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Tensor tomography using V-line transforms with vertices restricted to a circle

ANALYSIS AND MATHEMATICAL PHYSICS 2025年第1期15卷 1-23页

作者： Mishra, Rohit Kumar Purohit, Anamika Zamindar, Indrani Indian Inst Technol Gandhinagar Dept Math Gandhinagar 382355 Gujarat India

In this article, we study the problem of recovering symmetric m-tensor fields (including vector fields) supported in a unit disk D\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathbb {D}}$$\end{document} from a set of generalized V-line transforms, namely longitudinal, transverse, and mixed V-line transforms, and their integral moments. We work in a circular geometric setup, where the V-lines have vertices on a circle, and the axis of symmetry is orthogonal to the circle. We present two approaches to recover a symmetric m-tensor field from the combination of longitudinal, transverse, and mixed V-line transforms. With the help of these inversion results, we are able to give an explicit kernel description for these transforms. We also derive inversion algorithms to reconstruct a symmetric m-tensor field from its first (m+1) integral moment longitudinal/transverse V-line transforms.

关键词： Inverse problems V-line transform Tensor tomography inversion algorithms Integral moments

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V-Line Tensor Tomography: Numerical Results\ast

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SIAM JOURNAL ON IMAGING SCIENCES 2025年第1期18卷 597-630页

作者： Ambartsoumian, Gaik Mishra, Rohit Kumar Zamindar, Indrani Univ Texas Arlington Dept Math Arlington TX 76019 USA Indian Inst Technol Gandhinagar Dept Math Gandhinagar 382355 Gujarat India

This article presents the numerical verification and validation of several inversion algorithms for V-line transforms (VLTs) acting on symmetric 2-tensor fields in the plane. The analysis of these transforms and the theoretical foundation of their inversion methods were studied in the recent demonstrate the efficient recovery of an unknown symmetric 2-tensor field from various combinations of the longitudinal, transverse, and mixed VLTs, their corresponding first moments, and the star VLT. The paper examines the performance of the proposed algorithms in different settings and illustrates the results with numerical simulations on smooth and nonsmooth phantoms.

关键词： inverse problems V-line transform broken ray transform star transform tensor tomography numerical simulations inversion algorithms numerical solution of PDEs

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Review of Satellite Remote Sensing of Carbon Dioxide inversion and Assimilation

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REMOTE SENSING 2024年第18期16卷 3394页

作者： Hu, Kai Feng, Xinyan Zhang, Qi Shao, Pengfei Liu, Ziran Xu, Yao Wang, Shiqian Wang, Yuanyuan Wang, Han Di, Li Xia, Min Nanjing Univ Informat Sci & Technol NUIST Sch Automat Nanjing 210044 Peoples R China Nanjing Univ Informat Sci & Technol Jiangsu Collaborat Innovat Ctr Atmospher Environm Nanjing 210044 Peoples R China Univ Reading Sch Math Phys & Computat Sci POB 217 Reading RG6 6AH Berks England State Grid Henan Elect Power Co Econ & Tech Res Inst Zhengzhou 450052 Peoples R China State Grid Henan Elect Power Co Zhengzhou 450003 Peoples R China

With the rapid development of satellite remote sensing technology, carbon-cycle research, as a key focus of global climate change, has also been widely developed in terms of carbon source/sink-research methods. The internationally recognized "top-down" approach, which is based on satellite observations, is an important means to verify greenhouse gas-emission inventories. This article reviews the principles, categories, and development of satellite detection payloads for greenhouse gases and introduces inversion algorithms and datasets for satellite remote sensing of XCO2. It emphasizes inversion methods based on machine learning and assimilation algorithms. Additionally, it presents the technology and achievements of carbon-assimilation systems used to estimate carbon fluxes. Finally, the article summarizes and prospects the future development of carbon-assimilation inversion to improve the accuracy of estimating and monitoring Earth's carbon-cycle processes.

