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You searched for: Keyword remote sensing Remove constraint Keyword: remote sensing Journal name Remote Sensing Remove constraint Journal name: Remote Sensing
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1. The 2021 Mw6.7 Lake Hovsgol (Mongolia) Earthquake: Irregular Normal Faulting with Slip Partitioning Controlled by an Adjacent Strike-Slip Fault

Author:
Yuqing He; Teng Wang; Li Zhao
Source:
Remote Sensing 2022 v.14 no.18 pp. -
ISSN:
2072-4292
Subject:
basins; earthquakes; evolution; lakes; models; Mongolia
Abstract:
... In transtensional regions, structures striking obliquely to the extension direction generally exhibit oblique or partitioned slips. However, their on-fault partitioning patterns and controlling factors are less known, hindering our understanding of the evolution of the rifting process. Here, we study the slip distribution of the 2021 Mw6.7 Lake Hovsgol (Mongolia) earthquake occurred in a pull-apar ...
DOI:
10.3390/rs14184553

2. 2D Phase-Based RFID Localization for On-Site Landslide Monitoring

Author:
Arthur Charléty; Mathieu Le Breton; Eric Larose; Laurent Baillet
Source:
Remote Sensing 2022 v.14 no.15 pp. -
ISSN:
2072-4292
Subject:
landslides; models; radio frequency identification
Abstract:
... Passive radio-frequency identification (RFID) was recently used to monitor landslide displacement at a high spatio-temporal resolution but only measured 1D displacement. This study demonstrates the tracking of 2D displacements, using an array of antennas connected to an RFID interrogator. Ten tags were deployed on a landslide for 12 months and 2D relative localization was performed using a phase-o ...
DOI:
10.3390/rs14153577

3. 2D&3DHNet for 3D Object Classification in LiDAR Point Cloud

Author:
Wei Song; Dechao Li; Su Sun; Lingfeng Zhang; Yu Xin; Yunsick Sung; Ryong Choi
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
algorithms; data collection; lidar; neural networks
Abstract:
... Accurate semantic analysis of LiDAR point clouds enables the interaction between intelligent vehicles and the real environment. This paper proposes a hybrid 2D and 3D Hough Net by combining 3D global Hough features and 2D local Hough features with a classification deep learning network. Firstly, the 3D object point clouds are mapped into the 3D Hough space to extract the global Hough features. The ...
DOI:
10.3390/rs14133146

4. A 3-Stage Spectral-Spatial Method for Hyperspectral Image Classification

Author:
Raymond H. Chan; Ruoning Li
Source:
Remote Sensing 2022 v.14 no.16 pp. -
ISSN:
2072-4292
Subject:
aircraft; algorithms; data collection; hyperspectral imagery; image analysis; models; principal component analysis; probability
Abstract:
... Hyperspectral images often have hundreds of spectral bands of different wavelengths captured by aircraft or satellites that record land coverage. Identifying detailed classes of pixels becomes feasible due to the enhancement in spectral and spatial resolution of hyperspectral images. In this work, we propose a novel framework that utilizes both spatial and spectral information for classifying pixe ...
DOI:
10.3390/rs14163998

5. 3D Convolutional Neural Network for Low-Light Image Sequence Enhancement in SLAM

Author:
Yizhuo Quan; Dong Fu; Yuanfei Chang; Chengbo Wang
Source:
Remote Sensing 2022 v.14 no.16 pp. -
ISSN:
2072-4292
Subject:
cameras; data collection; neural networks; texture
Abstract:
... Typical visual simultaneous localization and mapping (SLAM) systems rely on front-end odometry for feature extraction and matching to establish the relations between adjacent images. In a low-light environment, the image obtained by a camera is dim and shows scarce information, hindering the extraction of sufficient stable feature points, consequently undermining visual SLAM. Most existing methods ...
DOI:
10.3390/rs14163985

6. 3D Distance Filter for the Autonomous Navigation of UAVs in Agricultural Scenarios

