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Road Extraction and Distress Assessment by Spaceborne, Airborne, and Terrestrial Platforms Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Valerio Baiocchi, Xianfeng Zhang, Alessandro Mei
The road systems connecting villages, cities, and countries stand as a pivotal transportation infrastructure in modern society [...]
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Mapping Integrated Crop–Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning Remote Sens. (IF 5.0) Pub Date : 2024-04-17 João P. S. Werner, Mariana Belgiu, Inacio T. Bueno, Aliny A. Dos Reis, Ana P. S. G. D. Toro, João F. G. Antunes, Alfred Stein, Rubens A. C. Lamparelli, Paulo S. G. Magalhães, Alexandre C. Coutinho, Júlio C. D. M. Esquerdo, Gleyce K. D. A. Figueiredo
Integrated crop–livestock systems (ICLS) are among the main viable strategies for sustainable agricultural production. Mapping these systems is crucial for monitoring land use changes in Brazil, playing a significant role in promoting sustainable agricultural production. Due to the highly dynamic nature of ICLS management, mapping them is a challenging task. The main objective of this research was
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Transfer-Aware Graph U-Net with Cross-Level Interactions for PolSAR Image Semantic Segmentation Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Shijie Ren, Feng Zhou, Lorenzo Bruzzone
Although graph convolutional networks have found application in polarimetric synthetic aperture radar (PolSAR) image classification tasks, the available approaches cannot operate on multiple graphs, which hinders their potential to generalize effective feature representations across different datasets. To overcome this limitation and achieve robust PolSAR image classification, this paper proposes a
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A Pseudo-Satellite Fingerprint Localization Method Based on Discriminative Deep Belief Networks Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Xiaohu Liang, Shuguo Pan, Baoguo Yu, Shuang Li, Shitong Du
Pseudo-satellite technology has excellent compatibility with the BDS satellite navigation system in terms of signal systems. It can serve as a stable and reliable positioning signal source in signal-blocking environments. User terminals can achieve continuous high-precision positioning both indoors and outdoors without any modification to the navigation module. As a result, pseudo-satellite indoor
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Radar Signal Classification with Multi-Frequency Multi-Scale Deformable Convolutional Networks and Attention Mechanisms Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Ruofei Liang, Yigang Cen
In the realm of short-range radar applications, the focus on detecting “low, slow, and small” (LSS) targets has escalated, marking a pivotal aspect of critical area defense. This study pioneers the use of one-dimensional convolutional neural networks (1D-CNNs) for direct slow-time dimension radar feature extraction, sidestepping the complexity tied to frequency and wavelet domain transformations. It
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Calculation Model of Radar Terrain Masking Based on Tensor Grid Dilation Operator Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Kaiyu Nie, Shengliang Fang, Hao Liu, Xiaofeng Wei, Yamin Zhang, Jianpeng Yang, Qinglei Kong, Bo Chen
In recent years, the three-dimensional (3D) radar detection range has played an essential role in the layout of devices such as aircraft and drones. To compensate for the shortcomings of three-dimensional calculations for radar terrain masking, a new calculation method is proposed for assessing the terrain occlusion of radar detection range. First, the high-dimensional electromagnetic data after discretization
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Raster Scale Farmland Productivity Assessment with Multi-Source Data Fusion—A Case of Typical Black Soil Region in Northeast China Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Yuwen Liu, Chengyuan Wang, Enheng Wang, Xuegang Mao, Yuan Liu, Zhibo Hu
Degradation of black soil areas is a serious threat to national food security and ecological safety; nevertheless, the current lack of information on the location, size, and condition of black soil farmland productivity is a major obstacle to the development of strategies for the sustainable utilization of black soil resources. We synthesized remote sensing data and geospatial thematic data to construct
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Assessment of the Real-Time and Rapid Precise Point Positioning Performance Using Geodetic and Low-Cost GNSS Receivers Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Mengmeng Chen, Lewen Zhao, Wei Zhai, Yifei Lv, Shuanggen Jin
Precise Point Positioning (PPP), coupled with the ambiguity resolution (AR) method, has demonstrated substantial potential in fields like agricultural navigation and airborne mapping. However, there remains a notable deficiency in the comprehensive comparative evaluation of its performance when using rapid and real-time satellite products, especially for mass low-cost receivers. Stations equipped with
