Search Results (57)

This paper presents a hybrid pipeline based on zero-shot vision models for automatic node count estimation in Lisianthus (Eustoma grandiflorum) cultivation and a system for real-time growth information sharing. The multistage image analysis pipeline integrates Grounding DINO for zero-shot leaf-region detection, MiDaS for monocular depth estimation, and a YOLO-based classifier, using daily time-lapse images from low-cost fixed cameras in commercial greenhouses. The model parameters are derived from field measurements of 2024 seasonal crops (Trial 1) and then applied to different cropping seasons, growers, and cultivars (Trials 2 and 3) without any additional retraining. Trial 1 indicates high accuracy (R² = 0.930, mean absolute error (MAE) = 0.73). Generalization performance is confirmed in Trials 2 (MAE = 0.45) and 3 (MAE = 1.14); reproducibility across multiple growers and four cultivars yields MAEs of approximately ±1 node. The model effectively captures the growth progression despite variations in lighting, plant architecture, and grower practices, although errors increase during early growth stages and under unstable leaf detection. Furthermore, an automated Discord-based notification system enables real-time sharing of node trends and analytical images, facilitating communication. The feasibility of combining zero-shot vision models with cloud-based communication tools for sustainable and collaborative floricultural production is thus demonstrated. Full article

The paper presents a comparison of two methods for determining the burning time of an electric arc in a vacuum chamber: the classic oscilloscope method and the author’s own photographic analysis using an ultra-high-speed camera. A specially designed laboratory station enabled precise recording of electrical and optical parameters during switching operations conducted at different pressures in the discharge chamber. The photographic method consisted of a time-lapse analysis of the ignition and extinction of the arc using dedicated software to precisely determine its duration based on the recorded images. In total, five repeated measurements were performed for each pressure value. All the results were subjected to a detailed statistical analysis, including the determination of standard deviations and confidence intervals. The reported mean relative error for the new photographic method did not exceed 1.12%. The developed photographic method proved to be a reliable tool for assessing the duration of the arc, while also enabling a detailed analysis of the dynamics of arc channel development. Possible applications include laboratory testing and diagnostics of switching devices, especially where traditional measurement methods are difficult to apply. Full article

Reliable monitoring of snow cover in mountainous regions remains a challenge due to frequent cloud cover and the revisit limitations of optical satellites. This study compares satellite snow-cover records with >99,000 ground-based time-lapse camera observations across northern Spain (2003–2025). Cloud cover caused major data loss, with up to 57% of satellite images affected. Effective revisit intervals (the average time between usable images) diverge substantially from nominal values: 2.3 days for MODIS, 6.9 days for Sentinel-2, and over 21 days for Landsat. A hierarchical multisensor approach with 5-day gap-filling reduced this to just 1.3 days. On dates when cameras confirmed snow, satellites underestimated snow presence by 61.6% (Sentinel-2), 71.5% (Landsat), and 79.7% (MODIS), though gap-filling approaches reduced underestimation to 49.4%—deficits largely attributable to cloud-obscured scenes. When both satellite and camera provided cloud-free observations for the same date and location, classification agreement exceeded 85%. Despite this, satellites consistently failed to detect short-lived snow events and introduced temporal biases. On average, Snow Onset Dates were detected 13–52 days later, and Snow Melt-Out Dates differed by up to 40 days compared to camera-derived records. These results have implications for snow-cover monitoring using satellite images and highlight the need for integrating ground-based observations to compensate for satellite limitations and improve snow cover seasonality assessments in complex terrains. Full article

Common eastern bumble bees (Bombus impatiens Cresson) play an essential role in pollinating lowbush blueberries (LB) in northern Quebec, but their costs and the suboptimal weather conditions during pollination highlight the need to find appropriate hive management strategies. A study was conducted in a LB field in Saguenay (Québec, Canada) focusing on the effects of hive insulation (I+ and I−), heating (H+ and H−), and placement in a single-row tree line windbreak. High-definition time-lapse cameras monitored hive activities and bumble bee foraging behaviors. We found that the conventional management of placing hives in full sun without insulation (I−) resulted in the lowest levels of bumble bee foraging activity and overall hive traffic. Placing bumble bee hives against a windbreak resulted in the highest numbers of bees entering hives with pollen (+156%), leaving hives (+69%), and overall hive traffic (+76%). Insulating hives with extruded polystyrene foam gave intermediate results, with a 105% increase in foraging activity compared to the conventional management method (I−H−). Interestingly, placing hives on seedling mats to maintain colony temperatures above 15 °C (H+) tended to decrease foraging activity and overall hive traffic. Our results show that strategic placement of bumble bee hives against windbreaks can significantly increase the activity of Bombus workers from those hives and can be used as a simple, low-cost, and efficient bumble bee hive management method by LB growers. Full article