Author:
Cesare Donati; Martina Mammarella; Lorenzo Comba; Alessandro Biglia; Paolo Gay; Fabrizio Dabbene
Source:
Remote Sensing 2022 v.14 no.6 pp. -
ISSN:
2072-4292
Subject:
digital images; georeferencing; precision agriculture; ultrasonics; vines
Abstract:
... In precision agriculture, remote sensing is an essential phase in assessing crop status and variability when considering both the spatial and the temporal dimensions. To this aim, the use of unmanned aerial vehicles (UAVs) is growing in popularity, allowing for the autonomous performance of a variety of in-field tasks which are not limited to scouting or monitoring. To enable autonomous navigation ...
DOI:
10.3390/rs14061374

7. 3D Interpretation of a Broadband Magnetotelluric Data Set Collected in the South of the Chinese Zhongshan Station at Prydz Bay, East Antarctica

Author:
Enzhao Xiao; Feng Jiang; Jingxue Guo; Khalid Latif; Lei Fu; Bo Sun
Source:
Remote Sensing 2022 v.14 no.3 pp. -
ISSN:
2072-4292
Subject:
data collection; geometry; geophysics; glaciers; hydrology; ice; models; tectonics; Antarctic region; Antarctica
Abstract:
... Antarctica is covered by a thick ice sheet, and the application of geophysical methods is necessary to image the subglacial structures for studying the hydrologic systems and tectonic deformations in the Antarctic continent. The magnetotelluric (MT) method is one of the best approaches to obtain the subglacial electrical resistivities. However, only a very small volume of data has been collected s ...
DOI:
10.3390/rs14030496

8. 3D LiDAR Aided GNSS/INS Integration Fault Detection, Localization and Integrity Assessment in Urban Canyons

Author:
Zhipeng Wang; Bo Li; Zhiqiang Dan; Hongxia Wang; Kun Fang
Source:
Remote Sensing 2022 v.14 no.18 pp. -
ISSN:
2072-4292
Subject:
algorithms; chi-square distribution; global positioning systems; lidar
Abstract:
... The performance of Global Navigation Satellite System (GNSS) and Inertial Navigation System (INS) integrated navigation can be severely degraded in urban canyons due to the non-line-of-sight (NLOS) signals and multipath effects. Therefore, to achieve a high-precision and robust integrated system, real-time fault detection and localization algorithms are needed to ensure integrity. Currently, the r ...
DOI:
10.3390/rs14184641

9. 3D Lightning Location Method Based on Range Difference Space Projection

Author:
Ling Fan; Changhai Zhou
Source:
Remote Sensing 2022 v.14 no.4 pp. -
ISSN:
2072-4292
Subject:
remote sensing,   etc   ; Monte Carlo method; exhibitions; lightning; measurement; uncertainty;     Show all 6 Subjects
Abstract:
... Most lightning location networks obtain the position results by optimizing the goodness of fit to determine that all combinatorial time differences of arrivals (TDOAs) are due to a common discharge. This paper proposes a three-dimensional (3D) lightning location method based on range difference (RD) space projection. The proposed method projects all the measurements into the RD space, which has th ...
DOI:
10.3390/rs14041003

10. 3D Modeling of Urban Area Based on Oblique UAS Images—An End-to-End Pipeline

Author:
Valeria-Ersilia Oniga; Ana-Ioana Breaban; Norbert Pfeifer; Maximilian Diac
Source:
Remote Sensing 2022 v.14 no.2 pp. -
ISSN:
2072-4292
Subject:
algorithms; computer software; data collection; flight; forestry equipment; lidar; models; photogrammetry; urban areas; urban development; vegetation; vegetation index
Abstract:
... 3D modelling of urban areas is an attractive and active research topic, as 3D digital models of cities are becoming increasingly common for urban management as a consequence of the constantly growing number of people living in cities. Viewed as a digital representation of the Earth’s surface, an urban area modeled in 3D includes objects such as buildings, trees, vegetation and other anthropogenic ...
DOI:
10.3390/rs14020422

