IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium最新文献

{"title":"Latest Developments of the ATLID Instrument: A Year from Launch of the Earthcare Mission","authors":"K. Ghose, G. Tzeremes, K. Wallace, D. Bernaerts","doi":"10.1109/IGARSS46834.2022.9883728","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883728","url":null,"abstract":"ATLID (ATmospheric LIDar) is one of the active payloads of the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) spacecraft, the sixth Earth Explorer Mission of the European Space Agency (ESA) Living Planet Programme [1]. The EarthCARE mission has four instruments whose products will be used in a synergistic manner to retrieve vertical profiles of clouds and aerosols, and thereby determine characteristics of the radiative and micro-physical properties, and determine flux gradients within the atmosphere and top of atmosphere radiance. ATLID's objective is to measure vertical profiles of optically thin cloud and aerosol layers, as well as cloud boundary altitude. To achieve this, ATLID operates at an UV emission wavelength of 355.4 nm, emitting pulses of approximately 35 mJ and duration <35ns, at a repetition rate of 51 Hz, while pointing in a near nadir direction along the track of the satellite. The backscatter signal is collected by a telescope of aperture 620 mm and directed into the instrument focal plane assembly, where the atmospheric Mie and Rayleigh scattering contributions are separated and measured on separate channels. After the complete instrument integration, ATLID has had an ambient performance test campaign, followed by a mechanical, thermal-vacuum environmental and EMC qualification test campaign which included performance calibration and characterization in an approximation of on-orbit operational conditions. The analysis of the test data indicates that the instrument is compliant with expected performance goals, and will be able to meet them in orbit. The instrument has since been integrated onto the EarthCARE spacecraft, and is undergoing system level integrated checks. The EMC qualification will be completed at spacecraft level. Test data from the calibration campaign is currently being used to validate the processor software that will ingest the in-orbit data from the instrument and provide calibrated results on ground. In parallel, the flight spare of the ATLID laser has undergone a six month burn-in and lifetime test. Initial results from this test give confidence that the flight lasers have sufficient reliability to meet the designed for mission lifetime. This paper gives an overview of the design of ATLID, and presents some important results from the calibration campaign. Some preliminary data from the lifetime tests are also reported.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122855790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Terahertz Scattering and Emission from the Lunar Surface","authors":"Su-Long Wang, Takayoshi Yamada, Kun Shan Chen, Y. Kasai","doi":"10.1109/IGARSS46834.2022.9884114","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884114","url":null,"abstract":"Lunar Terahertz Surveyor for Kilometer-scale Mapping (TSUKIMI), a collaborative mission for lunar exploration, is introduced. We numerically explore terahertz scattering and emission from the lunar surface as an initial step forward. Regarding the characterization of the lunar surface, the power-law spectrum is adopted to model the roughness. While for the dielectric constant of the lunar surface, tentatively simplifying into a homogeneous condition. The scattering and emission models are briefly described. To investigate the terahertz scattering effect from the lunar surface, we conducted the preliminary experiments with dielectric constant and surface roughness using THz- TDS and T-Ray 4000 Picometric, respectively. The measurement results are subsequently presented.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122467906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Update of ALOS-3 Calibration and Validation Preparation Status","authors":"T. Tadono, Yousei Mizukami, J. Takaku, T. Hashiguchi, F. Ohgushi, Kazufumi Kobayashi","doi":"10.1109/IGARSS46834.2022.9884087","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884087","url":null,"abstract":"The “Advanced Optical Satellite” (ALOS-3, nicknamed “DAICHI-3”) is the next high-resolution optical mission as a successor of the Advanced Land Observing Satellite (ALOS) in Japan Aerospace Exploration Agency (JAXA), and will be launched in early 2022. The mission objectives of ALOS-3 are (1) to contribute safe and secure social including provision for natural disasters, and (2) to create and update geospatial information. The “wide-swath and high-resolution optical imager” is designed to be achieved the missions, which consists of the panchromatic band with 0.8 m ground sampling distance (GSD) and multispectral six bands with 3.2 m GSD, and the observation swath width is 70 km at nadir. This paper introduces the updated ALOS-3 calibration and validation preparation status at JAXA. As the target accuracy of ALOS-3 standard product, the absolute geometric accuracy is 1.25 m in horizontal and 2.5 m in vertical with GCPs (1 sigma), and the absolute radiometric accuracy is +/ - 10 % for the multispectral band.