Near Real-time Monitoring Research Articles

Application of innovative monitoring tools for safety and alert procedures in road tunnels

Abstract Tunnels and underground structures are one of the most important components of road and railway networks, especially near urban areas. For this reason, it is particularly important to identify potentially hazardous conditions in order to guarantee the structure’s durability and practicability. This paper presents a case study where a seismic event severely damaged a road tunnel located in Central Italy, impairing its accessibility and leading to its closure for safety reasons. Following the damage assessment, and given the importance of this specific structure, it was decided to perform a series of renovation works aimed to restore the tunnel’s operability. In this context, an innovative automatic monitoring device, able to measure the structure deformation, was installed in a critical section of the road tunnel. This instrument, called Cir Array, is specifically designed for near-real time monitoring of convergence phenomena and localized deformations inside underground structures, obtaining accurate and reliable results during their operational phase. The instrumentation provided useful information about the structure’s conditions, playing a major role into assessing the tunnel’s accessibility and safety during the renovation works. Moreover, thanks to its automated and high frequency sampling process, it will allow the implementation of dedicated warning procedures related to the passage of the vehicles inside the tunnel.

From Picture to Movie: Twenty Years of Ground Deformation Recording Over Tuscany Region (Italy) With Satellite InSAR

Synthetic Aperture Radar Interferometry (InSAR) techniques have been long exploited for detecting and mapping slow-moving ground surface displacements due to their millimetre accuracy, non-invasiveness and wide area coverage. A review on different applications of Persistent Scatterers InSAR approaches, proposed and applied over Tuscany region (Italy) across time, is here presented. The study area is characterized by both subsidence of alluvial plains and landslides on hilly and mountainous reliefs. Tuscany has a leading role in Italy in the field of interferometric applications: the first InSAR analysis, which date back to 2003, have been performed at local basin scale, by exploiting various PSI-based approaches for risk mapping. First InSAR applications at regional scale date back to 2009, relying on historical SAR archives of ERS and ENVISAT satellites for updating subsidence and landslide inventory maps at a certain temporal date. Nowadays, the availability of Sentinel-1 SAR data with a regular and systematic 6-days acquisitions plan, allows a near-real time monitoring of deformative scenario at regional scale rather than a solely mapping of geo-hydrological phenomena. Last innovative InSAR applications over Tuscany region scan the territory, exploiting the regular repeat pass of Sentinel-1, and promptly highlight the sites affected by the highest ground movements with high temporal frequency. Such approach permits to pass from a static ‘picture’ of the regional slope instability up to a weekly-updated ‘movie’ with improved detail, useful for civil protection practices. These last ongoing works significantly enhance the value of multi-temporal InSAR approaches for investigating and managing geo-hazards over the Region.

Monitoring Aquaculture Water Quality: Design of an Early Warning Sensor with Aliivibrio fischeri and Predictive Models.

A novel toxicity-warning sensor for water quality monitoring in recirculating aquaculture systems (RAS) is presented. The design of the sensor system mainly comprises a whole-cell biosensor. Aliivibrio fischeri, a luminescent bacterium widely used in toxicity analysis, was tested for a mixture of known fish-health stressors, namely nitrite, un-ionized ammonia, copper, aluminum and zinc. Two toxicity predictive models were constructed. Correlation, root mean squared error, relative error and toxic behavior were analyzed. The linear concentration addition (LCA) model was found suitable to ally with a machine learning algorithm for prediction of toxic events, thanks to additive behavior near the limit concentrations for these stressors, with a root-mean-squared error (RMSE) of 0.0623, and a mean absolute error of 4%. The model was proved to have a smaller relative deviation than other methods described in the literature. Moreover, the design of a novel microfluidic chip for toxicity testing is also proposed, which is to be integrated in a fluidic system that functions as a bypass of the RAS tank to enable near-real time monitoring. This chip was tested with simulated samples of RAS water spiked with zinc, with an EC50 of 6,46E-7 M. Future work will be extended to the analysis of other stressors with the novel chip.

