bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Airborne HySpex and Spaceborne PRISMA Hyperspectral Remote Sensing Data for Soil Organic Matter and Carbonates Estimation
Authors: Angelopoulou Theodora , Chabrillat Sabine , Pignatti Stefano , Milewski Robert , Karyotis Konstantinos , Brell Maximilian , Ruhtz Thomas , Bochtis Dionysis , Zalidis George
Published: February 2023

Remote sensing and soil spectroscopy applications are valuable techniques for soil property estimation. Soil organic matter (SOM) and calcium carbonate are important factors in soil quality, and although organic matter is well studied, calcium carbonates require more investigation. In this study, we validated the performance of laboratory soil spectroscopy for estimating the aforementioned properties with referenced in situ data. We also examined the performance of imaging spectroscopy sensors, such as the airborne HySpex and the spaceborne PRISMA. For this purpose, we applied four commonly used machine learning algorithms and six preprocessing methods for the evaluation of the best fitting algorithm.. The study took place over crop areas of Amyntaio in Northern Greece, where extensive soil sampling was conducted. This is an area with a very variable mineralogical environment (from lignite mine to mountainous area). The SOM results were very good at the laboratory scale and for both remote sensing sensors with R2 = 0.79 for HySpex and R2 = 0.76 for PRISMA. Regarding the calcium carbonate estimations, the remote sensing accuracy was R2 = 0.82 for HySpex and R2 = 0.36 for PRISMA. PRISMA was still in the commissioning phase at the time of the study, and therefore, the acquired image did not cover the whole study area. Accuracies for calcium carbonates may be lower due to the smaller sample size used for the modeling procedure. The results show the potential for using quantitative predictions of SOM and the carbonate content based on soil and imaging spectroscopy at the air and spaceborne scales and for future applications using larger datasets.
TMTNet: A Transformer-Based Multimodality Information Transfer Network for Hyperspectral Object Tracking
Authors: Zhao Chunhui , Liu Hongjiao , Su Nan , Xu Congan , Yan Yiming , Feng Shou
Published: February 2023

Hyperspectral video with spatial and spectral information has great potential to improve object tracking performance. However, the limited hyperspectral training samples hinder the development of hyperspectral object tracking. Since hyperspectral data has multiple bands, from which any three bands can be extracted to form pseudocolor images, we propose a Transformer-based multimodality information transfer network (TMTNet), aiming to improve the tracking performance by efficiently transferring the information of multimodality data composed of RGB and hyperspectral in the hyperspectral tracking process. The multimodality information needed to be transferred mainly includes the RGB and hyperspectral multimodality fusion information and the RGB modality information. Specifically, we construct two subnetworks to transfer the multimodality fusion information and the robust RGB visual information, respectively. Among them, the multimodality fusion information transfer subnetwork is designed based on the dual Siamese branch structure. The subnetwork employs the pretrained RGB tracking model as the RGB branch to guide the training of the hyperspectral branch with little training samples. The RGB modality information transfer subnetwork is designed based on a pretrained RGB tracking model with good performance to improve the tracking network’s generalization and accuracy in unknown complex scenes. In addition, we design an information interaction module based on Transformer in the multimodality fusion information transfer subnetwork. The module can fuse multimodality information by capturing the potential interaction between different modalities. We also add a spatial optimization module to TMTNet, which further optimizes the object position predicted by the subject network by fully retaining and utilizing detailed spatial information. Experimental results on the only available hyperspectral tracking benchmark dataset show that the proposed TMTNet tracker outperforms the advanced trackers, demonstrating the effectiveness of this method.
First Results on the Systematic Search of Land Surface Temperature Anomalies as Earthquakes Precursors
Authors: Boudriki Semlali Badr-Eddine , Molina Carlos , Park Hyuk , Camps Adriano
Published: February 2023

Every year, earthquakes cause thousands of casualties and high economic losses. For example, in the time frame from 1998 to 2018, the total number of casualties due to earthquakes was larger than 846 thousand people, and the recorded economic losses were about USD 661 billion. At present, there are no earthquake precursors that can be used to trigger a warning. However, some studies have analyzed land surface temperature (LST) anomalies as a potential earthquake precursor. In this study, a large database of global LST data from the Geostationary Operational Environmental Satellite (GOES) and AQUA satellites during the whole year 2020 has been used to study the LST anomalies in the areas affected by earthquakes. A total of 1350 earthquakes with a magnitude larger than M4 were analyzed. Two methods widely used in the literature have been used to detect LST anomalies in the detrended LST time series: the interquartile (IQT) method and the standard deviation (STD). To the authors’ knowledge, it is the first time that the confusion matrix (CM), the receiver operating characteristic curve (ROC), and some other figures of merit (FoM) are used to assess and optimize the performance of the methods, and to select the optimum combination that could be used as a proxy for their occurrence. A positive anomaly was found a few days before the studied earthquakes, followed by the LST decrease after the event. Further studies over larger regions and more extended periods will be needed to consolidate these encouraging results.
Severe Precipitation Recognition Using Attention-UNet of Multichannel Doppler Radar
Authors: Chen Weishu , Hua Wenjun , Ge Mengshu , Su Fei , Liu Na , Liu Yujia , Xiong Anyuan
Published: February 2023

