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Journal articles on the topic 'UAV remote sensing'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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1

Ma, Guangdi, and Weichen Yang. "Dynamic reconstruction method of unmanned aerial vehicle aerial remote sensing image based on compressed sensing." Journal of Geography and Cartography 5, no. 1 (2021): 17. http://dx.doi.org/10.24294/jgc.v5i1.1413.

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Aiming at the current problems of poor dynamic reconstruction of UAV aerial remote sensing images and low image clarity, the dynamic reconstruction method of UAV aerial remote sensing images based on compression perception is proposed. Construct a quality reduction model for UAV aerial remote sensing images, obtain image feature information, and further noise reduction preprocessing of UAV aerial remote sensing images to better improve the resolution, spectral and multi-temporal trends of UAV aerial remote sensing images, and effectively solve the problems of resource waste such as large amoun

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Wang, Jia Feng, Xi Min Cui, De Bao Yuan, Jing Jing Jin, Ya Hui Qiu, and Huan Liu. "Segmenting Algorithm and Publishing Based on UVA Image." Applied Mechanics and Materials 195-196 (August 2012): 594–98. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.594.

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With the continuous development of UAV remote sensing technology, UAV remote sensing will become one of the main airborne remote sensing platforms, Image acquisition and its post-processing of the UAV remote sensing have become focus of todays study. This paper presents an idea of image segmentation and image publication of UAV remote sensing, and provides reliable information for decision makers. It possesses a certain value.

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Lyu, Xin, Xiaobing Li, Dongliang Dang, Huashun Dou, Kai Wang, and Anru Lou. "Unmanned Aerial Vehicle (UAV) Remote Sensing in Grassland Ecosystem Monitoring: A Systematic Review." Remote Sensing 14, no. 5 (2022): 1096. http://dx.doi.org/10.3390/rs14051096.

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In recent years, the application of unmanned aerial vehicle (UAV) remote sensing in grassland ecosystem monitoring has increased, and the application directions have diversified. However, there have been few research reviews specifically for grassland ecosystems at present. Therefore, it is necessary to systematically and comprehensively summarize the application of UAV remote sensing in grassland ecosystem monitoring. In this paper, we first analyzed the application trend of UAV remote sensing in grassland ecosystem monitoring and introduced common UAV platforms and remote sensing sensors. Th

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Yin, Ninghao, Ruian Liu, Beibei Zeng, and Nan Liu. "A review: UAV-based Remote Sensing." IOP Conference Series: Materials Science and Engineering 490 (April 12, 2019): 062014. http://dx.doi.org/10.1088/1757-899x/490/6/062014.

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Luo, Xin, Guangling Lai, Xiao Wang, et al. "UAV Remote Sensing Image Automatic Registration Based on Deep Residual Features." Remote Sensing 13, no. 18 (2021): 3605. http://dx.doi.org/10.3390/rs13183605.

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With the rapid development of unmanned aerial vehicle (UAV) technology, UAV remote sensing images are increasing sharply. However, due to the limitation of the perspective of UAV remote sensing, the UAV images obtained from different viewpoints of a same scene need to be stitched together for further applications. Therefore, an automatic registration method of UAV remote sensing images based on deep residual features is proposed in this work. It needs no additional training and does not depend on image features, such as points, lines and shapes, or on specific image contents. This registration

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Wu, Yiguang, Meizhen Wang, Xuejun Liu, et al. "Monitoring the Work Cycles of Earthmoving Excavators in Earthmoving Projects Using UAV Remote Sensing." Remote Sensing 13, no. 19 (2021): 3853. http://dx.doi.org/10.3390/rs13193853.

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Monitoring the work cycles of earthmoving excavators is an important aspect of construction productivity assessment. Currently, the most advanced method for the recognition of work cycles is the “Stretching-Bending” Sequential Pattern (SBSP), which is based on fixed-carrier video monitoring (FC-SBSP). However, the application of this method presupposes the availability of preconstructed installation carriers to act as a surveillance camera as well as installed and commissioned surveillance systems that work in tandem with them. Obviously, this method is difficult to apply to projects with no c

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Mesas-Carrascosa, Francisco Javier. "UAS-Remote Sensing Methods for Mapping, Monitoring and Modeling Crops." Remote Sensing 12, no. 23 (2020): 3873. http://dx.doi.org/10.3390/rs12233873.

