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- 2018
- green tide
- Elegant End-to-End Fully Convolutional Network (E3FCN)
- deep learning
- remote sensing
- Moderate Resolution Imaging Spectroradiometer (MODIS)
- Optoelectronic Information Science and Engineering
- Ocean University of China
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Process control and quality assurance in remote laser beam welding by optical coherence tomography
摘要： Remote laser beam welding significantly outperforms conventional joining techniques in terms of flexibility and productivity. This process benefits in particular from a highly focused laser radiation and thus from a well-defined heat input. The small spot sizes of high brilliance laser beam sources, however, require a highly dynamic and precise positioning of the beam. Also, the laser intensities typically applied in this context result in high process dynamics and in demand for a method to ensure a sufficient weld quality. A novel sensor concept for remote laser processing based on optical coherence tomography (OCT) was used for both quality assurance and edge tracking. The OCT sensor was integrated into a 3D scanner head equipped with an additional internal scanner to deflect the measuring beam independently of the processing beam. With this system, the surface topography of the process zone as well as the surrounding area can be recorded. Fundamental investigations on aluminum, copper, and galvanized steel were carried out. Initially, the influence of the material, the angle of incidence, the welding position within the scanning field, and the temperature on the OCT measuring signal were evaluated. Based on this, measuring strategies for edge tracking were developed and validated. It was shown that orthogonal measuring lines in the advance of the process zone can reliably track the edge of a fillet weld. By recording the topography in the trailing area of the process zone, it was possible to assess the weld seam quality. Comparing the results to microscopic measurements, it was shown that the system is capable of clearly identifying characteristic features of the weld seam. Also, it was possible to observe an influence of the welding process on the surface properties in the heat-affected zone, based on the quality of the measuring signal.
关键词： inline quality assurance,optical coherence tomography,remote laser beam welding,process control
更新于2025-11-28 14:24:20
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Characterization of a non-contact imaging scintillator-based dosimetry system for total skin electron therapy
摘要： Surface dosimetry is required for ensuring effective administration of total skin electron therapy (TSET); however, its use is often reduced due to the time consuming and complex nature of acquisition. A new surface dose imaging technique was characterized in this study and found to provide accurate, rapid and remote measurement of surface doses without the need for post-exposure processing. Disc-shaped plastic scintillators (1 mm thick x 15 mm) were chosen as optimal-sized samples and designed to attach to a flat-faced phantom for irradiation using electron beams. Scintillator dosimeter response to radiation damage, dose rate, and temperature were studied. The effect of varying scintillator diameter and thickness on light output was evaluated. Furthermore, the scintillator emission spectra and impact of dosimeter thickness on surface dose were also quantified. Since the scintillators were custom-machined, dosimeter-to-dosimeter variation was tested. Scintillator surface dose measurements were compared to those obtained by optically stimulated luminescence dosimeters (OSLD). Light output from scintillator dosimeters evaluated in this study was insensitive to radiation damage, temperature, and dose rate. Maximum wavelength of emission was found to be 422 nm. Dose reported by scintillators was linearly related to that from OSLDs. Build-up from placement of scintillators and OSLDs had a similar effect on surface dose (3.9% increase). Variation among scintillator dosimeters was found to be 0.3 ± 0.2%. Scintillator light output increased linearly with dosimeter thickness (~1.9×/mm). All dosimeter diameters tested were able to accurately measure surface dose. Scintillator dosimeters can potentially improve surface dosimetry-associated workflow for TSET in the radiation oncology clinic. Since scintillator data output can be automatically recorded to a patient medical record, the chances of human error in reading out and recording surface dose are minimized.
关键词： non-contact,surface dosimetry,optical imaging,scintillator,remote
更新于2025-11-14 15:30:11
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Multi-Spectral Ship Detection Using Optical, Hyperspectral, and Microwave SAR Remote Sensing Data in Coastal Regions
摘要： The necessity of efficient monitoring of ships in coastal regions has been increasing over time. Multi-satellite observations make it possible to effectively monitor vessels. This study presents the results of ship detection methodology, applied to optical, hyperspectral, and microwave satellite images in the seas around the Korean Peninsula. Spectral matching algorithms are used to detect ships using hyperspectral images with hundreds of spectral channels and investigate the similarity between the spectra and in-situ measurements. In the case of SAR (Synthetic Aperture Radar) images, the Constant False Alarm Rate (CFAR) algorithm is used to discriminate the vessels from the backscattering coefficients of Sentinel-1B SAR and ALOS-2 PALSAR2 images. Validation results exhibited that the locations of the satellite-detected vessels showed good agreement with real-time location data within the Sentinel-1B coverage in the Korean coastal region. This study presented the probability of detection values of optical and SAR-based ship detection and discussed potential causes of the errors. This study also suggested a possibility for real-time operational use of vessel detection from multi-satellite images based on optical, hyperspectral, and SAR remote sensing, particularly in the inaccessible coastal regions off North Korea, for comprehensive coastal management and sustainability.
