Detection and characterization of small hot fires: Comparing FireBird, BIRD, S-NPP VIIRS and MODIS capacities over gas flares

NASA Astrophysics Data System (ADS)

Ruecker, Gernot; Schroeder, Wilfrid; Lorenz, Eckehard; Kaiser, Johannes; Caseiro, Alexandre

2016-04-01

According to recent research, black carbon has the second strongest effect on the earth climate system after carbon dioxide. In high Northern latitudes, industrial gas flares are an important source of black carbon, especially in winter. This fact is particularly relevant for the relatively fast observed climate change in the Arctic since deposition of black carbon changes the albedo of snow and ice, thus leading to a positive feedback cycle. Here we explore gas flare detection and Fire Radiative Power (FRP) retrievals of the German FireBird TET-1 and BIRD Hotspot Recognition Systems (HSRS), the VIIRS sensor on board of the S-NPP satellite, and the MODIS sensor using temporally close to near coincident data acquisitions. Comparison is based on level 2 products developed for fire detection for the different sensors; in the case of S-NPP VIIRS we use two products: the new VIIRS 750m algorithm based on MODIS collection 6, and the 350 m algorithm based on the VIIRS mid-infrared I (Imaging) band, which offers high resolution, but no FRP retrievals. Results indicate that the highest resolution FireBird sensors offer the best detection capacities, though the level two product shows false alarms, followed by the VIIRS 350 m and 750 m algorithms. MODIS has the lowest detection rate. Preliminary results of FRP retrievals show that FireBird and VIIRS algorithms have a good agreement. Given the fact that most gas flaring is at the detection limit for medium to coarse resolution space borne sensors - and hence measurement errors may be high - our results indicates that a quantitative evaluation of gas flaring using these sensors is feasible. Results shall be used to develop a gas flare detection algorithm for Sentinel-3, and a similar methodology will be employed to validate the capacity of Sentinel 3 to detect and characterize small high temperature sources such as gas flares.

Improvement of Forest Fire Detection Algorithm Using Brightness Temperature Lapse Rate Correction in HIMAWARI-8 IR Channels: Application to the 6 may 2017 Samcheok City, Korea

NASA Astrophysics Data System (ADS)

Park, S. H.; Park, W.; Jung, H. S.

2018-04-01

Forest fires are a major natural disaster that destroys a forest area and a natural environment. In order to minimize the damage caused by the forest fire, it is necessary to know the location and the time of day and continuous monitoring is required until fire is fully put out. We have tried to improve the forest fire detection algorithm by using a method to reduce the variability of surrounding pixels. We focused that forest areas of East Asia, part of the Himawari-8 AHI coverage, are mostly located in mountainous areas. The proposed method was applied to the forest fire detection in Samcheok city, Korea on May 6 to 10, 2017.

Comparing different approaches for an effective monitoring of forest fires based on MSG/SEVIRI images

NASA Astrophysics Data System (ADS)

Laneve, Giovanni

2010-05-01

The remote sensing sensors on board of geostationary satellite, as consequence of the high frequency of the observations, allow, in principle, the monitoring of these phenomena characterized by a fast dynamics. The only condition for is that the events to be monitored should be enough strong to be recognizable notwithstanding the low spatial resolution of the present geostationary systems (MSG/SEVIRI, GOES Imager, MTSAT). Apart from meteorological phenomena other events, like those associated with forest fires and/or volcanic eruption, are characterized by a very fast dynamics. These events are also associated with a very strong signal that make them observable by geostationary satellite in a quasi-continuous way. However, in order to make possible the detection of small fires by using the low resolution multi-spectral imagery provided by geostationary sensor like SEVIRI (3x3 km2 at the equator) new algorithms, capable to exploit it high observation frequency, has been developed. This paper is devoted to show the results obtained by comparing some of these algorithms trying to highlight their advantages and limits. The algorithms herein considered are these developed by CRPSM (SFIDE®), UNIBAS/CNR (RST-FIRES) and ESA-ESRIN (MDIFRM). In general, the new approaches proposed by each one of them are capable to promptly detect small fires making possible an operational utilization of the satellite based fire detection system in the fire fighting phases. In fact, these algorithms are quite different from these introduced in the past and specifically devoted to fire detection using low resolution multi-spectral imagery on LEO (Low Earth Orbit) satellite. Thanks to these differences they are capable of detecting sub-hectare (0.2 ha) forest fires providing an useful instrument for monitoring quasi-continuously forest fires, estimating the FRP (Fire Radiative Power), evaluating the burned biomass, retrieving the emission in the atmosphere.

Algorithm and assessment work of active fire detection based on FengYun-3C/VIRR

NASA Astrophysics Data System (ADS)

Lin, Z.; Chen, F.

2017-12-01

The wildfire is one of the most destructive and uncontrollable disasters and causes huge environmental, ecological, social effects. To better serve scientific research and practical fire management, an algorithm and corresponding validation work of active fire detection based on FengYun-3C/VIRR data, which is an optical sensor onboard the Chinese polar-orbiting meteorological sun-synchronous satellite, is hereby introduced. While the main structure heritages the `contextual algorithm', some new concepts including `infrared channel slope' are introduced for better adaptions to different situations. The validation work contains three parts: 1) comparing with the current FengYun-3C fire product GFR; 2) comparing with MODIS fire products; 3) comparing with Landsat series data. Study areas are selected from different places all over the world from 2014 to 2016. The results showed great improvement on GFR files on accuracy of both positioning and detection rate. In most study areas, the results match well with MODIS products and Landsat series data (with over 85% match degree) despite the differences in imaging time. However, detection rates and match degrees in Africa and South-east Asia are not satisfied (around 70%), where the occurrences of numerous small fire events and corresponding smokes may strongly affect the results of the algorithm. This is our future research direction and one of the main improvements requires achieving.

Recent Developments for Satellite-Based Fire Monitoring in Canada

NASA Astrophysics Data System (ADS)

Abuelgasim, A.; Fraser, R.

2002-05-01

Wildfires in Canadian forests are a major source of natural disturbance. These fires have a tremendous impact on the local environment, humans and wildlife, ecosystem function, weather, and climate. Approximately 9000 fires burn 3 million hectares per year in Canada (based on a 10-year average). While only 2 to 3 percent of these wildfires grow larger than 200 hectares in size, they account for almost 97 percent of the annual area burned. This provides an excellent opportunity to monitor active fires using a combination of low and high resolution sensors for the purpose of determining fire location and burned areas. Given the size of Canada, the use of remote sensing data is a cost-effective way to achieve a synoptic overview of large forest fire activity in near-real time. In 1998 the Canada Centre for Remote Sensing (CCRS) and the Canadian Forest Service (CFS) developed a system for Fire Monitoring, Mapping and Modelling (Fire M3;http://fms.nofc.cfs.nrcan.gc.ca/FireM3/). Fire M3 automatically identifies, monitors, and maps large forest fires on a daily basis using NOAA AVHRR data. These data are processed daily using the GEOCOMP-N satellite image processing system. This presentation will describe recent developments to Fire M3, included the addition of a set of algorithms tailored for NOAA-16 (N-16) data. The two fire detection algorithms are developed for N-16 day and night-time daily data collection. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. The set of N-16 day and night algorithms was used to generate daily active fire maps across North America for the 2001 fire season. Such a combined approach for fire detection leads to an improved detection rate, although day-time detection based on the new 1.6 um channel was much less effective (note - given the low detection rate with day time imagery, I don't think we can make the statement about capturing the diurnal cycle). Selected validation sites in western Canada and the United States showed reasonable correspondence with the location of fires mapped by CFS and those mapped by the USDA Forest Service using conventional means.

Development of Fire Detection Algorithm at Its Early Stage Using Fire Colour and Shape Information

NASA Astrophysics Data System (ADS)

Suleiman Abdullahi, Zainab; Hamisu Dalhatu, Shehu; Hassan Abdullahi, Zakariyya

2018-04-01

Fire can be defined as a state in which substances combined chemically with oxygen from the air and give out heat, smoke and flame. Most of the conventional fire detection techniques such as smoke, fire and heat detectors respectively have a problem of travelling delay and also give a high false alarm. The algorithm begins by loading the selected video clip from the database developed to identify the present or absence of fire in a frame. In this approach, background subtraction was employed. If the result of subtraction is less than the set threshold, the difference is ignored and the next frame is taken. However, if the difference is equal to or greater than the set threshold then it subjected to colour and shape test. This is done by using combined RGB colour model and shape signature. The proposed technique was very effective in detecting fire compared to those technique using only motion or colour clues.

Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review.

PubMed

Fonollosa, Jordi; Solórzano, Ana; Marco, Santiago

2018-02-11

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative.

Chemical Sensor Systems and Associated Algorithms for Fire Detection: A Review

PubMed Central

Fonollosa, Jordi

2018-01-01

Indoor fire detection using gas chemical sensing has been a subject of investigation since the early nineties. This approach leverages the fact that, for certain types of fire, chemical volatiles appear before smoke particles do. Hence, systems based on chemical sensing can provide faster fire alarm responses than conventional smoke-based fire detectors. Moreover, since it is known that most casualties in fires are produced from toxic emissions rather than actual burns, gas-based fire detection could provide an additional level of safety to building occupants. In this line, since the 2000s, electrochemical cells for carbon monoxide sensing have been incorporated into fire detectors. Even systems relying exclusively on gas sensors have been explored as fire detectors. However, gas sensors respond to a large variety of volatiles beyond combustion products. As a result, chemical-based fire detectors require multivariate data processing techniques to ensure high sensitivity to fires and false alarm immunity. In this paper, we the survey toxic emissions produced in fires and defined standards for fire detection systems. We also review the state of the art of chemical sensor systems for fire detection and the associated signal and data processing algorithms. We also examine the experimental protocols used for the validation of the different approaches, as the complexity of the test measurements also impacts on reported sensitivity and specificity measures. All in all, further research and extensive test under different fire and nuisance scenarios are still required before gas-based fire detectors penetrate largely into the market. Nevertheless, the use of dynamic features and multivariate models that exploit sensor correlations seems imperative. PMID:29439490

Using NPP-Suomi VIIRS I-band data to delineate high- and low-intensity burn areas for forest fires in interior Alaska

NASA Astrophysics Data System (ADS)

Waigl, C. F.; Prakash, A.; Stuefer, M.; Ichoku, C. M.