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The advances in Unmanned Aerial Vehicle (UAV) platforms and on-board sensors in the past few years have greatly increased our ability to monitor and map crops. The ability to register images at ultra-high spatial resolution at any moment has made remote sensing techniques increasingly useful in crop management. These technologies have revolutionized the way in which remote sensing is applied in precision agriculture, allowing for decision-making in a matter of days instead of weeks. However, it is still necessary to continue research to improve and maximize the potential of UAV remote sensing

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Lei, T. J., R. R. Xu, J. H. Cheng, et al. "A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 471–78. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-471-2020.

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Abstract. Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample C

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Zhao, Ling Li, Shuai Liu, and Li Ma. "Data Acquisition Considering of Fixed-Wing UAVs in Mountainous Areas." Applied Mechanics and Materials 543-547 (March 2014): 2151–54. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2151.

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Over the past decade, there has been a great demand of Unmanned Aerial Vehicles (UAVs) in numerous industrial and military operations around the world. This paper is focused on low fixed-wing UAV remote sensing system, put remote sensing technology and UAV technology closely to fixed-wing unmanned aircraft as a platform, which is equipped with high-resolution digital remote sensing sensors, it has easy transition since the airport does not depend on landing site, it is a new low-speed high-resolution remote sensing data acquisition system. It has capability of a survey of real-time quick monit

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Boesch, R. "THERMAL REMOTE SENSING WITH UAV-BASED WORKFLOWS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W6 (August 23, 2017): 41–46. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w6-41-2017.

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Climate change will have a significant influence on vegetation health and growth. Predictions of higher mean summer temperatures and prolonged summer draughts may pose a threat to agriculture areas and forest canopies. Rising canopy temperatures can be an indicator of plant stress because of the closure of stomata and a decrease in the transpiration rate. <br><br> Thermal cameras are available for decades, but still often used for single image analysis, only in oblique view manner or with visual evaluations of video sequences. <br><br> Therefore remote sensing using a t

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Dorbu, Freda Elikem, Leila Hashemi-Beni, Ali Karimoddini, and Abolghasem Shahbazi. "UAV Remote Sensing Assessment of Crop Growth." Photogrammetric Engineering & Remote Sensing 87, no. 12 (2021): 891–99. http://dx.doi.org/10.14358/pers.21-00060r2.

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The introduction of unmanned-aerial-vehicle remote sensing for collecting high-spatial- and temporal-resolution imagery to derive crop-growth indicators and analyze and present timely results could potentially improve the management of agricultural businesses and enable farmers to apply appropriate solution, leading to a better food-security framework. This study aimed to analyze crop-growth indicators such as the normalized difference vegetation index (NDVI), crop height, and vegetated surface roughness to determine the growth of corn crops from planting to harvest. Digital elevation models a

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Liu, Jianli, Xiaohan Liao, Huping Ye, et al. "UAV Swarm Scheduling Method for Remote Sensing Observations during Emergency Scenarios." Remote Sensing 14, no. 6 (2022): 1406. http://dx.doi.org/10.3390/rs14061406.

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Recently, unmanned aerial vehicle (UAV) remote sensing has been widely used in emergency scenarios; the operating mode has transitioned from one UAV to multiple UAVs. However, the current multiple-UAV remote sensing mode is characterized by high labor costs and limited operational capabilities; meanwhile, there is no suitable UAV swarm scheduling method that can be applied to remote sensing in emergency scenarios. To solve these problems, this study proposes a UAV swarm scheduling method. Firstly, the tasks were formulated and decomposed according to the data requirements and the maximum fligh

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An, Qing, Qiqi Hu, Ruoli Tang, and Lang Rao. "Intelligent Scheduling Methodology for UAV Swarm Remote Sensing in Distributed Photovoltaic Array Maintenance." Sensors 22, no. 12 (2022): 4467. http://dx.doi.org/10.3390/s22124467.

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In recent years, the unmanned aerial vehicle (UAV) remote sensing technology has been widely used in the planning, design and maintenance of urban distributed photovoltaic arrays (UDPA). However, the existing studies rarely concern the UAV swarm scheduling problem when applied to remoting sensing in UDPA maintenance. In this study, a novel scheduling model and algorithm for UAV swarm remote sensing in UDPA maintenance are developed. Firstly, the UAV swarm scheduling tasks in UDPA maintenance are described as a large-scale global optimization (LSGO) problem, in which the constraints are defined

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Liu, Hong, Tao Yu, Bingliang Hu, et al. "UAV-Borne Hyperspectral Imaging Remote Sensing System Based on Acousto-Optic Tunable Filter for Water Quality Monitoring." Remote Sensing 13, no. 20 (2021): 4069. http://dx.doi.org/10.3390/rs13204069.