关键词： ship detection,coastal region,hyperspectral,sustainability,optical remote sensing,SAR
更新于2025-09-23 15:23:52
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An Interplay between Photons, Canopy Structure, and Recollision Probability: A Review of the Spectral Invariants Theory of 3D Canopy Radiative Transfer Processes
摘要： Earth observations collected by remote sensors provide unique information to our ever-growing knowledge of the terrestrial biosphere. Yet, retrieving information from remote sensing data requires sophisticated processing and demands a better understanding of the underlying physics. This paper reviews research efforts that lead to the developments of the stochastic radiative transfer equation (RTE) and the spectral invariants theory. The former simplifies the characteristics of canopy structures with a pair-correlation function so that the 3D information can be succinctly packed into a 1D equation. The latter indicates that the interactions between photons and canopy elements converge to certain invariant patterns quantifiable by a few wavelength independent parameters, which satisfy the law of energy conservation. By revealing the connections between plant structural characteristics and photon recollision probability, these developments significantly advance our understanding of the transportation of radiation within vegetation canopies. They enable a novel physically-based algorithm to simulate the 'hot-spot' phenomenon of canopy bidirectional reflectance while conserving energy, a challenge known to the classic radiative transfer models. Therefore, these theoretical developments have a far-reaching influence in optical remote sensing of the biosphere.
关键词： vegetation remote sensing,stochastic radiative transfer equation,spectral invariants theory
更新于2025-09-23 15:23:52
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Remote sensing quantifies widespread abundance of permafrost region disturbances across the Arctic and Subarctic
摘要： Local observations indicate that climate change and shifting disturbance regimes are causing permafrost degradation. However, the occurrence and distribution of permafrost region disturbances (PRDs) remain poorly resolved across the Arctic and Subarctic. Here we quantify the abundance and distribution of three primary PRDs using time-series analysis of 30-m resolution Landsat imagery from 1999 to 2014. Our dataset spans four continental-scale transects in North America and Eurasia, covering ~10% of the permafrost region. Lake area loss (?1.45%) dominated the study domain with enhanced losses occurring at the boundary between discontinuous and continuous permafrost regions. Fires were the most extensive PRD across boreal regions (6.59%), but in tundra regions (0.63%) limited to Alaska. Retrogressive thaw slumps were abundant but highly localized (<10?5%). Our analysis synergizes the global-scale importance of PRDs. The findings highlight the need to include PRDs in next-generation land surface models to project the permafrost carbon feedback.
关键词： permafrost,disturbances,Subarctic,fires,remote sensing,lakes,retrogressive thaw slumps,Arctic
更新于2025-09-23 15:23:52
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Heat Response of Global Vegetation Biomes to Ongoing Climate Warming Based on Remote Sensing
摘要： Research is needed by global change scientists on how global vegetation biomes respond to ongoing climate warming. To address this issue, we selected study sites with significant climate warming for diverse vegetation biomes, and used global gridded temperature and remote sensing data over the past 32 years (1982–2013). The results suggested that climate warming in areas above approximately 60° N is relaxing the heat-constraints on vegetation activity, thus promoting plant growth; whereas, in mid to low latitude areas, ongoing climate warming probably imposes negative impacts on vegetation biomes through drought and heat stress. Understanding these potential effects is important for planning adaptation strategies to mitigate the impacts of climate warming, particularly for agro-ecosystems.
关键词： climate warming,heat responses,remote sensing,global vegetation biomes
更新于2025-09-23 15:23:52
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Optical Remote Sensing Potentials for Looting Detection
摘要： Looting of archaeological sites is illegal and considered a major anthropogenic threat for cultural heritage, entailing undesirable and irreversible damage at several levels, such as landscape disturbance, heritage destruction, and adverse social impact. In recent years, the employment of remote sensing technologies using ground-based and/or space-based sensors has assisted in dealing with this issue. Novel remote sensing techniques have tackled heritage destruction occurring in war-conflicted areas, as well as illicit archeological activity in vast areas of archaeological interest with limited surveillance. The damage performed by illegal activities, as well as the scarcity of reliable information are some of the major concerns that local stakeholders are facing today. This study discusses the potential use of remote sensing technologies based on the results obtained for the archaeological landscape of Ayios Mnason in Politiko village, located in Nicosia district, Cyprus. In this area, more than ten looted tombs have been recorded in the last decade, indicating small-scale, but still systematic, looting. The image analysis, including vegetation indices, fusion, automatic extraction after object-oriented classification, etc., was based on high-resolution WorldView-2 multispectral satellite imagery and RGB high-resolution aerial orthorectified images. Google Earth? images were also used to map and diachronically observe the site. The current research also discusses the potential for wider application of the presented methodology, acting as an early warning system, in an effort to establish a systematic monitoring tool for archaeological areas in Cyprus facing similar threats.