2016-12-01

The aim of this work is to present and evaluate an algorithm that generates near real-time fire detections suitable for use by fire and related hazard management agencies in Alaska. Our scheme offers benefits over available global products and is sensitive to low-intensity residual burns while at the same time avoiding common sources of false detections as they are observed in the Alaskan boreal forest, such as refective river banks and old fire scars. The algorithm is based on I-band brightness temperature data form the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NOAA's NPP Suomi spacecraft. Using datasets covering the entire 2015 Alaska fire season, we first evaluate the performance of two global fire products: MOD14/MYD14, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the more recent global VIIRS I-band product. A comparison with the fire perimeter and properties data published by the Alaska Interagency Coordination Center (AICC) shows that both MODIS and VIIRS fire products successfully detect all fires larger than approx. 1000 hectares, with the VIIRS I-band product only moderately outperforming MOD14/MYD14. For smaller fires, the VIIRS I-band product offers higher detection likelihood, but still misses one fifth of the fire events overall. Furthermore, some daytime detections are missing, possibly due to processing difficulties or incomplete data transfer. Second, as an alternative, we present a simple algorithm that uses the normalized difference between the 3.74µm and 11.45 µm VIIRS-I band at-sensor brightness temperatures to map both low- and high-intensity burn areas. Such an approach has the advantage that it makes use of data that is available via the direct readout station operated by Geographic Information Network of Alaska (GINA). We apply this scheme to known Alaskan boreal forest fires and validate it using GIS data produced by fire management agencies, fire detections from near simultanous Landsat imagery, and sub-pixel analysis. We find that our VIIRS derived fire product more accurately captures the fire spread, can differentiate well between low- and high-intensity burn areas, and has fewer errors of omission compared to the MODIS and VIIRS global fire products.

Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery

NASA Astrophysics Data System (ADS)

Hardtke, Leonardo A.; Blanco, Paula D.; Valle, Héctor F. del; Metternicht, Graciela I.; Sione, Walter F.

2015-06-01

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Remote sensing has become the most widely used tool to detect fire affected areas over large tracts of land (e.g., ecosystem, regional and global levels). Standard satellite burned area and active fire products derived from the 500-m Moderate Resolution Imaging Spectroradiometer (MODIS) and the Satellite Pour l'Observation de la Terre (SPOT) are available to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applications. Consequently, we propose a novel semi-automated algorithm for identification and mapping of burned areas at regional scale. The semi-arid Monte shrublands, a biome covering 240,000 km2 in the western part of Argentina, and exposed to seasonal bushfires was selected as the test area. The algorithm uses a set of the normalized burned ratio index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. Additionally, the performance of the adaptive algorithm was assessed against standard global fire products derived from MODIS Aqua and Terra satellites, total burned area (MCD45A1), the active fire algorithm (MOD14); and the L3JRC SPOT VEGETATION 1 km GLOBCARBON products. The correlation between the size of burned areas detected by the global fire products and independently-derived Landsat reference data ranged from R2 = 0.01-0.28, while our algorithm performed showed a stronger correlation coefficient (R2 = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.

A Novel Arc Fault Detector for Early Detection of Electrical Fires

PubMed Central

Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

2016-01-01

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. PMID:27070618

Suomi NPP VIIRS active fire product status

NASA Astrophysics Data System (ADS)

Ellicott, E. A.; Csiszar, I. A.; Schroeder, W.; Giglio, L.; Wind, B.; Justice, C. O.

2012-12-01

We provide an overview of the evaluation and development of the Active Fires product derived from the Visible Infrared Imager Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (SNPP) satellite during the first year of on-orbit data. Results from the initial evaluation of the standard SNPP Active Fires product, generated by the SNPP Interface Data Processing System (IDPS), supported the stabilization of the VIIRS Sensor Data Record (SDR) product. This activity focused in particular on the processing of the dual-gain 4 micron VIIRS M13 radiometric measurements into 750m aggregated data, which are fundamental for active fire detection. Following the VIIRS SDR product's Beta maturity status in April 2012, correlative analysis between VIIRS and near-simultaneous fire detections from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Aqua satellite confirmed the expected relative detection rates driven primarily by sensor differences. The VIIRS Active Fires Product Development and Validation Team also developed a science code that is based on the latest MODIS Collection 6 algorithm and provides a full spatially explicit fire mask to replace the sparse array output of fire locations from a MODIS Collection 4 equivalent algorithm in the current IDPS product. The Algorithm Development Library (ADL) was used to support the planning for the transition of the science code into IDPS operations in the future. Product evaluation and user outreach was facilitated by a product website that provided end user access to fire data in user-friendly format over North America as well as examples of VIIRS-MODIS comparisons. The VIIRS fire team also developed an experimental product based on 375m VIIRS Imagery band measurements and provided high quality imagery of major fire events in US. By August 2012 the IDPS product achieved Beta maturity, with some known and documented shortfalls related to the processing of incorrect SDR input data and to apparent algorithm deficiencies in select observing and environmental conditions.

An algorithm to detect fire activity using Meteosat: fine tuning and quality assesment

NASA Astrophysics Data System (ADS)

Amraoui, M.; DaCamara, C. C.; Ermida, S. L.

2012-04-01

Hot spot detection by means of sensors on-board geostationary satellites allows studying wildfire activity at hourly and even sub-hourly intervals, an advantage that cannot be met by polar orbiters. Since 1997, the Satellite Application Facility for Land Surface Analysis has been running an operational procedure that allows detecting active fires based on information from Meteosat-8/SEVIRI. This is the so-called Fire Detection and Monitoring (FD&M) product and the procedure takes advantage of the temporal resolution of SEVIRI (one image every 15 min), and relies on information from SEVIRI channels (namely 0.6, 0.8, 3.9, 10.8 and 12.0 μm) together with information on illumination angles. The method is based on heritage from contextual algorithms designed for polar, sun-synchronous instruments, namely NOAA/AVHRR and MODIS/TERRAAQUA. A potential fire pixel is compared with the neighboring ones and the decision is made based on relative thresholds as derived from the pixels in the neighborhood. Generally speaking, the observed fire incidence compares well against hot spots extracted from the global daily active fire product developed by the MODIS Fire Team. However, values of probability of detection (POD) tend to be quite low, a result that may be partially expected by the finer resolution of MODIS. The aim of the present study is to make a systematic assessment of the impacts on POD and False Alarm Ratio (FAR) of the several parameters that are set in the algorithms. Such parameters range from the threshold values of brightness temperature in the IR3.9 and 10.8 channels that are used to select potential fire pixels up to the extent of the background grid and thresholds used to statistically characterize the radiometric departures of a potential pixel from the respective background. The impact of different criteria to identify pixels contaminated by clouds, smoke and sun glint is also evaluated. Finally, the advantages that may be brought to the algorithm by adding contextual tests in the time domain are discussed. The study lays the grounds to the development of improved quality flags that will be integrated in the FD&M product in the nearby future.

Three-dimensional tracking for efficient fire fighting in complex situations

NASA Astrophysics Data System (ADS)

Akhloufi, Moulay; Rossi, Lucile

2009-05-01

Each year, hundred millions hectares of forests burn causing human and economic losses. For efficient fire fighting, the personnel in the ground need tools permitting the prediction of fire front propagation. In this work, we present a new technique for automatically tracking fire spread in three-dimensional space. The proposed approach uses a stereo system to extract a 3D shape from fire images. A new segmentation technique is proposed and permits the extraction of fire regions in complex unstructured scenes. It works in the visible spectrum and combines information extracted from YUV and RGB color spaces. Unlike other techniques, our algorithm does not require previous knowledge about the scene. The resulting fire regions are classified into different homogenous zones using clustering techniques. Contours are then extracted and a feature detection algorithm is used to detect interest points like local maxima and corners. Extracted points from stereo images are then used to compute the 3D shape of the fire front. The resulting data permits to build the fire volume. The final model is used to compute important spatial and temporal fire characteristics like: spread dynamics, local orientation, heading direction, etc. Tests conducted on the ground show the efficiency of the proposed scheme. This scheme is being integrated with a fire spread mathematical model in order to predict and anticipate the fire behaviour during fire fighting. Also of interest to fire-fighters, is the proposed automatic segmentation technique that can be used in early detection of fire in complex scenes.

Automated mapping of burned areas in semi-arid ecosystems using modis time-series imagery

NASA Astrophysics Data System (ADS)

Hardtke, L. A.; Blanco, P. D.; del Valle, H. F.; Metternicht, G. I.; Sione, W. F.

2015-04-01

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Standard satellite burned area and active fire products derived from the 500-m MODIS and SPOT are avail - able to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applica - tions. Consequently, we propose a novel algorithm for automated identification and mapping of burned areas at regional scale in semi-arid shrublands. The algorithm uses a set of the Normalized Burned Ratio Index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. The correlation between the size of burnt areas detected by the global fire products and independently-derived Landsat reference data ranged from R2 = 0.01 - 0.28, while our algorithm performed showed a stronger correlation coefficient (R2 = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.

Non-supervised method for early forest fire detection and rapid mapping

NASA Astrophysics Data System (ADS)

Artés, Tomás; Boca, Roberto; Liberta, Giorgio; San-Miguel, Jesús

2017-09-01

Natural hazards are a challenge for the society. Scientific community efforts have been severely increased assessing tasks about prevention and damage mitigation. The most important points to minimize natural hazard damages are monitoring and prevention. This work focuses particularly on forest fires. This phenomenon depends on small-scale factors and fire behavior is strongly related to the local weather. Forest fire spread forecast is a complex task because of the scale of the phenomena, the input data uncertainty and time constraints in forest fire monitoring. Forest fire simulators have been improved, including some calibration techniques avoiding data uncertainty and taking into account complex factors as the atmosphere. Such techniques increase dramatically the computational cost in a context where the available time to provide a forecast is a hard constraint. Furthermore, an early mapping of the fire becomes crucial to assess it. In this work, a non-supervised method for forest fire early detection and mapping is proposed. As main sources, the method uses daily thermal anomalies from MODIS and VIIRS combined with land cover map to identify and monitor forest fires with very few resources. This method relies on a clustering technique (DBSCAN algorithm) and on filtering thermal anomalies to detect the forest fires. In addition, a concave hull (alpha shape algorithm) is applied to obtain rapid mapping of the fire area (very coarse accuracy mapping). Therefore, the method leads to a potential use for high-resolution forest fire rapid mapping based on satellite imagery using the extent of each early fire detection. It shows the way to an automatic rapid mapping of the fire at high resolution processing as few data as possible.