Analyzing the December 2013 Metaponto Plain (Southern Italy) Flood Event by Integrating Optical Sensors Satellite Data

Timely and continuous information about flood dynamics are fundamental to ensure an effective implementation of the relief and rescue operations. Satellite data provided by optical sensors onboard meteorological satellites could have great potential in this framework, offering an adequate trade-off between spatial and temporal resolution. The latest would benefit from the integration of observations coming from different satellite systems, also helping to increase the probability of finding cloud free images over the investigated region. The Robust Satellite Techniques for detecting flooded areas (RST-FLOOD) is a sensor-independent multi-temporal approach aimed at detecting flooded areas which has already been applied with good results on different polar orbiting optical sensors. In this work, it has been implemented on both the 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) and the 375 m Suomi National Polar-orbiting Partnership (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The flooding event affecting the Basilicata and Puglia regions (southern Italy) in December 2013 has been selected as a test case. The achieved results confirm the RST-FLOOD potential in reliably detecting, in case of small basins, flooded areas regardless of the sensor used. Flooded areas have indeed been detected with similar performance by the two sensors, allowing for their continuous and near-real time monitoring.

Tracking drug-related overdoses at the local level: Using Syndromic Surveillance in the CO-NCR

Objective: In order to better describe local drug-related overdoses, we developed a novel syndromic case definition using discharge diagnosis codes from emergency department data in the Colorado North Central Region (CO-NCR). Secondarily, we used free text fields to understand the use of unspecified diagnosis fields.Introduction: The United States is in the midst of a drug crisis; drug-related overdoses are the leading cause of unintentional death in the country. In Colorado the rate of fatal drug overdose increased 68% from 2002-2014 (9.7 deaths per 100,000 to 16.3 per 100,000, respectively)1, and non-fatal overdose also increased during this time period (23% increase in emergency department visits since 2011)2. The CDC’s National Syndromic Surveillance Program (NSSP) provides near-real time monitoring of emergency department (ED) events across the country, with information uploaded daily on patient demographics, chief complaint for visit, diagnosis codes, triage notes, and more. Colorado North Central Region (CO-NCR) receives data for 4 local public health agencies from 25 hospitals across Adams, Arapahoe, Boulder, Denver, Douglas, and Jefferson Counties.Access to local syndromic data in near-real time provides valuable information for local public health program planning, policy, and evaluation efforts. However, use of these data also comes with many challenges. For example, we learned from key informant interviews with ED staff in Boulder and Denver counties, about concern with the accuracy and specificity of drug-related diagnosis codes, specifically for opioid-related overdoses.Methods: Boulder County Public Health (BCPH) and Denver Public Health (DPH) developed a query in Early Notification of Community Based Epidemics (ESSENCE) using ICD-10-CM codes to identify cases of drug-related overdose [T36-T51] from October 2016 to September 2017. The Case definition included unintentional, self-harm, assault and undetermined poisonings, but did not include cases coded as adverse effects or underdosing of medication. Cases identified in the query were stratified by demographic factors (i.e., gender and age) and substance used in poisoning. The first diagnosis code in the file was considered the primary diagnosis. Chief complaint and triage note fields were examined to further describe unspecified cases and to describe how patients present to emergency departments in the CO-NCR. We also explored whether detection of drug overdose visits captured by discharge diagnosis data varied by patient sex, age, or county.Results: The query identified 2,366 drug-related overdoses in the CO-NCR. The prevalence of drug overdoses differed across age groups. The detection of drug overdoses was highest among our youth and young adult populations; 16 to 20 year olds (16.0%), 21-25 year olds (11.4%), 26-30 year olds (11.4%). Females comprised 56.1% of probable general drug overdoses. The majority of primary diagnoses (31.0%) included poisonings related to diuretics and other unspecified drugs (T50), narcotics (T40) (12.6%), or non-opioid analgesics (T39) (7.8%). For some cases with unspecified drug overdose codes there was additional information about drugs used and narcan administration found in the triage notes and chief complaint fields.Conclusions: Syndromic surveillance offers the opportunity to capture drug-related overdose data in near-real time. We found variation in drug-related overdose by demographic groups. Unspecified drug overdose codes are extremely common, which likely negatively impacts the quality of drug-specific surveillance. Leveraging chief complaint and triage notes could improve our understanding of factors involved in drug-related overdose with limitations in discharge diagnosis. Chart reviews and access to more fields from the ED electronic health record could improve local drug surveillance.

