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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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Sparse Reconstruction-Based Thermal Imaging for Defect Detection
摘要： This paper proposes an idea of employing sparse reconstruction-based technique for thermal imaging defect detection. The implementation of the reconstruction technique is tested on a carbon fiber reinforced polymer test piece with artificially drilled defects and the test results are compared with the established cross correlation method. The two processes are compared in terms of defect detectability, their SNR variation with defect depth and their computation complexity. When compared with cross correlation algorithm, the technique is expected to solve memory space problems by compressing all information from large cross-correlated pulse video into a single reconstructed image as an output. Furthermore, in existing cross correlation methods, the pulse peak time shifts with defect depth. Hence, defect quantification algorithms, such as SNR calculation, require multiple frame analysis. Such algorithms are comparatively simplified in sparse reconstruction technique. This paper explores sparse reconstruction algorithm for resolving close-spaced defects. This paper further describes cross-validation method for optimization of a user parameter in sparse reconstruction method.
关键词： thermal nondestructive testing,sparse reconstruction,pulse compression,nondestructive evaluation and remote sensing,frequency modulated thermal wave imaging,Cross correlation algorithm
更新于2025-09-23 15:22:29
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[IEEE 2018 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) - Saint-Petersburg, Russia (2018.11.26-2018.11.30)] 2018 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF) - Electronic Methods to Protect Unmanned Aerial Vehicles from Seizing Control
摘要： the article deals with the issues of security in the transmission of control information over a wireless communication channel between an unmanned aerial vehicle and the control panel, as well as options for electronic methods of protection against external (unauthorized) interception of control of unmanned aerial vehicles.
关键词： wireless data transfer,remote control,control interception,wireless networks,unmanned aerial vehicles
更新于2025-09-23 15:22:29
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Rela??es empíricas entre características dendrométricas da Caatinga brasileira e dados TM Landsat 5
摘要： The objective of this work was to adjust models to estimate dendrometric characteristics of the Brazilian dry tropical forest (Caatinga) from Landsat 5 TM sensor data. Measures for tree diameter and height were taken in 60 inventory plots (400 m2), in two municipalities of the state of Sergipe, Brazil. Basal area and wood volume were estimated using an allometric equation and form factor (f = 0.9). Explanatory variables were taken from the TM sensor, after radiometric and geometric correction, having considered, in the analysis, six spectral bands, with 30 m spatial resolution, besides the indexes of simple ratio (SR), of normalized difference vegetation (NDVI), and of soil-adjusted vegetation (Savi). To choose the best explanatory variables, the coefficient of determination (R2), the root mean square error (RMSE), and the Bayesian information criterion (BIC) were considered. The basal area per hectare did not show a significant correlation with any of the explanatory variables used. The best models were adjusted to tree mean height per plot (R2 = 0.4; RMSE = 13%) and to wood volume per hectare (R2 = 0.6; RMSE = 42%). The metrics derived from the Landsat 5 TM sensor have great potential to explain variation in the mean height of trees and in the wood volume per hectare, in remaining areas of the tropical dry forest in the Brazilian Northeast.
关键词： Savi,REDD,vegetation index,reducing emissions,remote sensing,NDVI
更新于2025-09-23 15:22:29
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Individual Tree Detection from Multi-View Satellite Images
摘要： Individual tree detection is critical in forest monitoring and inventory. In this paper, we propose a novel method to use multi-view satellite images to detect individual trees and delineate their crowns. As compared to previous methods that only use image information, we generate the DSM from the multi-view high-resolution satellite images and combine it with the spectral information to detect the trees. Firstly, the vegetation areas are extracted to remove the non-vegetation objects while terrain areas are extracted to help estimate the tree height. Then, we utilize top-hat morphological operation to efficiently find the local maximal points as tree tops and further refine them by checking their heights and doing non-maximum suppression. Finally, we use a revised superpixel segmentation algorithm to delineate the tree crowns which considered both 2D spectral and 3D structure similarities. To effectively assess the performance, we rigorously match and evaluate the detected and reference trees in a one-to-one relationship. A quantitative evaluation at three different sites shows that the proposed method is able to detect individual trees at different regions with high accuracy.