Monitoring Fires from Space: a case study in transitioning from research to applications

NASA Astrophysics Data System (ADS)

Justice, C. O.; Giglio, L.; Vadrevu, K. P.; Csiszar, I. A.; Schroeder, W.; Davies, D.

2012-12-01

This paper discusses the heritage and relationships between science and applications in the context of global satellite-based fire monitoring. The development of algorithms for satellite-based fire detection has been supported primarily by NASA for the polar orbiters with a global focus, and initially by NOAA and more recently by EUMETSAT for the geostationary satellites, with a regional focus. As the feasibility and importance of space-based fire monitoring was recognized, satellite missions were designed to include fire detection capabilities. As a result, the algorithms and accuracy of the detections have improved. Due to the role of fire in the Earth System and its relevance to society, at each step in the development of the sensing capability the research has made a transition into fire-related applications to such an extent that there is now broad use of these data worldwide. The origin of the polar-orbiting satellite fire detection capability was with the AVHRR sensor beginning in the early 1980s, but was transformed with the launch of the EOS MODIS instruments, which included sensor characteristics specifically for fire detection. NASA gave considerable emphasis on the accuracy assessment of the fire detection and the development of fire characterization and burned area products from MODIS. Collaboration between the MODIS Fire Team and the RSAC USFS, initiated in the context of the Montana wildfires of 2001, prompted the development of a Rapid Response System for fire data and eventually led to operational use of MODIS data by the USFS for strategic fire monitoring. Building on this success, the Fire Information for Resource Management Systems (FIRMS) project was funded by NASA Applications to further develop products and services for the fire information community. The FIRMS was developed as a web-based geospatial tool, offering a range of geospatial data services, including SMS text messaging and is now widely used. This system, developed in the research domain, has now been successfully moved to an operational home at the UN FAO, as the Global Fire Information Management System (GFIMS). With a view to operational data continuity, the Suomi-NPP/JPSS VIIRS system was also designed with a fire detection capability, and is providing promising results for fire monitoring both from the standard operational production system and experimental product enhancements. International coordination on fire observations and outreach has been successfully developed under the GOFC GOLD program.

Near-Real-Time Detection and Monitoring of Intense Pyroconvection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Fromm, M. D.; Hyer, E. J.; Surratt, M. L.; Solbrig, J. E.; Campbell, J. R.

2016-12-01

Intense fire-triggered thunderstorms, known as pyrocumulonimbus (or pyroCb), can alter fire behavior, influence smoke plume trajectories, and hinder fire suppression efforts. PyroCb are also known for injecting a significant quantity of aerosol mass into the upper-troposphere and lower-stratosphere (UTLS). Near-real-time (NRT) detection and monitoring of pyroCb is highly desirable for a variety of forecasting and research applications. The Naval Research Laboratory (NRL) recently developed the first automated NRT pyroCb detection algorithm for geostationary satellite sensors. The algorithm uses multispectral infrared observations to isolate deep convective clouds with the distinct microphysical signal of pyroCb. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation of the current system is that pyroCb anvils can be small relative to satellite pixel size, especially in in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. This algorithm has been automated using the GeoIPS processing system developed at NRL, which produces a variety of imagery products and statistical output for rapid analysis of potential pyroCb events. NRT application of this algorithm has been extended to the majority of regions worldwide known to have a high frequency of pyroCb occurrence. This involves a constellation comprised of GOES-East, GOES-West, and Himawari-8. Imagery is posted immediately to an NRL-maintained web page. Alerts are generated by the system and disseminated via email. This detection system also has potential to serve as a data source for other NRT environmental monitoring systems. While the current geostationary constellation has several important limitations, the next-generation of geostationary sensors will offer significant advantages for achieving the goal of global NRT pyroCb detection.

The Hazard Mapping System (HMS)-a Multiplatform Remote Sensing Approach to Fire and Smoke Detection

NASA Astrophysics Data System (ADS)

Kibler, J.; Ruminski, M. G.

2003-12-01

The HMS is a multiplatform remote sensing approach to detecting fires and smoke over the US and adjacent areas of Canada and Mexico that has been in place since June 2002. This system is an integral part of the National Environmental Satellite and Data Information Service (NESDIS) near realtime hazard detection and mitigation efforts. The system utilizes NOAA's Geostationary Operational Environmental Satellites (GOES), Polar Operational Environmental Satellites (POES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Terra and Aqua spacecraft. Automated detection algorithms are employed for each of the satellites for the fire detects while smoke is added by a satellite image analyst. In June 2003 the HMS underwent an upgrade. A number of features were added for users of the products generated on the HMS. Sectors covering Alaska and Hawaii were added. The use of Geographic Information System (GIS) shape files for smoke analysis is a new feature. Shape files show the progression and time of a single smoke plume as each analysis is drawn and then updated. The analyst now has the ability to view GOES, POES, and MODIS data in a single loop. This allows the fire analyst the ability to easily confirm a fire in three different data sets. The upgraded HMS has faster satellite looping and gives the analyst the ability to design a false color image for a particular region. The GOES satellites provide a relatively coarse 4 km infrared resolution at satellite subpoint for thermal fire detection but provide the advantage of a rapid update cycle. GOES imagery is updated every 15 minutes utilizing both GOES-10 and GOES-12. POES imagery from NOAA-15, NOAA-16 and NOAA-17 and MODIS from Terra and Aqua are employed with each satellite providing twice per day coverage (more frequent over Alaska). While the frequency of imagery is much less than with GOES the higher resolution of these satellites (1 km along the suborbital track) allows for detection of smaller and/or cooler burning fires. Each of the algorithms utilizes a number of temporal, thermal and contextual filters in an attempt to screen out false detects. However, false detects do get processed by the algorithms to varying degrees. Therefore, the automated fire detects from each algorithm are quality controlled by an analyst who scans the imagery and may either accept or delete fire points. The analyst also has the ability to manually add additional fire points based on the imagery. Smoke is outlined by the analyst using visible imagery, primarily GOES which provides 1 km resolution. Occasionally a smoke plume seen in visible imagery is the only indicator of a fire and would be manually added to the fire detect file. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) is a forecast model that projects the trajectory and dispersion of a smoke plume over a period of time. The HYSPLIT is run for fires that are selected by the analyst that are seen to be producing a significant smoke plume. The analyst defines a smoke producing area commensurate with the size of the fire and amount of smoke detected. The output is hosted on an Air Resources Lab (ARL) web site which can be accessed from the web site listed below. All of the information is posted to the web page noted below. Besides the interactive GIS presentation users can view the product in graphical jpg format. The analyst edited points as well as the unedited automated fire detects are available for users to view directly on the web page or to download. All of the data is also archived and accessed via ftp.

Survey of Fire Detection Technologies and System Evaluation/Certification Methodologies and Their Suitability for Aircraft Cargo Compartments

NASA Technical Reports Server (NTRS)

Cleary, T.; Grosshandler, W.

1999-01-01

As part of the National Aeronautics and Space Administration (NASA) initiated program on global civil aviation, NIST is assisting Federal Aviation Administration in its research to improve fire detection in aircraft cargo compartments. Aircraft cargo compartment detection certification methods have been reviewed. The Fire Emulator-Detector Evaluator (FE/DE) has been designed to evaluate fire detection technologies such as new sensors, multi-element detectors, and detectors that employ complex algorithms. The FE/DE is a flow tunnel that can reproduce velocity, temperature, smoke, and Combustion gas levels to which a detector might be exposed during a fire. A scientific literature survey and patent search have been conducted relating to existing and emerging fire detection technologies, and the potential use of new fire detection strategies in cargo compartment areas has been assessed. In the near term, improved detector signal processing and multi-sensor detectors based on combinations of smoke measurements, combustion gases and temperature are envisioned as significantly impacting detector system performance.

Assessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module

NASA Technical Reports Server (NTRS)

Gay, Robert S.

2011-01-01

Orion Crew Module (CM) touchdown detection is critical to activating the post-landing sequence that safe?s the Reaction Control Jets (RCS), ensures that the vehicle remains upright, and establishes communication with recovery forces. In order to accommodate safe landing of an unmanned vehicle or incapacitated crew, an onboard automated detection system is required. An Orion-specific touchdown detection algorithm was developed and evaluated to differentiate landing events from in-flight events. The proposed method will be used to initiate post-landing cutting of the parachute riser lines, to prevent CM rollover, and to terminate RCS jet firing prior to submersion. The RCS jets continue to fire until touchdown to maintain proper CM orientation with respect to the flight path and to limit impact loads, but have potentially hazardous consequences if submerged while firing. The time available after impact to cut risers and initiate the CM Up-righting System (CMUS) is measured in minutes, whereas the time from touchdown to RCS jet submersion is a function of descent velocity, sea state conditions, and is often less than one second. Evaluation of the detection algorithms was performed for in-flight events (e.g. descent under chutes) using hi-fidelity rigid body analyses in the Decelerator Systems Simulation (DSS), whereas water impacts were simulated using a rigid finite element model of the Orion CM in LS-DYNA. Two touchdown detection algorithms were evaluated with various thresholds: Acceleration magnitude spike detection, and Accumulated velocity changed (over a given time window) spike detection. Data for both detection methods is acquired from an onboard Inertial Measurement Unit (IMU) sensor. The detection algorithms were tested with analytically generated in-flight and landing IMU data simulations. The acceleration spike detection proved to be faster while maintaining desired safety margin. Time to RCS jet submersion was predicted analytically across a series of simulated Orion landing conditions. This paper details the touchdown detection method chosen and the analysis used to support the decision.

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

From Data to Knowledge — Faster: GOES Early Fire Detection System to Inform Operational Wildfire Response and Management

NASA Astrophysics Data System (ADS)

Koltunov, A.; Quayle, B.; Prins, E. M.; Ambrosia, V. G.; Ustin, S.

2014-12-01

Fire managers at various levels require near-real-time, low-cost, systematic, and reliable early detection capabilities with minimal latency to effectively respond to wildfire ignitions and minimize the risk of catastrophic development. The GOES satellite images collected for vast territories at high temporal frequencies provide a consistent and reliable source for operational active fire mapping realized by the WF-ABBA algorithm. However, their potential to provide early warning or rapid confirmation of initial fire ignition reports from conventional sources remains underutilized, partly because the operational wildfire detection has been successfully optimized for users and applications for which timeliness of initial detection is a low priority, contrasting to the needs of first responders. We present our progress in developing the GOES Early Fire Detection (GOES-EFD) system, a collaborative effort led by University of California-Davis and USDA Forest Service. The GOES-EFD specifically focuses on first detection timeliness for wildfire incidents. It is automatically trained for a monitored scene and capitalizes on multiyear cross-disciplinary algorithm research. Initial retrospective tests in Western US demonstrate significantly earlier identification detection of new ignitions than existing operational capabilities and a further improvement prospect. The GOES-EFD-β prototype will be initially deployed for the Western US region to process imagery from GOES-NOP and the rapid and 4 times higher spatial resolution imagery from GOES-R — the upcoming next generation of GOES satellites. These and other enhanced capabilities of GOES-R are expected to significantly improve the timeliness of fire ignition information from GOES-EFD.