Gas emissions and crustal deformation from the Krýsuvík high temperature geothermal system, Iceland

The Krýsuvík volcanic system is located on the oblique spreading Reykjanes Peninsula, SW Iceland. Since early 2009 the region has been undergoing episodes of localized ground uplift and subsidence. From April–November 2013, we operated near-real time monitoring of gas emissions in Krýsuvík, using a Multi-component Gas Analyzer System (Multi-GAS), collecting data on gas composition from a fumarole (H2O, CO2, SO2, H2S). The dataset in this study, comprises a near-continuous gas composition time series, the quantification of diffuse CO2 gas flux, analytical results for direct samples of dry gas, seismic records, and GPS data. Gas emissions from the Krýsuvík geothermal system were examined and compared with crustal deformation and seismicity.The gas emissions from the Krýsuvík system are H2O-dominated, with CO2 as the most abundant dry gas species, followed by smaller concentrations of H2S. The average subsurface equilibrium temperature was calculated as 278 °C. This is consistent with previous observations made through sporadic spot sampling campaigns. In addition, the semi-continuous Multi-GAS dataset reveals higher variations in gas composition than previously reported by spot sampling.The diffuse soil CO2 flux is found to be variable between the three studied degassing areas in Krýsuvík, ranging from 10.9–70.9 T/day, with the highest flux in Hveradalir where the Multi-GAS station is located. The total flux is estimated as 101 T/day.Comparison between Multi-GAS and geophysical data shows that peaks of H2O-rich emissions appears to follow crustal movements. Coinciding with the H2O-rich peaks, SO2 is detected in minor amounts (~0.6 ppmv), allowing for calculations of H2O/SO2, CO2/SO2 and H2S/SO2 ratios. This is the first time SO2 has been detected in the Krýsuvík area.The large variations in H2O/CO2 and H2O/H2S ratios are considered to reflect variable degassing activity in the fumarole. The activity of the fumarole appears less intense during intervals of low or no recorded seismic events. The H2O/CO2 and H2O/H2S ratios are lower, presumably due to H2O condensation affecting the steam jet before reaching the Multi-GAS inlet tube.

Optimized anion exchange column isolation of zirconium-89 (89Zr) from yttrium cyclotron target: Method development and implementation on an automated fluidic platform

Zirconium-89 (89Zr), produced by the (p, n) reaction from naturally monoisotopic yttrium (natY), is a promising positron emitting isotope for immunoPET imaging. Its long half-life of 78.4 h is sufficient for evaluating slow physiological processes. A prototype automated fluidic system, coupled to on-line and in-line detectors, has been constructed to facilitate development of new 89Zr purification methodologies. The highly reproducible reagent delivery platform and near-real time monitoring of column effluents allows for efficient method optimization. The separation of Zr from dissolved Y metal targets was evaluated using several anion exchange resins. Each resin was evaluated against its ability to quantitatively capture Zr from a load solution high in dissolved Y. The most appropriate anion exchange resin for this application was identified, and the separation method was optimized. The method is capable of a high Y decontamination factor (>105) and has been shown to remove Fe, an abundant contaminant in Y foils, from the 89Zr elution fraction. Finally, the method was evaluated using cyclotron bombarded Y foil targets; the method was shown to achieve >95% recovery of the 89Zr present in the foils. The anion exchange column method described here is intended to be the first 89Zr isolation stage in a dual-column purification process.