关键词： satellite remote sensing inversion algorithms XCO2 carbon assimilation

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Thermal response tests for the identification of soil thermal parameters: A review

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RENEWABLE ENERGY 2021年 173卷 1123-1135页

作者： Zhang, Xueping Han, Zongwei Ji, Qiang Zhang, Hongzhi Li, Xiuming Northeastern Univ Sch Met SEP Key Lab Ecoind Shenyang Peoples R China

Ground source heat pump systems (GSHPs) for soil heat utilization have been widely concerned in the world due to their energy saving, high efficiency, and no pollutant emission. The thermal parameters of the local soil must be known first when designing GSHPs, and the in-situ thermal response test (TRT) is currently the conventional method for determining their values. Given this, this paper deals with the related contents of parameter identification based on TRT from four aspects. First, various modeling methods for ground heat exchanger (GHE) and inversion algorithms are introduced and compared. Next, many factors that influence the identification accuracy are summarized, including test conditions, external disturbance, groundwater seepage and subsurface natural convection. Then, the negative in-fluence of correlation between parameters on identification results is analyzed, and the research progress of the uncertainty assessment of identification results is introduced, which can improve the reliability of the results. Furthermore, the characteristics of various advanced TRT setups are also summarized. Finally, several imperfects and objectives for improving the reliability of parameters identification are discussed. This work provides useful information for improving the identification accuracy of soil thermal pa-rameters so that the GHSPs can be designed more reliably. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Ground source heat pump Thermal response test Ground heat exchanger inversion algorithms Uncertainty assessment

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Mapping Woody Volume of Mediterranean Forests by Using SAR and Machine Learning: A Case Study in Central Italy

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REMOTE SENSING 2021年第4期13卷 809-809页

作者： Santi, Emanuele Chiesi, Marta Fontanelli, Giacomo Lapini, Alessandro Paloscia, Simonetta Pettinato, Simone Ramat, Giuliano Santurri, Leonardo Natl Res Council Italy IFAC CNR Inst Appl Phys Via Madonna Piano 10 I-50019 Florence Italy Natl Res Council Italy IBE CNR Inst BioEcon Via Madonna Piano 10 I-50019 Florence Italy

In this paper, multi-frequency synthetic aperture radar (SAR) data at L- and C-bands (ALOS PALSAR and Envisat/ASAR) were used to estimate forest biomass in Tuscany, in Central Italy. The ground measurements of woody volume (WV, in m(3)/ha), which can be considered as a proxy of forest biomass, were retrieved from the Italian National Forest Inventory (NFI). After a preliminary investigation to assess the sensitivity of backscatter at C- and L-bands to forest biomass, an approach based on an artificial neural network (ANN) was implemented. The ANN was trained using the backscattering coefficient at L-band (ALOS PALSAR, HH and HV polarization) and C-band (Envisat ASAR in HH polarization) as inputs. Spatially distributed WV values for the entire test area were derived by the integration (fusion) of a canopy height map derived from the Ice, Cloud, and Land Elevation Geoscience Laser Altimeter System (ICESat GLAS) and the NFI data, in order to build a significant ground truth dataset for the training stage. The analysis of the backscattering sensitivity to WV showed a moderate correlation at L-band and was almost negligible at C-band. Despite this, the ANN algorithm was able to exploit the synergy of SAR frequencies and polarizations, estimating WV with average Pearson's correlation coefficient (R) = 0.96 and root mean square error (RMSE) similar or equal to 39 m(3)/ha when applied to the test dataset and average R = 0.86 and RMSE similar or equal to 75 m(3)/ha when validated on the direct measurements from the NFI. Considering the heterogeneity of the scenario (Mediterranean mixed forests in hilly landscape) and the small amount of available ground measurements with respect to the spatial variability of different plots, the obtained results can be considered satisfactory. Moreover, the successful use of WV from global maps for implementing the algorithm suggests the possibility to apply the algorithm to wider areas or even to global scales.