Quantitative precipitation estimation (QPE) plays an important role in meteorology and hydrology. Currently, multichannel Doppler radar image is used for QPE based on some traditional methods like the Z − R relationship, which struggles to capture the complicated non-linear spatial relationship. Encouraged by the great success of using Deep Learning (DL) segmentation networks in medical science and remoting sensing, a UNet-based network named Reweighted Regression Encoder–Decoder Net (RRED-Net) is proposed for QPE in this paper, which can learn more complex non-linear information from the training data. Firstly, wavelet transform (WT) is introduced to alleviate the noise in radar images. Secondly, a wider receptive field is obtained by taking advantage of attention mechanisms. Moreover, a new Regression Focal Loss is proposed to handle the imbalance problem caused by the extreme long-tailed distribution in precipitation. Finally, an efficient feature selection strategy is designed to avoid exhaustion experiments. Extensive experiments on 465 real processes data demonstrate that the superiority of our proposed RRED-Net not only in the threat score (TS) in the severe precipitation (from 17.6% to 39.6%, ≥20 mm/h) but also the root mean square error (RMSE) comparing to the traditional Z-R relationship-based method (from 2.93 mm/h to 2.58 mm/h, ≥20 mm/h), baseline models and other DL segmentation models.
Quality Analysis of a High-Precision Kinematic Laser Scanning System for the Use of Spatio-Temporal Plant and Organ-Level Phenotyping in the Field
Authors: Esser Felix , Klingbeil Lasse , Zabawa Lina , Kuhlmann Heiner
Published: February 2023

Spatio–temporal determination of phenotypic traits, such as height, leaf angles, and leaf area, is important for the understanding of crop growth and development in modern agriculture and crop science. Measurements of these parameters for individual plants so far have been possible only in greenhouse environments using high-resolution 3D measurement techniques, such as laser scanning or image-based 3D reconstruction. Although aerial and ground-based vehicles equipped with laser scanners and cameras are more and more used in field conditions to perform large-scale phenotyping, these systems usually provide parameters more on the plot level rather than on a single plant or organ level. The reason for this is that the quality of the 3D information generated with those systems is mostly not high enough to reconstruct single plants or plant organs. This paper presents the usage of a robot equipped with a high-resolution mobile laser scanning system. We use the system, which is usually used to create high-definition 3D maps of urban environments, for plant and organ-level morphological phenotyping in agricultural field conditions. The analysis focuses on the point cloud quality as well as the system’s potential by defining quality criteria for the point cloud and system and by using them to evaluate the measurements taken in an experimental agricultural field with different crops. Criteria for evaluation are the georeferencing accuracy, point precision, spatial resolution, and point cloud completeness. Additional criteria are the large-scale scan efficiency and the potential for automation. Wind-induced plant jitter that may affect the crop point cloud quality is discussed afterward. To show the system’s potential, exemplary phenotypic traits of plant height, leaf area, and leaf angles for different crops are extracted based on the point clouds. The results show a georeferencing accuracy of 1–2 cm, a point precision on crop surfaces of 1–2 mm, and a spatial resolution of just a few millimeters. Point clouds become incomplete in the later stages of growth since the vegetation is denser. Wind-induced plant jitters can lead to distorted crop point clouds depending on wind force and crop size. The phenotypic parameter extraction of leaf area, leaf angles, and plant height from the system’s point clouds highlight the outstanding potential for 3D crop phenotyping on the plant-organ level in agricultural fields.
AF-OSD: An Anchor-Free Oriented Ship Detector Based on Multi-Scale Dense-Point Rotation Gaussian Heatmap
Authors: Hua Zizheng , Pan Gaofeng , Gao Kun , Li Hengchao , Chen Su
Published: February 2023

Due to the complexity of airborne remote sensing scenes, strong background and noise interference, positive and negative sample imbalance, and multiple ship scales, ship detection is a critical and challenging task in remote sensing. This work proposes an end-to-end anchor-free oriented ship detector (AF-OSD) framework based on a multi-scale dense-point rotation Gaussian heatmap (MDP-RGH) to tackle these aforementioned challenges. First, to solve the sample imbalance problem and suppress the interference of negative samples such as background and noise, the oriented ship is modeled via the proposed MDP-RGH according to its shape and direction to generate ship labels with more accurate information, while the imbalance between positive and negative samples is adaptively learned for the ships with different scales. Then, the AF-OSD based on MDP-RGH is further devised to detect the multi-scale oriented ship, which is the accurate identification and information extraction for multi-scale vessels. Finally, a multi-task object size adaptive loss function is designed to guide the training process, improving its detection quality and performance for multi-scale oriented ships. Simulation results show that extensive experiments on HRSC2016 and DOTA ship datasets reveal that the proposed method achieves significantly outperforms the compared state-of-the-art methods.
Decadal Quasi-2-Day Wave Observations in the Equatorial Mesopause Region by a Meteor Radar over Kototabang (0.2°S, 100.3°E) and TIMED/TIDI and Comparison with Quasi-2-Day Wave Observations at Mid-Latitudes
Authors: Sun Ruidi , Gu Sheng-Yang , Dou Xiankang , Wei Yafei , Qin Yusong , Yang Zhenlin
Published: February 2023

