| 1. |
- Ahlberg, Jörgen
(author)
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Optimizing Object, Atmosphere, and Sensor Parameters in Thermal Hyperspectral Imagery
- 2017
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In: IEEE Transactions on Geoscience and Remote Sensing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0196-2892 .- 1558-0644. ; 55:2, s. 658-670
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Journal article (peer-reviewed)abstract
- We address the problem of estimating atmosphere parameters (temperature and water vapor content) from data captured by an airborne thermal hyperspectral imager and propose a method based on linear and nonlinear optimization. The method is used for the estimation of the parameters (temperature and emissivity) of the observed object as well as sensor gain under certain restrictions. The method is analyzed with respect to sensitivity to noise and the number of spectral bands. Simulations with synthetic signatures are performed to validate the analysis, showing that the estimation can be performed with as few as 10-20 spectral bands at moderate noise levels. The proposed method is also extended to exploit additional knowledge, for example, measurements of atmospheric parameters and sensor noise. Additionally, we show how to extend the method in order to improve spectral calibration.
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| 2. |
- Asgarimehr, Milad, et al.
(author)
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Remote Sensing of Precipitation Using Reflected GNSS Signals: Response Analysis of Polarimetric Observations
- 2022
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 60
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Journal article (peer-reviewed)abstract
- For the first time, rain effects on the polarimetric observations of the global navigation satellite system reflectometry (GNSS-R) are investigated. The physical feasibility of tracking the modifications in the surface roughness by rain splash and the surface salinity by the accumulation of freshwater is theoretically discussed. An empirical analysis is carried out using measurements of a coastal GNSS-R station with two side-looking antennas in right- and left-handed circular polarizations (RHCP and LHCP). Discernible drops in RHCP and LHCP powers are observed during rain over a calm sea. The power drop becomes larger at higher elevation angles. The average LHCP power drops by ≈ 5 dB at an elevation angle of 45°. The amplitude of the correlation sum shows a dampening, responding to rain rate systematically. The LHCP observations show higher sensitivity to rainfall compared to RHCP observations. The retrieved standard deviation of surface heights shows a steady increase with the rain rate. The derived surface salinity shows a decrease at rains higher than 10 mm/h. This study confirms the potential under environmental conditions of the GNSS-R ground-based station, e.g., with salinity mostly lower than 30 psu, over a calm sea, being a starting point for future investigations.
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| 3. |
- Asihene, Elvis, et al.
(author)
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Toward the Detection of Oil Spills in Newly Formed Sea Ice Using C-Band Multipolarization Radar
- 2022
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In: IEEE Transactions on Geoscience and Remote Sensing. - : IEEE Geoscience and Remote Sensing Society. - 0196-2892 .- 1558-0644. ; 60
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Journal article (peer-reviewed)abstract
- Oil spills in the Arctic are becoming more likely as shipping traffic increases in response to climate-related sea ice loss. To improve oil spill detection capability, we used a controlled mesocosm to analyze the multipolarized C-band backscatter response of oil in newly formed sea ice (NI). Artificial sea ice was grown in two cylindrical tubs at the Sea-ice Environmental Research Facility, University of Manitoba. The sea ice physical characteristics, including surface roughness, thickness, temperature, and salinity, were measured before and after oil injection below the ice sheet. Time-series C-band radar backscatter measurements detected the differences in the sea ice evolution and oil migration to the sea ice surface in the oil-contaminated tub, which was compared to uncontaminated ice in a control tub. Immediately prior to the presence of oil on the ice surface, the copolarized backscatter is increased by 13-dB local maximum, while the cross-polarized backscatter is decreased by 9-dB. Ice physical properties suggest that the local backscatter maximum and minimum, which occurred immediately before oil migrated onto the surface, were related to a combination of brine and oil upward migration. The findings of this work provide a baseline data interpretation for oil detection in the Arctic Ocean using current and future C-band multipolarization radar satellites.
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| 4. |
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| 5. |
- Askne, Jan, 1936, et al.