Monitoring Hydro Temporal Variability in Alberta, Canada with Multi-Temporal Sentinel-1 SAR Data

ABSTRACTFreely available high temporal and spatial resolution synthetic aperture radar (SAR) satellite data such as Sentinel-1 have made it possible for almost near-real time monitoring of surface water extent. We present a method to track temporal variability in surface water extent, hereafter hydro temporal variability (HTV) in Alberta, Canada. Multi-temporal Sentinel-1-C band SAR data was used to classify each pixel in a pixel stack across time into water or non-water. This dataset can tell the percent of time a given 10 m × 10 m pixel was seen as open water. HTV was then summarized by calculating the percentage of the total pixel stack, which was detected as water. Comparison to the waterbodies in the Government of Alberta Base Features Hydrography Polygon dataset shows that the HTV dataset is able to differentiate between permanent and recurring lakes as well as capture rivers with a width of over 30 m. It is anticipated that the methodology presented here will be further enhanced and refined with imagery available for 2018 and beyond, due to now operational Sentinel-1B satellite and future RADARSAT Constellation Mission (2018), which will both provide improved data opportunities.

Intraoperative Auditory System Monitoring.

A new electrophysiological system for intraoperative, continuous, near-real time monitoring of cochlear nerve function through acoustic stimulation in the ear canal and recording of the evoked dorsal cochlear nucleus potentials (DNAPs) by a specially designed DNAP electrode placed directly on the brainstem is described. The system is denominated "(cerebellopontine angle) CPA Master" and is designed for hearing preservation surgery in the cerebello-pontine angle, through the retro-sigmoid or the retro-labyrinthine approach. As an additional novelty within the field, the system allows intraoperative mapping and thus precise localization of the cochlear nerve in its entire trajectory from the brainstem to the fundus of the internal auditory canal, which is a major advance in relation to atraumatic dissection of the nerve. The system can be used for surgery of all types of CPA tumors, for example, vestibular schwannomas, meningiomas and epidermoid cysts, but also for vestibular nerve section and vascular decompression. The system also allows evaluation of the electrical functionality of an anatomically intact cochlear nerve in translabyrinthine surgery, thus predicting the benefit of optional cochlear implantation.

Remote sensing of surface water quality in relation to catchment condition in Zimbabwe

The degradation of river catchments is one of the most important contemporary environmental problems affecting water quality in tropical countries. In this study, we used remotely sensed Normalised Difference Vegetation Index (NDVI) to assess how catchment condition varies within and across river catchments in Zimbabwe. We then used non-linear regression to test whether catchment condition assessed using the NDVI is significantly (α = 0.05) related with levels of Total Suspended Solids (TSS) measured at different sampling points in thirty-two sub-catchments in Zimbabwe. The results showed a consistent negative curvilinear relationship between Landsat 8 derived NDVI and TSS measured across the catchments under study. In the drier catchments of the country, 98% of the variation in TSS is explained by NDVI, while in wetter catchments, 64% of the variation in TSS is explained by NDVI. Our results suggest that NDVI derived from free and readily available multispectral Landsat series data (Landsat 8) is a potential valuable tool for the rapid assessment of physical water quality in data poor catchments. Overall, the finding of this study underscores the usefulness of readily available satellite data for near-real time monitoring of the physical water quality at river catchment scale, especially in resource-constrained areas, such as the sub-Saharan Africa.

Near-Real-Time Detection of Tephra Eruption Onset and Mass Flow Rate Using Microwave Weather Radar and Infrasonic Arrays

During an eruptive event, the near-real-time monitoring of volcanic explosion onset and its mass flow rate (MFR) is a key factor to predict ash plume dispersion and to mitigate risk to air traffic. Microwave (MW) weather radars have proved to be a fundamental instrument to derive eruptive source parameters. We extend this capability to include an early-warning detection scheme within the overall volcanic ash radar retrieval methodology. This scheme, called the volcanic ash detection (VAD) algorithm, is based on a hybrid technique using both fuzzy logic and conditional probability. Examples of VAD applications are shown for some case studies, including the Icelandic Grimsvotn eruption in 2011, the Eyjafjallajokull eruption in 2010, and the Italian Mt. Etna volcano eruption in 2013. Estimates of the eruption onset from the radar-based VAD module are compared with infrasonic array data. One-dimensional numerical simulations and analytical model estimates of MFR are also discussed and intercompared with sensor-based retrievals. Results confirm in all cases the potential of MW weather radar for ash plume monitoring in near real time and its complementarity with infrasonic array for early-warning system design.