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Unmanned aerial vehicle (UAV) hyperspectral remote sensing technologies have unique advantages in high-precision quantitative analysis of non-contact water surface source concentration. Improving the accuracy of non-point source detection is a difficult engineering problem. To facilitate water surface remote sensing, imaging, and spectral analysis activities, a UAV-based hyperspectral imaging remote sensing system was designed. Its prototype was built, and laboratory calibration and a joint air–ground water quality monitoring activity were performed. The hyperspectral imaging remote sensing sy

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Meng, Lingxuan, Zhixing Peng, Ji Zhou, et al. "Real-Time Detection of Ground Objects Based on Unmanned Aerial Vehicle Remote Sensing with Deep Learning: Application in Excavator Detection for Pipeline Safety." Remote Sensing 12, no. 1 (2020): 182. http://dx.doi.org/10.3390/rs12010182.

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Unmanned aerial vehicle (UAV) remote sensing and deep learning provide a practical approach to object detection. However, most of the current approaches for processing UAV remote-sensing data cannot carry out object detection in real time for emergencies, such as firefighting. This study proposes a new approach for integrating UAV remote sensing and deep learning for the real-time detection of ground objects. Excavators, which usually threaten pipeline safety, are selected as the target object. A widely used deep-learning algorithm, namely You Only Look Once V3, is first used to train the exca

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Trinh, Ha Linh, Hieu Trung Kieu, Hui Ying Pak, Dawn Sok Cheng Pang, Angel Anisa Cokro, and Adrian Wing-Keung Law. "A Framework for Survey Planning Using Portable Unmanned Aerial Vehicles (pUAVs) in Coastal Hydro-Environment." Remote Sensing 14, no. 9 (2022): 2283. http://dx.doi.org/10.3390/rs14092283.

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Recently, remote sensing using survey-grade UAVs has been gaining tremendous momentum in applications for the coastal hydro-environment. UAV-based remote sensing provides high spatial and temporal resolutions and flexible operational availability compared to other means, such as satellite imagery or point-based in situ measurements. As strict requirements and government regulations are imposed for every UAV survey, detailed survey planning is essential to ensure safe operations and seamless coordination with other activities. This study established a comprehensive framework for the planning of

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Liu, Di, Qingling Zhang, Jiao Wang, Yifang Wang, Yanyun Shen, and Yanmin Shuai. "The Potential of Moonlight Remote Sensing: A Systematic Assessment with Multi-Source Nightlight Remote Sensing Data." Remote Sensing 13, no. 22 (2021): 4639. http://dx.doi.org/10.3390/rs13224639.

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One recent trend in optical remote sensing is to increase observation frequencies. However, there are still challenges on the night side when sunlight is not available. Due to their powerful capabilities in low-light sensing, nightlight satellite sensors have been deployed to capture nightscapes of Earth from space, observing anthropomorphic and natural activities at night. To date, the mainstream of nightlight remote sensing applications has mainly focused on artificial lights, especially within cities or self-luminous bodies, such as fisheries, oil, offshore rigs, etc. Observations taken und

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Chen, Rong. "Application of UAV-Low Altitude Remote Sensing System in Sea Area Supervision." Earth Sciences Research Journal 25, no. 1 (2021): 65–68. http://dx.doi.org/10.15446/esrj.v25n1.94162.

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The sea area supervision is the premise and guarantee of safeguarding national security, protecting national sovereignty, and realizing the development of marine resources, and its importance is self-evident. To carry out the national sea area work more efficiently, this study designed low altitude-Unmanned Aerial Vehicles (UAV) remote sensing system applied to the sea area supervision and analyzed the remote sensing photography technology and remote sensing image processing technology. Experiments verified the effectiveness of the system. The research results show that the UAV-based low altit

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Huang, Yanbo, Krishna N. Reddy, Reginald S. Fletcher, and Dean Pennington. "UAV Low-Altitude Remote Sensing for Precision Weed Management." Weed Technology 32, no. 1 (2017): 2–6. http://dx.doi.org/10.1017/wet.2017.89.