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122594910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Deep Learning Solution for Height Reconstruction in SAR Tomography","authors":"Wenyu Yang, A. Budillon, G. Ferraioli, V. Pascazio, Gilda Schirinzi, S. Vitale","doi":"10.1109/IGARSS46834.2022.9883582","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883582","url":null,"abstract":"Elevation estimation of canopy and ground is one of the main aims in dealing with forest scenario using Synthetic Aperture Radar (SAR) Tomography. Theoretically, SAR Tomography (TomoSAR) provides layover solution, allowing to reconstruct the elevation of the different contributions collapsing in the same resolution cell. TomoSAR is commonly applied on both urban and vegetated areas. Within the latter scenario, one of the most interesting outcomes of TomoSAR is the possibility of separating the canopy and ground, allowing the reconstruction of their height maps. Within this paper, we propose a Deep Learning (DL) based method for TomoSAR. In particular, a neural network was trained for predicting the elevation value of canopy and ground of an area under investigation, based on a stack of SAR fully polarimetric multi-baseline acquisitions. The method uses the Light Detection And Ranging (LiDAR) data as reference and exploit a classification approach. The process was operated on a tropical forest over the TropiSAR2009 test site in Paracou, French Guiana. Testing results on real data are presented showing interesting results.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122602671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Mask Interaction Network for SAR Ship Instance Segmentation","authors":"Tianwen Zhang, Xiaoling Zhang","doi":"10.1109/IGARSS46834.2022.9884709","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884709","url":null,"abstract":"We propose an enhanced mask interaction network (EMIN) for ship instance segmentation from synthetic aperture radar (SAR) images. EMIN adopts three techniques to improve SAR ship instance segmentation performance — 1) an atrous spatial pyramid pooling (ASPP) to enable multi-resolution feature responses, 2) a non-local block (NLB) to capture long-range spatial dependencies, and 3) a concatenation shuffle attention (CSA) to boost mask interaction benefits. Results on the public SAR ship detection dataset (SSDD) show that — 1) the above each technique can offer an observable accuracy gain, and 2) EMIN surpasses the original MIN by 2.1% detection AP and 2.4% mask AP on SSDD.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122624400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optical-SAR Decision Fusion with Markov Random Fields for High-Resolution Large-Scale Land Cover Mapping","authors":"Luca Maggiolo, David Solarna, G. Moser, S. Serpico","doi":"10.1109/IGARSS46834.2022.9884751","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884751","url":null,"abstract":"Decision fusion allows making a common decision by combining multiple opinions. In the context of remote sensing classification, such techniques are of great importance in all the cases where data collected by multiple sensors are merged into a final decision. Decision fusion may be used to combine the posterior probabilities associated with the output of single classifiers when applied to single sensor data. Meanwhile, techniques such as Markov Random Fields (MRFs) can integrate contextual information in the fusion process and are commonly used in classification. However, in the context of very large scale mapping (e.g., for global climate change monitoring), computation time can be critical and the application of both data fusion and spatial-contextual modeling comes with several constraints. In this paper, we propose a Bayesian decision fusion approach for optical-SAR image classification, integrated with a fast formulation of the iterated conditional modes (ICM) MRF-optimization algorithm based on a convolution operation. he validation on wide areas of Siberia proved the scalability and efficiency of the method for large scale applications.