(author)
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Multitemporal Repeat Pass SAR Interferometry of Boreal Forests
- 2005
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 43:6, s. 1219-1228
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Journal article (peer-reviewed)abstract
- Multitemporal interferometric European Remote Sensing 1 and 2 satellite tandem pairs from a forest test site in Finland are examined in order to determine the stem volume retrieval accuracy. A form of multitemporal filtering is introduced to investigate what forest stands show a multitemporal consistency in coherence. It is found that a large stand size is a major factor to obtain accurate retrievals. The effect of heterogeneity of forest stands is also discussed. Based on the stands showing highest multitemporal consistency different models for scattering and coherence are compared. The interferometric water cloud model is chosen for stem volume retrieval. The variation of the model parameters with meteorological parameters is investigated and the results illustrate that the best imaging conditions are obtained for subzero temperatures and windy conditions. It is shown that for the 20 stands showing highest multitemporal consistency the stem volume can be retrieved with a relative error of 21%, deteriorating when the number of testing stands is increased, e.g., for 80 stands the error is 48%. For 37 large forest stands representing 48% of the investigated area the relative stem volume error is 26%. With experience from another site in Sweden we may conclude that the error level for a multitemporal interferometric synthetic aperture radar evaluation of stem volume for large forest stands ( > 2 ha) in a well managed and homogeneous boreal forest may be expected to be in the 15% to 25% range, deteriorating for small and heterogeneous stands and for images acquired under nonwinter conditions. © 2005 IEEE.
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| 6. |
- Bai, Tao, et al.
(author)
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Stealthy Adversarial Examples for Semantic Segmentation in Remote Sensing
- 2024
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In: IEEE Transactions on Geoscience and Remote Sensing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 0196-2892 .- 1558-0644. ; 62
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Journal article (peer-reviewed)abstract
- Deep learning methods have been proven effective in remote sensing image analysis and interpretation, where semantic segmentation plays a vital role. These deep segmentation methods are susceptible to adversarial attacks, while most of the existing attack methods tend to manipulate the image globally, leading to noticeable perturbations and chaotic segmentation. In this work, we propose a novel stealthy attack for semantic segmentation (SASS), which can largely increase the effectiveness and stealthiness from the existing attack methods on remote sensing images. SASS manipulates specific victim classes or objects of interest while preserving the original segmentation results for other classes or objects. In practice, as different inference mechanisms, overlapped inference, can be applied in segmentation, the efficacy of SASS may be degraded. To this end, we further introduce the masked SASS (MSASS), which generates augmented adversarial perturbations that only affect victim areas. We evaluate the effectiveness of SASS and MSASS using four state-of-the-art semantic segmentation models on the Vaihingen and Zurich Summer datasets. Extensive experiments demonstrate that our SASS and MSASS methods achieve superior attack performances on victim areas while maintaining high accuracies of other areas (drop less than 2%). The detection success rates of adversarial examples for segmentation, as characterized by Xiao et al., significantly drop from 97.78% for the untargeted projected gradient descent (PGD) attack to 28.71% for our MSASS method on the Zurich Summer dataset. Our work contributes to the field of adversarial attacks in semantic segmentation for remote sensing images by improving stealthiness, flexibility, and robustness. We anticipate that our findings will inspire the development of defense methods to enhance the security and reliability of semantic segmentation models against our stealthy attack.
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| 7. |
- Ban, Yifang, et al.
(author)
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Object-Based Fusion of Multitemporal Multiangle ENVISAT ASAR and HJ-1B Multispectral Data for Urban Land-Cover Mapping
- 2013
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 51:4, s. 1998-2006
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Journal article (peer-reviewed)abstract
- The objectives of this research are to develop robust methods for segmentation of multitemporal synthetic aperture radar (SAR) and optical data and to investigate the fusion of multitemporal ENVISAT advanced synthetic aperture radar (ASAR) and Chinese HJ-1B multispectral data for detailed urban land-cover mapping. Eight-date multiangle ENVISAT ASAR images and one-date HJ-1B charge-coupled device image acquired over Beijing in 2009 are selected for this research. The edge-aware region growing and merging (EARGM) algorithm is developed for segmentation of SAR and optical data. Edge detection using a Sobel filter is applied on SAR and optical data individually, and a majority voting approach is used to integrate all edge images. The edges are then used in a segmentation process to ensure that segments do not grow over edges. The segmentation is influenced by minimum and maximum segment sizes as well as the two homogeneity criteria, namely, a measure of color and a measure of texture. The classification is performed using support vector machines. The results show that our EARGM algorithm produces better segmentation than eCognition, particularly for built-up classes and linear features. The best classification result (80%) is achieved using the fusion of eight-date ENVISAT ASAR and HJ-1B data. This represents 5%, 11%, and 14% improvements over eCognition, HJ-1B, and ASAR classifications, respectively. The second best classification is achieved using fusion of four-date ENVISAT ASAR and HJ-1B data (78%). The result indicates that fewer multitemporal SAR images can achieve similar classification accuracy if multitemporal multiangle dual-look-direction SAR data are carefully selected.