We studied the characteristics of quasi-two-day wave (QTDW) using the meridional wind in the mesosphere and lower thermosphere (MLT) obtained from a meteor radar over Kototabang (KB, 0.2°S, 100.3°E) from 2003 to 2012. Atmospheric oscillations have a crucial impact on atmospheric dynamics, which contributes to more accurate space weather forecasting, thus providing a more secure space environment for human space exploration activities such as remote sensing and satellite navigation. QTDWs are typical atmospheric oscillations in the upper stratosphere, mesosphere and lower thermosphere. The occurrence time, amplitudes, periods and vertical wavelengths of QTDW events are analyzed statistically. Data obtained from the TIMED Doppler Interferometer (TIDI), which can measure wind and temperature and is onboard the Thermosphere, Ionosphere, Mesosphere Energetics and Dynamics (TIMED) satellite, are used to analyze the global distribution and spatial structure of QTDWs with different zonal wavenumbers. The characteristics of the QTDWs over KB are compared with the QTDWs at the middle latitudes using the meridional wind data from a meteor radar over Wuhan (114.4°E, 30.6°N), Beijing (116.5°E, 39.9°N) and Mohe (121.1°E, 50.1°N). The amplitudes of the QTDW and spectral analysis are calculated by the least squares fitting method. Our results demonstrate that QTDWs are present almost all year around over KB. The occurrence time, amplitudes, periods and vertical wavelengths of QTDW events with different zonal wavenumbers are determined in this study. We also find that the statistical characteristics of the QTDWs in KB are different from those at middle latitudes. The westward zonal wavenumber −4 (W4) events gradually increase with increasing latitude, whereas westward zonal wavenumbers −1, −2, and −3 (W1, W2 and W3, respectively) events all decrease with increasing latitude.
Superpixel Generation for Polarimetric SAR Images with Adaptive Size Estimation and Determinant Ratio Test Distance
Authors: Li Meilin , Zou Huanxin , Qin Xianxiang , Dong Zhen , Sun Li , Wei Juan
Published: February 2023

Superpixel generation of polarimetric synthetic aperture radar (PolSAR) images is widely used for intelligent interpretation due to its feasibility and efficiency. However, the initial superpixel size setting is commonly neglected, and empirical values are utilized. When prior information is missing, a smaller value will increase the computational burden, while a higher value may result in inferior boundary adherence. Additionally, existing similarity metrics are time-consuming and cannot achieve better segmentation results. To address these issues, a novel strategy is proposed in this article for the first time to construct the function relationship between the initial superpixel size (number of pixels contained in the initial superpixel) and the structural complexity of PolSAR images; additionally, the determinant ratio test (DRT) distance, which is exactly a second form of Wilks’ lambda distribution, is adopted for local clustering to achieve a lower computational burden and competitive accuracy for superpixel generation. Moreover, a hexagonal distribution is exploited to initialize the PolSAR image based on the estimated initial superpixel size, which can further reduce the complexity of locating pixels for relabeling. Extensive experiments conducted on five real-world data sets demonstrate the reliability and generalization of adaptive size estimation, and the proposed superpixel generation method exhibits higher computational efficiency and better-preserved details in heterogeneous regions compared to six other state-of-the-art approaches.
Coseismic Rupture Behaviors of the January and March 2022 MW > 5.5 Hala Lake Earthquakes, NE Tibet, Constrained by InSAR Observations
Authors: Yang Jiuyuan , Xu Caijun , Wen Yangmao
Published: February 2023

On 23 January and 25 March 2022, two MW > 5.5 Hala Lake earthquakes characterized by right-lateral strike-slip faulting occurred around the Elashan Fault in Northeastern Tibet, marking the two largest events since the 1927 MW 6.2 Hala Lake earthquake. Since no surface rupture related to the two earthquakes has been reported, the seismogenic faults and coseismic rupture behaviors of the two events are still unknown. The occurrence of the two events provides a rare opportunity to gain insight into the seismogenic structure and rupture behavior of the less studied region, further helping us accurately evaluate the regional seismic hazard. Here, we first exploit Interferometric synthetic aperture radar (InSAR) data to obtain the coseismic deformation associated with the two earthquakes and then invert for the fault geometry and detailed coseismic slip of the two events. Coseismic modeling reveals that the January and March 2022 earthquakes ruptured two buried west-dipping moderate-angle and high-angle right-lateral strike-slip faults, respectively. Most of the slip of the January event occurred at depths from 1.7–7.6 km, while the majority of the slip associated with the March event occurred at depths from 2.5–10 km, which may have been restricted by the intersections between the January and March Hala Lake seismogenic faults. By a comprehensive analysis of the coseismic inversions, stress changes, and early postseismic signal, we suggest that the significant fault dip difference (~30°), highlighting a fault segmentation, stops the rupture propagation from one fault segment to another and that fluid migration may encourage the restart of the rupture of the later event, which requires further investigation. Moreover, Coulomb stress modeling shows stress loading on the eastern segment of the Daxueshan–Shule Fault and the northern segment of the Elashan fault, which we should pay more attention to.
Rectangular Microstrip Array Feed Antenna for C-Band Satellite Communications: Preliminary Results
Authors: Apriono Catur , Mahatmanto B. Pratiknyo Adi , Juwono Filbert H.
Published: February 2023