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AbstractPrecision weed management, an application of precision agriculture, accounts for within-field variability of weed infestation and herbicide damage. Unmanned aerial vehicles (UAVs) provide a unique platform for remote sensing of field crops. They are more efficient and flexible than manned agricultural airplanes in acquiring high-resolution images at low altitudes and low speeds. UAVs are more universal than agricultural aircraft, because the latter are used only in specific regions. We have developed and used UAV systems for red–green–blue digital and color–infrared imaging over crop f

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Hu, Ji Ping, Wen Bin Wu, and Qu Lin Tan. "Application of Unmanned Aerial Vehicle Remote Sensing for Geological Disaster Reconnaissance along Transportation Lines: A Case Study." Applied Mechanics and Materials 226-228 (November 2012): 2376–79. http://dx.doi.org/10.4028/www.scientific.net/amm.226-228.2376.

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Compared with conventional airborne remote sensing application to engineering geological investigation, High precision Unmanned Aerial Vehicle Remote Sensing (UAV-RS) technology can improve work condition with advantages of high flexibility, low cost, high efficiency and up-to-date situation acquisition. Especially, it has very important engineering significance for quick and urgent geological disaster reconnaissance along transportation lines. In the paper, some aspects of application to transportation-line (pipeline, highway and railway) engineering geological investigation were discussed. T

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Yu, J., Z. Gan, L. Zhong, and L. Deng. "RESEARCH AND PRACTICE OF UAV REMOTE SENSING IN THE MONITORING AND MANAGEMENT OF CONSTRUCTION PROJECTS IN RIPARIAN AREAS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 2161–65. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2161-2018.

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The objective of this paper is to investigate the use of UAV remote sensing in the monitoring and management of construction projects in riparian areas through the case study of embankment construction projects’ monitoring in the Three Gorges Reservoir area. A three-step approach is proposed to address the problem: data acquisition with UAV, data processing, and monitoring information extraction. The results of the case study demonstrate that UAV remote sensing is capable of providing fast and accurate measurements and calculations for the needs of monitoring of riparian constructions.

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Eskandari, Roghieh, Masoud Mahdianpari, Fariba Mohammadimanesh, Bahram Salehi, Brian Brisco, and Saeid Homayouni. "Meta-analysis of Unmanned Aerial Vehicle (UAV) Imagery for Agro-environmental Monitoring Using Machine Learning and Statistical Models." Remote Sensing 12, no. 21 (2020): 3511. http://dx.doi.org/10.3390/rs12213511.

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Unmanned Aerial Vehicle (UAV) imaging systems have recently gained significant attention from researchers and practitioners as a cost-effective means for agro-environmental applications. In particular, machine learning algorithms have been applied to UAV-based remote sensing data for enhancing the UAV capabilities of various applications. This systematic review was performed on studies through a statistical meta-analysis of UAV applications along with machine learning algorithms in agro-environmental monitoring. For this purpose, a total number of 163 peer-reviewed articles published in 13 hig

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Wang, S., X. Wang, A. Dou, X. Yuan, L. Ding, and X. Ding. "NEAR REAL-TIME GEOREFERENCE OF UMANNED AERIAL VEHICLE IMAGES FOR POST-EARTHQUAKE RESPONSE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1773–76. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1773-2018.

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The rapid collection of Unmanned Aerial Vehicle (UAV) remote sensing images plays an important role in the fast submitting disaster information and the monitored serious damaged objects after the earthquake. However, for hundreds of UAV images collected in one flight sortie, the traditional data processing methods are image stitching and three-dimensional reconstruction, which take one to several hours, and affect the speed of disaster response. If the manual searching method is employed, we will spend much more time to select the images and the find images do not have spatial reference. There

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Machovina, Brian L., Kenneth J. Feeley, and Brett J. Machovina. "UAV remote sensing of spatial variation in banana production." Crop and Pasture Science 67, no. 12 (2016): 1281. http://dx.doi.org/10.1071/cp16135.

