Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery DOI
Hui Ying Pak, Weisi Lin, Adrian Wing‐Keung Law

et al.

International Journal of Remote Sensing, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 23

Published: Dec. 26, 2024

Mosaicking of Unmanned Aerial Vehicles (UAV) imagery over featureless water bodies has been known to be challenging, and poses a significant impediment monitoring applications. Techniques such as Structure-from-motion typically fail under conditions due the lack distinctive features in scene, direct georeferencing is currently only practical solution, albeit lower accuracy expected. However, hardware issues, particularly typical time delay between GPS unit image capture, can lead systematic misalignment further reducing accuracy. The arises recording geographical coordinates by may not precisely correspond exact moment exposure, exposure always occur at mid-exposure time. Hardware solutions mitigate this issue but require technical expertise resources. Alternatively, software address problem without necessitating any modifications. This study introduces an open-source solution for correction alignment accounting distance discrepancy measurements capture. method was validated with field UAV surveys conducted various flight configurations (different altitudes overlap ratios), effective obtained using proposed which reduced error around 67.7%. Specifically, RMSE = 1.409 m σ 0.6356 achieved use ground control points (GCPs). Finally, demonstrated study, low (e.g. 15 m) should discouraged errors could amplify limited GPS, resulting visual artefacts.

Language: Английский

A review of methods and instruments to monitor turbidity and suspended sediment concentration DOI Creative Commons
Tiago Matos, M.S. Martins, Renato Henriques

et al.

Journal of Water Process Engineering, Journal Year: 2024, Volume and Issue: 64, P. 105624 - 105624

Published: June 14, 2024

Language: Английский

Citations

17
Monitoring Coastal Water Turbidity Using Sentinel2—A Case Study in Los Angeles DOI Creative Commons
Yuwei Kong, Karina Jimenez, Christine Lee

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(2), P. 201 - 201

Published: Jan. 8, 2025

Los Angeles coastal waters are an ecologically important marine habitat and a famed recreational area for tourists. Constant surveillance is essential to ensure compliance with established health standards address the persistent water quality challenges in region. Remotely sensed datasets increasingly being applied toward improved detection of by augmenting monitoring programs spatially intensive accessible data. This study evaluates potential satellite remote sensing augment traditional analyzing relationship between situ satellite-derived turbidity Field measurements were performed from July 2021 March 2024 build synchronous matchup consisting field Correlation analysis indicated positive field-measured (R2 = 0.451). Machine learning models assessed predictive accuracy, random forest model achieving highest performance 0.632), indicating its robustness modeling complex patterns. Seasonal trends revealed higher during wet months, likely due stormwater runoff Ballona Creek watershed. Despite limitations cloud cover spatial resolution, findings suggest that integrating data machine can enhance large-scale, efficient waters.

Language: Английский

Citations

1
A Comparative Study of Multi-Rotor Unmanned Aerial Vehicles (UAVs) with Spectral Sensors for Real-Time Turbidity Monitoring in the Coastal Environment DOI Creative Commons

Ha Linh Trinh,

Hieu Trung Kieu, Hui Ying Pak

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(2), P. 52 - 52

Published: Feb. 5, 2024

Complex coastal environments pose unique logistical challenges when deploying unmanned aerial vehicles (UAVs) for real-time image acquisition during monitoring operations of marine water quality. One the key is difficulty in synchronizing images acquired by UAV spectral sensors and ground-truth situ quality measurements calibration, due to a typical time delay between these two modes data acquisition. This study investigates logistics concurrent deployment UAV-borne sampling vessel effects on turbidity predictions operations. The results show that minimizing can significantly enhance efficiency consequently improve calibration process. In particular, outcomes highlight notable improvements model’s predictive accuracy distribution derived from images. Furthermore, comparative analysis based pilot conducted multirotor configurations: DJI M600 Pro with hyperspectral camera M300 RTK multispectral camera. performance evaluation includes complexity, processing productivity, sensitivity environmental noises. RTK, equipped camera, found offer higher cost-effectiveness, faster setup times, better endurance while yielding good at same time. It therefore more compelling choice widespread industry adoption. Overall, this contribute advancement UAVs monitoring.

Language: Английский

Citations

5
Sun Glint-Aware Restoration (SUGAR): a robust sun glint correction algorithm for UAV imagery to enhance monitoring of turbid coastal environments DOI
Hui Ying Pak, Adrian Wing‐Keung Law, Weisi Lin

et al.