This paper proposes a rectangular array configuration of microstrip antennas combined with a parabolic reflector for C-band satellite communications. The antenna operates in the frequency range of 3.8–4.2 GHz. In particular, the proposed antenna is a 2 × 2 feed antenna on a parabolic system. It uses a multilayer microstrip array antenna with proximity coupling and coaxial probe techniques as a feeding technique. The fabricated antenna operates at 3.8–4.4 GHz and 12.1 dBi gain at frequency 4.148 GHz. Through simulation, combining the antenna with a 2.4 m parabolic reflector results in a gain of 33.1 dBi. In conclusion, the proposed antenna configuration achieves the expected high gain and narrow beamwidth for the E plane and the H plane.
Effects of Wave-Induced Doppler Velocity on the Sea Surface Current Measurements by Ka-Band Real-Aperture Radar with Small Incidence Angle
Authors: Ma Xiangchao , Meng Junmin , Fan Chenqing , Chen Ping
Published: February 2023

The Doppler shift of microwave radar sea surface echoes serves as the foundation for sea surface current field retrieval; it includes the shift caused by satellite platform motion, ocean waves, and sea surface currents. The Doppler shift caused by ocean waves is known as the wave-induced Doppler velocity (UWD), and its removal is critical for the accurate retrieval of sea surface current fields. The low-incidence Ka-band real-aperture radar rotary scan regime has the capability of directly observing wide-swath two-dimensional current fields, but as a new regime to be further explored and validated, simulation and analysis of UWD in this regime have a significant influence on the hardware design and currently observed applications of this satellite system in its conceptual stage. In this study, we simulated and investigated the impacts of radar parameters and sea-state conditions on the UWD obtained from small-incidence-angle Ka-band rotational scanning radar data and verified the simulation results with the classical analytical solution of average specular scattering point velocity. Simulation results indicate that the change in the azimuth direction of platform observation affects UWD accuracy. Accuracy is the lowest when the antenna is in a vertical side-view. The UWD increases slowly with the incidence angle. Ocean waves are insensitive to polarization in the case of small-incidence-angle specular scattering. The increase in wind speed and the development of wind waves result in a substantial increase in UWD. We classified swell by wavelength and wave height and found that UWD increases with swell size, especially the contribution of swell height to UWD, which is more significant. The contribution of the swell to UWD is smaller than that of wind waves to UWD. Furthermore, the existence of sea surface currents changes the contribution of ocean waves to UWD, and the contribution weakens with increasing wind speed and increases with wind wave development.
Airborne Streak Tube Imaging LiDAR Processing System: A Single Echo Fast Target Extraction Implementation
Authors: Yan Yongji , Wang Hongyuan , Song Boyi , Chen Zhaodong , Fan Rongwei , Chen Deying , Dong Zhiwei
Published: February 2023

In this paper, a ground target extraction system for a novel LiDAR, airborne streak tube imaging LiDAR (ASTIL), is proposed. This system depends on only a single echo and a single data source, and can achieve fast ground target extraction. This system consists of two modules: Autofocus SSD (Single Shot MultiBox Detector) and post-processing. The Autofocus SSD proposed in this paper is used for object detection in the ASTIL echo signal, and its prediction speed exceeds that of the original SSD by a factor of three. In the post-processing module, we describe in detail how the echoes are processed into point clouds. The system was tested on a test set, and it can be seen from a visual perspective that satisfactory results were obtained for the extraction of buildings and trees. The system mAPIoU=0.5 is 0.812, and the FPS is greater than 34. The results prove that this ASTIL processing system can achieve fast ground target extraction based on a single echo and a single data source.
Assessing Glacier Boundaries in the Ala-Archa Valley of Kyrgyzstan by Using Sentinel-1 SAR Dataset and High-Resolution UAV Imagery
Authors: Zholdoshbekov Emilbek , Duishonakunov Murataly , Du Qingyun , Voda Mihai
Published: February 2023

The significant retreat of glaciers in terms of climate change compels researchers to increase the frequency of studies regarding the transformations occurring in glacier boundaries. In this study, we provided glacier area delineation of Ala-Archa valley glaciers by using a Sentinel-1 SAR dataset and the InSAR Coherence technique. Since glaciers have specific patterns of movement, the low coherence method signals the presence of ice. The analysis used the pair of Sentinel-1 datasets for the summer, to ensure the lowest coherence and provide an areal estimation during the peak of ablation. The independence of the SAR images from cloud and light conditions permits us to acquire the images in a timely manner, which highly affects the results of glacier monitoring. This method has shown high potential in the mapping of debris-covered ice and the indication of dead ice. To identify and separate areas of low coherence, such as glacier lakes and unstable slopes, we used object-based mapping by using the geomorphological features of the ice. In this study, we defined a coherence value of less than 0.3 in the glacier area. Our research identified a number of 56 glaciers within the study area of 31.45 km2 and obtained highly accurate glacier maps for the glaciers with a smooth terminus. The analysis shows that automatic and manual delineation of the glaciers’ boundaries have certain limitations, but using the advantages of both scientific approaches, further studies will generate more accurate results.
The Impact of Altimetry Corrections of Sentinel-3A Sea Surface Height in the Coastal Zone of the Northwest Atlantic
Authors: Abele Anrijs , Royston Sam , Bamber Jonathan
Published: February 2023