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Sun/Shade Separation in Optical and Thermal UAV Images for Assessing the Impact of Agricultural Practices Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Claire Marais-Sicre, Solen Queguiner, Vincent Bustillo, Luka Lesage, Hugues Barcet, Nathalie Pelle, Nicolas Breil, Benoit Coudert
Unmanned aerial vehicles (UAVs) provide images at decametric spatial resolutions. Their flexibility, efficiency, and low cost make it possible to apply UAV remote sensing to multisensor data acquisition. In this frame, the present study aims at employing RGB UAV images (at a 3 cm resolution) and multispectral images (at a 16 cm resolution) with related vegetation indices (VIs) for mapping surfaces
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Changes in Surface and Terrestrial Waters in the China–Pakistan Economic Corridor Due to Climate Change and Human Activities Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Jiayu Bao, Yanfeng Wu, Xiaoran Huang, Peng Qi, Ye Yuan, Tao Li, Tao Yu, Ting Wang, Pengfei Zhang, Vincent Nzabarinda, Sulei Naibi, Jingyu Jin, Gang Long, Shuya Yang
The surface water area (SWA) and terrestrial water storage (TWS) are both essential metrics for assessing regional water resources. However, the combined effects of climate change and human activities on the dynamics of the SWA and TWS have not been extensively researched within the context of the CPEC. To fill this gap, we first analyzed the annual changes in the SWA and TWS in the China–Pakistan
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Exploring Spatiotemporal Characteristics and Driving Forces of Straw Burning in Hunan Province, China, from 2010 to 2020 Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Yu Zeng, Shuguang Liu, Sheng Huang, Sopan D. Patil, Wenyuan Gao, Hao Li
Straw burning is a significant source of atmospheric pollutants, releasing particulate matter and trace gases. Capturing the characteristics of straw burning and understanding its influencing factors are important prerequisites for regulating straw burning. Based on the fire points detected by the Moderate-resolution Imaging Spectroradiometer (MODIS) in Hunan province, China, from 2010 to 2020, this
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Detecting Moving Wildlife Using the Time Difference between Two Thermal Airborne Images Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Yu Oishi, Natsuki Yoshida, Hiroyuki Oguma
Wildlife damage to agriculture is serious in Japan; therefore, it is important to understand changes in wildlife population sizes. Although several studies have been conducted to detect wildlife from drone images, behavioral changes (such as wildlife escaping when a drone approaches) have been confirmed. To date, the use of visible and near-infrared images has been limited to the daytime because many
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A Real-Time Method for Railway Track Detection and 3D Fitting Based on Camera and LiDAR Fusion Sensing Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Tiejian Tang, Jinghao Cao, Xiong Yang, Sheng Liu, Dongsheng Zhu, Sidan Du, Yang Li
Railway track detection, which is crucial for train operational safety, faces numerous challenges such as the curved track, obstacle occlusion, and vibrations during the train’s operation. Most existing methods for railway track detection use a camera or LiDAR. However, the vision-based approach lacks essential 3D environmental information about the train, while the LiDAR-based approach tends to detect
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Studying the Internal Wave Generation Mechanism in the Northern South China Sea Using Numerical Simulation, Synthetic Aperture Radar, and In Situ Measurements Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Kan Zeng, Ruyin Lyu, Hengyu Li, Rongqing Suo, Tao Du, Mingxia He
The internal waves in the South China Sea are highly correlated with the tidal currents in the Luzon Strait, which makes it possible to establish an internal wave prediction model based on internal wave kinematics. However, the kinematic model requires the input of the exact location and time of the initial internal wave for which the generation mechanism of internal waves in the northern South China
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Assessing Greenhouse Gas Monitoring Capabilities Using SolAtmos End-to-End Simulator: Application to the Uvsq-Sat NG Mission Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Cannelle Clavier, Mustapha Meftah, Alain Sarkissian, Frédéric Romand, Odile Hembise Fanton d’Andon, Antoine Mangin, Slimane Bekki, Pierre-Richard Dahoo, Patrick Galopeau, Franck Lefèvre, Alain Hauchecorne, Philippe Keckhut
Monitoring atmospheric concentrations of greenhouse gases (GHGs) like carbon dioxide and methane in near real time and with good spatial resolution is crucial for enhancing our understanding of the sources and sinks of these gases. A novel approach can be proposed using a constellation of small satellites equipped with miniaturized spectrometers having a spectral resolution of a few nanometers. The