关键词： SAR forest biomass woody volume ANN inversion algorithms

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Model Based inversion for Pulse Thermography

Model Based Inversion for Pulse Thermography

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Society-for Experimental-Mechanics (SEM) Annual Conference and Exposition on Experimental and Applied Mechanics

作者： Holland, Stephen D. Iowa State Univ Ames IA 50011 USA

ISBN: (纸本)9783319950747;9783319950730

We present a model-based inversion approach to the interpretation of flash thermography data. Traditionally, flash thermography has been image sequences have been hard to interpret in the presence of lateral heat flows. This is a particularly significant problem for composite laminate materials where heat conducts readily in the fiber planes. We use a linear inversion approach to represent the observed surface temperature as a superposition of contributions from buried reflectors. We investigate the additional complexities of considering cases where the specimen is curved, changing the nature of the heat flow. By solving a large linear inversion problem we are able to determine the strengths of the buried reflectors and create a concrete representation of observed defects. Results from this approach are compared to more traditional analysis approaches for flash thermography.

关键词： Flash thermography Nondestructive evaluation (NDE) inversion algorithms Model-based inversion

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Optoacoustic model-based inversion using anisotropic adaptive total-variation regularization

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PHOTOACOUSTICS 2019年 16卷 100142-100142页

作者： Biton, Shai Arbel, Nadav Drozdov, Gilad Gilboa, Guy Rosenthal, Amir Technion Israel Inst Technol Andrew & Erna Viterbi Fac Elect Engn IL-31999 Haifa Israel

In optoacoustic tomography, image reconstruction is often performed with incomplete or noisy data, leading to reconstruction errors. Significant improvement in reconstruction accuracy may be achieved in such cases by using nonlinear regularization schemes, such as total-variation minimization and L-1-based sparsity-preserving schemes. In this paper, we introduce a new framework for optoacoustic image reconstruction based on adaptive anisotropic total-variation regularization, which is more capable of preserving complex boundaries than conventional total-variation regularization. The new scheme is demonstrated in numerical simulations on blood-vessel images as well as on experimental data and is shown to be more capable than the total-variation-L-1 scheme in enhancing image contrast.

关键词： Optoacoustic imaging Total variation inversion algorithms Model-based reconstruction

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Development and assessment of lidar modeling to retrieve IOPs 10

Development and assessment of lidar modeling to retrieve IOP...

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Conference on Ocean Sensing and Monitoring X

作者： Strait, Christopher Twardowski, Michael Dalgleish, Fraser Tonizzo, Alberto Vuorenkoski, Anni Florida Atlantic Univ Harbor Branch Oceanog Inst 5600 US 1 North Ft Pierce FL 34946 USA

ISBN: (数字)9781510617742

ISBN: (纸本)9781510617742

A synthetic bio-optical dataset of inherent optical properties (IOPs) was created based on Chlorophyll concentrations ranging between 0.01 and 30 mg m(-3). Dissolved and particulate fractions of absorption were varied to account for the natural ranges in values. The IOPs will then be used as inputs to a time-resolved Monte-Carlo radiative transfer model to generate accurate lidar backscatter time history wave forms. Test experiments were performed to validate the model, where the primary lidar geometry in the model matched an existing system developed at HBOI under NOAA-OAR funding. The system uses blue and green pulsed laser sources (473 and 532 nm, respectively) and has two telescopes arranged at a 10 degrees offset (on and off axis) from one another. The field of view of the telescopes is set at 1 degrees. Approaches are being investigated to invert simulated and measured lidar results to derive input water column IOP properties. Results are tested through application to lidar measurements collected in an experimental tank with known suspended particle type and concentration.

关键词： Ocean sensing and monitoring underwater imaging remote sensing inversion algorithms

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PROGRESS ON A NEW ANALYTICAL ALGORITHM TO RETRIEVE INHERENT OPTICAL PROPERTIES FROM OCEAN COLOR REMOTE SENSING 38

PROGRESS ON A NEW ANALYTICAL ALGORITHM TO RETRIEVE INHERENT ...