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(3)

Published: Feb. 8, 2025

Language: Английский

Citations

0
Development of UAV-based LiDAR and multispectral measurement techniques for monitoring sediment intrusion in coastal wetlands DOI Creative Commons
Paweł Tysiąc, Damian Moskalewicz, Łukasz Janowski

et al.

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117459 - 117459

Published: April 1, 2025

Language: Английский

Citations

0
CoastalWQL: An Open-Source Tool for Drone-Based Mapping of Coastal Turbidity Using Push Broom Hyperspectral Imagery DOI Creative Commons
Hui Ying Pak, Hieu Trung Kieu, Weisi Lin

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 708 - 708

Published: Feb. 17, 2024

Uncrewed-Aerial Vehicles (UAVs) and hyperspectral sensors are emerging as effective alternatives for monitoring water quality on-demand. However, image mosaicking largely featureless coastal surfaces or open seas has shown to be challenging. Another pertinent issue observed is the systematic misalignment between adjacent flight lines due time delay UAV-borne sensor GNSS system. To overcome these challenges, this study introduces a workflow that entails GPS-based method push-broom images, together with correction address aforementioned misalignment. An open-source toolkit, CoastalWQL, was developed facilitate workflow, which includes essential pre-processing procedures improving mosaic’s quality, such radiometric correction, de-striping, sun glint object masking classification. For validation, UAV-based imaging surveys were conducted monitor turbidity in Singapore, implementation of CoastalWQL’s evaluated at each step via retrieval. Overall, results confirm imagery over surface using CoastalWQL enabled better localisation plume. Radiometric de-striping also found most important procedures, improved prediction by 46.5%.

Language: Английский

Citations

3
DiffuYOLO: A novel method for small vehicle detection in remote sensing based on diffusion models DOI Creative Commons
Jing Li, Zhiyong Zhang, Haochen Sun

et al.

Alexandria Engineering Journal, Journal Year: 2024, Volume and Issue: 114, P. 485 - 496

Published: Dec. 5, 2024

Language: Английский

Citations

1
Multispectral Inversion of Citrus Multi-Slope Evapotranspiration by UAV Based on Modified RSEB Model DOI Open Access

Shijiang Zhu,

Zhiwei Zhang, Chenfei Duan

et al.

Water, Journal Year: 2024, Volume and Issue: 16(11), P. 1520 - 1520

Published: May 25, 2024

Evaptotranspiration (ETc) is a crucial link in the farmland water cycle process. To accurately obtain citrus ETc different slope positions, METRIC, RSEB, and FAO Penman–Monteith (P-M) models were constructed based on unmanned aerial vehicle (UAV) multispectral images to invert values. The of calculated by P-M model was used as reference standard, accuracy inversion evaluated METRIC RSEB model. results showed that R2, RMSE, SE 0.396 0.486, 4.940 3.010, 4.570 2.090, respectively, indicating higher for inverting Furthermore, could be improved introducing optimal correction coefficient (after correction: RMSE = 1.470, 0.003). Based modified model, values positions obtained. We also found middle > top bottom ETc, position indeed affected ETc. This research provides favorable framework inversion, are theoretical practical importance realize crop conservation.

Language: Английский

Citations

0
Image recognition applied in the study of water turbidity analysis DOI
Hui‐Ming Fang, Yun-Chih Chiang, Ting-Chieh Lin

et al.

Published: April 20, 2024

Language: Английский

Citations

0
Enhancing Turbidity Predictions in Coastal Environments by Removing Obstructions from Unmanned Aerial Vehicle Multispectral Imagery Using Inpainting Techniques DOI Creative Commons
Hieu Trung Kieu,

Yoong Sze Yeong,

Ha Linh Trinh

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(10), P. 555 - 555

Published: Oct. 7, 2024

High-resolution remote sensing of turbidity in the coastal environment with unmanned aerial vehicles (UAVs) can be adversely affected by presence obstructions vessels and marine objects images, which introduce significant errors modeling predictions. This study evaluates use two deep-learning-based inpainting methods, namely, Decoupled Spatial–Temporal Transformer (DSTT) Deep Image Prior (DIP), to recover obstructed information. Aerial images plumes were first acquired using a UAV system multispectral sensor that included on water surface at various obstruction percentages. The performance models was then assessed through both qualitative quantitative analyses inpainted data, focusing accuracy retrieval. results show DIP model performs well across wide range percentages from 10 70%. In comparison, DSTT produces good only low less than 20% poorly when percentage increases.

Language: Английский

Citations

0