11. 3D Reconstruction of Remote Sensing Mountain Areas with TSDF-Based Neural Networks

Author:
Zipeng Qi; Zhengxia Zou; Hao Chen; Zhenwei Shi
Source:
Remote Sensing 2022 v.14 no.17 pp. -
ISSN:
2072-4292
Subject:
computers; data collection; geometry; landscapes; lighting; texture
Abstract:
... The remote sensing 3D reconstruction of mountain areas has a wide range of applications in surveying, visualization, and game modeling. Different from indoor objects, outdoor mountain reconstruction faces additional challenges, including illumination changes, diversity of textures, and highly irregular surface geometry. Traditional neural network-based methods that lack discriminative features str ...
DOI:
10.3390/rs14174333

12. 3D Rock Structure Digital Characterization Using Airborne LiDAR and Unmanned Aerial Vehicle Techniques for Stability Analysis of a Blocky Rock Mass Slope

Author:
Qiang Xu; Zhen Ye; Qian Liu; Xiujun Dong; Weile Li; Shanao Fang; Chen Guo
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
carbonate rocks; computer software; direct contact; geometry; landscapes; lidar
Abstract:
... Airborne light detection and ranging (LiDAR) and unmanned aerial vehicle-structure from motion (UAV-SfM) provide point clouds with unprecedented resolution and accuracy that are well suited for the digital characterization of rock outcrops where direct contact measurements cannot be obtained due to terrain or safety constraints. Today, however, how to better apply these techniques to the practice ...
DOI:
10.3390/rs14133044

13. 3D Sea Surface Electromagnetic Scattering Prediction Model Based on IPSO-SVR

Author:
Chunlei Dong; Xiao Meng; Lixin Guo; Jiamin Hu
Source:
Remote Sensing 2022 v.14 no.18 pp. -
ISSN:
2072-4292
Subject:
algorithms; data collection; models; prediction; regression analysis
Abstract:
... An Improved Particle Swarm Optimization Algorithm-Support Vector Regression Machine (IPSO-SVR) prediction model is developed in this paper to predict the electromagnetic (EM) scattering coefficients of the three-dimensional (3D) sea surface for large scenes in real-time. At first, the EM scattering model of the 3D sea surface is established based on the Semi-Deterministic Facet Scattering Model (S ...
DOI:
10.3390/rs14184657

14. 3D Sensor Based Pedestrian Detection by Integrating Improved HHA Encoding and Two-Branch Feature Fusion

Author:
Fang Tan; Zhaoqiang Xia; Yupeng Ma; Xiaoyi Feng
Source:
Remote Sensing 2022 v.14 no.3 pp. -
ISSN:
2072-4292
Subject:
computer vision; data collection; gravity; lighting; people
Abstract:
... Pedestrian detection is vitally important in many computer vision tasks but still suffers from some problems, such as illumination and occlusion if only the RGB image is exploited, especially in outdoor and long-range scenes. Combining RGB with depth information acquired by 3D sensors may effectively alleviate these problems. Therefore, how to utilize depth information and how to fuse RGB and dept ...
DOI:
10.3390/rs14030645

15. 3DVAR Aerosol Data Assimilation and Evaluation Using Surface PM2.5, Himawari-8 AOD and CALIPSO Profile Observations in the North China

Author:
Zengliang Zang; Wei You; Hancheng Ye; Yanfei Liang; Yi Li; Daichun Wang; Yiwen Hu; Peng Yan
Source:
Remote Sensing 2022 v.14 no.16 pp. -
ISSN:
2072-4292
Subject:
aerosols; case studies; chemistry; lidar; models; particulates; satellites; China
Abstract:
... Based on the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) aerosol scheme of the Weather Research and Forecasting model coupled with online Chemistry (WRF-Chem) and the three-dimensional variational (3DVAR) assimilation method, a 3DVAR data assimilation (DA) system for aerosol optical depth (AOD) and aerosol concentration observations was developed. A case study on assimilating ...
DOI:
10.3390/rs14164009

