High Acquisition Frequency Research Articles

Simulating tumor volume dynamics in response to radiotherapy: Implications of model selection

From the beginning of the usage of radiotherapy (RT) for cancer treatment, mathematical modeling has been integral to understanding radiobiology and for designing treatment approaches and schedules. There has been extensive modeling of response to RT with the inclusion of various degrees of biological complexity. In this study, we compare three models of tumor volume dynamics: (1) exponential growth with RT directly reducing tumor volume, (2) logistic growth with direct tumor volume reduction, and (3) logistic growth with RT reducing the tumor carrying capacity with the objective of understanding the implications of model selection and informing the process of model calibration and parameterization. For all three models, we: examined the rates of change in tumor volume during and RT treatment course; performed parameter sensitivity and identifiability analyses; and investigated the impact of the parameter sensitivity on the tumor volume trajectories. In examining the tumor volume dynamics trends, we coined a new metric – the point of maximum reduction of tumor volume (MRV) – to quantify the magnitude and timing of the expected largest impact of RT during a treatment course. We found distinct timing differences in MRV, dependent on model selection. The parameter identifiability and sensitivity analyses revealed the interdependence of the different model parameters and that it is only possible to independently identify tumor growth and radiation response parameters if the underlying tumor growth rate is sufficiently large. Ultimately, the results of these analyses help us to better understand the implications of model selection while simultaneously generating falsifiable hypotheses about MRV timing that can be tested on longitudinal measurements of tumor volume from pre-clinical or clinical data with high acquisition frequency. Although, our study only compares three particular models, the results demonstrate that caution is necessary in selecting models of response to RT, given the artifacts imposed by each model.

High-speed measurement of thickness of a water film formed by a jet obliquely impinging onto a plate using an LED-induced fluorescence method

A transient thickness distribution measured with a high temporal resolution is elemental for exploring the flow characteristics and mechanism of a liquid film formed by an impinging jet. Therefore, this paper develops a high-speed Light-Emitting Diode-Induced Fluorescence (LEDIF) system based on the brightness measured directly above the liquid film. An Ultraviolet (UV) LED lamp is used to provide sufficient and continuous excitation light. Then, a system performance analysis proves that the system can continuously measure the global film thickness at a high acquisition frequency of 5000 Hz when the dye concentration is 200 mg/L. The influence of the irregularity of the excitation intensity, including the spatial non-uniformity, temporal instability, and long-term instability, on the measurement uncertainty is analyzed in detail. The analysis indicates that the system has an acceptable uncertainty of 10%. Compared with theoretical results, experimental results verify that the LEDIF system can accurately measure the global thickness of a liquid film formed by a water jet obliquely impinging onto a plate. An experimental investigation of the radial section of the raised zone demonstrates that the radial section changes from a sewing needle to an oval when the azimuth angle increases from 10° to 90°. Meanwhile, the dynamic contact angle exponentially decreases from 41.4° to 30.1°. A dynamic analysis of surface waves shows that the measured wave velocity decreases from 12 m/s to 1 m/s and the dominant frequency decreases from 1000 Hz to 10 Hz along the flow direction.

Short communication: Potential of Sentinel-1 interferometric synthetic aperture radar (InSAR) and offset tracking in monitoring post-cyclonic landslide activities on Réunion