Color model and method for video fire flame and smoke detection using Fisher linear discriminant

NASA Astrophysics Data System (ADS)

Wei, Yuan; Jie, Li; Jun, Fang; Yongming, Zhang

2013-02-01

Video fire detection is playing an increasingly important role in our life. But recent research is often based on a traditional RGB color model used to analyze the flame, which may be not the optimal color space for fire recognition. It is worse when we research smoke simply using gray images instead of color ones. We clarify the importance of color information for fire detection. We present a fire discriminant color (FDC) model for flame or smoke recognition based on color images. The FDC models aim to unify fire color image representation and fire recognition task into one framework. With the definition of between-class scatter matrices and within-class scatter matrices of Fisher linear discriminant, the proposed models seek to obtain one color-space-transform matrix and a discriminate projection basis vector by maximizing the ratio of these two scatter matrices. First, an iterative basic algorithm is designed to get one-component color space transformed from RGB. Then, a general algorithm is extended to generate three-component color space for further improvement. Moreover, we propose a method for video fire detection based on the models using the kNN classifier. To evaluate the recognition performance, we create a database including flame, smoke, and nonfire images for training and testing. The test experiments show that the proposed model achieves a flame verification rate receiver operating characteristic (ROC I) of 97.5% at a false alarm rate (FAR) of 1.06% and a smoke verification rate (ROC II) of 91.5% at a FAR of 1.2%, and lots of fire video experiments demonstrate that our method reaches a high accuracy for fire recognition.

A bioinspired collision detection algorithm for VLSI implementation

NASA Astrophysics Data System (ADS)

Cuadri, J.; Linan, G.; Stafford, R.; Keil, M. S.; Roca, E.

2005-06-01

In this paper a bioinspired algorithm for collision detection is proposed, based on previous models of the locust (Locusta migratoria) visual system reported by F.C. Rind and her group, in the University of Newcastle-upon-Tyne. The algorithm is suitable for VLSI implementation in standard CMOS technologies as a system-on-chip for automotive applications. The working principle of the algorithm is to process a video stream that represents the current scenario, and to fire an alarm whenever an object approaches on a collision course. Moreover, it establishes a scale of warning states, from no danger to collision alarm, depending on the activity detected in the current scenario. In the worst case, the minimum time before collision at which the model fires the collision alarm is 40 msec (1 frame before, at 25 frames per second). Since the average time to successfully fire an airbag system is 2 msec, even in the worst case, this algorithm would be very helpful to more efficiently arm the airbag system, or even take some kind of collision avoidance countermeasures. Furthermore, two additional modules have been included: a "Topological Feature Estimator" and an "Attention Focusing Algorithm". The former takes into account the shape of the approaching object to decide whether it is a person, a road line or a car. This helps to take more adequate countermeasures and to filter false alarms. The latter centres the processing power into the most active zones of the input frame, thus saving memory and processing time resources.

Meteosat SEVIRI Fire Radiative Power (FRP) products from the Land Surface Analysis Satellite Applications Facility (LSA SAF) - Part 1: Algorithms, product contents and analysis

NASA Astrophysics Data System (ADS)

Wooster, M. J.; Roberts, G.; Freeborn, P. H.; Xu, W.; Govaerts, Y.; Beeby, R.; He, J.; Lattanzio, A.; Mullen, R.

2015-06-01

Characterising changes in landscape scale fire activity at very high temporal resolution is best achieved using thermal observations of actively burning fires made from geostationary Earth observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from these types of geostationary observations, often with the aim of supporting the generation of data related to biomass burning fuel consumption and trace gas and aerosol emission fields. The Fire Radiative Power (FRP) products generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from data collected by the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) are one such set of products, and are freely available in both near real-time and archived form. Every 15 min, the algorithms used to generate these products identify and map the location of new SEVIRI observations containing actively burning fires, and characterise their individual rates of radiative energy release (fire radiative power; FRP) that is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the highest spatial resolution FRP dataset, delivered for all of Europe, northern and southern Africa, and part of South America at a spatial resolution of 3 km (decreasing away from the west African sub-satellite point) at the full 15 min temporal resolution. The FRP-GRID product is an hourly summary of the FRP-PIXEL data, produced at a 5° grid cell size and including simple bias adjustments for meteorological cloud cover and for the regional underestimation of FRP caused, primarily, by the non-detection of low FRP fire pixels at SEVIRI's relatively coarse pixel size. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) algorithm used to detect the SEVIRI active fire pixels, and detail methods used to deliver atmospherically corrected FRP information together with the per-pixel uncertainty metrics. Using scene simulations and analysis of real SEVIRI data, including from a period of Meteosat-8 "special operations", we describe some of the sensor and data pre-processing characteristics influencing fire detection and FRP uncertainty. We show that the FTA algorithm is able to discriminate actively burning fires covering down to 10-4 of a pixel, and is more sensitive to fire than algorithms used within many other widely exploited active fire products. We also find that artefacts arising from the digital filtering and geometric resampling strategies used to generate level 1.5 SEVIRI data can significantly increase FRP uncertainties in the SEVIRI active fire products, and recommend that the processing chains used for the forthcoming Meteosat Third Generation attempt to minimise the impact of these types of operations. Finally, we illustrate the information contained within the current Meteosat FRP-PIXEL and FRP-GRID products, providing example analyses for both individual fires and multi-year regional-scale fire activity. A companion paper (Roberts et al., 2015) provides a full product performance evaluation for both products, along with examples of their use for prescribing fire smoke emissions within atmospheric modelling components of the Copernicus Atmosphere Monitoring Service (CAMS).

ESA fire_cci product assessment

NASA Astrophysics Data System (ADS)

Heil, Angelika; Yue, Chao; Mouillot, Florent; Storm, Thomas; Chuvieco, Emilio; Ramo Sanchez, Ruben; Kaiser, Johannes W.

2017-04-01

Vegetation fires are a major disturbance in the Earth System. Fires change the biophysical properties and dynamics of ecosystems and alter terrestrial carbon pools. By altering the atmosphere's composition, fire emissions exert a significant climate forcing. To realistically model past and future changes of the Earth System, fire disturbances must be taken into account. Related modelling efforts require consistent global burned area observations covering at least 10 to 20 years. Guided by the specific requirements of a wide range of end users, the ESA fire_cci project has computed a new global burned area dataset. It applies a newly developed spectral change detection algorithm upon the ENVISAT-MERIS archive. The algorithm relies on MODIS active fire information as "seed". It comprises a pixel burned area product (spatial resolution of 333 m) with date detection information and a biweekly grid product at 0.25 degree spatial resolution. We compare fire_cci burned area with other global burned area products (MCD64 Collection 6, MCD45, GFED4, GFED4s and GEOLAND) and a set of active fires data (hotspots from MODIS, TRMM, AATSR and fire radiative power from GFAS). The analysis of patterns of agreement and disagreement between fire_cci and other products provides a better understanding of product characteristics and uncertainties. The intercomparison of the 2005-2011 fire_cci time series shows a close agreement with GFED4 data in terms of global burned area and the general spatial and temporal patterns. Pronounced differences, however, emerge for specific regions or fire events. Burned area mapped by fire_cci tends to be notably higher in regions where small agricultural fires predominate. The improved detection of small agricultural fires by fire_cci can be related to the increased spatial resolution of the MERIS sensor (333 m compared to 500 in MODIS). This is illustrated in detail using the example of the extreme 2006 spring fires in Eastern Europe.

LSA SAF Meteosat FRP products - Part 1: Algorithms, product contents, and analysis

NASA Astrophysics Data System (ADS)

Wooster, M. J.; Roberts, G.; Freeborn, P. H.; Xu, W.; Govaerts, Y.; Beeby, R.; He, J.; Lattanzio, A.; Fisher, D.; Mullen, R.

2015-11-01

Characterizing changes in landscape fire activity at better than hourly temporal resolution is achievable using thermal observations of actively burning fires made from geostationary Earth Observation (EO) satellites. Over the last decade or more, a series of research and/or operational "active fire" products have been developed from geostationary EO data, often with the aim of supporting biomass burning fuel consumption and trace gas and aerosol emission calculations. Such Fire Radiative Power (FRP) products are generated operationally from Meteosat by the Land Surface Analysis Satellite Applications Facility (LSA SAF) and are available freely every 15 min in both near-real-time and archived form. These products map the location of actively burning fires and characterize their rates of thermal radiative energy release (FRP), which is believed proportional to rates of biomass consumption and smoke emission. The FRP-PIXEL product contains the full spatio-temporal resolution FRP data set derivable from the SEVIRI (Spinning Enhanced Visible and Infrared Imager) imager onboard Meteosat at a 3 km spatial sampling distance (decreasing away from the west African sub-satellite point), whilst the FRP-GRID product is an hourly summary at 5° grid resolution that includes simple bias adjustments for meteorological cloud cover and regional underestimation of FRP caused primarily by underdetection of low FRP fires. Here we describe the enhanced geostationary Fire Thermal Anomaly (FTA) detection algorithm used to deliver these products and detail the methods used to generate the atmospherically corrected FRP and per-pixel uncertainty metrics. Using SEVIRI scene simulations and real SEVIRI data, including from a period of Meteosat-8 "special operations", we describe certain sensor and data pre-processing characteristics that influence SEVIRI's active fire detection and FRP measurement capability, and use these to specify parameters in the FTA algorithm and to make recommendations for the forthcoming Meteosat Third Generation operations in relation to active fire measures. We show that the current SEVIRI FTA algorithm is able to discriminate actively burning fires covering down to 10-4 of a pixel and that it appears more sensitive to fire than other algorithms used to generate many widely exploited active fire products. Finally, we briefly illustrate the information contained within the current Meteosat FRP-PIXEL and FRP-GRID products, providing example analyses for both individual fires and multi-year regional-scale fire activity; the companion paper (Roberts et al., 2015) provides a full product performance evaluation and a demonstration of product use within components of the Copernicus Atmosphere Monitoring Service (CAMS).