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Remote sensing through Unmanned Aerial Vehicles (UAV) can potentially be used to identify the factors influencing agricultural yield and thereby increase production efficiency. The use of UAV remains largely underutilised in tropical agricultural systems. In this study we tested a fixed-wing UAV system equipped with a sensor system for mapping spatial patterns of photosynthetic activity in banana plantations in Costa Rica. Spatial patterns derived from the Normalised Difference Vegetation Index (NDVI) were compared with spatial patterns of physical soil quality and banana fruit production data

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Qin, Jianxin, Wenjie Yang, Tao Wu, Bin He, and Longgang Xiang. "Incremental Road Network Update Method with Trajectory Data and UAV Remote Sensing Imagery." ISPRS International Journal of Geo-Information 11, no. 10 (2022): 502. http://dx.doi.org/10.3390/ijgi11100502.

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GPS trajectory and remote sensing data are crucial for updating urban road networks because they contain critical spatial and temporal information. Existing road network updating methods, whether trajectory-based (TB) or image-based (IB), do not integrate the characteristics of both types of data. This paper proposed and implemented an incremental update method for rapid road network checking and updating. A composite update framework for road networks is established, which integrates trajectory data and UAV remote sensing imagery. The research proposed utilizing connectivity between adjacent

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Tožička, Jan, and Antonín Komenda. "Diverse Planning for UAV Control and Remote Sensing." Sensors 16, no. 12 (2016): 2199. http://dx.doi.org/10.3390/s16122199.

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连, 鹏. "Mariculture Areas Recognition Based on UAV Remote Sensing." Open Journal of Fisheries Research 06, no. 04 (2019): 179–88. http://dx.doi.org/10.12677/ojfr.2019.64024.

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Lee, Woonghee. "Federated Reinforcement Learning-Based UAV Swarm System for Aerial Remote Sensing." Wireless Communications and Mobile Computing 2022 (April 29, 2022): 1–15. http://dx.doi.org/10.1155/2022/4327380.

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In recent years, due to the development of technologies for unmanned aerial vehicles (UAVs), also known as drones, UAVs have developed rapidly. Because of UAVs’ high mobility and computational capability, UAVs have a wide range of applications in Industrial Internet of Things (IIoT), such as infrastructure inspection, rescue, exploration, and surveillance. To accomplish such missions, it is more proper and efficient to utilize multiple UAVs in a swarm, rather than a single UAV. However, it is difficult for an operator to understand and control numerous UAVs in different situations, so UAVs req

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Ling, Min, Qun Cheng, Jun Peng, Ling Jiang, and Ruifeng Wang. "Retrieval Algorithm of Water Pollutant Concentration Based on UAV Remote Sensing Technology." Mobile Information Systems 2022 (April 30, 2022): 1–11. http://dx.doi.org/10.1155/2022/5017000.

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With the development of the society and economy, traditional water pollution monitoring methods can no longer meet the normal needs of work. Unmanned aerial vehicle remote sensing technology has gradually emerged, and it has shown a development trend of multimodel and multifunction. However, the application of UAV remote sensing technology in water pollution monitoring is in its infancy and has not formed a unified method and standard. This paper introduces the disadvantages of UAV Remote Sensing Technology in water pollution monitoring and provides a way to improve the application level of UA

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Peng, Xingshuo, Wenting Han, Jianyi Ao, and Yi Wang. "Assimilation of LAI Derived from UAV Multispectral Data into the SAFY Model to Estimate Maize Yield." Remote Sensing 13, no. 6 (2021): 1094. http://dx.doi.org/10.3390/rs13061094.

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In this study, we develop a method to estimate corn yield based on remote sensing data and ground monitoring data under different water treatments. Spatially explicit information on crop yields is essential for farmers and agricultural agencies to make well-informed decisions. One approach to estimate crop yield with remote sensing is data assimilation, which integrates sequential observations of canopy development from remote sensing into model simulations of crop growth processes. We found that leaf area index (LAI) inversion based on unmanned aerial vehicle (UAV) vegetation index has a high

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Bareth, G., and C. Hütt. "UPSCALING AND VALIDATION OF RTK-DIRECT GEOREFERENCED UAV-BASED RGB IMAGE DATA WITH PLANET IMAGERY USING POLYGON GRIDS FOR PASTURE MONITORING." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2021 (June 29, 2021): 533–38. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2021-533-2021.