Abstract. This study examines the results of an interferometric synthetic aperture radar (InSAR) and SAR offset tracking (OT) study in Cirque de Salazie (CdS), Réunion Island, France, within the context of the RENOVRISK project, a multidisciplinary programme to study the cyclonic risks in the south-western Indian Ocean. Despite numerous landslides in this territory, CdS is one of the more densely populated areas on Réunion Island. One of the aims of the project is to assess whether Sentinel-1 SAR methods can be used to measure landslide motion and/or accelerations due to post-cyclonic activity in CdS. We concentrate on the post-2017 cyclonic activity. We use the Copernicus Sentinel-1 data, acquired between 30 October 2017 and 6 November 2018. Sentinel-1 is a C-band SAR, and its signal can be severely affected by the presence of changing vegetation between two SAR acquisitions, particularly in CdS, where the vegetation canopy is well developed. This is why C-band radars such as the ones on board RADARSAT or Envisat, characterized by low acquisition frequency (24 and 36 d, respectively), could not be routinely used in CdS to measure landslide motion with InSAR in the past. In this study, we use InSAR and OT techniques applied to Sentinel-1 SAR. We find that C-band SAR on board Sentinel-1 can be used to monitor landslide motion in densely vegetated areas, thanks to its high acquisition frequency (12 d). OT stacking reveals a useful complement to InSAR, especially in mapping fast moving areas. In particular, we can highlight ground motion in the Hell-Bourg, Ilet à Vidot, Grand-Ilet, Camp Pierrot, and Le Bélier landslides.

Evaluation of Terra/Aqua MODIS and Sentinel-2 MSI NDVI data for predicting actual evapotranspiration in Mediterranean regions

ABSTRACT Conventional meteorological data and remotely sensed Normalized Difference Vegetation Index (NDVI) images can be proficiently combined to predict actual evapotranspiration (ETA) on different spatial and temporal scales. Up to now, however, the operational application of this approach in heterogeneous Mediterranean regions has found difficulty due to the insufficient spatial resolution of satellite sensors having high acquisition frequency (i.e. 250 m of Terra/Aqua Moderate Resolution Imaging Spectroradiometer, MODIS). The current study investigates the advantages brought for this objective by the recent availability of NDVI data taken from the Sentinel-2 MultiSpectral Instrument (MSI), which has a spatial resolution of 10 m. The investigation has been performed in two Mediterranean areas characterized by different spatio-temporal variability of vegetation cover. The first is a mountain coniferous forest, where such variability is low, while the second is a relatively small (around 10 ha) irrigated tomato field surrounded by other annual crops showing diversified growing cycles. An ETA estimation method based on NDVI data is applied in the two study areas and its performances are evaluated against ground references obtained through the elaboration of site measurements (i.e. meteorological, soil water content, and crop coefficient observations). The advantage of using MSI over MODIS NDVI images is marginal in the first case study, while is evident in the second. More particularly, such advantage is outstanding when the remote sensing method is applied in an operational mode, i.e. without using the information on the water supplied to the tomato crop by irrigation. This confirms that the utility of higher spatial resolution data is dependent not only on the fragmentation of the observed landscapes but also on the synchronicity of major vegetation growing cycles, which is influenced by both environmental and human-induced factors.

A recurrent neural network based on attention mechanism to predict the trend of univariate time series

For the time series with high acquisition frequency and high noise, it is difficult to establish the prediction model directly. If we simply take their average values, we will lose a lot of trend information. Therefore, we studied how to accurately obtain the trend information of the time series and establish its accurate prediction model, and proposed a prediction model based on K-means clustering. The first step of the model is to obtain the trend information of the original time series based on the K-means clustering idea, and the second step is to use the gated recurrent unit based on the attention mechanism to establish a prediction model for the trend information. Experiments on three dataset show that the proposed K-means clustering method can effectively reduce noise interference and accurately obtain trend information. Comparative experiments on different prediction models show that our proposed prediction model has the best prediction accuracy.

A recurrent neural network based on attention mechanism to predict the trend of univariate time series

For the time series with high acquisition frequency and high noise, it is difficult to establish the prediction model directly. If we simply take their average values, we will lose a lot of trend information. Therefore, we studied how to accurately obtain the trend information of the time series and establish its accurate prediction model, and proposed a prediction model based on K-means clustering. The first step of the model is to obtain the trend information of the original time series based on the K-means clustering idea, and the second step is to use the gated recurrent unit based on the attention mechanism to establish a prediction model for the trend information. Experiments on three dataset show that the proposed K-means clustering method can effectively reduce noise interference and accurately obtain trend information. Comparative experiments on different prediction models show that our proposed prediction model has the best prediction accuracy.