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38th IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Twardowski, Michael Tonizzo, Alberto Florida Atlantic Univ Harbor Branch Oceanog Inst Ft Pierce FL 34946 USA Sunstone Sci LLC Vero Beach FL 32963 USA

ISBN: (纸本)9781538671504

Approximations are vital to interpret ocean color remote sensing since it is not possible to analytically invert the full the radiative transfer (RT) equation. RT approximations to date have almost exclusively relied on relating [b(b) / (a + b(b))] to remote sensing reflectance (r(RS)). This shifts uncertainty for several parameters associated with viewing geometry and the volume scattering function into the proportionality. Zaneveld [1] developed a RT approximation that explicitly incorporates these aspects in a fully analytical relationship, but it has not been rigorously evaluated to date. We rework the Zaneveld approximation so that rRS is only dependent on bb and a, while retaining explicit dependencies on the shape of the volume scattering function and viewing geometry. The algorithm is fully spectral. We also, for the first time, demonstrate inversion of this algorithm to derive inherent optical properties (IOPs) backscattering bb and absorption a. The algorithm shows promise for a new operational ocean color retrieval algorithm.

关键词： Radiative Transfer Ocean Color inversion algorithms

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The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas

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REMOTE SENSING OF ENVIRONMENT 2017年 200卷 63-73页

作者： Santi, Emanuele Paloscia, Simonetta Pettinato, Simone Fontanelli, Giacomo Mura, Matteo Zolli, Catherine Maselli, Fabio Chiesi, Marta Bottai, Lorenzo Chirici, Gherardo Natl Res Council Italy IFAC CNR Inst Appl Phys Via Madonna Piano 10 I-50019 Florence Italy Univ Firenze Dept Agr Food & Forestry Syst Via San Bonaventura 13 I-50145 Florence Italy Italian Acad Forest Sci Pzza Edison 11 I-50133 Florence Italy Natl Res Council Italy IBIMET CNR Inst Biometeorol Via Madonna Piano 10 I-50019 Florence Italy LaMMA Consortium Via Madonna Piano 10 I-50019 Florence Italy

The extraction of forest information from SAR images is particularly complex in Mediterranean areas, since they are characterized by high spatial fragmentation and heterogeneity. We have investigated the use of multi-frequency SAR data from different sensors (ALOS/PALSAR and ENVISAT/ASAR) for estimating forest biomass in two test areas in Central Italy (San Rossore and Molise), where detailed in-situ measurements and Airborne Laser Scanning (ALS) data were available. The study focused on the estimation of growing stock volume (GS, in m(3)/ha) by using an inversion algorithm based on artificial neural networks (ANN). The ANN algorithm was first appropriately trained using the available GS estimates obtained from ALS data. The potential of this algorithm was then improved through the innovative use of a simulated dataset, generated by a forward electromagnetic model based on the Radiative Transfer Theory (RTT). The algorithm is able to merge SAR data at L and C bands for predicting GS in diversified Mediterranean environments. The performed analyses indicated that GS was correctly estimated by integrating information from L and C bands on both test areas, with the following statistics: R > 0.97 and RMSE = 28.5 m(3)/ha for the independent test, and R = 0.86 and RMSE approximate to 77 m(3)/ha for the final independent validation, the latter performed on the forest stands of both areas not included in the ALS acquisitions and where conventional measurements were available. The research then illustrates the potential of using the obtained GS estimates from SAR data to drive the simulations of forest net primary production (NPP). This experiment produced spatially explicit estimates of GS current annual increments that are slightly less accurate than those obtained from ground observations (R = 0.75 and RMSE approximate to 1.5 m(3)/ha/year).

关键词： SAR Growing stock volume ANN inversion algorithms Net primary production (NPP)

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