关键词： image analysis,satellite data,remote sensing archaeology,looting,Cyprus
更新于2025-09-23 15:23:52
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Identifying Emerging Reservoirs along Regulated Rivers Using Multi-Source Remote Sensing Observations
摘要： The number of reservoirs is rapidly increasing owing to the growth of the world’s economy and related energy and water needs. Yet, for the vast majority of reservoirs around the world, their locations and related information, especially for newly dammed reservoirs, are not readily available due to financial, political, or legal considerations. This study proposes an automated method of identifying newly dammed reservoirs from time series of MODIS-derived NDWI (normalized difference water index) images. Its main idea lies in the detection of abrupt changes in the NDWI time series that are associated with land-to-water conversion due to the reservoir impoundment. The proposed method is tested in the upper reach of the Yellow River that is severely regulated by constructed reservoirs. Our results show that five newly dammed reservoirs were identified in the test area during 2000–2018. Validated against high-resolution Google Earth imagery, our method is effective to determine both locations of the emerging medium-size reservoirs and the timing of their initial water impoundments. Such information then allows for a refined calculation of the reservoir inundation extents and storage capacities through the combination of higher-resolution Landsat imagery and SRTM DEM. The comparison of our estimated reservoir areas and capacities against documented information further indicates that the integration of multi-mission remote sensing data may provide useful information for understanding reservoir operations and impacts on river discharges. Our method also demonstrates a potential for regional or global inventory of emerging reservoirs, which is crucial to assessing human impacts on river systems and the global water cycle.
关键词： reservoir,time series,NDWI,remote sensing,BFAST,Yellow River
更新于2025-09-23 15:23:52
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FusionCNN: a remote sensing image fusion algorithm based on deep convolutional neural networks
摘要： In remote sensing image fusion field, traditional algorithms based on the human-made fusion rules are severely sensitive to the source images. In this paper, we proposed an image fusion algorithm using convolutional neural networks (FusionCNN). The fusion model implicitly represents a fusion rule whose inputs are a pair of source images and the output is a fused image with end-to-end property. As no datasets can be used to train FusionCNN in remote sensing field, we constructed a new dataset from a natural image set to approximate MS and Pan images. In order to obtain higher fusion quality, low frequency information of MS is used to enhance the Pan image in the pre-processing step. The method proposed in this paper overcomes the shortcomings of the traditional fusion methods in which the fusion rules are artificially formulated, because it learns an adaptive strong robust fusion function through a large amount of training data. In this paper, Landsat and Quickbird satellite data are used to verify the effectiveness of the proposed method. Experimental results show that the proposed fusion algorithm is superior to the comparative algorithms in terms of both subjective and objective evaluation.
关键词： Convolutional neural networks,Deep learning,Remote sensing image fusion,Image enhancement
更新于2025-09-23 15:23:52
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PhenoFly Planning Tool: flight planning for high-resolution optical remote sensing with unmanned areal systems
摘要： Background: Driven by a huge improvement in automation, unmanned areal systems (UAS) are increasingly used for field observations and high-throughput phenotyping. Today, the bottleneck does not lie in the ability to fly a drone anymore, but rather in the appropriate flight planning to capture images with sufficient quality. Proper flight preparation for photography with digital frame cameras should include relevant concepts such as view, sharpness and exposure calculations. Additionally, if mapping areas with UASs, one has to consider concepts related to ground control points (GCPs), viewing geometry and way-point flights. Unfortunately, non of the available flight planning tools covers all these aspects. Results: We give an overview of concepts related to flight preparation, present the newly developed open source software PhenoFly Planning Tool, and evaluate other recent flight planning tools. We find that current flight planning and mapping tools strongly focus on vendor-specific solutions and mostly ignore basic photographic properties—our comparison shows, for example, that only two out of thirteen evaluated tools consider motion blur restrictions, and none of them depth of field limits. In contrast, PhenoFly Planning Tool enhances recent sophisticated UAS and autopilot systems with an optical remote sensing workflow that respects photographic concepts. The tool can assist in selecting the right equipment for your needs, experimenting with different flight settings to test the performance of the resulting imagery, preparing the field and GCP setup, and generating a flight path that can be exported as waypoints to be uploaded to an UAS. Conclusion: By considering the introduced concepts, uncertainty in UAS-based remote sensing and high-throughput phenotyping may be considerably reduced. The presented software PhenoFly Planning Tool (https://shiny.usys.ethz.ch/PhenoFlyPlanningTool) helps users to comprehend and apply these concepts.
关键词： Flight planning,Ground control point (GCP),High-throughput phenotyping,Viewing geometry,Low-altitude remote sensing,Mapping from imagery
更新于2025-09-23 15:23:52