A novel method for quantitative analysis on the post-necking behavior during uniaxial tension

In this study, a combined experimental–numerical method is proposed for quantitatively characterizing the post-necking behavior of cylindrical metal specimens merely through its experimental force–displacement curve during quasi-static tension. This method is based on a rational phenomenological analysis of the correspondence between the necking levels and the experimental variables (force and displacement) in plastic tension. Firstly, the definitions of the global and local inhomogeneity factors based on the statistical analysis of the radial change within the gauge section were introduced to assess the inhomogeneity degrees of post-necking specimens. In the proposed method, a number of tensile deformations with different necking levels are modeled through implanting different initial defects into specimen model in finite element analysis, respectively, outputting the corresponding simulated force–displacement curves. The inhomogeneity factors are calculated based on the intersected points between the experimental and simulated force–displacement curves. Through validation of optical measurement, it is proved that the proposed method has high accuracy and good reliability for investigating the inhomogeneous deformation with significant neck rather than those without significant neck and could exactly replace optical measurement, especially when the camera needs high resolution and acquisition frequency. This indicates it is feasible to utilize the force versus stroke curve in metal plastic forming to quantitatively analyze the localization behavior under general stress states besides uniaxial tension, concerning the contribution of initial defects.

Perrogator: A Portable Energy-Efficient Interrogator for Dynamic Monitoring of Wavelength-Based Sensors in Wearable Applications.

In this paper, we report the development of a portable energy-efficient interrogator (Perrogator) for wavelength-based optical sensors. The interrogator is based on a compact solution encompassing a white light source and the spectral convolution between the sensor and a tunable filter, which is acquired by a photodetector, where a microcontroller has two functions: (i) To control the filter tuning and to (ii) acquire the photodetector signal. Then, the data is sent to a single-board computer for further signal processing. Furthermore, the employed single-board computer has a Wi-Fi module, which can be used to send the sensors data to the cloud. The proposed approach resulted in an interrogator with a resolution as high as 3.82 pm (for 15.64 nm sweeping range) and maximum acquisition frequency of about 210 Hz (with lower resolution ~15.30 pm). Perrogator was compared with a commercial fiber Bragg grating (FBG) interrogator for strain measurements and good agreement between both devices was found (1.226 pm/µε for the commercial interrogator and 1.201 pm/µε for the proposed approach with root mean square error of 0.0144 and 0.0153, respectively), where the Perrogator has the additional advantages of lower cost, higher portability and lower energy consumption. In order to demonstrate such advantages in conjunction with the high acquisition frequency allowed us to demonstrate two wearable applications using the proposed interrogation device over FBG and Fabry-Perot interferometer (FPI) sensors. In the first application, an FBG-embedded smart textile for knee angle assessment was used to analyze the gait of a healthy person. Due to the capability of reconstructing the FBG spectra, it was possible to employ a technique based on the FBG wavelength shift and reflectivity to decouple the effects of the bending angle and axial strain on the FBG response. The measurement of the knee angle as well as the estimation of the angular and axial displacements on the grating that can be correlated to the variations of the knee center of rotation were performed. In the second application, a FPI was embedded in a chest band for simultaneous measurement of breath and heart rates, where good agreement (error below 5%) was found with the reference sensors in all analyzed cases.