16. 3MRS: An Effective Coarse-to-Fine Matching Method for Multimodal Remote Sensing Imagery

Author:
Zhongli Fan; Yuxian Liu; Yuxuan Liu; Li Zhang; Junjun Zhang; Yushan Sun; Haibin Ai
Source:
Remote Sensing 2022 v.14 no.3 pp. -
ISSN:
2072-4292
Subject:
remote sensing,   etc   ; data collection; deformation; design; exhibitions; filters; image analysis; models;     Show all 8 Subjects
Abstract:
... The fusion of image data from multiple sensors is crucial for many applications. However, there are significant nonlinear intensity deformations between images from different kinds of sensors, leading to matching failure. To address this need, this paper proposes an effective coarse-to-fine matching method for multimodal remote sensing images (3MRS). In the coarse matching stage, feature points ar ...
DOI:
10.3390/rs14030478

17. 4D U-Nets for Multi-Temporal Remote Sensing Data Classification

Author:
Michalis Giannopoulos; Grigorios Tsagkatakis; Panagiotis Tsakalides
Source:
Remote Sensing 2022 v.14 no.3 pp. -
ISSN:
2072-4292
Subject:
remote sensing,   etc   ; Landsat; architecture; crops; exhibitions; floods; image analysis; models; monitoring; spatial data;     Show all 10 Subjects
Abstract:
... Multispectral sensors constitute a core earth observation imaging technology generating massive high-dimensional observations acquired across multiple time instances. The collected multi-temporal remote sensed data contain rich information for Earth monitoring applications, from flood detection to crop classification. To easily classify such naturally multidimensional data, conventional low-order ...
DOI:
10.3390/rs14030634

18. AC-LSTM: Anomaly State Perception of Infrared Point Targets Based on CNN+LSTM

Author:
Jiaqi Sun; Jiarong Wang; Zhicheng Hao; Ming Zhu; Haijiang Sun; Ming Wei; Kun Dong
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
data collection; monitoring; neural networks; time series analysis
Abstract:
... Anomaly perception of infrared point targets has high application value in many fields, such as maritime surveillance, airspace surveillance, and early warning systems. This kind of abnormality includes the explosion of the target, the separation between stages, the disintegration caused by the abnormal strike, etc. By extracting the radiation characteristics of continuous frame targets, it is pos ...
DOI:
10.3390/rs14133221

19. ACE R-CNN: An Attention Complementary and Edge Detection-Based Instance Segmentation Algorithm for Individual Tree Species Identification Using UAV RGB Images and LiDAR Data

Author:
Yingbo Li; Guoqi Chai; Yueting Wang; Lingting Lei; Xiaoli Zhang
Source:
Remote Sensing 2022 v.14 no.13 pp. -
ISSN:
2072-4292
Subject:
algorithms; biodiversity; canopy height; carbon sinks; forests; lidar; models; species identification; tree crown; trees; China
Abstract:
... Accurate and automatic identification of tree species information at the individual tree scale is of great significance for fine-scale investigation and management of forest resources and scientific assessment of forest ecosystems. Despite the fact that numerous studies have been conducted on the delineation of individual tree crown and species classification using drone high-resolution red, green ...
DOI:
10.3390/rs14133035

20. AFE-RCNN: Adaptive Feature Enhancement RCNN for 3D Object Detection

Author:
Feng Shuang; Hanzhang Huang; Yong Li; Rui Qu; Pei Li
Source:
Remote Sensing 2022 v.14 no.5 pp. -
ISSN:
2072-4292
Subject:
bicycling; data collection; lidar; neural networks
Abstract:
... The point clouds scanned by lidar are generally sparse, which can result in fewer sampling points of objects. To perform precise and effective 3D object detection, it is necessary to improve the feature representation ability to extract more feature information of the object points. Therefore, we propose an adaptive feature enhanced 3D object detection network based on point clouds (AFE-RCNN). AFE ...
DOI:
10.3390/rs14051176