Active fire detection using a peat fire radiance model

NASA Astrophysics Data System (ADS)

Kushida, K.; Honma, T.; Kaku, K.; Fukuda, M.

2011-12-01

The fire fractional area and radiances at 4 and 11 μm of active fires in Indonesia were estimated using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. Based on these fire information, a stochastic fire model was used for evaluating two fire detection algorithms of Moderate Resolution Imaging Spectroradiometer (MODIS). One is single-image stochastic fire detection, and the other is multitemporal stochastic fire detection (Kushida, 2010 - IEEE Geosci. Remote Sens. Lett.). The average fire fractional area per one 1 km2 ×1 km2 pixel was 1.7%; this value corresponds to 32% of that of Siberian and Mongolian boreal forest fires. The average radiances at 4 and 11 μm of active fires were 7.2 W/(m2.sr.μm) and 11.1 W/(m2.sr.μm); these values correspond to 47% and 91% of those of Siberian and Mongolian boreal forest fires, respectively. In order to get false alarms less than 20 points per 106 km2 area, for the Siberian and Mongolian boreal forest fires, omission errors (OE) of 50-60% and about 40% were expected for the detections by using the single and multitemporal images, respectively. For Indonesian peat fires, OE of 80-90% was expected for the detections by using the single images. For the peat-fire detections by using the multitemporal images, OE of about 40% was expected, provided that the background radiances were estimated from past multitemporal images with less than the standard deviation of 1K. The analyses indicated that it was difficult to obtain sufficient active-fire information of Indonesian peat fires from single MODIS images for the fire fighting, and that the use of the multitemporal images was important.

Smoke regions extraction based on two steps segmentation and motion detection in early fire

NASA Astrophysics Data System (ADS)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.

The Global Geostationary Wildfire ABBA: Current Implementation and Future Plans

NASA Astrophysics Data System (ADS)

Prins, E.; Schmidt, C. C.; Hoffman, J.; Brunner, J.; Hyer, E. J.; Reid, J. S.

2012-12-01

The Wild Fire Automated Biomass Burning Algorithm (WF_ABBA), developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS), has a long legacy of operational near real-time wildfire detection and characterization in the Western Hemisphere. The first phase of the global geostationary WF_ABBA was made operational at NOAA NESDIS in 2009 and currently includes diurnal active fire monitoring from GOES-East, GOES-South America, GOES-West, Meteosat-9 and MTSAT-1R/-2. This allows for near global active fire monitoring with coverage of Europe, Africa, Southeast Asia and the Western Pacific utilizing distinct geostationary sensors and a consistent algorithm. Version 6.5.006 of the WF_ABBA was specifically designed to address the capabilities and limitations of diverse geostationary sensors and requests from the global fire monitoring and user community. This presentation will provide an overview of version 6.5.006 of the global WF_ABBA fire product including the new fire and opaque cloud mask and associated metadata. We will demonstrate the WF_ABBA showing examples from around the globe with a focus on the capabilities and plans for integrating new geostationary platforms with coverage of Eastern Europe and Asia (INSAT-3D, Korean COMS, Russian GOMS Elektro-L MSU-GS). We are also preparing for future fire monitoring in the Western Hemisphere, Europe, and Africa utilizing the next generation GOES-R Imager and Meteosat Third Generation Flexible Combined Imager (MTG - FCI). The goal is to create a globally consistent long-term fire product utilizing the capabilities of each of these unique operational systems and a common fire detection algorithm. On an international level, development of a global geostationary fire monitoring system is supported by the IGOS GOFC/GOLD Fire Implementation Team. This work also generally supports Committee on Earth Observation Satellites (CEOS) activities and the Group on Earth Observations (GEO).

ESA Fire CCI product assessment

NASA Astrophysics Data System (ADS)

Heil, Angelika; Yue, Chao; Mouillot, Florent; Storm, Thomas; Chuvieco, Emilio; Kaiser, Johannes

2016-04-01

Vegetation fires are a major disturbance in the Earth System. Fires change the biophysical properties and dynamics of ecosystems and alter terrestrial carbon pools. By altering the atmosphere's composition, fire emissions exert a significant climate forcing. To realistically model past and future changes of the Earth System, fire disturbances must be taken into account. Related modelling efforts require consistent global burned area observations covering at least 10 to 20 years. Guided by the specific requirements of a wide range of end users, the ESA fire_cci project is currently computing a new global burned area dataset. It applies a newly developed spectral change detection algorithm upon the full ENVISAT-MERIS archive (2002 to 2012). The algorithm relies on MODIS active fire information as "seed". A first, formally validated version has been released for the period 2006 to 2008. It comprises a pixel burned area product (spatial resolution of 333 m) with date detection information and a biweekly grid product at 0.5 degree spatial resolution. We compare fire_cci burned area with other global burned area products (MCD64, GFED4(s), GEOLAND) and a set of active fires data (hotspots from MODIS, TRMM, AATSR and fire radiative power from GFAS). Output from the ongoing processing of the full MERIS timeseries will be incorporated into the study, as far as available. The analysis of patterns of agreement and disagreement between fire_cci and other products provides a better understanding of product characteristics and uncertainties. The intercomparison of the 2006-2008 fire_cci time series shows a close agreement with GFED4 data in terms of global burned area and the general spatial and temporal patterns. Pronounced differences, however, emerge for specific regions or fire events. Burned area mapped by fire_cci tends to be notably higher in regions where small agricultural fires predominate. The improved detection of small agricultural fires by fire_cci can be related to the increased spatial resolution of the MERIS sensor (333 m compared to 500 in MODIS). This is illustrated in detail using the example of the extreme 2006 spring fires in Eastern Europe.

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

NASA Astrophysics Data System (ADS)

Li, Shengbo Eben; Li, Guofa; Yu, Jiaying; Liu, Chang; Cheng, Bo; Wang, Jianqiang; Li, Keqiang

2018-01-01

Detection and tracking of objects in the side-near-field has attracted much attention for the development of advanced driver assistance systems. This paper presents a cost-effective approach to track moving objects around vehicles using linearly arrayed ultrasonic sensors. To understand the detection characteristics of a single sensor, an empirical detection model was developed considering the shapes and surface materials of various detected objects. Eight sensors were arrayed linearly to expand the detection range for further application in traffic environment recognition. Two types of tracking algorithms, including an Extended Kalman filter (EKF) and an Unscented Kalman filter (UKF), for the sensor array were designed for dynamic object tracking. The ultrasonic sensor array was designed to have two types of fire sequences: mutual firing or serial firing. The effectiveness of the designed algorithms were verified in two typical driving scenarios: passing intersections with traffic sign poles or street lights, and overtaking another vehicle. Experimental results showed that both EKF and UKF had more precise tracking position and smaller RMSE (root mean square error) than a traditional triangular positioning method. The effectiveness also encourages the application of cost-effective ultrasonic sensors in the near-field environment perception in autonomous driving systems.

Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird)

PubMed Central

Atwood, Elizabeth C.; Englhart, Sandra; Lorenz, Eckehard; Halle, Winfried; Wiedemann, Werner; Siegert, Florian

2016-01-01

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2–3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future. PMID:27486664

Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird).

PubMed

Atwood, Elizabeth C; Englhart, Sandra; Lorenz, Eckehard; Halle, Winfried; Wiedemann, Werner; Siegert, Florian

2016-01-01

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.

A Validation of Remotely Sensed Fires Using Ground Reports

NASA Astrophysics Data System (ADS)

Ruminski, M. G.; Hanna, J.

2007-12-01

A satellite based analysis of fire detections and smoke emissions for North America is produced daily by NOAA/NESDIS. The analysis incorporates data from the MODIS (Terra and Aqua) and AVHRR (NOAA-15/16/17) polar orbiting instruments and GOES East and West geostationary spacecraft with nominal resolutions of 1km and 4 km for the polar and geostationary platforms respectively. Automated fire detection algorithms are utilized for each of the sensors. Analysts perform a quality control procedure on the automated detects by deleting points that are deemed to be false detects and adding points that the algorithms did not detect. A limited validation of the final quality controlled product was performed using high resolution (30 m) ASTER data in the summer of 2006. Some limitations in using ASTER data are that each scene is only approximately 3600 square km, the data acquisition time is relatively constant at around 1030 local solar time and ASTER is another remotely sensed data source. This study expands on the ASTER validation by using ground reports of prescribed burns in Montana and Idaho for 2003 and 2004. It provides a non-remote sensing data source for comparison. While the ground data do not have the limitations noted above for ASTER there are still limitations. For example, even though the data set covers a much larger area (nearly 600,000 square km) than even several ASTER scenes, it still represents a single region of North America. And while the ground data are not restricted to a narrow time window, only a date is provided with each report, limiting the ability to make detailed conclusions about the detection capabilities for specific instruments, especially for the less temporally frequent polar orbiting MODIS and AVHRR sensors. Comparison of the ground data reports to the quality controlled fire analysis revealed a low rate of overall detection of 23.00% over the entire study period. Examination of the daily detection rates revealed a wide variation, with some days resulting in as little as 5 detects out of 107 reported fires while other days had as many as 84 detections out of 160 reports. Inspection of the satellite imagery from the days with very low detection rates revealed that extensive cloud cover prohibited satellite fire detection. On days when cloud cover was at a minimum, detection rates were substantially higher. An estimate of the fire size was also provided with the ground data set. Statistics will be presented for days with minimal cloud cover which will indicate the probability of detection for fires of various sizes.

Onboard Science and Applications Algorithm for Hyperspectral Data Reduction

NASA Technical Reports Server (NTRS)

Chien, Steve A.; Davies, Ashley G.; Silverman, Dorothy; Mandl, Daniel

2012-01-01

An onboard processing mission concept is under development for a possible Direct Broadcast capability for the HyspIRI mission, a Hyperspectral remote sensing mission under consideration for launch in the next decade. The concept would intelligently spectrally and spatially subsample the data as well as generate science products onboard to enable return of key rapid response science and applications information despite limited downlink bandwidth. This rapid data delivery concept focuses on wildfires and volcanoes as primary applications, but also has applications to vegetation, coastal flooding, dust, and snow/ice applications. Operationally, the HyspIRI team would define a set of spatial regions of interest where specific algorithms would be executed. For example, known coastal areas would have certain products or bands downlinked, ocean areas might have other bands downlinked, and during fire seasons other areas would be processed for active fire detections. Ground operations would automatically generate the mission plans specifying the highest priority tasks executable within onboard computation, setup, and data downlink constraints. The spectral bands of the TIR (thermal infrared) instrument can accurately detect the thermal signature of fires and send down alerts, as well as the thermal and VSWIR (visible to short-wave infrared) data corresponding to the active fires. Active volcanism also produces a distinctive thermal signature that can be detected onboard to enable spatial subsampling. Onboard algorithms and ground-based algorithms suitable for onboard deployment are mature. On HyspIRI, the algorithm would perform a table-driven temperature inversion from several spectral TIR bands, and then trigger downlink of the entire spectrum for each of the hot pixels identified. Ocean and coastal applications include sea surface temperature (using a small spectral subset of TIR data, but requiring considerable ancillary data), and ocean color applications to track biological activity such as harmful algal blooms. Measuring surface water extent to track flooding is another rapid response product leveraging VSWIR spectral information.