The main component of vacuum interrupters responsible for ensuring the correct flow of current is the contact system. In a vacuum environment, due to the higher values of the mean free path of electrons and particles in the contact gap, the material and condition of the contacts exert the greatest influence on the development of the arc discharge. To accurately analyze the phenomenon of discharge development in vacuum insulating systems, the authors conducted a time-lapse photographic analysis of a vacuum electric arc. For this purpose, they used a test setup comprising a discharge chamber, a vacuum pump set, a power and load assembly, an ultra-high-speed camera, and an oscilloscope with dedicated probes. The measurement process involved connecting the system, determining the power supply, load, and measurement parameters and subsequently performing contact opening operations while simultaneously recording the process using the oscilloscope and ultra-high-speed camera. An analysis of a low-current vacuum arc in a residual helium gas environment, with a pressure of p = 1.00 × 10¹ Pa was carried out. Different phases of vacuum arc burning between electrodes in the discharge chamber were identified. In the stable phase, the arc voltage remained constant, while in the unstable phase, the arc voltage increased. The results of the time-lapse analysis were compared with the characteristics recorded by the oscilloscope, revealing a correlation between the increase in vacuum arc voltage and the intensity of flashes in the interelectrode space. The movement of microparticles ejected from the surface of the contacts—either reflecting or adhering to one of the electrodes—was observed. This analysis provides a deeper understanding of the processes involved in discharge formation and development under reduced pressure conditions. Understanding these mechanisms can support the design of vacuum interrupters, particularly in the selection of suitable contact materials and shapes. Full article

Monitoring animal populations is crucial for assessing the health of ecosystems. Traditional methods, which require extensive fieldwork, are increasingly being supplemented by time-lapse camera-trap imagery combined with an automatic analysis of the image data. The latter usually involves some object detector aimed at detecting relevant targets (commonly animals) in each image, followed by some postprocessing to gather activity and population data. In this paper, we show that the performance of an object detector in a single frame of a time-lapse sequence can be improved by including spatio-temporal features from the prior frames. We propose a method that leverages temporal information by integrating two additional spatial feature channels which capture stationary and non-stationary elements of the scene and consequently improve scene understanding and reduce the number of stationary false positives. The proposed technique achieves a significant improvement of 24% in mean average precision (mAP@0.05:0.95) over the baseline (temporal feature-free, single frame) object detector on a large dataset of breeding tropical seabirds. We envisage our method will be widely applicable to other wildlife monitoring applications that use time-lapse imaging. Full article

Long-term observation of single-cell oscillations within tissue networks is now possible by combining bioluminescence reporters with stable tissue explant culture techniques. This method is particularly effective in revealing the network dynamics in systems with slow oscillations, such as circadian clocks. However, the low intensity of luciferase-based bioluminescence requires signal amplification using specialized cameras (e.g., I-CCDs and EM-CCDs) and prolonged exposure times, increasing baseline noise and reducing temporal resolution. To address this limitation, we implemented a cost-effective optical enhancement technique called telecompression, first used in astrophotography and now commonly used in digital photography. By combining a high numerical aperture objective lens with a magnification-reducing relay lens, we significantly increased the collection efficiency of the bioluminescence signal without raising the baseline CCD noise. This method allows for shorter exposure times in time-lapse imaging, enhancing temporal resolution and enabling more precise period estimations. Our implementation demonstrates the feasibility of telecompression for enhancing bioluminescence imaging for the tissue-level network observation of circadian clocks. Full article

We study the interrelations between salt karst and landscape evolution at the Ze’elim and Hever alluvial fans, Dead Sea (DS), Israel, in an attempt to characterize the ongoing surface and subsurface processes and identify future trends. Using light detection and ranging, interferometric synthetic aperture radar, drone photography, time-lapse cameras, and direct measurements of floodwater levels, we document floodwater recharge through riverbed sinkholes, subsurface salt dissolution, groundwater flow, and brine discharge at shoreline sinkholes during the years 2011–2023. At the Ze’elim fan, most of the surface floodwater drains into streambed sinkholes and discharges at shoreline sinkholes, whereas at the Hever fan, only a small fraction of the floodwater drains into sinkholes, while the majority flows downstream to the DS. This difference is attributed to the low-gradient stream profiles in Ze’elim, which enable water accumulation and recharge in sinkholes and their surrounding depressions, in contrast with the higher-gradient Hever profiles, which yield high-energy floods capable of carrying coarse gravel that eventually fill the sinkholes. The rapid drainage of floodwater into sinkholes also involves slope failure due to pore-pressure drop and cohesion loss within hours after each drainage event. Surface subsidence lineaments detected by InSAR indicate the presence of subsurface dissolution channels between recharge and discharge sites in the two fans and in the nearby Lynch straits. Subsidence and streambed sinkholes occur in most other fans and streams that flow to the DS; however, with the exception of Ze’elim, all other streams show only minor or no recharge along their course. This is due to either the high-gradient profiles, the gravelly sediments, the limited floods, or the lack of conditions for sinkhole development in the other streambeds. Thus, understanding the factors that govern the flood-related karst formation is of great importance for predicting landscape evolution in the DS region and elsewhere and for sinkhole hazard assessment. Full article

