filtering is applied to both pixel backscattering values and statistical parameters.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Gino Caspari, Jegor Blochin, Timur Sadykov, Timo Balz
Article
Environmental Sciences
Hashir Tanveer, Timo Balz, Francesca Cigna, Deodato Tapete
Article
Environmental Sciences
Bahaa Mohamadi, Timo Balz, Ali Younes
Article
Environmental Sciences
Ling Yang, Jinfang Wang, Haojun Li, Timo Balz
Summary: This study analyzed the biases introduced by residual tropospheric delay on SPP solutions when using 9 different Zenith Tropospheric Delay models, showing that the biases mainly occur in the vertical direction and significant discrepancies are observed among different models at different geographical locations.
Article
Environmental Sciences
Haonan Jiang, Timo Balz, Francesca Cigna, Deodato Tapete
Summary: This study utilized high-resolution COSMO-SkyMed StripMap HIMAGE scenes to monitor long-term land subsidence in Wuhan, revealing several observable subsidence zones and investigating the underlying mechanisms through soil mechanics analysis.
Article
Environmental Sciences
Fabio Rocca, Deren Li, Stefano Tebaldini, Mingsheng Liao, Lu Zhang, Fabrizio Lombardini, Timo Balz, Norbert Haala, Xiaoli Ding, Ramon Hanssen
Summary: This research report outlines activities conducted under Dragon project 32278 on Three- and Four-Dimensional Topographic Measurement and Validation. The project was divided into three subprojects aimed at validating various satellite systems, developing new processing methods for SAR data, and improving methodologies for topographic mapping accuracy. Subproject 2 specifically focused on decorrelating targets using multi-baseline interferometric and tomographic SAR processing to accurately estimate target displacement over time.
Article
Geography, Physical
Fulong Chen, Wei Zhou, Yunwei Tang, Ru Li, Hui Lin, Timo Balz, Jin Luo, Pilong Shi, Meng Zhu, Chaoyang Fang
Summary: In this study, deformation monitoring of the Bagan heritage site in Myanmar was conducted using high resolution TerraSAR-X imagery and multi-temporal SAR interferometry. The results revealed displacement anomalies in pagodas linked to land cover change and previous earthquakes. The method showed millimetric precision and is suitable for monitoring large-scale World Heritage sites.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2022)
Article
Environmental Sciences
Zechao Bai, Yanping Wang, Timo Balz
Summary: Beijing has been experiencing land subsidence due to excessive groundwater exploitation. The implementation of the South-to-North Water Diversion Project has had a significant impact on the water consumption structure in Beijing, leading to changes in the land subsidence. Using PS-InSAR technology, this study investigates the evolution of land subsidence in Beijing over a decade and provides valuable insights, such as the correlation between changes in the water supply structure and groundwater level rise after 2015.
Article
Environmental Sciences
Jinghui Wang, Ke Gong, Timo Balz, Norbert Haala, Uwe Soergel, Lu Zhang, Mingsheng Liao
Summary: Radargrammetry is a useful approach for generating Digital Surface Models (DSMs) and offers an alternative to InSAR techniques. Stereo image matching plays a crucial role in determining the quality of DSMs for spatial-temporal analysis of landscapes and terrains. We propose a hierarchical semi-global matching (SGM) pipeline to reconstruct DSMs in forested and mountainous regions using stereo TerraSAR-X images.
Review
Environmental Sciences
Timo Balz
Summary: In-depth scientometric analyses were conducted on the full texts of papers published in MDPI's Remote Sensing between 2009 and 2021. The analyses reveal trends in publications, including an increase in the overall number of papers and a shift towards the use of SAR sensors in remote sensing research. The analyses also highlight distinctive styles and writing patterns among papers from different sub-fields, countries, and even cities. Factors such as readability and institutional co-authorship were also examined, showing a decrease in the overall readability of papers and revealing the ongoing 'scientific decoupling' between China and the USA in remote sensing research.
Article
Environmental Sciences
Gino Caspari, Torbjorn Preus Schou, Noah Steuri, Timo Balz
Summary: Norway leads in monitoring ice patches and glaciers for archaeological remains, with thousands of artifacts recovered due to melting. However, little is known about glacial archaeology in Norway's far north. Historical maps and LiDAR models are used to monitor ice flow and identify potential archaeological sites. An exploratory survey on the arctic island of Seiland reveals a previously unknown type of stone structure related to sheltering and reindeer activities.
Article
Remote Sensing
Haonan Jiang, Timo Balz, Francesca Cigna, Deodato Tapete, Jianan Li, Yakun Han
Summary: This paper introduces a new multi-sensor InSAR time series data fusion method to address cases when partial overlaps and/or temporal gaps exist. The proposed method, which combines the Power Exponential Knothe Model and LSTM neural network, successfully maps long-term surface deformation in Wuhan by fusing COSMO-SkyMed, TerraSAR-X, and Sentinel-1 SAR datasets.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
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
Remote Sensing
Francesca Cigna, Timo Balz, Deodato Tapete, Gino Caspari, Bihong Fu, Michele Abballe, Haonan Jiang
Summary: This paper showcases the main research avenues in optical and Synthetic Aperture Radar (SAR) remote sensing for archaeological and cultural heritage applications. It focuses on archaeological prospection and heritage site protection, utilizing novel sensor data, big data, and high-performance computing. Six demonstration use-cases are presented with various heritage asset types and research objectives. The results achieved contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Keren Dai, Ye Feng, Guanchen Zhuo, Yongbo Tie, Jin Deng, Timo Balz, Zhenhong Li
Summary: This study investigates the applicability of InSAR technology in identifying potential landslides in alpine-canyon terrain areas. Using time-series InSAR Sentinel-1 datasets, six potential landslides were detected and analyzed. The results show that combining ascending and descending data increases the detectable area, and L-band data performs better in identifying landslides with high vegetation coverage.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2022)