On the robustness of EC-PC spike detection method for online neural recording.

PubMed

Zhou, Yin; Wu, Tong; Rastegarnia, Amir; Guan, Cuntai; Keefer, Edward; Yang, Zhi

2014-09-30

Online spike detection is an important step to compress neural data and perform real-time neural information decoding. An unsupervised, automatic, yet robust signal processing is strongly desired, thus it can support a wide range of applications. We have developed a novel spike detection algorithm called "exponential component-polynomial component" (EC-PC) spike detection. We firstly evaluate the robustness of the EC-PC spike detector under different firing rates and SNRs. Secondly, we show that the detection Precision can be quantitatively derived without requiring additional user input parameters. We have realized the algorithm (including training) into a 0.13 μm CMOS chip, where an unsupervised, nonparametric operation has been demonstrated. Both simulated data and real data are used to evaluate the method under different firing rates (FRs), SNRs. The results show that the EC-PC spike detector is the most robust in comparison with some popular detectors. Moreover, the EC-PC detector can track changes in the background noise due to the ability to re-estimate the neural data distribution. Both real and synthesized data have been used for testing the proposed algorithm in comparison with other methods, including the absolute thresholding detector (AT), median absolute deviation detector (MAD), nonlinear energy operator detector (NEO), and continuous wavelet detector (CWD). Comparative testing results reveals that the EP-PC detection algorithm performs better than the other algorithms regardless of recording conditions. The EC-PC spike detector can be considered as an unsupervised and robust online spike detection. It is also suitable for hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

An overview of GOES-8 diurnal fire and smoke results for SCAR-B and 1995 fire season in South America

NASA Astrophysics Data System (ADS)

Prins, Elaine M.; Feltz, Joleen M.; Menzel, W. Paul; Ward, Darold E.

1998-12-01

The launch of the eighth Geostationary Operational Environmental Satellite (GOES-8) in 1994 introduced an improved capability for diurnal fire and smoke monitoring throughout the western hemisphere. In South America the GOES-8 automated biomass burning algorithm (ABBA) and the automated smoke/aerosol detection algorithm (ASADA) are being used to monitor biomass burning. This paper outlines GOES-8 ABBA and ASADA development activities and summarizes results for the Smoke, Clouds, and Radiation in Brazil (SCAR-B) experiment and the 1995 fire season. GOES-8 ABBA results document the diurnal, spatial, and seasonal variability in fire activity throughout South America. A validation exercise compares GOES-8 ABBA results with ground truth measurements for two SCAR-B prescribed burns. GOES-8 ASADA aerosol coverage and derived albedo results provide an overview of the extent of daily and seasonal smoke coverage and relative intensities. Day-to-day variability in smoke extent closely tracks fluctuations in fire activity.

Forest Fire Finder - DOAS application to long-range forest fire detection

NASA Astrophysics Data System (ADS)

Valente de Almeida, Rui; Vieira, Pedro

2017-06-01

Fires are an important factor in shaping Earth's ecosystems. Plant and animal life, in almost every land habitat, are at least partially dependent on the effects of fire. However, their destructive force, which has often proven uncontrollable, is one of our greatest concerns, effectively resulting in several policies in the most important industrialised regions of the globe. This paper aims to comprehensively characterise the Forest Fire Finder (FFF), a forest fire detection system based mainly upon a spectroscopic technique called differential optical absorption spectroscopy (DOAS). The system is designed and configured with the goal of detecting higher-than-the-horizon smoke columns by measuring and comparing scattered sunlight spectra. The article covers hardware and software, as well as their interactions and specific algorithms for day mode operation. An analysis of data retrieved from several installations deployed in the course of the last 5 years is also presented. Finally, this paper features a discussion on the most prominent future improvements planned for the system, as well as its ramifications and adaptations, such as a thermal imaging system for short-range fire seeking or environmental quality control.

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

NASA Technical Reports Server (NTRS)

Morton, Douglas C.; DeFries, Ruth S.; Nagol, Jyoteshwar; Souza, Carlos M., Jr.; Kasischke, Eric S.; Hurtt, George C.; Dubayah, Ralph

2011-01-01

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

PubMed Central

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K.

2011-01-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status. PMID:21909297

Detection, emission estimation and risk prediction of forest fires in China using satellite sensors and simulation models in the past three decades--an overview.

PubMed

Zhang, Jia-Hua; Yao, Feng-Mei; Liu, Cheng; Yang, Li-Min; Boken, Vijendra K

2011-08-01

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status.

Prototype global burnt area algorithm using the AVHRR-LTDR time series

NASA Astrophysics Data System (ADS)

López-Saldaña, Gerardo; Pereira, José Miguel; Aires, Filipe

2013-04-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05° spatial resolution and is available for the 1981-1999 time period. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR dataset, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for year 1998, which was selected because of a positive fire anomaly, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

Advancement and results in hostile fire indication using potassium line missile warning sensors

NASA Astrophysics Data System (ADS)

Montgomery, Joel; Montgomery, Marjorie; Hardie, Russell

2014-06-01

M&M Aviation has been developing and conducting Hostile Fire Indication (HFI) tests using potassium line emission sensors for the Air Force Visible Missile Warning System (VMWS) to advance both algorithm and sensor technologies for UAV and other airborne systems for self protection and intelligence purposes. Work began in 2008 as an outgrowth of detecting and classifying false alarm sources for the VMWS using the same K-line spectral discrimination region but soon became a focus of research due to the high interest in both machine-gun fire and sniper geo-location via airborne systems. Several initial tests were accomplished in 2009 using small and medium caliber weapons including rifles. Based on these results, the Air Force Research Laboratory (AFRL) funded the Falcon Sentinel program in 2010 to provide for additional development of both the sensor concept, algorithm suite changes and verification of basic phenomenology including variance based on ammunition type for given weapons platform. Results from testing over the past 3 years have showed that the system would be able to detect and declare a sniper rifle at upwards of 3km, medium machine gun at 5km, and explosive events like hand-grenades at greater than 5km. This paper will outline the development of the sensor systems, algorithms used for detection and classification, and test results from VMWS prototypes as well as outline algorithms used for the VMWS. The Falcon Sentinel Program will be outlined and results shown. Finally, the paper will show the future work for ATD and transition efforts after the Falcon Sentinel program completed.

Implementing a combined polar-geostationary algorithm for smoke emissions estimation in near real time

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Schmidt, C. C.; Hoffman, J.; Giglio, L.; Peterson, D. A.

2013-12-01

Polar and geostationary satellites are used operationally for fire detection and smoke source estimation by many near-real-time operational users, including operational forecast centers around the globe. The input satellite radiance data are processed by data providers to produce Level-2 and Level -3 fire detection products, but processing these data into spatially and temporally consistent estimates of fire activity requires a substantial amount of additional processing. The most significant processing steps are correction for variable coverage of the satellite observations, and correction for conditions that affect the detection efficiency of the satellite sensors. We describe a system developed by the Naval Research Laboratory (NRL) that uses the full raster information from the entire constellation to diagnose detection opportunities, calculate corrections for factors such as angular dependence of detection efficiency, and generate global estimates of fire activity at spatial and temporal scales suitable for atmospheric modeling. By incorporating these improved fire observations, smoke emissions products, such as NRL's FLAMBE, are able to produce improved estimates of global emissions. This talk provides an overview of the system, demonstrates the achievable improvement over older methods, and describes challenges for near-real-time implementation.

Hot Spot Detection System Using Landsat 8/OLI Data

NASA Astrophysics Data System (ADS)

Kato, S.; Nakamura, R.; Oda, A.; Iijima, A.; Kouyama, T.; Iwata, T.

2015-12-01

We developed a simple algorithm and a Web-based visualizing system to detect hot spots using Landsat 8 OLI multispectral data as one of the applications of the real-time processing of Landsat 8 data. An empirical equation and radiometric and reflective thresholds were derived to detect hot spots using the OLI data at band 5 (0.865 μm) and band 7 (2.200 μm) based on the increase in spectral radiance at shortwave infrared (SWIR) region due to the emission from objects with high surface temperature. We surveyed typical patterns of surface spectra using the ASTER spectral library to delineate a threshold to distinguish hot spots from background surfaces. To adjust the empirical coefficients of our detection algorithm, we visually inspected the detected hot spots using 6593 Landsat 8 scenes, which cover eastern part of East Asia, taken from January 1, 2014 to December 31, 2014, displayed on a dedicated Web GIS system. Eventually we determined threshold equations which can theoretically detect hot spots at temperatures above 230 °C over isothermal pixels and hot spots as small as 1 m2 at temperatures of 1000 °C as the lowest temperature and the smallest subpixel coverage, respectively, for daytime scenes. The algorithm detected hot spots including wildfires, volcanos, open burnings and factories. 30-m spatial resolution of Landsat 8 enabled to detect wild fires and open burnings accompanied by clearer shapes of fire front lines than MODIS and VIIRS fire products. Although the 16-day revisit cycle of Landsat 8 is too long to effectively find unexpected wildfire or outbreak of eruption, the revisit cycle is enough to monitor temporally stable heat sources, such as continually erupting volcanos and factories. False detection was found over building rooftops, which have relatively smooth surfaces at longer wavelengths, when specular reflection occurred at the satellite overpass.