Corrections to altimeter-measured sea surface height anomalies (SSHA) have a larger proportional effect for synthetic aperture radar (SAR) altimetry than conventional, pulse-limited altimetry because of lower range noise. Here, we quantified the impact of the current generation of altimeter corrections in the coastal zone of the Northwest Atlantic, a region with significant dynamic activity. In this study, we used the sea level variance analysis to determine the change in variance for the altimeter corrections—range, geophysical, and mean surface—compared to the baseline. We also evaluated the performance of two coastal retrackers, ALES (empirical) and SAMOSA++ (fully analytical), against the SSHA from the Radar Altimeter Database System (RADS), which uses the standard SAR retracker. Tide corrections caused the largest change in sea level variance, followed by wet tropospheric corrections and sea state bias. Most non-standard altimeter corrections failed to reduce the sea level variance and performed markedly worse closer to the coast. Coastal retrackers showed a higher deviation from the standard SSHA closer to the coast, especially when the backscatter coefficient was high and the significant wave height was low. We conclude that further development of coastal corrections is needed. Contrary to our prior expectation, we found that standard altimetry corrections appear to perform as well as alternative more advanced/tailored corrections.
Analysis and Simulation of a Sequential Rotationally Excited Circular Polarized Multi-Dipole Array for a Bi-Static Antenna GPR for Deep Exploration
Authors: Fan Haifeng , Zhang Yiming , Tian Qianqian , Wang Xuhong , Meng Hongyan
Published: February 2023

As an effective active remote sensing technology for the exploration of shallow underground targets, ground-penetrating radar (GPR) is a detection method that can be used to obtain information about the characteristics of underground targets by transmitting an electromagnetic wave from an antenna and analyzing the propagation of the electromagnetic wave underground. Due to the frequency (1 MHz–3 GHz) of GPRs, the depth of geological exploration is shallow (0.1–30 m). In order to penetrate the deeper Earth, it is necessary to increase the size of the antenna in accordance with the wavelength ratio and, thus, reduce the radiation frequency. For most bi-static antenna GPRs, a dipole antenna is used as the transmitting antenna and another antenna device is used as a receiving antenna, with both being horizontally linearly polarized (LP) antennas. In some cases, such a design can cause problems, such as the multi-path effect and polarization mismatching. When a GPR is used for deep exploration, increased numbers of errors and greater signal attenuation during data reception and processing often occur. In contrast, at the radiation source, with the use of large-aperture multiple-dipole antennas and multi-channel sequential rotational excitation, the electromagnetic wave can radiate in the form of circular polarization at a low frequency. In the receiving antenna, the issues caused by the multi-path effect and polarization mismatching can be addressed, even if LP antennas are used. A novel sequential rotationally excited (SRE) circularly polarized (CP) multiple-dipole array for a bi-static antenna GPR for deep exploration is proposed in this paper. A large-aperture CP multiple-dipole array is used instead of a small-size LP dipole antenna. The analysis and simulation results demonstrated that, comparing circular polarization and linear polarization with the premise of the same transmitting power, the SRE CP multiple-dipole antenna array radiation source achieved a significant enhancement (about 7 dB) in the signal-to-noise ratio (SNR) as the radiant energy was collected at the receiving antenna. More importantly, by reducing the exploration frequency to 10 KHz, the exploration depth could also be greatly increased by about tenfold.
Structural Nonlinear Damage Identification Method Based on the Kullback–Leibler Distance of Time Domain Model Residuals
Authors: Zuo Heng , Guo Huiyong
Published: February 2023

Under external load excitation, damage such as breathing cracks and bolt loosening will cause structural time domain acceleration to have nonlinear features. To solve the problem of time domain nonlinear damage identification, a damage identification method based on the Kullback–Leibler (KL) distance of time domain model residuals is proposed in this paper. First, an autoregressive (AR) model order was selected using the autocorrelation function (ACF) and Akaike information criterion (AIC). Then, an AR model was obtained based on the structural acceleration response time series, and the AR model residual was extracted. Finally, the KL distance was used as a damage indicator to judge the structural damage source location. The effectiveness of the proposed method was verified by using a multi-story, multi-span stand model experiment and a simulated eight-story shear structure. The results show that the proposed structural nonlinear damage identification method can effectively distinguish the structural damage location of multi-degree-of-freedom shear structures and complex stand structures, and it is robust enough to detect environmental noise and small damage.
Remote Sensing Monitoring of the Pietrafitta Earth Flows in Southern Italy: An Integrated Approach Based on Multi-Sensor Data
Authors: Mazza Davide , Cosentino Antonio , Romeo Saverio , Mazzanti Paolo , Guadagno Francesco M. , Revellino Paola
Published: February 2023