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Potential Modulation of Aerosol on Precipitation Efficiency in Southwest China Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Pengguo Zhao, Xiaoran Liu, Chuanfeng Zhao
The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possible modulation of aerosol on the precipitation capacity of clouds has received limited attention. In this study, we utilized multi-source data on aerosol, cloud properties, precipitation, and meteorological factors to investigate the impact of aerosols
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Object-Based Semi-Supervised Spatial Attention Residual UNet for Urban High-Resolution Remote Sensing Image Classification Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Yuanbing Lu, Huapeng Li, Ce Zhang, Shuqing Zhang
Accurate urban land cover information is crucial for effective urban planning and management. While convolutional neural networks (CNNs) demonstrate superior feature learning and prediction capabilities using image-level annotations, the inherent mixed-category nature of input image patches leads to classification errors along object boundaries. Fully convolutional neural networks (FCNs) excel at pixel-wise
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A Multiscale Filtering Method for Airborne LiDAR Data Using Modified 3D Alpha Shape Remote Sens. (IF 5.0) Pub Date : 2024-04-18 Di Cao, Cheng Wang, Meng Du, Xiaohuan Xi
The complexity of terrain features poses a substantial challenge in the effective processing and application of airborne LiDAR data, particularly in regions characterized by steep slopes and diverse objects. In this paper, we propose a novel multiscale filtering method utilizing a modified 3D alpha shape algorithm to increase the ground point extraction accuracy in complex terrain. Our methodology
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Long-Tailed Effect Study in Remote Sensing Semantic Segmentation Based on Graph Kernel Principles Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Wei Cui, Zhanyun Feng, Jiale Chen, Xing Xu, Yueling Tian, Huilin Zhao, Chenglei Wang
The performance of semantic segmentation in remote sensing, based on deep learning models, depends on the training data. A commonly encountered issue is the imbalanced long-tailed distribution of data, where the head classes contain the majority of samples while the tail classes have fewer samples. When training with long-tailed data, the head classes dominate the training process, resulting in poorer
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Enhancing Soil Moisture Active–Passive Estimates with Soil Moisture Active–Passive Reflectometer Data Using Graph Signal Processing Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Johanna Garcia-Cardona, Nereida Rodriguez-Alvarez, Joan Francesc Munoz-Martin, Xavier Bosch-Lluis, Kamal Oudrhiri
The Soil Moisture Active–Passive (SMAP) mission has greatly contributed to the use of remote sensing technologies for monitoring the Earth’s land surface and estimating geophysical parameters that influence the climate system. Since the SMAP mission switched its radar receiver to allow the reception of Global Positioning System (GPS) signals, Global Navigation Satellite System Reflectometry (GNSS-R)
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Methane Retrieval from Hyperspectral Infrared Atmospheric Sounder on FY3D Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Xinxin Zhang, Ying Zhang, Fan Meng, Jinhua Tao, Hongmei Wang, Yapeng Wang, Liangfu Chen
This study utilized an infrared spotlight Hyperspectral infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) mounted on FY3D cloud products from the National Satellite Meteorological Center of China to obtain methane profile information. Methane inversion channels near 7.7 μm were selected based on the different distribution of methane weighting functions across different
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Estimation of Top-of-Atmosphere Longwave Cloud Radiative Forcing Using FengYun-4A Geostationary Satellite Data Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Ri Xu, Jun Zhao, Shanhu Bao, Huazhe Shang, Fangling Bao, Gegen Tana, Lesi Wei
The distribution and variation of top-of-atmosphere longwave cloud radiative forcing (LCRFTOA) has drawn a significant amount of attention due to its importance in understanding the energy budget. Advancements in sensor and data processing technology, as well as a new generation of geostationary satellites, such as the FengYun-4A (FY-4A), allow for high spatiotemporal resolutions that are crucial for
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Analysis of Height of the Stable Boundary Layer in Summer and Its Influencing Factors in the Taklamakan Desert Hinterland Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Guocheng Yang, Wei Shu, Minzhong Wang, Donglei Mao, Honglin Pan, Jiantao Zhang
Stable boundary layer height (SBLH) is an important parameter to characterize the characteristics and vertical structure of the nocturnal lower atmosphere at night. The distribution of SBLH has obvious spatial and temporal differences, and there are many meteorological factors affecting the SBLH, but at present, there are few quantitative studies on the effects of near-surface meteorological factors