Patterns of fire activity over Indonesia and Malaysia from polar and geostationary satellite observations

NASA Astrophysics Data System (ADS)

Hyer, Edward J.; Reid, Jeffrey S.; Prins, Elaine M.; Hoffman, Jay P.; Schmidt, Christopher C.; Miettinen, Jukka I.; Giglio, Louis

2013-03-01

Biomass burning patterns over the Maritime Continent of Southeast Asia are examined using a new active fire detection product based on application of the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) to data from the imagers on the MTSAT geostationary satellites operated by the Japanese space agency JAXA. Data from MTSAT-1R and MTSAT-2 covering 34 months from September 2008 to July 2011 are examined for a study region consisting of Indonesia, Malaysia, and nearby environs. The spatial and temporal distributions of fires detected in the MTSAT WF_ABBA product are described and compared with active fire observations from MODIS MOD14 data. Land cover distributions for the two instruments are examined using a new 250 m land cover product from the National University of Singapore. The two products show broadly similar patterns of fire activity, land cover distribution of fires, and pixel fire radiative power (FRP). However, the MTSAT WF_ABBA data differ from MOD14 in important ways. Relative to MODIS, the MTSAT WF_ABBA product has lower overall detection efficiency, but more fires detected due to more frequent looks, a greater relative fraction of fires in forest and a lower relative fraction of fires in open areas, and significantly higher single-pixel retrieved FRP. The differences in land cover distribution and FRP between the MTSAT and MODIS products are shown to be qualitatively consistent with expectations based on pixel size and diurnal sampling. The MTSAT WF_ABBA data are used to calculate coverage-corrected diurnal cycles of fire for different regions within the study area. These diurnal cycles are preliminary but demonstrate that the fraction of diurnal fire activity sampled by the two MODIS sensors varies significantly by region and vegetation type. Based on the results from comparison of the two fire products, a series of steps is outlined to account for some of the systematic biases in each of these satellite products in order to produce a successful merged fire detection product.

Error reduction in EMG signal decomposition

PubMed Central

Kline, Joshua C.

2014-01-01

Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions. Decomposition errors were classified into two general categories: location errors representing variability in the temporal localization of each motor-unit firing instance and identification errors consisting of falsely detected or missed firing instances. To mitigate these errors, we developed an error-reduction algorithm that combines multiple decomposition estimates to determine a more probable estimate of motor-unit firing instances with fewer errors. The performance of the algorithm is governed by a trade-off between the yield of MUAPTs obtained above a given accuracy level and the time required to perform the decomposition. When applied to a set of sEMG signals synthesized from real MUAPTs, the identification error was reduced by an average of 1.78%, improving the accuracy to 97.0%, and the location error was reduced by an average of 1.66 ms. The error-reduction algorithm in this study is not limited to any specific decomposition strategy. Rather, we propose it be used for other decomposition methods, especially when analyzing precise motor-unit firing instances, as occurs when measuring synchronization. PMID:25210159

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

PubMed

Hsu, Yu-Liang; Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-07-15

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents' wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident's feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment.

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology

PubMed Central

Chou, Po-Huan; Chang, Hsing-Cheng; Lin, Shyan-Lung; Yang, Shih-Chin; Su, Heng-Yi; Chang, Chih-Chien; Cheng, Yuan-Sheng; Kuo, Yu-Chen

2017-01-01

This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an intelligent smart home environment: (1) a wearable motion sensing device to be placed on residents’ wrists and its corresponding 3D gesture recognition algorithm to implement a convenient automated household appliance control system; (2) a wearable motion sensing device mounted on a resident’s feet and its indoor positioning algorithm to realize an effective indoor pedestrian navigation system for smart energy management; (3) a multisensor circuit module and an intelligent fire detection and alarm algorithm to realize a home safety and fire detection system. In addition, an intelligent monitoring interface is developed to provide in real-time information about the smart home system, such as environmental temperatures, CO concentrations, communicative environmental alarms, household appliance status, human motion signals, and the results of gesture recognition and indoor positioning. Furthermore, an experimental testbed for validating the effectiveness and feasibility of the smart home system was built and verified experimentally. The results showed that the 3D gesture recognition algorithm could achieve recognition rates for automated household appliance control of 92.0%, 94.8%, 95.3%, and 87.7% by the 2-fold cross-validation, 5-fold cross-validation, 10-fold cross-validation, and leave-one-subject-out cross-validation strategies. For indoor positioning and smart energy management, the distance accuracy and positioning accuracy were around 0.22% and 3.36% of the total traveled distance in the indoor environment. For home safety and fire detection, the classification rate achieved 98.81% accuracy for determining the conditions of the indoor living environment. PMID:28714884

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Next generation fire suppressants

NASA Technical Reports Server (NTRS)

Brown, Jerry A.

1995-01-01

Spectrex, Inc., located in Cedar Grove, NJ is a manufacturer of fire detection and suppression equipment. Spectrex is one of the original pioneers in high speed fire detection and suppression systems for combat vehicles. Spectrex has installed fire suppressions systems in thousands of combat vehicles and ships throughout the world. Additionally, they manufacture flame explosion detectors, ship damage control systems, and optical gas and vapor detectors. The culmination of several years of research and development has recently produced an innovative electro-optical continuous monitoring systems called SharpEye 20/20I IR(sup 3) and SAFEYE that provide fast and reliable gas, vapor, aerosol, flame, and explosion detection. SharpEye 20/20I IR(sup 3) is a self-contained triple spectrum flame detector which scans for oscillating IR radiation (1 to 10 Hz) in the spectral bands ranging from 4.0 to 5.0 microns and uses programmed algorithms to check the ratio and correlation of data received by the three sensors to make the system highly immune to false alarms. It is extremely sensitive as it can detect a 1 x 1 square foot gasoline pan fire at 200 feet in less than 3 seconds. The sensitivity is user programmable, offering 4 ranges of detection. SAFEYE is comprised of a selected number of multispectral ban microprocessors controlled detectors which are in communication with one or more radiation sources that is projected along a 600 feet optical path. The signals from the selected narrow bands are processed and analyzed by highly sophisticated algorithms. It is ideal for high risk, remote, large areas such as petroleum and chemical manufacturing sites, waste dumps, aircraft cargo bays, and ship compartments. The SAFEYE will perform direct readings of the presence or rate of rise of concentrations of gases, vapors, or aerosols at the range of parts per million and provide alarms at various set points at different levels of concentrations.

Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

NASA Astrophysics Data System (ADS)

Chatterjee, R. S.; Singh, Narendra; Thapa, Shailaja; Sharma, Dravneeta; Kumar, Dheeraj

2017-06-01

The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVITHM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is significantly larger in the derived LST products than the corresponding radiant temperature images.

Edge-preserving data assimilation for fire monitoring using optical data

NASA Astrophysics Data System (ADS)

Gomez-Dans, Jose; Lewis, Philip; Disney, Mathias; Roy, David; Quaife, Tristan; Wooster, Martin

2013-04-01

Monitoring fire using optical data from moderate spatial resolution sensors is in essence a change detection process, where changes in reflectance (or a vegetation index) within two dates or periods are interpreted as fires if the change meets a number of spectral rules. A major challenge in any of these algorithms is accounting for angular effects due to different acquistion/illumination geometry. The MODIS Coll5 algorithm for example, uses linear kernel models to forward predict observations, and based on a statistical test, decides whether a change has occurred and labels it as a potential fire. While the algorithm is successful in many regions, it has problems dealing with cloudy periods, and with limitations in the available observations. In this work, we propose a new approach based on (i) a more advanced signal tracking method using edge-preserving data assimilation techniques and (ii) an interpretation of the change signal using a spectral linear model. The signal tracking approach uses linear kernel models, but solves for them using regularisation in time as a prior. This allows for a transfer of information from data rich periods to other periods where data may be more sparse. To minimise information leaking over the actual fire, we implement an edge-preserving mechanism that limits the information transfer over the disturbance. The result of this is a complete time series of surface reflectance acquired with a constant geometry. Note that the system provides complete uncertainty estimates of the parameters, taking into account the initial level of uncertainty in the observations of surface reflectance. A second stage interprets post-fire reflectance as a mixture of a "typical burn signal" and an unburned component, which we assume to be the pre-fire reflectance. We propose a simple spectral model for the burn signal, a constrained quadratic function. This model is appropriate for a number of burned material spectrum. We demonstrate using the MODIS burned area product that the approach provides useful complementary information about fires, describing the spectral nature of the burn signal, as well as providing information on potentially the impact of the fire in the pixel. Both approaches are then combined into a multispectral burned area algorithm with MODIS land surface observations. We test the performance of the proposed method, compare to other well-established products, and show some of the shortcomings of the proposed algorithm.

Results of field testing with the FightSight infrared-based projectile tracking and weapon-fire characterization technology

NASA Astrophysics Data System (ADS)

Snarski, Steve; Menozzi, Alberico; Sherrill, Todd; Volpe, Chris; Wille, Mark

2010-04-01

This paper describes experimental results from recent live-fire data collects that demonstrate the capability of a prototype system for projectile detection and tracking. This system, which is being developed at Applied Research Associates, Inc., under the FightSight program, consists of a high-speed thermal camera and sophisticated image processing algorithms to detect and track projectiles. The FightSight operational vision is automated situational intelligence to detect, track, and graphically map large-scale firefights and individual shooting events onto command and control (C2) systems in real time (shot location and direction, weapon ID, movements and trends). Gaining information on enemy-fire trajectories allows educated inferences on the enemy's intent, disposition, and strength. Our prototype projectile detection and tracking system has been tested at the Joint Readiness Training Center (Ft Polk, LA) during live-fire convoy and mortar registration exercises, in the summer of 2009. It was also tested during staged military-operations- on-urban-terrain (MOUT) firefight events at Aberdeen Test Center (Aberdeen, MD) under the Hostile Fire Defeat Army Technology Objective midterm experiment, also in the summer of 2009, where we introduced fusion with acoustic and EO sensors to provide 3D localization and near-real time display of firing events. Results are presented in this paper that demonstrate effective and accurate detection and localization of weapon fire (5.56mm, 7.62mm, .50cal, 81/120mm mortars, 40mm) in diverse and challenging environments (dust, heat, day and night, rain, arid open terrain, urban clutter). FightSight's operational capabilities demonstrated under these live-fire data collects can support closecombat scenarios. As development continues, FightSight will be able to feed C2 systems with a symbolic map of enemy actions.

Detection of Wildfires with Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Umphlett, B.; Leeman, J.; Morrissey, M. L.