Integrated Monitoring of Mola mola Behaviour in Space and Time.

Over the last decade, ocean sunfish movements have been monitored worldwide using various satellite tracking methods. This study reports the near-real time monitoring of fine-scale (< 10 m) behaviour of sunfish. The study was conducted in southern Portugal in May 2014 and involved satellite tags and underwater and surface robotic vehicles to measure both the movements and the contextual environment of the fish. A total of four individuals were tracked using custom-made GPS satellite tags providing geolocation estimates of fine-scale resolution. These accurate positions further informed sunfish areas of restricted search (ARS), which were directly correlated to steep thermal frontal zones. Simultaneously, and for two different occasions, an Autonomous Underwater Vehicle (AUV) video-recorded the path of the tracked fish and detected buoyant particles in the water column. Importantly, the densities of these particles were also directly correlated to steep thermal gradients. Thus, both sunfish foraging behaviour (ARS) and possibly prey densities, were found to be influenced by analogous environmental conditions. In addition, the dynamic structure of the water transited by the tracked individuals was described by a Lagrangian modelling approach. The model informed the distribution of zooplankton in the region, both horizontally and in the water column, and the resultant simulated densities positively correlated with sunfish ARS behaviour estimator (rs = 0.184, p<0.001). The model also revealed that tracked fish opportunistically displace with respect to subsurface current flow. Thus, we show how physical forcing and current structure provide a rationale for a predator’s fine-scale behaviour observed over a two weeks in May 2014.

Application of innovative technologies in landslide research in the area of the City of Zagreb (Croatia, Europe)

This paper describes the application of innovative technologies for landslide detection, mapping and monitoring in the City of Zagreb since 2010. Airborne Light Detection and Ranging (LiDAR) data are used to visually identify landslides in the Podsljeme Zone over the area of 180 km2 for the purpose of landslide inventory mapping. The total number of landslides in the analyzed area (approx. 1,600 landslides) is estimated based on the average landslide density (9 landslides per square km) from the most reliable geomorphological historical inventory, which was produced in 1979. Examples of the visual interpretation of very-high-resolution bare-earth DEMs (Digital Elevation Model) are given to show the potential of these innovative techniques to identify the landslide contours of the very small, small and moderately small landslides that are characteristic of the study area, which is composed of engineering soils and/or soft rocks (marls). In the framework of the described landslide research, the biggest landslide in the Podsljeme Zone, the Kostanjek landslide (landslide area of 1 km2), was also equipped with an automated near-real time monitoring system that encompassed approximately 40 sensors to monitor landslide movement and landslide causal factors. Monitoring of this deep and large landslide during multiple extreme hydro-meteorological events from January 2013 to January 2015 enabled collection of data for the analysis of landslide movement on the surface and in the underground and as well as analysis of the relationship between landslide reactivations and its triggers, i.e., changes in groundwater level and precipitation. The final aim of the described scientific research in terms of landslide mapping and monitoring is its practical application in land-use planning and civil protection systems in the City of Zagreb. Namely, the conclusions propose reliable and efficient methods for landslide identification and monitoring, which are necessary to provide data and solutions for hazard and risk reduction to local authorities that are managed by the City.