Synergy between Sentinel-1 radar time series and Sentinel-2 optical for the mapping of restored areas in Danube delta

Abstract. Wetlands are important and valuable ecosystems, yet, since 1900, more than 50 % of wetlands have been lost worldwide. An example of altered and partially restored coastal wetlands is the Danube Delta in Romania. Over time, human intervention has manifested itself in more than a quarter of the entire Danube surface. This intervention was brutal and has rendered ecosystem restoration very difficult. Studies for the rehabilitation / re-vegetation were started immediately after the Danube Delta was declared as a Biosphere Reservation in 1990. Remote sensing offers accurate methods for detecting and mapping change in restored wetlands. Vegetation change detection is a powerful indicator of restoration success. The restoration projects use vegetative cover as an important indicator of restoration success. To follow the evolution of the vegetation cover of the restored areas, satellite images radar and optical of last generation have been used, such as Sentinel-1 and Sentinel-2. Indeed the sensor sensitivity to the landscape depends on the wavelength what- ever radar or optical data and their polarization for radar data. Combining this kind of data is particularly relevant for the classification of wetland vegetation, which are associated with the density and size of the vegetation. In addition, the high temporal acquisition frequency of Sentinel-1 which are not sensitive to cloud cover al- low to use temporal signature of the different land cover. Thus we analyse the polarimetric and temporal signature of Sentinel-1 data in order to better understand the signature of the different study classes. In a second phase, we performed classifications based on the Random Forest supervised classification algorithm involving the entire Sentinel-1 time series, then starting from a Sentinel-2 collection and finally involving combinations of Sentinel-1 and -2 data.

On Temperature Rise Within the Shear Bands in Bulk Metallic Glasses

Room temperature deformation process in a bulk metallic glassy sample was studied by using a hydraulic thermomechanical simulator. The temperature rise during each separate shear band propagation event was measured with a high data acquisition frequency by a thermocouple welded to the sample. Calculation showed that when propagation of the well developed shear bands takes place along the entire sample the temperature inside the shear band should be close to the glass-transition temperature. It was also possible to resolve the temporal stress distribution and a double-stage character of stress drops was also observed. The obtained results are compared with the literature data obtained by infrared camera measurements and the results of finite elements modeling.

Multilevel characterization of marine microbial biodegradation potentiality by means of flow-modulated comprehensive two-dimensional gas chromatography combined with a triple quadrupole mass spectrometer

The present research is focused on the use of a triple quadrupole mass spectrometer (QqQ MS) coupled with flow modulated comprehensive two-dimensional gas chromatography (FM GC × GC) for a multilevel elucidation of biodegradation potentiality of natural marine microbial populations during a bioremediation (biostimulation) treatment. The crude oil used for the evaluation of the bioremediation process, namely Dansk Blend Pier E1, represents a very complex sample. Hence, in order to understand the metabolic activity of microbial populations during the bioremediation process, a GC × GC system was used. The high separation power has allowed a detailed characterization of the different chemical families; moreover, thanks to the high acquisition frequency of the QqQ MS spectrometer, both full scan and multiple reaction monitoring (MRM) data were acquired in the same run. By using this system, both qualitative analysis of untargeted hydrocarbons mixture (crude oil) and qualitative analysis of biomarker compounds, present in low amount and often hindered under the bulk of the sample (i.e. adamantanes, diamantanes, steranes and hopanes), were performed simultaneously.The bioremediation capability of biostimulated bacteria was evaluated at four (T4), eight (T8) and fourteen (T14) days. Progressive degradation of linear, branched, and aromatic hydrocarbons, adamantanes, and diamantanes has been showed, whereas, results underline the lack of any kind of activity against steranes, and hopanes.

Automatic plume episode identification and cloud shine reconstruction method for ambient gamma dose rates during nuclear accidents

Ambient gamma dose rate (GDR) is the primary observation quantity for nuclear emergency management due to its high acquisition frequency and dense spatial deployment. However, ambient GDR is the sum of both cloud and ground shine, which hinders its effective utilization. In this study, an automatic method is proposed to identify the radioactive plume passage and to separate the cloud and ground shine in the total GDR. The new method is evaluated against a synthetic GDR dataset generated by JRODOS (Real Time On-line Decision Support) System and compared with another method (Hirayama, H. et al., 2014. Estimation of I-131 concentration using time history of pulse height distribution at monitoring post and detector response for radionuclide in plume. Transactions of the Atomic Energy Society of Japan 13:119–126, in Japanese (with English abstract)). The reconstructed cloud shine agrees well with the actual values for the whole synthetic dataset (1451 data points), with a very small absolute fractional bias (FB = 0.02) and normalized mean square error (NMSE = 2.04) as well as a large correlation coefficient (r = 0.95). The new method significantly outperforms the existing one (more than 95% reduction of FB and NMSE, and 61% improvement of the correlation coefficient), mainly due to the modification for high deposition events. The code of the proposed methodology and all the test data are available for academic and non-commercial use. The new approach with the detailed interpretation of the in-situ environment data will help improving the ability of off-site source term inverse estimation for nuclear accidents.