Earth flows are complex gravitational events characterised by a heterogeneous displacement pattern in terms of scale, style, and orientation. As a result, their monitoring, for both knowledge and emergency purposes, represents a relevant challenge in the field of engineering geology. This paper aims to assess the capabilities, peculiarities, and limitations of different remote sensing monitoring techniques through their application to the Pietrafitta earth flow (Southern Italy). The research compared and combined data collected during the main landslide reactivations by different ground-based remote sensors such as Robotic Total Station (R-TS), Terrestrial Synthetic Aperture Radar Interferometry (T-InSAR), and Terrestrial Laser Scanner (TLS), with data being derived by satellite-based Digital Image Correlation (DIC) analysis. The comparison between R-TS and T-InSAR measurements showed that, despite their different spatial and temporal resolutions, the observed deformation trends remain approximately coherent. On the other hand, DIC analysis was able to detect a kinematic process, such as the expansion of the landslide channel, which was not detected by the other techniques used. The results suggest that, when faced with complex events, the use of a single monitoring technique may not be enough to fully observe and understand the processes taking place. Therefore, the limitations of each different technique alone can be solved by a multi-sensor monitoring approach.
A Distributionally Robust Fusion Framework for Autonomous Multisensor Spacecraft Navigation during Entry Phase of Mars Entry, Descent, and Landing
Authors: Zewge Natnael S. , Bang Hyochoong
Published: February 2023

A robust multisensor navigation filter design for the entry phase of next-generation Mars entry, descent, and landing (EDL) is presented. The entry phase is the longest and most uncertain portion of a Mars landing sequence. Navigation performance at this stage determines landing precision at the end of the powered descent phase of EDL. In the present work, measurements from a ground-based radio beacon array, an inertial measurement unit (IMU), as well as an array of atmospheric and aerothermal sensors on the body of a Mars entry vehicle are fused using an M-estimation-based iterated extended Kalman filtering (MIEKF) framework. The multisensor approach enables an increased positioning accuracy as well as the estimation of parameters that are otherwise unobservable. Furthermore, owing to the proposed statistically robust filter formulation, states and parameters can be accurately estimated in the presence of non-Gaussian measurement noise. Deviations from normally distributed observation noise correspond to outlier events such as sensor faults or other sources of spurious sensor data such as interference. The proposed framework provides a significant reduction in estimation error at the parachute phase of EDL, thereby increasing the likelihood of a pinpoint landing at a chosen landing site. Six states and three parameters are estimated. The suggested method is compared to the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). Detailed simulation results show that the presented fusion architecture is able to meet future pinpoint planetary landing requirements in realistic sensor measurement scenarios.
Developing a near Real-Time Cloud Cover Retrieval Algorithm Using Geostationary Satellite Observations for Photovoltaic Plants
Authors: Xia Pan , Min Min , Yu Yu , Wang Yun , Zhang Lu
Published: February 2023

Clouds can block solar radiation from reaching the surface, so timely and effective cloud cover test and forecasting is critical to the operation and economic efficiency of photovoltaic (PV) plants. Traditional cloud cover algorithms based on meteorological satellite observation require many auxiliary data and computing resources, which are hard to implement or transplant for applications at PV plants. In this study, a portable and fast cloud mask algorithm (FCMA) is developed to provide near real-time (NRT) spatial-temporally matched cloud cover products for PV plants. The geostationary satellite imager data from the Advanced Himawari Imager aboard Himawari-8 and the related operational cloud mask algorithm (OCMA) are employed as benchmarks for comparison and validation. Furthermore, the ground-based manually observed cloud cover data at seven quintessential stations at 08:00 and 14:00 BJT (Beijing Time) in 2017 are employed to verify the accuracy of cloud cover data derived from FCMA and OCMA. The results show a high consistency with the ground-based data, and the average correlation coefficient (R) is close to 0.85. Remarkably, the detection accuracy of FCMA is slightly higher than that of OCMA, demonstrating the feasibility of FCMA for providing NRT cloud cover at PV plants.
Non-Destructive Diagnosis on the Masaccio Frescoes at the Brancacci Chapel, Church of Santa Maria del Carmine (Florence)
Authors: Leucci Giovanni , Giorgi Lara De , Ferrari Ivan , Giuri Francesco , Longhitano Lucrezia , Felici Alberto , Riminesi Cristiano
Published: February 2023

The Basilica of Santa Maria del Carmine in Florence, in the Oltrarno area, was built in 1268 (pre-Renaissance low medieval context) and consecrated in 1422. Following a devastating fire in the interior of the original church, in 1771, very little remained. Among the parts that were saved were the Corsini and Brancacci chapels. The architect Giuseppe Ruggeri was responsible for the reconstruction of the church, which was completed in 1782 (with the exception of the gabled façade which remained unfinished, as can still be seen today). Geophysical investigations were undertaken into the Brancacci chapel in order to have information on the structure of the wall that contains wall paintings by Masaccio, Masolino, and Filippino Lippi, to understand the stratigraphy of the mortars, and to formulate some hypotheses on the causes of their detachment. The results are interesting.
Greenland-Ice-Sheet Surface Temperature and Melt Extent from 2000 to 2020 and Implications for Mass Balance
Authors: Fang Zhenxiang , Wang Ninglian , Wu Yuwei , Zhang Yujie
Published: February 2023