Digital photogrammetry has attracted widespread attention in the field of geotechnical and geological surveys due to its low-cost, ease of use, and contactless mode. In this work, with the purpose of studying the progressive block surficial detachments of a landslide, we developed a monitoring system based on fixed multi-view time-lapse cameras. Thanks to a newly developed photogrammetric algorithm based on the comparison of photo sequences through a structural similarity metric and the computation of the disparity map of two convergent views, we can quickly detect the occurrence of collapse events, determine their location, and calculate the collapse volume. With the field data obtained at the Perarolo landslide site (Belluno Province, Italy), we conducted preliminary tests of the effectiveness of the algorithm and its accuracy in the volume calculation. The method of quickly and automatically obtaining the collapse information proposed in this paper can extend the potential of landslide monitoring systems based on videos or photo sequence and it will be of great significance for further research on the link between the frequency of collapse events and the driving factors. Full article

Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and considerable hardware costs. As such, there is a need for an autonomous low-cost system (~EUR 500), such as Timex cameras, that can be rapidly deployed in the field, while still producing the outcomes required for coastal monitoring. This research presents an assessment of the effect of the sampling strategy (time-lapse intervals) on the precision of shoreline detection for two low-cost cameras located in a remote coastal area in western Ireland, overlooking a dissipative beach–dune system. The analysis shows that RMSD in the detected shoreline is similar to other studies for sampling intervals ranging between 1 s and 30 s (i.e., RMSD_mean for Camera 1 = 1.4 m and Camera 2 = 0.9 m), and an increase in the sampling interval from 1 s to 30 s had no significant adverse effect on the precision of shoreline detection. The research shows that depending on the intended use of the detected shorelines, the current standard of 1 s image sampling interval when using Timex cameras can be increased up to 30 s without any significant loss of accuracy. This positively impacts battery life and memory storage, making the systems more autonomous; for example, the battery life increased from ~10 days to ~100 days when the sampling interval was increased from 1 to 5 s. Full article

(1) Background: Global climate change is expected to significantly alter growing conditions along mountain gradients. Landscape ecological patterns are likely to shift significantly as species attempt to adapt to these changes. We evaluated the extent to which spatial (elevation and canopy cover) and temporal (decadal trend and El Niño–Southern Oscillation/Pacific Decadal Oscillation) factors impact seasonal snowmelt and forest community dynamics in the Western Hemlock–True Fir ecotone region of the Oregon Western Cascades, USA. (2) Methods: Tsuga heterophylla and Abies amabilis seedling locations were mapped three times over 20 years (2002–2022) on five sample transects strategically placed to cross the ecotone. Additionally, daily ground temperature readings were collected over 10 years for the five transects using 123 data loggers to estimate below-canopy snow metrics. (3) Results: Based on validation using time-lapse cameras, the data loggers proved highly reliable for estimating snow cover. The method reported fewer days of snow cover as compared to meteorological station-based snow products for the region, emphasizing the importance of direct under-canopy field observations of snow. Snow season variability was most significantly impacted temporally by cyclical ENSO/PDO climate patterns and spatially by differences in canopy cover within the ecotone. The associated seedling analysis identified clear sorting of species by elevation within the ecotone but reflected a lack of a long-term trend, as species dominance in the seedling strata did not significantly shift along the elevation gradient over the 20-year study. (4) Conclusions: The data logger-based approach provided estimates of snow cover at ecologically significant locations and fine enough spatial resolutions to allow for the study of forest regeneration dynamics. The results highlight the importance of long-term, understory snow measurements and the influence of climatic oscillations in understanding the vulnerability of mountain areas to the changing climate. Full article