Suivi à hautes résolutions spatiale et temporelle du système karstique des Fonts (Gard, France)

Since 2011 a dense network of measurements has been installed on the karst system of Les Fonts (into and outside this system). This network combines measurements of water level and water temperature on 4 stations into the karst and 6 on rivers (with a spring). The acquisition frequency varies from 5 to 30 minutes in according to hydrological period. The database validated the conceptual scheme of the karst system. In addition some hydrological phenomena have been showed (e. g. variation of water temperature during floods). This is the combined effect of the sensor density and the high acquisition frequency that allowed the acquisition of these results. The main objective (for the next 5 years) is to keep operational this network despite (i) the difficulties for accessing to sites (water level in caves, level of CO2…) (ii) without funding dedicated and (iii) with the experimental difficulties linked to the treatment, critical and storage of data. In perspective, this research network could become an operational network for those local authorities improve them qualitative and quantitative water resource management.

Phenomenology of a flow around a circular cylinder at sub-critical and critical Reynolds numbers

In this work, the flow around a circular cylinder is investigated at Reynolds numbers ranging from 79 000 up to 238 000 by means of a combined acquisition system based on Temperature Sensitive Paint (TSP) and particle velocimetry. The proposed setup allows simultaneous and time-resolved measurement of absolute temperature and relative skin friction fields onto the cylinder surface and near-wake velocity field. Combination of time-resolved surface measurements and planar near-field velocity data allows the investigation of the profound modifications undergone by the wall shear stress topology and its connections to the near-field structure as the flow regime travels from the sub-critical to the critical regime. Laminar boundary-layer separation, transition, and re-attachment are analyzed in the light of temperature, relative skin friction maps, and Reynolds stress fields bringing about a new perspective on the relationship between boundary layer development and shear layer evolution. The fast-responding TSP employed allows high acquisition frequency and calculation of power spectral density from surface data. Correlation maps of surface and near-wake data provide insight into the relationship between boundary-layer evolution and vortex shedding. We find that as the Reynolds number approaches the critical state, the separation line oscillations feature an increasingly weaker spectrum peak compared to the near-wake velocity spectrum. In the critical regime, separation line oscillations are strongly reduced and the correlation to the local vorticity undergoes an overall decrease giving evidence of modifications in the vortex shedding mechanism.