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Remote, Rugged Field Scenarios for Archaeology and the Field Sciences: Object Avoidance and 3D Flight Planning with sUAS Photogrammetry Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Carla Klehm, Malcolm D. Williamson, Leland C. Bement, Brandi Bethke
Advances built into recent sUASs (drones) offer a compelling possibility for field-based data collection in logistically challenging and GPS-denied environments. sUASs-based photogrammetry generates 3D models of features and landscapes, used extensively in archaeology as well as other field sciences. Until recently, navigation has been limited by the expertise of the pilot, as objects, like trees,
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Time Series Analysis of Multisensor Data for Precision Viticulture—Assessing Microscale Variations in Plant Development with Respect to Irrigation and Topography Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Melanie Brandmeier, Daniel Heßdörfer, Philipp Siebenlist, Adrian Meyer-Spelbrink, Anja Kraus
In the context of climate change, vineyard monitoring to better understand spatiotemporal patterns of grapevine development is of utter importance for precision viticulture. We present a time series analysis of hyperspectral in situ and multispectral UAV data for different irrigation systems in Lower Franconia and correlate results with sensor data for soil moisture, temperature, and precipitation
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Spatial and Temporal Variation Patterns of NO 5.3 µm Infrared Radiation during Two Consecutive Auroral Disturbances Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Fan Wu, Congming Dai, Shunping Chen, Cong Zhang, Wentao Lian, Heli Wei
The variation in key parameters of the solar–terrestrial space during two consecutive auroral disturbances (the magnetic storm index, Dst index = −422 nT) that occurred during the 18–23 November 2003 period was analyzed in this paper, as well as the spatiotemporal characteristics of NO 5.3 μm radiation with an altitude around the location of 55°N 160°W. The altitude was divided into four regions (50–100
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Remote Sensing Image Dehazing via a Local Context-Enriched Transformer Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Jing Nie, Jin Xie, and Hanqing Sun
Remote sensing image dehazing is a well-known remote sensing image processing task focused on restoring clean images from hazy images. The Transformer network, based on the self-attention mechanism, has demonstrated remarkable advantages in various image restoration tasks, due to its capacity to capture long-range dependencies within images. However, it is weak at modeling local context. Conversely
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Monsoon-Based Linear Regression Analysis for Filling Data Gaps in Gravity Recovery and Climate Experiment Satellite Observations Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Hussein A. Mohasseb, Wenbin Shen, Jiashuang Jiao
Over the past two decades, the Gravity Recovery and Climate Experiment (GRACE) satellite mission and its successor, GRACE-follow on (GRACE-FO), have played a vital role in climate research. However, the absence of certain observations during and between these missions has presented a persistent challenge. Despite numerous studies attempting to address this issue with mathematical and statistical methods
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Lightweight Deep Neural Network with Data Redundancy Removal and Regression for DOA Estimation in Sensor Array Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Aifei Liu, Jiapeng Guo, Yauhen Arnatovich, Zhiling Liu
In this paper, a lightweight deep neural network (DNN) for direction of arrival (DOA) estimation is proposed, of which the input vector is designed to remove data redundancy as well as remaining DOA information. By exploring the Vandermonde property of the steering vector of a uniform linear array (ULA), the size of the newly designed input vector is greatly reduced. Furthermore, the DOA estimation
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Through-Wall Imaging Using Low-Cost Frequency-Modulated Continuous Wave Radar Sensors Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Mirel Paun
Many fields of human activity benefit from the ability to create images of obscured objects placed behind walls and to map their displacement in a noninvasive way. Usually, imaging devices like Synthetic Aperture Radars (SARs) and Ground-Penetrating Radars (GPRs) use expensive dedicated electronics which results in prohibitive prices. This paper presents the experimental implementation and the results
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An Optimized Variational Processing Method Based on Satellite-Station Data on Snow Cover Days on the Qinghai–Tibet Plateau Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Xiaoying Xue, Xiangde Xu, Runze Zhao, Wenyue Cai