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122627177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On-Board RFI Detection Performance of a Multichannel SAR System with Digital Square-Law Detectors","authors":"T. Bollian, M. Younis, G. Krieger, A. Moreira","doi":"10.1109/IGARSS46834.2022.9883878","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883878","url":null,"abstract":"Radio Frequency Interference (RFI) is a growing problem for future Synthetic Aperture Radar (SAR) missions, resulting in data loss, image artifacts and undetected biases. A new approach for mitigating RFI is digital beamforming (DBF), which is possible with the next generation of multichannel SAR systems and allows for a spatial filtering of signals from different directions. While on-board RFI removal with DBF is challenging for spaceborne systems due to the computational load, past publications have shown that this problem can be overcome with DBF-based auxiliary beams by moving most of the processing to the ground without requiring the down-linking of all channels. A remaining problem of measuring RFI information with auxiliary beams is determining the interferer position. This paper shows the performance simulation of a series of digital square-law detectors which can be used to overcome this issue. It is shown that a series of digital square-law detectors provides the opportunity to simultaneously determine if RFI is present and under which direction, while maintaining a low system complexity. This is possible because the detectors provide a good probability of detection and false alarm rate even if the data rate is decimated. The simulated system performs well for a decimation factor of 110.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114594806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"InSAR Analysis Ready Data","authors":"Lan-Wei Wang, M. Garthwaite, Zheyuan Du, Alistair Deane, J. McCubbine, Mitchell Wheeler, Aaron O'Hehir, Ben Davies","doi":"10.1109/IGARSS46834.2022.9884464","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9884464","url":null,"abstract":"The Sentinel-1 satellite constellation provides temporally dense and high spatial resolution Synthetic Aperture Radar (SAR) imagery. The open data policy and global coverage of Sentinel-1 enables applications that require long time series, such as modelling surface deformation rates from Interferometric Synthetic Aperture Radar (InSAR) data, to be scaled-up and generate continent-scale products. In this paper, we present a workflow to generate interferometric products from the Copernicus Australasia Regional Data Hub archive of Single Look Complex (SLC) Sentinel-1 data, with the objective to derive a continent-wide ground surface deformation map for Australia. The proposed workflow can be used to generate Sentinel-1 InSAR Analysis Ready Data (ARD) suitable for ongoing monitoring of ground deformation.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121991465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Causality for Remote Sensing: An Exploratory Study","authors":"Soronzonbold Otgonbaatar, M. Datcu, B. Demir","doi":"10.1109/IGARSS46834.2022.9883060","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883060","url":null,"abstract":"Causality is one of the most important topics in a Machine Learning (ML) research, and it gives insights beyond the dependency of data points. Causality is a very vital concept also for investigating the dynamic surface of our living planet. However, there are not many attempts for integrating a causal model in Remote Sensing (RS) methodologies. Hence, in this paper, we propose to use patch-based RS images and to represent each patch-based image by a single variable (e.g. entropy). Then we use a Structural Equation Model (SEM) to study their cause-effect relation. Moreover, the SEM is a simple causal model characterized by a Directed Acyclic Graph (DAG). Its nodes are causal variables, and its edges represent causal relationships among causal variables if and only if causal variables are dependent.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116842432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FOAM Emissivity Modelling with Foam Properties Tuned by Frequency and Polarization","authors":"M. Anguelova, E. Dinnat, L. Kilic, M. Bettenhausen, S. English, C. Prigent, T. Meissner, J. Boutin, S. Newman, Ben Johnson, S. Yueh, M. Kazumori, F. Weng, A. Stoffelen, C. Accadia","doi":"10.1109/IGARSS46834.2022.9883610","DOIUrl":"https://doi.org/10.1109/IGARSS46834.2022.9883610","url":null,"abstract":"We model the sea foam emissivity at frequencies from 1 to 89 GHz. This model is part of the work done by an international science team to develop a radiative transfer model of reference quality for the ocean surface emissivity from L band to infrared frequencies. A study of the sensitivity to different foam properties (foam layer thickness and upper limit of the foam void fraction) guided the effort to tune the foam emissivity model by frequency and polarization. The results show that the differences between simulated and observed brightness temperatures decrease when using the tuned foam model.","PeriodicalId":426003,"journal":{"name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}