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Abstract. The monitoring of managed grasslands with remote sensing methods is becoming more important for spatial decision support. Various remote sensing data acquisition techniques are applied for that purpose in different spatial resolutions ranging from UAV-borne to satellite-based remote sensing. In the last decade, UAV-borne imaging and analysis techniques or in the focus of crop and grassland monitoring and provide very high spatial resolutions. In contrast, satellite data are only available in high to moderate spatial resolutions. In this contribution, we introduce direct georeferenced

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Yao, Huang, Rongjun Qin, and Xiaoyu Chen. "Unmanned Aerial Vehicle for Remote Sensing Applications—A Review." Remote Sensing 11, no. 12 (2019): 1443. http://dx.doi.org/10.3390/rs11121443.

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The unmanned aerial vehicle (UAV) sensors and platforms nowadays are being used in almost every application (e.g., agriculture, forestry, and mining) that needs observed information from the top or oblique views. While they intend to be a general remote sensing (RS) tool, the relevant RS data processing and analysis methods are still largely ad-hoc to applications. Although the obvious advantages of UAV data are their high spatial resolution and flexibility in acquisition and sensor integration, there is in general a lack of systematic analysis on how these characteristics alter solutions for

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Raju, P. L. N., C. Gupta, V. Saikhom, et al. "NEW INITIATIVE OF UNMANNED AERIAL VEHICLE (UAV) EMERGING TECHNOLOGY APPLICATIONS IN NORTH EAST FOR CAPACITY BUILDING AND OUTREACH ACTIVITIES OF NORTH EASTERN SPACE APPLICATIONS CENTRE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (November 15, 2018): 421–24. http://dx.doi.org/10.5194/isprs-annals-iv-5-421-2018.

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<p><strong>Abstract.</strong> Unmanned Aerial Vehicle (UAV) technology is revolutionizing and acting as an alternative for many of remote sensing applications, particularly for very high resolution satellite requirements, considering easy of flying in the areas of persistent cloud cover like North East. According to top market reports, UAV business is growing at very fast rate. It is valued at USD 18.14 Billion in 2017 and is projected to reach USD 52.30 Billion by 2025, at a CAGR of 14.15% from 2018 to 2025.</p><p>North Eastern Space Applications Centre, Umiam, S

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Zhu, Wanxue, Ehsan Eyshi Rezaei, Hamideh Nouri, et al. "Quick Detection of Field-Scale Soil Comprehensive Attributes via the Integration of UAV and Sentinel-2B Remote Sensing Data." Remote Sensing 13, no. 22 (2021): 4716. http://dx.doi.org/10.3390/rs13224716.

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Satellite and unmanned aerial vehicle (UAV) remote sensing can be used to estimate soil properties; however, little is known regarding the effects of UAV and satellite remote sensing data integration on the estimation of soil comprehensive attributes, or how to estimate quickly and robustly. In this study, we tackled those gaps by employing UAV multispectral and Sentinel-2B data to estimate soil salinity and chemical properties over a large agricultural farm (400 ha) covered by different crops and harvest areas at the coastal saline-alkali land of the Yellow River Delta of China in 2019. Spati

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Salem, Mohammed A. M., and Sultan Almotairi. "Vehicle Detection In Remote Sensing Images." International Journal of Innovative Technology and Exploring Engineering 8, no. 11 (2019): 928–33. http://dx.doi.org/10.35940/ijitee.k1807.0881119.

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Traffic monitoring and management is one of the most crucial tasks of governing bodies in modern big cities. With each passing day the traffic problem grows in complexity due to the continuous increase of participating vehicles and the hard expansion of the road network and parking places. In this article we introduce a new method for vehicle detection and localization in parking lots using high resolution UAV images. In order to end up with practical and yet effective approach, which could be implemented on low computing hardware resources and integrated with the camera in the UAV, we conside

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Emery, William, and John Schmalzel. "Editorial for “Remote Sensing from Unmanned Aerial Vehicles”." Remote Sensing 10, no. 12 (2018): 1877. http://dx.doi.org/10.3390/rs10121877.

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Zhang, Tiantian, Dongha SHIM, and Jae-sang Cha. "Application of UAV Remote Sensing Technology in the Construction of Modern Smart Farm." Mobile Information Systems 2022 (April 8, 2022): 1–13. http://dx.doi.org/10.1155/2022/7119113.

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This article is to study the application and optimization of UAV remote sensing technology in the construction of smart farms. Multiparty calculations, circuit design, remote sensing, and remote control are used wirelessly, with a wide field of vision and easy evasion. Its transmitting frequency, transmitting power, interference electromagnetic wave intensity, receiving sensitivity, and gain coefficient are all factors that affect wireless remote sensing. Stress and strain are also important factors for the timely response and control of remote sensing technology. This article first outlines s

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Yang, Ying, Li Jun Wang, and Lei Yang. "Processing and Mosaicing System of Civil Unmanned Aerial Vehicle Remote Sensing Image." Advanced Materials Research 989-994 (July 2014): 3548–51. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3548.