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| 8. |
- Berg, Anders, 1983, et al.
(author)
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Investigation of a Hybrid Algorithm for Sea Ice Drift Measurements Using Synthetic Aperture Radar Images
- 2014
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 52:8, s. 5023 - 5033
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Journal article (peer-reviewed)abstract
- Areal matching by phase correlation and feature tracking are two complementary methods used to measure sea ice drift between synthetic aperture radar images. This paper evaluates a new algorithm that combines the two methods. Areal matching is improved by new methods to handle large motions and rotated ice. It is shown that areal rotation can be resolved using a frequency-domain approach. Image segmentation is a prerequisite for feature tracking and achieved by a new method that performs better than Otsu's method for two-component Gaussian mixture distributions. A circular weighted median filter is found to be suitable for the filtering of the motion field. The algorithm is evaluated through a thorough analysis of the response and sensitivity to various algorithm settings. The accuracy of the algorithm varies by up to 50% for one image pair within the studied range of parameter settings, thus indicating the need for a proper initialization of the algorithm.
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| 9. |
- Berg, Anders, 1983, et al.
(author)
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X-Band Interferometric SAR Observations of Baltic Fast Ice
- 2015
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 53:3, s. 1248-1256
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Journal article (peer-reviewed)abstract
- Detailed mapping of fast-ice deformation can be used to characterize the rheological behavior of fast ice and subsequently improve sea ice modeling. This study uses interferometric synthetic aperture radar to map fast-ice deformation with unprecedented spatial resolution (meter range) and sensitivity (cm-mm range). Two interferometric acquisitions, each with a temporal baseline of 24 h, were performed by the X-band SAR satellite constellation Cosmo-SkyMed over the northeast Bay of Bothnia in the middle of the 2012 ice season. The first interferogram shows deformation of the fast ice due to force from impinging drift ice, and the normal strain within the fast ice is measured. Complementary intensity correlation measurements reveal a slow movement of the drift ice toward the fast ice. The second interferogram exhibits a low fringe rate over the fast ice with fringes being aligned along the coastline. Deformation appears to be stronger around leads, skerries, and grounded ice ridges. It is also observed that the coherence images provide information that is complementary to the information in the backscatter images.
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| 10. |
- Blomberg, Erik, 1987, et al.
(author)
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Evaluating P-Band TomoSAR for Biomass Retrieval in Boreal Forest
- 2021
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In: IEEE Transactions on Geoscience and Remote Sensing. - 0196-2892 .- 1558-0644. ; 59:5, s. 3793-3804
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Journal article (peer-reviewed)abstract
- P-band synthetic aperture radar (SAR) is sensitive to above-ground biomass (AGB) but retrieval accuracy has been shown to deteriorate in topographic areas. In boreal forest, the signal penetrates through the canopy to interact with the ground producing variations in backscatter depending on ground topography, forest structure, and soil moisture. Tomographic processing of multiple SAR images Tomographic SAR (TomoSAR) provides information about the vertical backscatter distribution. This article evaluates the use of P-band TomoSAR data to improve AGB retrievals from backscattered intensity by suppressing the backscattered signal from the ground. This approach can be used even when the tomographic resolution is insufficient to resolve the vertical backscatter profile. The analysis is based on P-band data from two campaigns: BioSAR-1 (2007) in Remingstorp, southern Sweden, and BioSAR-2 (2008) in Krycklan (KR), northern Sweden. BioSAR airborne data were also processed to correspond as closely as possible to future BIOMASS TomoSAR acquisitions, with BioSAR-2-based results shown. A power law AGB model using volumetric HV polarized backscatter performs best in KR, with training residual root mean-squared error (RMSE) of 30%-36% (27-33 t/ha) for airborne data and 38%-39% for simulated BIOMASS data. Airborne TomoSAR data suggest that both vertical and horizontal tomographic resolution are of importance and that it is possible to greatly reduce AGB retrieval bias when compared with airborne P-band SAR backscatter intensity-based retrievals. A lack of significant ground slopes in Remningstorp reduces the benefit of using TomoSAR data which performs similar to retrievals based solely on P-band SAR backscatter intensity.
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