An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade–Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12–0.14 m s −1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s −1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s −1 of the ADCP measurements, on average.

Figure 1: Comparison of surface flow velocities obtained with different algorithms.

How to cite: Pearce, S.; Ljubičić, R.; Peña-Haro, S.; Perks, M.; Tauro, F.; Pizarro, A.; Dal Sasso, S.F.; Strelnikova, D.; Grimaldi, S.; Maddock, I.; Paulus, G.; Plavšić, J.; Prodanović, D.; Manfreda, S. An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems. Remote Sens., 12, 232, 2020. [pdf]

Il ruolo dei droni nella tutela del territorio ed il monitoraggio ambientale

Il monitoraggio rappresenta la principale fonte di conoscenza nelle scienze ambientali. I recenti progressi nelle tecnologie nell’ambito dell’Osservazione della Terra offrono molteplici possibilità per il monitoring e la tutela ambientale. I Sistemi Aeromobili a Pilotaggio Remoto (SAPR), noti anche con la denominazione di droni, consentono di effettuare una nuova gamma di rilievi ambientali ad altissima risoluzione. Una delle caratteristiche chiave dei sistemi SAPR deriva dalla possibilità di operare come piattaforma multi-sensore, offrendo una visuale estesa dallo spettro del visibile a quello dell’infrarosso termico.

In questo articolo, vengono presentate le principali attività di monitoraggio ambientale svolte dal gruppo di ricerca HydroLAB dell’Università della Basilicata.

Mappatura termica dei vigneti delle Cantine del Notaio a Maschito (PZ)

Manfreda, S., S.F. Dal Sasso, L. Mita, Il ruolo dei droni nella tutela del territorio ed il monitoraggio ambientale, Knowledge Transfer Review, n. 5, 110-115, 2019. [link]

Workshop Standardization of procedures in using UAS for environmental monitoring

Workshop “Standardization of procedures in using UAS for environmental monitoring

Date: 6 November, 2019

Venue: Department of Civil Engineering, University of Coimbra (Coimbra, Portugal)

We are pleased to inform that the next Workshop of the COST Action HARMONIOUS will be held at the University of Coimbra, in Coimbra, Portugal, on November 6th, 2019. The Workshop will focus on the Standardization of procedures in using UAS for environmental monitoring, and will be opened to all interested (scientific and technical communities, stakeholders). Come to Coimbra to find out about our activities!

Contributions from the scientific and technical communities are welcome and will be presented in oral and poster sessions.

Submit an Abstract (Deadline 30/07/2019)

In the following days after this workshop, there will be other activities reserved for COST HARMONIOUS members only: WG meetings (7/11/2019) and MC meeting (8/11/2019).

More info are available here:

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, post-processing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

How to cite: Manfreda, S., M. F. McCabe, P. E. Miller, R. Lucas, V. Pajuelo Madrigal, G. Mallinis, E. Ben-Dor, D. Helman, L. Estes, G. Ciraolo, J. Müllerová, F. Tauro, M. I. de Lima, J. L. M. P. de Lima, A. Maltese, F. Frances, K. Caylor, M. Kohv, M. Perks, G. Ruiz-Pérez, Z. Su, G. Vico, and B. Toth, On the Use of Unmanned Aerial Systems for Environmental MonitoringRemote Sensing, 10(4), 641; (doi:10.3390/rs10040641) 2018.  [pdf

On the derivation of flow rating-curves in data-scarce environments

River monitoring is a critical issue for hydrological modelling that relies strongly on the use of flow rating curves (FRCs). In most cases, these functions are derived by least-squares fitting which usually leads to good performance indices, even when based on a limited range of data that especially lack high flow observations. In this context, cross-section geometry is a controlling factor which is not fully exploited in classical approaches. In fact, river discharge is obtained as the product of two factors: 1) the area of the wetted cross-section and 2) the cross-sectionally averaged velocity. Both factors can be expressed as a function of the river stage, defining a viable alternative in the derivation of FRCs. This makes it possible to exploit information about cross-section geometry limiting, at least partially, the uncertainty in the extrapolation of discharge at higher flow values. Numerical analyses and field data confirm the reliability of the proposed procedure for the derivation of FRCs.