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With combining Unmanned Aerial Vehicle (UAV) and the high-precision of the low altitude Remote Sensing (RS) technology, UAV RS technology has become an important compleme-nt for satellite and manned aircraft RS, so it has drawn great attention of people at home and abroad. Most of UAV RS image technologies use small digital cameras to shoot so that it causes some proble-ms such as lower magnitude, more and larger morphing image. The image processing and mosaicing system of UAV RS implements the function of image identifying, selection of image group control points, geometric correction, mosaic

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Pourroostaei Ardakani, Saeid, and Ali Cheshmehzangi. "Reinforcement Learning-Enabled UAV Itinerary Planning for Remote Sensing Applications in Smart Farming." Telecom 2, no. 3 (2021): 255–70. http://dx.doi.org/10.3390/telecom2030017.

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UAV path planning for remote sensing aims to find the best-fitted routes to complete a data collection mission. UAVs plan the routes and move through them to remotely collect environmental data from particular target zones by using sensory devices such as cameras. Route planning may utilize machine learning techniques to autonomously find/select cost-effective and/or best-fitted routes and achieve optimized results including: minimized data collection delay, reduced UAV power consumption, decreased flight traversed distance and maximized number of collected data samples. This paper utilizes a

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Zhang, Haidong, Lingqing Wang, Ting Tian, and Jianghai Yin. "A Review of Unmanned Aerial Vehicle Low-Altitude Remote Sensing (UAV-LARS) Use in Agricultural Monitoring in China." Remote Sensing 13, no. 6 (2021): 1221. http://dx.doi.org/10.3390/rs13061221.

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Precision agriculture relies on the rapid acquisition and analysis of agricultural information. An emerging method of agricultural monitoring is unmanned aerial vehicle low-altitude remote sensing (UAV-LARS), which possesses significant advantages of simple construction, strong mobility, and high spatial-temporal resolution with synchronously obtained image and spatial information. UAV-LARS could provide a high degree of overlap between X and Y during key crop growth periods that is currently lacking in satellite and remote sensing data. Simultaneously, UAV-LARS overcomes the limitations such

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Berra, E. F., and M. V. Peppa. "ADVANCES AND CHALLENGES OF UAV SFM MVS PHOTOGRAMMETRY AND REMOTE SENSING: SHORT REVIEW." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (December 22, 2020): 267–72. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-267-2020.

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Abstract. Interest in Unnamed Aerial Vehicle (UAV)-sourced data and Structure-from-Motion (SfM) and Multi-View-Stereo (MVS) photogrammetry has seen a dramatic expansion over the last decade, revolutionizing the fields of aerial remote sensing and mapping. This literature review provides a summary overview on the recent developments and applications of light-weight UAVs and on the widely-accepted SfM - MVS approach. Firstly, the advantages and limitations of UAV remote sensing systems are discussed, followed by an identification of the different UAV and miniaturised sensor models applied to num

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Yang, Shengtian, Juan Wang, Pengfei Wang, Tongliang Gong, and Huiping Liu. "Low Altitude Unmanned Aerial Vehicles (UAVs) and Satellite Remote Sensing Are Used to Calculated River Discharge Attenuation Coefficients of Ungauged Catchments in Arid Desert." Water 11, no. 12 (2019): 2633. http://dx.doi.org/10.3390/w11122633.

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The arid desert ecosystem is very fragile, and the change of its river discharge has a direct impact on irrigation and natural environment. River discharge attenuation coefficients is a key index to reveal the stability of desert river ecosystem. However, due to the harsh conditions in desert areas, it is difficult to establish a hydrological station to obtain data and calculate the attenuation coefficients, so it is urgent to develop new methods to master the attenuation coefficients of rivers. In this study, Taklamakan desert river was selected as the research area, and the river discharge o

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Feroz, Sainab, and Saleh Abu Dabous. "UAV-Based Remote Sensing Applications for Bridge Condition Assessment." Remote Sensing 13, no. 9 (2021): 1809. http://dx.doi.org/10.3390/rs13091809.