The Kenyan part of the East African Rift System hosts several geothermal fields for energy production. Changes in the extraction rate of geothermal fluids and the amount of water re-injected into the system affect reservoir pressure and production capacity over time. Understanding the balance of production, natural processes and the response of the geothermal system requires long-term monitoring. The presence of a geothermal system at depth is often accompanied by surface manifestations, such as hot water springs and fumaroles, which have the potential for monitoring subsurface activity. Two thermal camera timelapse systems were developed and installed as part of a multi-sensor observatory in Kenya to capture fumarole activity over time. These cameras are an aggregation of a camera unit, a control unit, and a battery charged by a solar panel, and they monitor fumarole activity on an hourly basis, with a deep sleep of the system in between recordings. The article describes the choice of hardware and software, presents the data that the cameras acquire, and discusses the system’s performance and possible improvement points. Full article

Changes in the masses of icebergs due to deterioration processes affect the drift of icebergs and should be taken into account when assessing iceberg risks in the areas of offshore development. In 2022 and 2023, eight laboratory experiments were carried out in the wave tank of the University Centre in Svalbard to study the melting of icebergs in sea water under calm and rough conditions. In the experiments, the water temperatures varied from $0 ℃$ to $2.2 ℃$. Cylindrical iceberg models were made from columnar ice cores with a diameter of 24 cm. In one experiment, the iceberg model was protected on the sides with plastic fencing to investigate the iceberg’s protection from melting when towed to deliver fresh water. The iceberg masses, water temperatures, and ice temperatures were measured in the experiments. The water velocity near the iceberg models was measured with an acoustic Doppler velocimeter. During the experiments, time-lapse cameras were used to describe the shapes and measure the vertical dimensions of the icebergs. Using experimental data, we calculated the horizontal dimensions of icebergs, latent heat fluxes, conductive heat fluxes inside the iceberg models, and turbulent heat fluxes in water as a function of time. We discovered the influence of surface waves and water mixing on the melt rates and found a significant reduction in the melt rates due to the lateral protection of the iceberg model using a plastic barrier. Based on the experimental data obtained, the ratio of the rates of lateral and bottom melting of the icebergs and lateral melting of the icebergs under wave conditions was parametrized depending on the wave frequency. Full article

Precision agriculture relies on understanding crop growth dynamics and plant responses to short-term changes in abiotic factors. In this technical note, we present and discuss a technical approach for cost-effective, non-invasive, time-lapse crop monitoring that automates the process of deriving further plant parameters, such as biomass, from 3D object information obtained via stereo images in the red, green, and blue (RGB) color space. The novelty of our approach lies in the automated workflow, which includes a reliable automated data pipeline for 3D point cloud reconstruction from dynamic scenes of RGB images with high spatio-temporal resolution. The setup is based on a permanent rigid and calibrated stereo camera installation and was tested over an entire growing season of winter barley at the Global Change Experimental Facility (GCEF) in Bad Lauchstädt, Germany. For this study, radiometrically aligned image pairs were captured several times per day from 3 November 2021 to 28 June 2022. We performed image preselection using a random forest (RF) classifier with a prediction accuracy of 94.2% to eliminate unsuitable, e.g., shadowed, images in advance and obtained 3D object information for 86 records of the time series using the 4D processing option of the Agisoft Metashape software package, achieving mean standard deviations (STDs) of 17.3–30.4 mm. Finally, we determined vegetation heights by calculating cloud-to-cloud (C2C) distances between a reference point cloud, computed at the beginning of the time-lapse observation, and the respective point clouds measured in succession with an absolute error of 24.9–35.6 mm in depth direction. The calculated growth rates derived from RGB stereo images match the corresponding reference measurements, demonstrating the adequacy of our method in monitoring geometric plant traits, such as vegetation heights and growth spurts during the stand development using automated workflows. Full article

Harbour seals (Phoca vitulina) are part of the Norwegian coastal ecosystem and can be observed on skerries, islands, and sandbanks along the coastline, sometimes in close proximity to inhabited areas. In this study, we used time-lapse camera surveys to monitor the haulout patterns of harbour seals at two selected sites in the Norwegian Skagerrak, Lyngør and Østre Bolæren, over 12 and 4 months, respectively. The goal was to investigate how the number of seals hauling out on land varied seasonally and how it was influenced by environmental parameters (wind speed, air temperature, and water level), the time of the day, and anthropogenic disturbances. As expected, the number of seals hauled out increased with increasing air temperature and decreased with increasing wind speed and water level. Clear circadian patterns in the seal haulout behaviour were identified during autumn and winter when a significantly higher number of seals were observed on land at night. Moreover, haulout patterns showed significant seasonal variation, with a peak in haul outs being observed during the moulting season in August. Despite an expected high usage of land during the breeding season in early summer, the number of seals hauled out at the Lyngor study site was low during this period, especially during weekends and summer holidays, maybe due to increased disturbance from boats. This study provides valuable insights into the factors influencing the haulout behaviour of the species in the region and suggests possible effects of human disturbance on harbour seal behaviour in the area. Full article