Refining image‐velocimetry performances for streamflow monitoring: Seeding metrics to errors minimization-Reference-Cited by-同舟云学术

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Refining image‐velocimetry performances for streamflow monitoring: Seeding metrics to errors minimization

Published:2020-10-08 Issue:25 Volume:34 Page:5167-5175
ISSN:0885-6087
Container-title:Hydrological Processes
language:en
Short-container-title:Hydrological Processes

Author:

Pizarro Alonso¹^ORCID,Dal Sasso Silvano Fortunato¹^ORCID,Manfreda Salvatore²^ORCID

Affiliation:

1. Department of European and Mediterranean Cultures: Architecture, Environment and Cultural Heritage (DICEM) University of Basilicata Matera Italy

2. Department of Civil, Architectural and Environmental Engineering University of Naples Federico II Naples Italy

Funder

European Cooperation in Science and Technology

Publisher

Wiley

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.13919

Reference42 articles.

1. Lessons learnt from checking the quality of openly accessible river flow data worldwide

2. Metrics for the Quantification of Seeding Characteristics to Enhance Image Velocimetry Performance in Rivers

3. Exploring the optimal experimental setup for surface flow velocity measurements using PTV

4. Proof‐of‐concept for low‐cost and non‐contact synoptic airborne river flow measurements

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4. Natural surface floaters in image-based river surface velocimetry: Insights from a case study;Flow Measurement and Instrumentation;2024-04

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