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Deterioration of bridge infrastructure is a serious concern to transport and government agencies as it declines serviceability and reliability of bridges and jeopardizes public safety. Maintenance and rehabilitation needs of bridge infrastructure are periodically monitored and assessed, typically every two years. Existing inspection techniques, such as visual inspection, are time-consuming, subjective, and often incomplete. Non-destructive testing (NDT) using Unmanned Aerial Vehicles (UAVs) have been gaining momentum for bridge monitoring in the recent years, particularly due to enhanced acces

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Zhang, Wen, and Juan Wu. "To Explore the UAV Application in Disaster Prevention and Reduction." Applied Mechanics and Materials 590 (June 2014): 609–12. http://dx.doi.org/10.4028/www.scientific.net/amm.590.609.

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The UAV remote sensing is an important way of aerial remote sensing, and increasingly become an important means for spatial data acquisition, which has the advantages of long life time, image real-time transmission, high-risk area detection, low cost, flexibility, is a powerful supplement satellite and aerial remote sensing."Tianyi" series of UAV has a number of intellectual property rights, and repeatedly used in major natural disaster emergency in the country. Has the advantages of small volume, light weight, small target characteristics, the use of fast, flexible, convenient operation and r

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Jia, Zhi Le, Xiao Ping Lu, Feng Jie Zheng, Wen Qan Zang, and Qing Chen Liu. "Research on Atmospheric Correction and Surface Reflectance Inversion of UAV (Unmanned Aerial Vehicle) Remote Sensing Data." Applied Mechanics and Materials 427-429 (September 2013): 1485–88. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1485.

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Through atmospheric correction of UAV remote sensing images, inversion to obtain surface reflectance, typical objects with measured experimental area water, vegetation and bare soil area reflectance comparative analysis, the experimental results prove the feasibility of using UVA to carry out the quantitative remote sensing research, and its advantages.

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Weintrit, B., K. Bakuła, M. Jędryka, et al. "EMERGENCY RESCUE MANAGEMENT SUPPORTED BY UAV REMOTE SENSING DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W4 (March 6, 2018): 563–67. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w4-563-2018.

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<p><strong>Abstract.</strong> In the proposed SAFEDAM system, aerial and satellite-based information is used for the monitoring of river bodies, flood monitoring during the event, and for post-disaster damage assessment. UAV constitute a valuable source of information about the current situation in the field during the operation of emergency services. Time is crucial, and the basic assumption to use UAV remote sensing data is to make them available immediately after landing. Therefore, the approach of automatic orthomosaics created based on the exterior orientation of the tra

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Osco, Lucas Prado, José Marcato Junior, Ana Paula Marques Ramos, et al. "A review on deep learning in UAV remote sensing." International Journal of Applied Earth Observation and Geoinformation 102 (October 2021): 102456. http://dx.doi.org/10.1016/j.jag.2021.102456.

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Carvajal-Ramírez, Fernando, Francisco Agüera-Vega, and Patricio Martínez-Carricondo. "Editorial for Special Issue “UAV Photogrammetry and Remote Sensing”." Remote Sensing 13, no. 12 (2021): 2327. http://dx.doi.org/10.3390/rs13122327.

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The concept of Remote Sensing as a way of capturing information from an object without making contact with it has, until recently, been exclusively focused on the use of earth observation satellites [...]

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Cui, Mengying, Yonghua Sun, Chen Huang, and Mengjun Li. "Water Turbidity Retrieval Based on UAV Hyperspectral Remote Sensing." Water 14, no. 1 (2022): 128. http://dx.doi.org/10.3390/w14010128.

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The water components affecting turbidity are complex and changeable, and the spectral response mechanism of each water quality parameter is different. Therefore, this study mainly aimed at the turbidity monitoring by unmanned aerial vehicle (UAV) hyperspectral technology, and establishes a set of turbidity retrieval models through the artificial control experiment, and verifies the model’s accuracy through UAV flight and water sample data in the same period. The results of this experiment can also be extended to different inland waters for turbidity retrieval. Retrieval of turbidity values of

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Wen-Qin Wang, Qicong Peng, and Jingye Cai. "Waveform-Diversity-Based Millimeter-Wave UAV SAR Remote Sensing." IEEE Transactions on Geoscience and Remote Sensing 47, no. 3 (2009): 691–700. http://dx.doi.org/10.1109/tgrs.2008.2008720.

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