Accurate monitoring of surface temperature and melting on the Greenland Ice Sheet (GrIS) is important for tracking the ice sheet’s mass balance as well as global and Arctic climate change. Using a moderate-resolution-imaging-spectroradiometer (MODIS)-derived land-surface-temperature (LST) data product with a resolution of 1 km from 2000 to 2020, the temporal and spatial variations of annual and seasonal ‘clear-sky’ surface temperature were evaluated. We also monitored summer surface melting and studied the relationship between the mass balance of the ice sheet and changes in surface temperature and melting. The results show that the mean annual LST during the study period is −24.86 ± 5.46 °C, with the highest of −22.48 ± 5.61 °C in 2010 and the lowest temperature of −26.49 ± 5.30 °C in 2015. With the change of season, the spatial variation of the ice-sheet surface temperature changes greatly. 2012 and 2019 experienced the warmest summers (−5.92 ± 4.01 °C and −6.51 ± 3.93 °C), with extreme cumulative melting detected on the ice-sheet surface (89.9% and 89.7%, respectively), and 2002 also experienced a greater extent of melting. But short period of melt in 2002 and 2019 (30.6% and 31.4%, respectively), accounted for a larger proportion, with neither the duration nor intensity of the melt reaching that of 2012. There is a strong correlation between the GrIS surface temperature and its mass balance. By fitting the relationship between surface temperature and mass balance, it was found that 93.83% (6.17%) of the ice-sheet response to surface-temperature change was via surface-mass balance (discharge and basal-mass balance).
Spatiotemporal Patterns of Evapotranspiration in Central Asia from 2000 to 2020
Authors: Hao Xingming , Fan Xue , Zhao Zhuoyi , Zhang Jingjing
Published: February 2023

Evapotranspiration (ET) affects the dry and wet conditions of a region, particularly in arid Central Asia, where changes in evapotranspiration profoundly influence society, the economy, and ecosystems. However, the changing trends in and driving factors of evapotranspiration in Central Asia remain unclear. Therefore, we used estimated ET and reanalysis data to answer research questions. Our results showed that (1) potential evapotranspiration (PET) and ET showed a generally downward trend, in which PET and ET decreased in 37.93% and 17.42% of the total area, respectively. However, PET and ET showed opposite trends in 59.41% of the study area, mainly showing a decrease in PET and an increase in ET. (2) The absolute contribution rates of vegetation–human activity coupling factor (VH), PET, and precipitation (P) to ET were 43.19%, 40.02%, and 16.79%, respectively, and the VH was the main determiner of ET. (3) Transpiration (ETc) dominated the change in ET in 56.4% of the region, whereas soil evaporation (ETs) dominated the change in ET in the rest of the region. The coverage threshold that determines the dominant contributions of ETc and ETs to ET was approximately 18–19%. Below this coverage threshold, the contribution rate of ETs to ET exceeded that of ETc and vice versa. In the context of global climate change, this study can provide scientific support for the restoration of water resources and sustainability evaluation of water resources.
CTFuseNet: A Multi-Scale CNN-Transformer Feature Fused Network for Crop Type Segmentation on UAV Remote Sensing Imagery
Authors: Xiang Jianjian , Liu Jia , Chen Du , Xiong Qi , Deng Chongjiu
Published: February 2023

Timely and accurate acquisition of crop type information is significant for irrigation scheduling, yield estimation, harvesting arrangement, etc. The unmanned aerial vehicle (UAV) has emerged as an effective way to obtain high resolution remote sensing images for crop type mapping. Convolutional neural network (CNN)-based methods have been widely used to predict crop types according to UAV remote sensing imagery, which has excellent local feature extraction capabilities. However, its receptive field limits the capture of global contextual information. To solve this issue, this study introduced the self-attention-based transformer that obtained long-term feature dependencies of remote sensing imagery as supplementary to local details for accurate crop-type segmentation in UAV remote sensing imagery and proposed an end-to-end CNN–transformer feature-fused network (CTFuseNet). The proposed CTFuseNet first provided a parallel structure of CNN and transformer branches in the encoder to extract both local and global semantic features from the imagery. A new feature-fusion module was designed to flexibly aggregate the multi-scale global and local features from the two branches. Finally, the FPNHead of feature pyramid network served as the decoder for the improved adaptation to the multi-scale fused features and output the crop-type segmentation results. Our comprehensive experiments indicated that the proposed CTFuseNet achieved a higher crop-type-segmentation accuracy, with a mean intersection over union of 85.33% and a pixel accuracy of 92.46% on the benchmark remote sensing dataset and outperformed the state-of-the-art networks, including U-Net, PSPNet, DeepLabV3+, DANet, OCRNet, SETR, and SegFormer. Therefore, the proposed CTFuseNet was beneficial for crop-type segmentation, revealing the advantage of fusing the features found by the CNN and the transformer. Further work is needed to promote accuracy and efficiency of this approach, as well as to assess the model transferability.
Evolution of Small and Micro Wetlands and Their Driving Factors in the Yangtze River Delta—A Case Study of Wuxi Area
Authors: Zhang Jiamin , Chu Lei , Zhang Zengxin , Zhu Bin , Liu Xiaoyan , Yang Qiang
Published: February 2023