The Qinghai–Tibet Plateau is a sensitive area to climate change, and snow cover has an important impact. Due to the high altitude and complex terrain, station observations of snow cover on the plateau are sparse but objective, while satellite data have high resolution but limited accuracy. Therefore, an optimized variational processing method based on daily satellite data from 1989 to 2020 and monthly
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Comprehensive Assessment and Analysis of the Current Global Aerosol Optical Depth Products Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Liping Zhang, Xufeng Wang, Guanghui Huang, Songlin Zhang
Aerosol Optical Depth (AOD) is one of the most important optical properties of aerosols that may affect the energy budgets of our Earth–atmosphere system significantly. Currently, while regional and even global AOD knowledge has been given by various satellites or models, these products are still fraught with uncertainties. In this study, one sophisticated satellite-derived AOD product from MODIS (MODerate
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Assessing Satellite-Derived OpenET Platform Evapotranspiration of Mature Pecan Orchard in the Mesilla Valley, New Mexico Remote Sens. (IF 5.0) Pub Date : 2024-04-17 Zada M. Tawalbeh, A. Salim Bawazir, Alexander Fernald, Robert Sabie, Richard J. Heerema
Pecan is a major crop in the Mesilla Valley, New Mexico. Due to prolonged droughts, growers face challenges related to water shortages. Therefore, irrigation management is crucial for farmers. Advancements in satellite-derived evapotranspiration (ET) models and accessibility to data from web-based platforms like OpenET provide farmers with new tools to improve crop irrigation management. This study
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Observation Analysis and Numerical Simulation of the Urban Barrier Effect on Thunderstorm Organization Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Tao Shi, Yuanjian Yang, Gaopeng Lu, Xiangcheng Wen, Lei Liu, Ping Qi
The urban underlying surface may affect the thunderstorm process. However, current research on this phenomenon is still in its infancy. This paper aimed to analyze the influence of the urban underlying surface on the evolution of thunderstorm organization through ground observation and numerical simulation. The results indicated that when the thunderstorm system with strong synoptic conditions passed
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A Novel Method for Cloud and Cloud Shadow Detection Based on the Maximum and Minimum Values of Sentinel-2 Time Series Images Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Kewen Liang, Gang Yang, Yangyan Zuo, Jiahui Chen, Weiwei Sun, Xiangchao Meng, Binjie Chen
Automatic and accurate detection of clouds and cloud shadows is a critical aspect of optical remote sensing image preprocessing. This paper provides a time series maximum and minimum mask method (TSMM) for cloud and cloud shadow detection. Firstly, the Cloud Score+S2_HARMONIZED (CS+S2) is employed as a preliminary mask for clouds and cloud shadows. Secondly, we calculate the ratio of the maximum and
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Automated Camera Pose Generation for High-Resolution 3D Reconstruction of Bridges by Unmanned Aerial Vehicles Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Jan Thomas Jung, Dominik Merkle, Alexander Reiterer
This work explores the possibility of automating the aerial survey of bridges to generate high-resolution images necessary for digital damage inspection. High-quality unmanned aerial vehicle (UAV) based 3D reconstruction of bridges is an important step towards autonomous infrastructure inspection. However, the calculation of optimal camera poses remains challenging due to the complex structure of bridges
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Spatial Downscaling of ESA CCI Soil Moisture Data Based on Deep Learning with an Attention Mechanism Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Danwen Zhang, Linjun Lu, Xuan Li, Jiahua Zhang, Sha Zhang, Shanshan Yang
Soil moisture (SM) is a critical variable affecting ecosystem carbon and water cycles and their feedback to climate change. In this study, we proposed a convolutional neural network (CNN) model embedded with a residual block and attention module, named SMNet, to spatially downscale the European Space Agency (ESA) Climate Change Initiative (CCI) SM product. In the SMNet model, a lightweight Convolutional
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Characteristics Analysis of Influence of Multiple Parameters of Mixed Sea Waves on Delay–Doppler Map in Global Navigation Satellite System Reflectometry Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Jianan Yan, Ding Nie, Kaicheng Zhang, Min Zhang
Feature capture and recognition of sea wave components in radar systems especially in global navigation satellite system reflectometry (GNSS-R) using signal processing approaches or computer simulative methods has become a research hotspot in recent years. At the same time, parameter inversion of marine phenomena from the discovered characteristics plays a significant role in monitoring and forewarning