关键词： Remote Sensing,DSM,Individual Tree Detection,Superpixel,Multi-view Satellite Image
更新于2025-09-23 15:22:29
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Application of Airborne Infrared Remote Sensing to the Study of Ocean Submesoscale Eddies
摘要： This paper explores the use of infrared remote sensing methods to examine submesoscale eddies that recur downstream of a deep-water island (Santa Catalina, CA). Data were collected using a mid-wave infrared camera deployed on an aircraft flown at an altitude of 3.7 km, and research boats made nearly simultaneous measurements of temperature and current profiles. Structure within the thermal field is generally adequate as a tracer of surface fluid motions, though the imagery needs to be processed in a novel way to preserve the smallest-scale tracer patterns. In the case we focus on, the eddy is found to have a thermal signature of about 1 km in diameter and a cyclonic swirling flow. Vorticity is concentrated over a smaller area of about 0.5 km in diameter. The Rossby number is 27, indicating the importance of the centrifugal force in the dynamical balance of the eddy. By approximating the eddy as a Rankine vortex, an estimate of upward doming of the thermocline (about 14 m at the center) is obtained that agrees qualitatively with the in-water measurements. Analysis also shows an outward radial flow that creates areas of convergence (sinking flow) along the perimeter of the eddy. The imagery also reveals areas of localized vertical mixing within the eddy thermal perimeter, and an area of external azimuthal banding that likely arises from flow instability.
关键词： infrared imagery,surface current,remote sensing of environment,submesoscale eddies,kinematics and dynamics
更新于2025-09-23 15:22:29
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Global and Local Real-Time Anomaly Detectors for Hyperspectral Remote Sensing Imagery
摘要： Anomaly detection has received considerable interest for hyperspectral data exploitation due to its high spectral resolution. A well-known algorithm for hyperspectral anomaly detection is the RX detector. A number of variations have been studied since then, including global and local versions for different type of anomalies. Aiming at a real-time requirement for practical applications, this paper extends the concept of global and local anomaly detectors to be real-time detectors. The algorithms exploit the fact that a true real-time detector must produce its output in a causal manner and at the same time as an input comes in. Taking advantage of the Woodbury matrix identity, the global and local real-time detectors can be implemented and processed pixel-by-pixel in real time. Both synthetic and real hyperspectral imagery are conducted to demonstrate their performance.
关键词： sliding local window,Woodbury matrix identity,hyperspectral remote sensing,anomaly detection,real-time
更新于2025-09-23 15:22:29
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STUDI PENURUNAN MUKA TANAH (LAND SUBSIDENCE) MENGGUNAKAN METODE PERMANENT SCATTERER INTERFEROMETRIC SYNTHETIC APERTURE RADAR (PS-INSAR) DI KAWASAN KOTA CIMAHI - JAWA BARAT
摘要： Process or movement of land subsidence has a lot going on in various regions of the world especially in big cities. The impact of land subsidence can damage urban infrastructure and a disruption to the economic stability and social life in the region. Because of it, we need a natural disaster mitigation system that is able to provide rapid and optimal a geoscience analysis in the concept of quick assessment. A remote sensing technology has the ability to assess large areas in a short time and related with the typical climate of Indonesia that lies in a tropical area (intensity and extensive high cloud cover). Selection of radar technology is one solution that is good for spatial mapping in land subsidence estimation. PS-InSAR is the newest method in RADAR image satellite processing which is give a good accuracy and minimize decorellation effects. PS-InSAR method implementation in Indonesia area is a good solution because this method can penetrate heavy dense clouds and fogs. This method was used in land subsidence analysis at Cimahi City-West Java Province which is result arounds 17.97 mm/yr ± 11.5 mm/yr. The South Cimahi District has a highest land subsidence rate arounds 22.9 mm/yr ± 12,7 mm/yr. This method has been proven as one of a good remote sensing method to investigate land subsidence movement.