Understanding the long-term dynamics and driving factors behind small and micro wetlands is critical for their management and future sustainability. This study explored the impacts of natural and anthropogenic factors on the spatiotemporal evolution of these areas in Wuxi area using the support vector machine (SVM) classification method and the geographic detector model based on Landsat satellite image data from 1985 to 2020. The results revealed that: (1) Natural wetlands were prominent in Wuxi area, with an average proportion of 70%, and although they exhibited a downward trend over the last ten years, the scale of natural small and micro wetlands increased 1.5-fold—from 4349.59 hm2 in 1985 to 10,841.59 hm2 in 2020. (2) The small and micro wetlands in Wuxi area had obvious seasonal variations, with most being 0.1–1 hm2 and 1–3 hm2, respectively. From the perspective of spatial distribution, they were primarily distributed in Yixing district, which accounts for 34% of Wuxi area. (3) The distribution of small and micro wetlands was systematically affected by natural and human activities. The main factors that affected the distribution of small and micro wetlands were the average annual temperature and GDP, with the interactions between all factors being nonlinear and bi-linear. The influences of natural factors on small and micro wetlands were weakened, with human activities steadily emerging as the dominant factor that affected their distribution. The results of this study can provide supportive data and a scientific basis for the ecological restoration and protection of wetlands.
Highly Accurate Radar Cross-Section and Transfer Function Measurement of a Digital Calibration Transponder without Known Reference—Part I: Measurement and Results
Authors: Reimann Jens , Büchner Anna Maria , Raab Sebastian , Weidenhaupt Klaus , Jirousek Matthias , Schwerdt Marco
Published: February 2023

Active Radar Calibrators (ARC), also called calibration transponders, are often used as reference targets for absolute radiometric calibration of radar systems due to their large achievable Radar Cross-Section (RCS). However, before using a transponder as a reference target, the hardware itself has to be calibrated. A novel method, called the three-transponder method, was proposed some years ago and allows for RCS calibration of digital transponders without using any RCS targets as reference. In this paper, this technique is further refined and applied to a setup utilizing only one digital transponder. The accurate measurement design is described and a novel, elaborated data processing scheme is developed to minimize remaining noise and clutter effects in the data. A comprehensive error analysis is presented in the second part of this paper.
Spatiotemporal Dynamics of Water Quality Indicators in Koka Reservoir, Ethiopia
Authors: Assegide Endaweke , Shiferaw Hailu , Tibebe Degefie , Peppa Maria V. , Walsh Claire L. , Alamirew Tena , Zeleke Gete
Published: February 2023

The science and application of the Earth observation system are receiving growing traction and wider application, and the scope is becoming wider and better owing to the availability of the higher resolution of satellite remote sensing products. A water quality monitoring model was developed using Sentinel-2 satellite remote sensing data set to investigate the spatiotemporal dynamics of water quality indicators at Koka Reservoir. L1C images were processed with an Atmospheric correction processor ACOLITE. The months from June 2021 to May 2022 and the years 2017 to 2022 were used for the temporal analyses. Algorithms were developed by using regression analysis and developing empirical models by correlating satellite reflectance data with in situ Chlorophyll-a (Chl-a), turbidity (TU), and Total suspended matter (TSS) measurements. All of the analyzed parameters have determination coefficients (R2) greater than 0.67, indicating that they can be turned into predictive models. R2 for the developed algorithms were 0.91, 0.92, and 0.67, indicating that good correlations have been found between field-based and estimated Chl-a, TU, and TSS, respectively. Accordingly, the mean monthly Chl-a, TU, and TSS levels have ranged from (59.69 to 144.25 g/L), (79.67 to 115.39 NTU), and (38.46 to 368.97 mg/L), respectively. The annual mean Chl-a, TU, and TSS vary from (52.86–96.19 µg/L), (71.04–83 NTU), and (36.58–159.26 mg/L), respectively, showing that the reservoir has been continuously polluted over the last seven years. The spatial study found that the distributions of Chl-a, TU, and TSS were heterogeneous, with Chl-a being greater in the south and southwest, and TU and TSS being higher on the western shore of the reservoir. In conclusion, these results show that there are spatial as well as temporal variations on water quality parameters. The proposed algorithms are capable of detecting optically active water quality indicators and can be applied in similar environmental situations.
Exploiting the Sensitivity of Dual-Frequency Smartphones and GNSS Geodetic Receivers for Jammer Localization
Authors: Pavlovčič-Prešeren Polona , Dimc Franc , Bažec Matej
Published: February 2023

Smartphones now dominate the Global Navigation Satellite System (GNSS) devices capable of collecting raw data. However, they also offer valuable research opportunities in intentional jamming, which has become a serious threat to the GNSS. Smartphones have the potential to locate jammers, but their robustness and sensitivity range need to be investigated first. In this study, the response of smartphones with dual-frequency, multi-constellation reception capability, namely, a Xiaomi Mi8, a Xiaomi 11T, a Samsung Galaxy S20, and a Huawei P40, to various single- and multi-frequency jammers is investigated. The two-day jamming experiments were conducted in a remote area with minimal impact on users, using these smartphones and two Leica GS18 and two Leica GS15 geodetic receivers, which were placed statically at the side of a road and in a line, approximately 10 m apart. A vehicle with jammers installed passed them several times at a constant speed. In one scenario, a person carrying the jammer was constantly tracked using a tacheometer to determine the exact distance to the receivers for each time stamp. The aim was, first, to determine the effects of the various jammers on the smartphones’ positioning capabilities and to compare their response in terms of the speed and quality of repositioning with professional geodetic receivers. Second, a method was developed to determine the position of the interference source by varying the signal loss threshold and the recovery time on the smartphone and the decaying carrier-to-noise ratio (CNR). The results indicate that GNSS observations from smartphones have an advantage over geodetic receivers in terms of localizing jammers because they do not lose the signal near the source of the jamming, but they are characterized by sudden drops in the CNR.