How to cite: Manfreda, S., On the derivation of flow rating-curves in data-scarce environmentsJournal of Hydrogy, 562, 151-154 (doi: 10.1016/j.jhydrol.2018.04.058) 2018.

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

Advances in flow monitoring are crucial to increase our knowledge on basin hydrology and to understand the interactions between flow dynamics and infrastructures. In this context, image processing offers great potential for hydraulic monitoring, allowing acquisition of a wide range of measurements with high spatial resolution at relatively low costs. In particular, the particle tracking velocimetry (PTV) algorithm can be used to describe the dynamics of surface flow velocity in both space and time using fixed cameras or unmanned aerial systems (UASs). In this study, analyses allowed exploration of the optimal particle seeding density and frame rate in different configurations. Numerical results provided useful indications for two field experiments that have been carried out with a low-cost quadrocopter equipped with an optical camera to record RGB videos of floating tracers manually distributed over the water surface. Field measurements have been carried out using different natural tracers under diverse hydraulic and morphological conditions; PTV’s processed velocities have been subsequently benchmarked with current meter measurements. The numerical results allowed rapid identification of the experimental configuration (e.g., required particle seeding density, image resolution, particle size, and frame frequency) producing flow velocity fields with high resolution in time and space with good agreement with the benchmark velocity values measured with conventional instruments.

How to cite: Dal Sasso, S. F., A. Pizarro, C. Samela, L. Mita, and S. Manfreda, Exploring the optimal experimental setup for surface flow velocity measurements using PTVEnvironmental Monitoring and Assessment, 190:460, (doi: 10.1007/s10661-018-6848-3) 2018. [pdf]


Le enormi innovazioni dei sistemi di osservazione delle terra hanno consentito di migliorare la nostra capacità di monitoraggio di sistemi naturali ed antropizzati. In tale ambito, i droni consentono di effettuare osservazioni ad un livello di dettaglio impensabile fino a qualche anno fa. Pertanto, sono stati sviluppati nuovi algoritmi e strumenti per il monitoraggio ambientale, mediante droni, per migliorare la risoluzione e l’accuratezza delle misure in campo agronomico, forestale ed idrologico. In particolare, sono stati sviluppati algoritmi finalizzati al monitoraggio dello stato della vegetazione e dell’umidità del suolo mediante camere multispettrali e termiche. Si riporta, a titolo di esempio, il rilievo da drone svolto con camera ottica e termica per caratterizzare lo stato di un vigneto nell’area del Vulture (Fig. 3).

Figura 3. Ortofoto da camera ottica e termica dei vigneti di Aglianico delle Cantine del Notaio a Maschito (Monte Vulture – Potenza). La mappatura descrive l’uso del suolo con una risoluzione di 1 cm e la temperatura superficiale con una risoluzione di 5 cm.

L’acquisizione di immagini e video da drone consentono di produrre stime spazialmente distribuite dei campi di velocità mediante le tecniche ottiche LSPIV e PTV. Queste offrono l’opportunità di migliorare le misure di portata in alveo e monitorare gli eventi di inondazione utilizzando filmati rinvenienti per esempio da Social Media. Si riporta qui di seguito una misurazione della velocità superficiale effettuata mediante tecniche ottiche applicate al fiume Bradano (Fig. 4).

Figure 4. Misure di velocità del flusso 2-D derivato utilizzando camera ottica montata su un quadricottero in volo sul fiume Bradano (Italia meridionale). Nei riquadri sono evidenziate le caratteristiche della superficie utilizzate per tracciare il flusso nel processo di analisi.

Emerging earth observing platforms offer new insights into hydrological processes

Data, and its timely delivery, presents one of the major constraints in advancing the hydrological sciences. Traditional monitoring techniques are time consuming, expensive, and discontinuous in space and time. Moreover, field observations are influenced by instrumental degradation and human errors. While providing the foundation upon which much of our hydrological knowledge is based, new observational strategies are required to drive further understanding and insights. Recent advances in earth observation (EO) technologies present a new frontier for hydrologic monitoring and process description.