The impact of Hurricane Katrina on the coastline west of New Orleans, USA

Forms of coastline are constantly modified by such driving forces as waves, sea level change, storms and winds. Among various driving forces, the effects of hurricanes can be the greatest and fastest. It is critical to continuously observe coastline changes in order to improve our understanding on the role of hurricane storms. One way is to make frequent field measurements along the coast before and after hurricane events. This is clearly labor-intensive at the regional scale. Remotely sensed data with sufficiently high acquisition frequency and spatial resolution can serve the purpose. Our question is if freely accessible Landsat data can be used to solve this problem. We used a 180-km long coast west of New Orleans that was affected by Hurricane Katrina as a case study. The storm surge induced by Hurricane Katrina caused well-known catastrophic damages in human lives and economic values. However, to what extent it has changed the coastline at the regional scale is an open question. We used Landsat time-series data (1984–2015) to estimate the rate of coastline change. First, the shortwave-infrared (1.55 mm) band of each Landsat image was selected to separate water and land. Water body detection was carried out using a simple threshold-based method. The optimal threshold was determined with a method based on the maximum inter-class variance criterion. Second, the boundary of the ocean water body was delineated as the coastline. Third, a linear regression model between water level and coastline position was established and an interpolation was conducted to remove the impact of clouds or shadows. To better analyze the impact of hurricanes on the coast, we removed the variation of water levels due to waves. Each average coastline positon was corrected to the long-term mean water level. The change rates were estimated during different observation periods. The results demonstrate that both the position and change rate of the coastline changed dramatically after the hurricane. Before Hurricane Katrina, 39% of the coastline advanced to ocean and 61% retreated to land, and the regional average change rate was - 2.53 m/a. After Hurricane Katrina, 27% of the coastline advanced to ocean and 73% retreated to land, and the regional average change rate was - 3.58 m/a. After Hurricane Katrina 87% of the coast suffered from serious erosion and the coastline shifted to land by 14.91 m during the hurricane. Further, we collected hurricane records in the study area from the National Hurricane Center and selected greater than level one hurricanes. We conducted an analysis of regime changes for coastline positions and found three regime turning points. We discovered that the regime turning points detected from Landsat time-series data matched well with the hurricane records. We conclude that there is a profound relationship between hurricane and coastline change. Landsat-level remote sensing data with 30 m spatial resolution can effectively estimate coastline changes caused by hurricanes in sediment dominated coastal areas. Coastline information derived from Landsat images could be used to assess impacts of hurricanes on the coast and to develop post-disaster reconstruction and restoration plans.

Earthquake Rapid Mapping Using Ascending and Descending Sentinel-1 TOPSAR Interferograms

The availability of new Sentinel-1A/B (S1A/B) satellites provides geohazards community with a large amount of Synthetic Aperture Radar (SAR) acquisitions over critical areas around the world. The current S1A mission has a minimum re-visit time of 12 days, but with the recent launch of S1B, this temporal gap will be reduced to only 6 days. This high acquisition frequency, jointly with the large coverage and high quality of S1 data, allows the rapid generation of interferograms1,2 for sudden events, such as earthquakes. This rapid response is crucial for the damage evaluation and fault model refinement.This paper presents results obtained for the latest earthquakes occurred in Japan in April 2016. Two S1A interferograms in ascending and descending orbits have been generated, and after phase unwrapping3,4 processing the Line Of Sight (LOS) motion maps are obtained. This LOS1,2 component corresponds to the range distance between the satellite and ground, and it does not provide real horizontal and vertical information of the displacement. The usage of two different view directions, in ascending and descending orbits, allows the decomposition of LOS motion into horizontal (West-East) and vertical (Up-Down) directions. These new motion maps are essential to better understand the dynamics of the earthquake and to perform further analysis and modelling by seismic experts.

Live monitoring of the distributed strain field in impulsive events through fiber Bragg gratings

In this paper, we propose a measurement technique based on local strain measurements to perform real-time reconstruction of the overall structural deformation and the distributed stress field produced by the impact of a body on a water free surface. In particular, we seek establishing a measurement chain capable of acquiring and elaborating the signals at high frequency, so that it can be utilized to study rapidly varying strain fields, such as those occurring in impulsive events. Fiber Bragg gratings are utilized to sense the local structural deformation. Experiments are conducted on flexible plastic wedges with variable deadrise angles impacting on a quiescent fluid surface. The experimental tests are performed in free fall and we explore variations of the entry velocity by varying the drop height. The structural deformation is reconstructed from point-wise strain measurements utilizing a modal reconstruction methodology. The impact dynamics are analysed through accelerometers and linear position sensors. Results show that the impact behaviour of the flexible body is characterized by a main overall deformation where the structure is distorted in the direction of the loading, whereby marked vibrations, whose amplitude increase with the entry velocity, dominate the dynamic response. The influence of the mode shapes considered in the present analysis on the accuracy of the results is also observed. The proposed methodology allows for a fairly high acquisition frequency, which translates into a real-time structural reconstruction technique. Results show that the proposed methodology can be a valuable tool for the live monitoring of structures undergoing impact events.