A Simple Security Architecture for Smart Water Management System

Water scarcity and water stress issues have become clear threat to the global population. This makes water management a critical aspect to ensure sustainable water. An efficient water management system requires thousands of constraint devices (sensors and/or actuators) to be deployed across the water distribution network to enable near-real time monitoring and control of the water grid components. Security at both the device and network level is critical to the operation of such a system. Although several IT security controls have developed over the past few decades, they cannot be used directly with such constraint devices. This is due to their limited resources and unique requirements. However, some of these techniques can be adapted and used with these constraint devices. In this paper, we propose security architecture for smart water management systems, the architecture leverages existing security solutions and design patterns

Fifteen years of thermal activity at Vanuatu's volcanoes (2000–2015) revealed by MIROVA

The Vanuatu archipelago consists of 80 islands and hosts 5 subaerial volcanoes (Yasur, Lopevi, Ambrym, Aoba and Gaua) that have shown sign of activity during the past decade. In this contribution we provide a 15years-long datasets (2000–2015) of the thermal activity recorded at these active volcanoes by means of MIROVA (Middle InfraRed Observation of Volcanic Activity) a new volcanic hotspot detection system based on MODIS data. The analyzed volcanoes are characterized by a spectrum of volcanic activities whose thermal signature has been tracked and carefully analyzed. These include strombolian–vulcanian explosions at Yasur, lava flows at Lopevi, lava lakes at Ambrym, surtseyan-type eruptions within the Voui crater lake of Aoba and ash-dominated eruptions with strong degassing at Gaua. The collected data reveal several details of the long term eruptive dynamics at single sites such as a monthly long pulse in thermal emissions at Yasur volcano as well as at the two active craters of Ambrym (Benbow and Marum). Heating cycles within Aoba crater lake and intermittent pressurized eruptions at Lopevi volcano has also been detected and shed light in the eruptive dynamics of the analyzed volcanoes. In addition we were able to track a two years long intensification of thermal output at Benbow crater (Ambrym) that preceded the occurrence of the first intra-caldera eruptions of this volcano since 1989. We emphasize how the data provided by MIROVA represent a new, safe and affordable method for monitoring in near-real time a large spectrum of volcanic activities taking place at Vanuatu and other volcanic areas.

Potential usage of met mast datasets for climatic parameters monitoring in Tulcea County, Romania

In order to evaluate the potential usage of high-accuracy climatic data measured continuously in the frame of newly developed renewable energy facilities in Romania for real-time local scale monitoring of climatic parameters, we used 2 years (May 2009 – May 2011) of in-situ climatic datasets measured at 7 met masts locations in Tulcea County. Realization of detailed thematic climatic maps afforded a more focused view of the spatial distribution and of the local patterns for air temperature, relative humidity and pressure, wind speed, direction and energy in the frame of the study site. On the basis of these preliminary results, we emphasize the great potential of similar in-situ real-time measured data to be integrated in the future, together with the data provided by meteorological stations, into complex databases. Their usefulness emerges from their capabilities of being integrated in specialized web-GIS platforms for real-time or nearreal-time monitoring of small spatial scale climatic parameters and of contributing to climatic models calibration, weather forecasting, feeding early warning systems for local climatic hazards or to rapid small spatial scale assessment of air pollutants dispersal following different scenarios of wind speed and direction. Further research and initiatives are necessary in the near future for the creation and implementation of these databases in order to become operational.

Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service

Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008–2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time data processing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed.

Improved rainfall estimation over the Indian monsoon region by synergistic use of Kalpana-1 and rain gauge data

In this paper, an attempt has been made to estimate rainfall over the Indian monsoon region by the synergistic use of the geostationary Kalpana-1 satellite-derived INSAT Multispectral Rainfall Algorithm (IMSRA) rainfall estimates and rain gauge data, using a successive correction method in order to further refine the operational IMSRA rainfall estimates. The successive correction method benefits from high spatial and temporal resolutions of the Kalpana-1 satellite and accurate rainfall estimates from rain gauges. A preliminary analysis is done for the southwest monsoon season of 2010 at a daily scale. The successive correction method is applied at a 1° latitude×1° longitude resolution determined by the spatial autocorrelation analysis. Results are compared with four independent global multisatellite rainfall products, namely the Global Satellite Mapping of Precipitation, the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis near-real time and research version rainfall monitoring products, and the Global Precipitation Climatology Project rainfall product. The objectively analyzed rainfall estimates show noticeable improvement over the satellite-based rainfall estimates alone over southern India. Comparison with independent rain gauge observations shows a considerable improvement in terms of correlation, bias and root-mean-square error after objective analysis, especially over the regions where density of rain gauge is fairly good. Overall results reveal that the synergistic use of satellite and in situ observations has potential for more accurate rainfall estimations over the Indian monsoon region.