关键词： Remote Sensing,Land Subsidence,PS-InSAR,Radar,DInSAR
更新于2025-09-23 15:22:29
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Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes
摘要： The European Parliament and The Council of the European Union have established the Water Framework Directive (2000/60/EC) for all European Union member states to achieve, at least, 'good' ecological status of all water bodies larger than 50 hectares in Europe. The MultiSpectral Instrument onboard European Space Agency satellite Sentinel-2 has suitable 10, 20, 60 m spatial resolution to monitor most of the Estonian lakes as required by the Water Framework Directive. The study aims to analyze the suitability of Sentinel-2 MultiSpectral Instrument data to monitor water quality in inland waters. This consists of testing various atmospheric correction processors to remove the influence of atmosphere and comparing and developing chlorophyll a algorithms to estimate the ecological status of water in Estonian lakes. This study shows that the Sentinel-2 MultiSpectral Instrument is suitable for estimating chlorophyll a in water bodies and tracking the spatial and temporal dynamics in the lakes. However, atmospheric corrections are sensitive to surrounding land and often fail in narrow and small lakes. Due to that, deriving satellite-based chlorophyll a is not possible in every case, but initial results show the Sentinel-2 MultiSpectral Instrument could still provide complementary information to in situ data to support Water Framework Directive monitoring requirements.
关键词： atmospheric correction,chlorophyll a,optically complex waters,remote sensing,European Union Water Framework Directive (2000/60/EC),ecological status of water bodies,Copernicus,Sentinel-2 MultiSpectral Instrument
更新于2025-09-23 15:22:29
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Deep Belief Network for Spectral–Spatial Classification of Hyperspectral Remote Sensor Data
摘要： With the development of high-resolution optical sensors, the classification of ground objects combined with multivariate optical sensors is a hot topic at present. Deep learning methods, such as convolutional neural networks, are applied to feature extraction and classification. In this work, a novel deep belief network (DBN) hyperspectral image classification method based on multivariate optical sensors and stacked by restricted Boltzmann machines is proposed. We introduced the DBN framework to classify spatial hyperspectral sensor data on the basis of DBN. Then, the improved method (combination of spectral and spatial information) was verified. After unsupervised pretraining and supervised fine-tuning, the DBN model could successfully learn features. Additionally, we added a logistic regression layer that could classify the hyperspectral images. Moreover, the proposed training method, which fuses spectral and spatial information, was tested over the Indian Pines and Pavia University datasets. The advantages of this method over traditional methods are as follows: (1) the network has deep structure and the ability of feature extraction is stronger than traditional classifiers; (2) experimental results indicate that our method outperforms traditional classification and other deep learning approaches.
关键词： classification,feature extraction,multi-sensor fusion,remote sensors,deep learning,hyperspectral image
更新于2025-09-23 15:22:29
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An efficient pixel clustering-based method for mining spatial sequential patterns from serial remote sensing images
摘要： The accumulation of serial remote sensing images provides plentiful data for discovering sequential spatial patterns in various fields such as agricultural monitoring, urban development, and vegetation cover. Otherwise, traditional sequential pattern-mining algorithms cannot be directly or efficiently applied to remote sensing images. In this study, we propose a pixel clustering-based method to improve the efficiency of mining spatial sequential patterns from raster serial remote sensing images (SRSI). Firstly, the images are compressed by using the Run-Length coding schema. Then, pixels with identical sequences are clustered by means of the Run-length code-based spatial overlay operation. Finally, a pruning strategy is proposed, to extend the prefixSpan algorithm to skip unnecessary database scanning when mining from pixel groups. The experimental results indicate that the method presented in this paper could extract spatial sequential patterns from SRSI efficiently. Although accurate support rates for the patterns may not be obtained, our method could ensure that all patterns are extracted with a lower time cost.
关键词： Sequence mining,Spatial sequential pattern,Pixels cluster,Serial remote sensing images
更新于2025-09-23 15:22:29