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Assessing Seasonal and Inter-Annual Changes in the Total Cover of Submerged Aquatic Vegetation Using Sentinel-2 Imagery Remote Sens. (IF 5.0) Pub Date : 2024-04-15 Ele Vahtmäe, Laura Argus, Kaire Toming, Tiia Möller-Raid, Tiit Kutser
Remote sensing is a valuable tool for surveying submerged aquatic vegetation (SAV) distribution patterns at extensive spatial and temporal scales. Only regular mapping over successive time periods (e.g., months, years) allows for a quantitative assessment of SAV loss or recolonization extent. Still, there are only a limited number of studies assessing temporal changes in SAV patterns. ESA Sentinel-2
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Coseismic and Early Postseismic Deformation Mechanism Following the 2021 Mw 7.4 Maduo Earthquake: Insights from Satellite Radar Interferometry and GPS Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Chuanzeng Shu, Zhiguo Meng, Qiong Wu, Wei Xiong, Lijia He, Xiaoping Zhang, Dan Xu
Exploring the deformation mechanism of the 2021 Mw 7.4 Maduo Earthquake is crucial for better understanding the seismic hazard of the faults with low strain rates inside the Bayan Har block. This study leverages deformation information derived from Sentient-1 A/B images and GPS data to investigate in detail the co- and postseismic deformation mechanisms using multiple methods. The main results are
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Advancement of Sea Surface Convective Wind Gust Observation by Different Satellite Sensors and Assessment with In Situ Measurements Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Tran Vu La, Christophe Messager
This paper shows the observation and estimation of convective wind gusts by different satellite sensors at the C-band (Sentinel-1 SAR) and L-band (ALOS-1 SAR and SMAP radiometer) over Lake Victoria, the Gulf of Guinea, and the Gulf of Mexico. These areas are significantly impacted by deep convection associated with strong surface winds and heavy rainfall. In particular, the collocation of Sentinel-1
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Early Prediction of Regional Red Needle Cast Outbreaks Using Climatic Data Trends and Satellite-Derived Observations Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Michael S. Watt, Andrew Holdaway, Pete Watt, Grant D. Pearse, Melanie E. Palmer, Benjamin S. C. Steer, Nicolò Camarretta, Emily McLay, Stuart Fraser
Red needle cast (RNC), mainly caused by Phytophthora pluvialis, is a very damaging disease of the widely grown species radiata pine within New Zealand. Using a combination of satellite imagery and weather data, a novel methodology was developed to pre-visually predict the incidence of RNC on radiata pine within the Gisborne region of New Zealand over a five-year period from 2019 to 2023. Sentinel-2
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Mapping Annual Tidal Flat Loss and Gain in the Micro-Tidal Area Integrating Dual Full-Time Series Spectral Indices Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Jiayi Luo, Wenting Cao, Xuecao Li, Yuyu Zhou, Shuangyan He, Zhaoyuan Zhang, Dongling Li, Huaguo Zhang
Tracking long-term tidal flat dynamics is crucial for coastal restoration decision making. Accurately capturing the loss and gain of tidal flats due to human-induced disturbances is challenging in the micro-tidal areas. In this study, we developed an automated method for mapping the annual tidal flat changes in the micro-tidal areas under intense human activities, by integrating spectral harmonization
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Vertical Features of Volatile Organic Compounds and Their Potential Photochemical Reactivities in Boundary Layer Revealed by In-Situ Observations and Satellite Retrieval Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Siqi Yang, Bin Zhu, Shuangshuang Shi, Zhuyi Jiang, Xuewei Hou, Junlin An, Li Xia
Based on in-situ vertical observations of volatile organic compounds (VOCs) in the lower troposphere (0–1.0 km) in Nanjing, China, during the summer and autumn, we analyzed the VOCs vertical profiles, diurnal variation, and their impact factors in meteorology and photochemistry. The results showed that almost all the concentrations of VOC species decreased with height, similar to the profiles of primary
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Exploring the Effects of Topography on Leaf Area Index Retrieved from Remote Sensing Data at Various Spatial Scales over Rugged Terrains Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Yajie Zheng, Zhiqiang Xiao, Hanyu Shi, Jinling Song
Topography significantly affects remotely sensed reflectance data and subsequently impacts the retrieval of the leaf area index (LAI) from surface reflectance data over rugged terrains. However, most LAI inversion algorithms ignore the influence of terrain. This paper quantitatively analyzes the topographic effects on LAI values retrieved from remote sensing data at various spatial scales (30, 90,