Figure: UAS derived 3D dense point cloud, (B) mesh model, and (C) tiled model derived from a UAS based survey of an earthen dam next to the village of Pischia (Timisoara, Romania). Such data provide the framework for development of high-resolution flood modeling, urban watershed mapping and civil engineering design and map updating.

How to cite: Manfreda, S., M.F. McCabe. Emerging earth observing platforms offer new insights into hydrological processesHydrolink, 1, 8-9, 2019.  [pdf]

Measurements and Observations in the XXI century (MOXXI): innovation and multidisciplinarity to disclose the hydrological cycle

To promote the advancement of novel observation techniques that may lead to new sources of information to help better understand the hydrological cycle, the International Association of Hydrological Sciences (IAHS) established the Measurements and Observations in the XXI century (MOXXI) Working Group in July 2013. The group comprises a growing community of tech-enthusiastic hydrologists that design and develop their own sensing systems, adopt a multi-disciplinary perspective in tackling complex observations, often use low-cost equipment intended for other applications to build innovative sensors, or perform opportunistic measurements. This paper states the objectives of the group and reviews major advances carried out by MOXXI members toward the advancement of hydrological sciences. Challenges and opportunities are outlined to provide strategic guidance for advancement of measurement, and thus discovery.

How to cite: Tauro, F., J. Selker, N. van de Giesen, T. Abrate, R. Uijlenhoet, M. Porfiri, S. Manfreda, K. Caylor, T. Moramarco, J.Benveniste, G. Ciraolo, L. Estes, A. Domeneghetti, M. T. Perks, C. Corbari, E. Rabiei, G. Ravazzani, H. Bogena, A.Harfouche, L. Brocca, A. Maltese, A. Wickert, C. Cudennec, T. Blume, R. Hut, and S. Grimaldi, Measurements and Observations in the XXI century (MOXXI): innovation and multidisciplinarity to disclose the hydrological cycleHydrological Sciences Journal, 63:2, 169-196, (doi: 10.1080/02626667.2017.1420191) 2018.  [pdf]

Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites

Soil moisture is a variable of paramount importance for a number of natural processes and requires the capacity to be routinely measured at different spatial and temporal scales (e.g., hillslope and/or small catchment scale). The electromagnetic induction (EMI) method is one of the geophysical techniques potentially useful in this regard. Indeed, it does not require contact with the ground, it allows a relatively fast survey of hillslope, it gives information related to soil depth greater than few centimetres and it can also be used in wooded areas. In this study, apparent electrical conductivity (EC a ) and soil moisture (SM) measurements were jointly carried out by using a multi-frequency EMI sensor (GEM-300) and Time Domain Reflectometry (TDR) probes, respectively. The aim was to retrieve SM variations at the hillslope scale over four sites, characterized by different land-soil units, located in a small mountainous catchment in southern Italy. Repeated measurements of ECa carried out over a fixed point showed that the signal variability of the GEM-300 sensor (Std. Err. [0.02–0.1 mS/m]) was negligible. The correlation estimated between point EC a and SM, measured with both portable and buried TDR probes, varied between 0.24 and 0.58, depending on the site considered. In order to reduce the effect of small-scale variability, a spatial smoothing filter was applied which allowed the estimation of linear relationships with higher coefficient of correlation (r 0.46–0.8). The accuracy obtained in the estimation of the temporal trend of the soil moisture spatial averages was in the range 4.5–7.8% v/v and up to the 70% of the point soil moisture variance was explained by the EC a signal. The obtained results highlighted the potential of EMI to provide, in a short time, sufficiently accurate estimate of soil moisture over large areas that are highly needed for hydrological and remote sensing applications.

How to cite: G. Calamita, A. Perrone, L. Brocca, B. Onorati, S. Manfreda, Field test of a multi-frequency electromagnetic induction sensor for soil moisture monitoring in southern Italy test sites, Journal of Hydrology, Pages 316 – 329 (doi: 10.1016/j.jhydrol.2015.07.023), 2015. [pdf]