A flexible spatiotemporal method for fusing satellite images with different resolutions

Abstract Studies of land surface dynamics in heterogeneous landscapes often require remote sensing data with high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial resolution images through blending two types of data, i.e., frequent coarse spatial resolution data, such as that from MODIS, and less frequent high spatial resolution data such as that from Landsat. The proposed method is based on spectral unmixing analysis and a thin plate spline interpolator. Compared with existing spatiotemporal data fusion methods, it has the following strengths: (1) it needs minimum input data; (2) it is suitable for heterogeneous landscapes; and (3) it can predict both gradual change and land cover type change. Simulated data and real satellite images were used to test the performance of the proposed method. Its performance was compared with two very popular methods, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and an unmixing-based data fusion (UBDF) method. Results show that the new method creates more accurate fused images and keeps more spatial detail than STARFM and UBDF. More importantly, it closely captures reflectance changes caused by land cover conversions, which is a big issue with current spatiotemporal data fusion methods. Because the proposed method uses simple principles and needs only one fine-resolution image as input, it has the potential to increase the availability of high-resolution time-series data that can support studies of rapid land surface dynamics.

First Results From the Phenology-Based Synthesis Classifier Using Landsat 8 Imagery

A fully automatic phenology-based synthesis (PBS) classification algorithm was developed to map land cover based on medium spatial resolution satellite data using the Google Earth Engine cloud computing platform. Vegetation seasonality, particularly in the tropical dry regions, can lead conventional algorithms based on a single date image classification to “misclassify” land cover types, as the selected date might reflect only a particular stage of the natural phenological cycle. The PBS classifier operates with occurrence rules applied to a selection of single date image classifications of the study area to assign the most appropriate land cover class. Since the launch of Landsat 8 in 2013, it has been possible to acquire imagery at any point on the Earth every 16 days with exceptional radiometric quality. The relatively high global acquisition frequency and the open data policy allow near-real-time land cover mapping and monitoring with automated tools such as the PBS classifier. We mapped four protected areas and their 20-km buffer zones from different ecoregions in Sub-Saharan Africa using the PBS classifier to present its first results. Accuracy assessment was carried out through a visual interpretation of very high resolution images using a Web geographic information system interface. The combined overall accuracy was over 90%, which demonstrates the potential of the classifier and the power of cloud computing in geospatial sciences.

Assessment of PIV-based analysis of water entry problems through synthetic numerical datasets

The phenomenon of hull-slamming, that is, the sudden impact of a solid body on the water surface, is critical in the design of naval structures. Thus, the development and validation of schemes to predict the slamming load and elucidate energy exchange during water entry are of fundamental importance in a wide range of engineering applications. Recent studies have demonstrated the possibility of using direct flow measurements from particle image velocimetry (PIV) to investigate the kinetics of water entry. Specifically, these efforts have contributed a first characterization of the hydrodynamic loading on impacting wedges and of the energy imparted to the water pile-up and the spray jets. Here, we seek to provide a thorough assessment of such a PIV-based approach through synthetic datasets, in which PIV parameters, such as the camera acquisition rate and the size of the interrogation area, are systematically varied, without experimental confounds. We implement a direct computational framework to study the two-dimensional flow physics generated during the water entry of a rigid wedge. Water and air are treated as immiscible phases and their relative motion is utilized to track the free surface dynamics. Our results show that the PIV-based methodology allows for an accurate reconstruction of the pressure field from the measured velocity field, except for early stages of the impact and for a small region close to the free surface. We also demonstrate that the reconstruction is only marginally affected by the spatial resolution, while a sufficiently high acquisition frequency is required to correctly predict the pressure field in the pile-up region. The proposed computational framework can also find application in the analysis of less studied aspects of water entry problems, such as cycling loading, flow transitions and separation, and formation of spray jets.