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Surface Solar Radiation Resource Evaluation of Xizang Region Based on Station Observation and High-Resolution Satellite Dataset Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Huangjie Kong, Jianguo Wang, Li Cai, Jinxin Cao, Mi Zhou, Yadong Fan
Xizang boasts a vast and geographically complex landscape with an average elevation surpassing 4000 m. Understanding the spatiotemporal distribution of surface solar radiation is indispensable for simulating surface processes, studying climate change, and designing photovoltaic power generation and solar heating systems. A multi-dimensional, long-term, spatial, and temporal investigation of solar radiation
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A Wide-Angle Hyperspectral Top-of-Atmosphere Reflectance Model for the Libyan Desert Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Fuxiang Guo, Xiaobing Zheng, Yanna Zhang, Wei Wei, Zejie Zhang, Quan Zhang, Xin Li
Reference targets with stability, uniformity, and known reflectance on the Earth’s surface, such as deserts, can be used for the absolute radiometric calibration of satellite sensors. A wide-angle hyperspectral reflectance model at the top of atmosphere (TOA) over such a reference target will expand the applicability of on-orbit calibration to different spectral bands and angles. To achieve the long-term
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Asymptotic Performance of GNSS Positioning Approaches under Cross-Correlation Effects Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Yuze Duan, Jiaolong Wei, Zuping Tang
Conventional global navigation satellite system receivers typically employ a two-step positioning procedure (2SP) by first independently estimating the synchronization parameters and then using these parameters to solve a system of superdeterministic equations derived from multilateration to accomplish positioning. Direct position estimation (DPE) has emerged as a promising alternative that utilizes
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Spatiotemporal Variation in Water Deficit- and Heatwave-Driven Flash Droughts in Songnen Plain and Its Ecological Impact Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Jiahao Sun, Yanfeng Wu, Qingsong Zhang, Lili Jiang, Qiusheng Ma, Mo Chen, Changlei Dai, Guangxin Zhang
The phenomenon of flash droughts, marked by their fast onset, limited predictability, and formidable capacity for devastation, has elicited escalating concern. Despite this growing interest, a comprehensive investigation of the spatiotemporal dynamics of flash drought events within zones of ecological sensitivity, alongside their consequential ecological ramifications, remains elusive. The Songnen
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A Micro-Motion Parameters Estimation Method for Multi-Rotor Targets without a Prior Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Jianfei Ren, Jia Liang, Huan Wang, Kai-ming Li, Ying Luo, Dongtao Zhao
Multi-rotor aircraft have the advantages of a simple structure, low cost, and flexible operation in the unmanned aerial vehicle (UAV) family, and have developed rapidly in recent years. Radar surveillance and classification of the growing number of multi-rotor aircraft has become a challenging problem due to their low-slow-small (LSS) characteristics. Estimation of the blade number is an important
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Estimation of All-Day Aerosol Optical Depth in the Beijing–Tianjin–Hebei Region Using Ground Air Quality Data Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Wenhao Zhang, Sijia Liu, Xiaoyang Chen, Xiaofei Mi, Xingfa Gu, Tao Yu
Atmospheric aerosols affect climate change, air quality, and human health. The aerosol optical depth (AOD) is a widely utilized parameter for estimating the concentration of atmospheric aerosols. Consequently, continuous AOD monitoring is crucial for environmental studies. However, a method to continuously monitor the AOD throughout the day or night remains a challenge. This study introduces a method
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Instantaneous Frequency Extraction for Nonstationary Signals via a Squeezing Operator with a Fixed-Point Iteration Method Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Zhen Li, Zhaoqi Gao, Fengyuan Sun, Jinghuai Gao, Wei Zhang
The instantaneous frequency (IF) is an important feature for the analysis of nonstationary signals. For IF estimation, the time–frequency representation (TFR)-based algorithm is used in a common class of methods. TFR-based methods always need the representation concentrated around the “true” IFs and the number of components within the signal. In this paper, we propose a novel method to adaptively estimate
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Spaceborne Radars for Mapping Surface and Subsurface Salt Pan Configuration: A Case Study of the Pozuelos Salt Flat in Northern Argentina Remote Sens. (IF 5.0) Pub Date : 2024-04-16 José Manuel Lattus, Matías Ernesto Barber, Dražen Skoković, Waldo Pérez-Martínez, Verónica Rocío Martínez, Laura Flores