Monitoring the Impacts of Wildfires on Forest Ecosystems and Public Health in the Exo-Urban Environment Using High-Resolution Satellite Aerosol Products from the Visible Infrared Imaging Radiometer Suite (VIIRS).

Increasing development of exo-urban environments and the spread of urbanization into forested areas is making humans and forest ecosystems more susceptible to the risks associated with wildfires. Larger and more damaging wildfires are having a negative impact on forest ecosystem services, and smoke from wildfires adversely affects the public health of people living in exo-urban environments. Satellite aerosol measurements are valuable tools that can track the evolution of wildfires and monitor the transport of smoke plumes. Operational users, such as air quality forecasters and fire management officials, can use satellite observations to complement ground-based and aircraft measurements of wildfire activity. To date, wildfire applications of satellite aerosol products, such as aerosol optical depth (AOD), have been limited by the relatively coarse resolution of available AOD data. However, the new Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on the Suomi National Polar-orbiting Partnership (S-NPP) satellite has high-resolution AOD that is ideally suited to monitoring wildfire impacts on the exo-urban scale. Two AOD products are available from VIIRS: the 750-m × 750-m nadir resolution Intermediate Product (IP) and the 6-km × 6-km resolution Environmental Data Record product, which is aggregated from IP measurements. True color (red, green, and blue [RGB]) imagery and a smoke mask at 750-m × 750-m resolution are also available from VIIRS as decision aids for wildfire applications; they serve as counterparts to AOD measurements by providing visible information about areas of smoke in the atmosphere. To meet the needs of operational users, who do not have time to process raw data files and need access to VIIRS products in near-real time (NRT), VIIRS AOD and RGB NRT imagery are available from the Infusing satellite Data into Environmental Applications (IDEA) web site. A key feature of IDEA is an interactive visualization tool that allows users to display tailored combinations of AOD and RGB imagery, as well as overlay the VIIRS smoke mask and fire hotspots at pixel resolution (~750-m × 750-m), and zoom into the county level. Two case studies of recent wildfires in the Western US are presented to show how operational users can access and display VIIRS aerosol products to monitor the transport of smoke plumes and evolution of fires in the exo-urban environment on the regional and county scales. The new National Oceanic and Atmospheric Administration (NOAA) Western Region Fire and Smoke Initiative is also discussed, which will enhance IDEA to allow visualization of VIIRS aerosol products down to the neighborhood scale. The new high-resolution VIIRS aerosol products can be used for NRT monitoring of human exposure to smoke, and they can be used to gauge the spread of fires and, thus, provide advanced warning for evacuations and fire suppression efforts, thereby reducing risks to human populations and forest ecosystems in the exo-urban environment.

Airborne near-real-time monitoring of assembly and parking areas in case of large-scale public events and natural disasters

A critical requirement for an effective and coordinated response by public entities tasked with management, security, and relief during large-scale public events or natural disasters is the availability of current situational information. However, today there is a lack of comprehensive operational systems allowing a near-real-time (NRT) collection, visualization, and provision of situational information for larger areas. In this study a methodological framework is proposed, which allows an NRT extraction and visualization of situational information based on aerial image acquisition. The framework combines digital image analysis using a generic supervised information extraction approach based on statistical modeling with a downstream web-based visualization component realized through an automatic update of web services. Even though being applicable for different scenarios, the workflow will be demonstrated for the specific use-case of a NRT monitoring of open spaces including assembly and parking areas. Compared to other approaches, image analysis results indicate a high robustness and a low demand for computational power sources (7 seconds per image). Due to a high degree of automation, the proposed workflow contributes to a NRT ‘end-to-end’ monitoring system, which was developed within the VABENE (German acronym for ‘traffic management under large-scale public events and disaster conditions’) project covering all parts from the acquisition of raw aerial imagery to the dissemination of information products to end-users.