Lithium mining has become a controversial issue in the transition to green technologies due to the intervention in natural basins that impact the native flora and fauna in these environments. Large resources of this element are concentrated in Andean salt flats in South America, where extraction is much easier than in other geological configurations. The Pozuelos highland salt flat, located in northern
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A Novel Flood Risk Analysis Framework Based on Earth Observation Data to Retrieve Historical Inundations and Future Scenarios Remote Sens. (IF 5.0) Pub Date : 2024-04-16 Kezhen Yao, Saini Yang, Zhihao Wang, Weihang Liu, Jichong Han, Yimeng Liu, Ziying Zhou, Stefano Luigi Gariano, Yongguo Shi, Carlo Jaeger
Global warming is exacerbating flood hazards, making the robustness of flood risk management a critical issue. Without considering future scenarios, flood risk analysis built only on historical knowledge may not adequately address the coming challenges posed by climate change. A comprehensive risk analysis framework based on both historical inundations and future projections to tackle uncertainty is
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Joint Radar Jamming and Communication System Design Based on Universal Filtered Multicarrier Chirp Waveform Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Gaogao Liu, Ziyu Huang, Qidong Zhang, Beibei Mu, Hongfu Guo
In this article, we propose a joint waveform based on universal filtered multicarrier (UFMC) chirp for radar jamming and communication joint systems. Modulation of radar jamming chirp signals and communication signals on different subcarrier groups in the UFMC sub-band is used to achieve the waveform design. The jamming signal in the waveform contains a frequency shift coefficient that depends on the
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A Multi-Hyperspectral Image Collaborative Mapping Model Based on Adaptive Learning for Fine Classification Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Xiangrong Zhang, Zitong Liu, Xianhao Zhang, Tianzhu Liu
Hyperspectral (HS) data, encompassing hundreds of spectral channels for the same area, offer a wealth of spectral information and are increasingly utilized across various fields. However, their limitations in spatial resolution and imaging width pose challenges for precise recognition and fine classification in large scenes. Conversely, multispectral (MS) data excel in providing spatial details for
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Automatic Building Roof Plane Extraction in Urban Environments for 3D City Modelling Using Remote Sensing Data Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Carlos Campoverde, Mila Koeva, Claudio Persello, Konstantin Maslov, Weiqin Jiao, Dessislava Petrova-Antonova
Delineating and modelling building roof plane structures is an active research direction in urban-related studies, as understanding roof structure provides essential information for generating highly detailed 3D building models. Traditional deep-learning models have been the main focus of most recent research endeavors aiming to extract pixel-based building roof plane areas from remote-sensing imagery
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Retrieval of Total Suspended Matter Concentration Based on the Iterative Analysis of Multiple Equations: A Case Study of a Lake Taihu Image from the First Sustainable Development Goals Science Satellite’s Multispectral Imager for Inshore Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Xueke Hu, Jiaguo Li, Yuan Sun, Yunfei Bao, Yonghua Sun, Xingfeng Chen, Yueguan Yan
Inland waters consist of multiple concentrations of constituents, and solving the interference problem of chlorophyll-a and colored dissolved organic matter (CDOM) can help to accurately invert total suspended matter concentration (Ctsm). In this study, according to the characteristics of the Multispectral Imager for Inshore (MII) equipped with the first Sustainable Development Goals Science Satellite
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MDANet: A High-Resolution City Change Detection Network Based on Difference and Attention Mechanisms under Multi-Scale Feature Fusion Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Shanshan Jiang, Haifeng Lin, Hongjin Ren, Ziwei Hu, Liguo Weng, Min Xia
In the domains of geographic information systems and remote sensing image analysis, change detection is vital for examining surface variations in high-resolution remote sensing pictures. However, the intricate texture characteristics and rich details found in high-resolution remote sensing photos are difficult for conventional change detection systems to deal with. Target misdetection, missed detections
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A Fast IAA−Based SR−STAP Method for Airborne Radar Remote Sens. (IF 5.0) Pub Date : 2024-04-14 Shuguang Zhang, Tong Wang, Cheng Liu, Bing Ren
Space−time adaptive processing (STAP) is an effective technology in clutter suppression and moving target detection for airborne radar. When working in the heterogeneous environment, the number of training samples that satisfy independent and identically distributed (IID) conditions is insufficient, making it difficult to ensure the estimation accuracy of the clutter plus noise covariance matrix for