2011-12-01

Currently fire detection for the National Oceanic and Atmospheric Administration (NOAA) using satellite data is accomplished with algorithms and error checking human analysts. Artificial neural networks (ANNs) have been shown to be more accurate than algorithms or statistical methods for applications dealing with multiple datasets of complex observed data in the natural sciences. ANNs also deal well with multiple data sources that are not all equally reliable or equally informative to the problem. An ANN was tested to evaluate its accuracy in detecting wildfires utilizing polar orbiter numerical data from the Advanced Very High Resolution Radiometer (AVHRR). Datasets containing locations of known fires were gathered from the NOAA's polar orbiting satellites via the Comprehensive Large Array-data Stewardship System (CLASS). The data was then calibrated and navigation corrected using the Environment for Visualizing Images (ENVI). Fires were located with the aid of shapefiles generated via ArcGIS. Afterwards, several smaller ten pixel by ten pixel datasets were created for each fire (using the ENVI corrected data). Several datasets were created for each fire in order to vary fire position and avoid training the ANN to look only at fires in the center of an image. Datasets containing no fires were also created. A basic pattern recognition neural network was established with the MATLAB neural network toolbox. The datasets were then randomly separated into categories used to train, validate, and test the ANN. To prevent over fitting of the data, the mean squared error (MSE) of the network was monitored and training was stopped when the MSE began to rise. Networks were tested using each channel of the AVHRR data independently, channels 3a and 3b combined, and all six channels. The number of hidden neurons for each input set was also varied between 5-350 in steps of 5 neurons. Each configuration was run 10 times, totaling about 4,200 individual network evaluations. Thirty network parameters were recorded to characterize performance. These parameters were plotted with various data display techniques to determine which network configuration was not only most accurate in fire classification, but also the most computationally efficient. The most accurate fire classification network used all six channels of AVHRR data to achieve an accuracy ranging from 73-90%.

Network-Based Real-time Integrated Fire Detection and Alarm (FDA) System with Building Automation

NASA Astrophysics Data System (ADS)

Anwar, F.; Boby, R. I.; Rashid, M. M.; Alam, M. M.; Shaikh, Z.

2017-11-01

Fire alarm systems have become increasingly an important lifesaving technology in many aspects, such as applications to detect, monitor and control any fire hazard. A large sum of money is being spent annually to install and maintain the fire alarm systems in buildings to protect property and lives from the unexpected spread of fire. Several methods are already developed and it is improving on a daily basis to reduce the cost as well as increase quality. An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm. This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. A shortest path algorithmic was chosen for series of buildings connected by fiber optic network. The framework shares information and communicates with each fire alarm panels connected in peer to peer configuration and declare the network state using network address declaration from any building connected in network. The fiber-optic connection was proposed to reduce signal noises, thus increasing large area coverage, real-time communication and long-term safety. Based on this proposed method an experimental setup was designed and a prototype system was developed to validate the performance in practice. Also, the distributed network system was proposed to connect with an optional remote monitoring terminal panel to validate proposed network performance and ensure fire survivability where the information is sequentially transmitted. The proposed FDA system is different from traditional fire alarm and detection system in terms of topology as it manages group of buildings in an optimal and efficient manner.Introduction

System for Anomaly and Failure Detection (SAFD) system development

NASA Technical Reports Server (NTRS)

Oreilly, D.

1992-01-01

This task specified developing the hardware and software necessary to implement the System for Anomaly and Failure Detection (SAFD) algorithm, developed under Technology Test Bed (TTB) Task 21, on the TTB engine stand. This effort involved building two units; one unit to be installed in the Block II Space Shuttle Main Engine (SSME) Hardware Simulation Lab (HSL) at Marshall Space Flight Center (MSFC), and one unit to be installed at the TTB engine stand. Rocketdyne personnel from the HSL performed the task. The SAFD algorithm was developed as an improvement over the current redline system used in the Space Shuttle Main Engine Controller (SSMEC). Simulation tests and execution against previous hot fire tests demonstrated that the SAFD algorithm can detect engine failure as much as tens of seconds before the redline system recognized the failure. Although the current algorithm only operates during steady state conditions (engine not throttling), work is underway to expand the algorithm to work during transient condition.

Detection and Monitoring of Intense Pyroconvection in Western North America using Remote Sensing and Meteorological Data

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Solbrig, J. E.; Hyer, E. J.; Campbell, J. R.; Fromm, M. D.

2015-12-01

Fire-triggered thunderstorms, known as pyrocumulonimbus (pyroCb), can alter fire behavior, influence smoke plume trajectory, and hinder fire suppression efforts. Intense pyroCb can also inject a significant quantity of aerosol mass into the lower stratosphere. Systematic detection and monitoring of these events is important for wildfire response and aviation applications, as well as understanding climate and air quality implications. The United States Naval Research Laboratory (NRL) recently developed a near-real-time pyroCb detection algorithm using geostationary satellite observations, currently focused on GOES-West. The algorithm is tuned to the microphysics of fire-perturbed thunderstorms over elevated terrain in western North America. By incorporating reanalysis data, NRL has also developed the first observationally-based conceptual model for pyroCb development. Results are focused on 41 large wildfires observed in the United States and Canada during 2013, which produced more than 50 intense pyroCb. The majority of these develop when a layer of increased moisture content and instability is advected over a dry, deep, and unstable mixed layer, typically along the leading edge of an approaching disturbance. The upper-tropospheric dynamics and synoptic pattern must also be conducive for vertical development of convection. Mid- and upper-tropospheric conditions similar to those that produce traditional dry thunderstorms are therefore paramount for development and maintenance of pyroCb. The amount of mid-level moisture and instability required is strongly dependent on the surface elevation of the contributing fire. Surface-based fire weather indices have limited capability for predicting pyroCb development. The intense radiant heat emitted by large wildfires can serve as a potential trigger, suggesting pyroCb may develop in the absence of traditional triggering mechanisms when an otherwise favorable meteorological environment is in place. This conceptual model suggests that pyroCb, traditionally considered a niche phenomenon, are in fact a significant and endemic feature of the regional summer climate. Results of this work will improve our ability to detect, monitor, and predict pyroCb, providing increased understanding of this phenomenon's role in the climate system.

Prototype Global Burnt Area Algorithm Using a Multi-sensor Approach

NASA Astrophysics Data System (ADS)

López Saldaña, G.; Pereira, J.; Aires, F.

2013-05-01

One of the main limitations of products derived from remotely-sensed data is the length of the data records available for climate studies. The Advanced Very High Resolution Radiometer (AVHRR) long-term data record (LTDR) comprises a daily global atmospherically-corrected surface reflectance dataset at 0.05Deg spatial resolution and is available for the 1981-1999 time period. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has been on orbit in the Terra platform since late 1999 and in Aqua since mid 2002; surface reflectance products, MYD09CMG and MOD09CMG, are available at 0.05Deg spatial resolution. Fire is strong cause of land surface change and emissions of greenhouse gases around the globe. A global long-term identification of areas affected by fire is needed to analyze trends and fire-clime relationships. A burnt area algorithm can be seen as a change point detection problem where there is an abrupt change in the surface reflectance due to the biomass burning. Using the AVHRR-LTDR and the aforementioned MODIS products, a time series of bidirectional reflectance distribution function (BRDF) corrected surface reflectance was generated using the daily observations and constraining the BRDF model inversion using a climatology of BRDF parameters derived from 12 years of MODIS data. The identification of the burnt area was performed using a t-test in the pre- and post-fire reflectance values and a change point detection algorithm, then spectral constraints were applied to flag changes caused by natural land processes like vegetation seasonality or flooding. Additional temporal constraints are applied focusing in the persistence of the affected areas. Initial results for years 1998 to 2002, show spatio-temporal coherence but further analysis is required and a formal rigorous validation will be applied using burn scars identified from high-resolution datasets.

A targeted change-detection procedure by combining change vector analysis and post-classification approach

NASA Astrophysics Data System (ADS)

Ye, Su; Chen, Dongmei; Yu, Jie

2016-04-01

In remote sensing, conventional supervised change-detection methods usually require effective training data for multiple change types. This paper introduces a more flexible and efficient procedure that seeks to identify only the changes that users are interested in, here after referred to as "targeted change detection". Based on a one-class classifier "Support Vector Domain Description (SVDD)", a novel algorithm named "Three-layer SVDD Fusion (TLSF)" is developed specially for targeted change detection. The proposed algorithm combines one-class classification generated from change vector maps, as well as before- and after-change images in order to get a more reliable detecting result. In addition, this paper introduces a detailed workflow for implementing this algorithm. This workflow has been applied to two case studies with different practical monitoring objectives: urban expansion and forest fire assessment. The experiment results of these two case studies show that the overall accuracy of our proposed algorithm is superior (Kappa statistics are 86.3% and 87.8% for Case 1 and 2, respectively), compared to applying SVDD to change vector analysis and post-classification comparison.

The Smart Mine Simulator User’s Guide and Algorithm Description

DTIC Science & Technology

1993-12-01

meters control kill range tank 2 meters * APC 1.5 meters other ground 1 meter munition burst type projectile 105APDS detonator M739 155mm C-1 WAM...in range 15 meters munition launch burst type projectile TOW detonator M739 155mm WAM Sublet: component parameter Index value sublet regular update...detonator M739 155mm sensor detection range 50 meters control firing angle -55 degrees munition fire burst type projectile TOW detonator M739 155mm

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

We have tested and deployed Artificial Neural Network (ANN) data mining techniques to analyze remotely sensed multi-channel imaging data from MODIS, GOES, and AVHRR. The goal is to train the ANN to learn the signatures of wildfires in remotely sensed data in order to automate the detection process. We train the ANN using the set of human-detected wildfires in the U.S., which are provided by the Hazard Mapping System (HMS) wildfire detection group at NOAA/NESDIS. The ANN is trained to mimic the behavior of fire detection algorithms and the subjective decision- making by N O M HMS Fire Analysts. We use a local extremum search in order to isolate fire pixels, and then we extract a 7x7 pixel array around that location in 3 spectral channels. The corresponding 147 pixel values are used to populate a 147-dimensional input vector that is fed into the ANN. The ANN accuracy is tested and overfitting is avoided by using a subset of the training data that is set aside as a test data set. We have achieved an automated fire detection accuracy of 80-92%, depending on a variety of ANN parameters and for different instrument channels among the 3 satellites. We believe that this system can be deployed worldwide or for any region to detect wildfires automatically in satellite imagery of those regions. These detections can ultimately be used to provide thermal inputs to climate models.

Using HFire for spatial modeling of fire in shrublands

Treesearch

Seth H. Peterson; Marco E. Morais; Jean M. Carlson; Philip E. Dennison; Dar A. Roberts; Max A. Moritz; David R. Weise

2009-01-01

An efficient raster fire-spread model named HFire is introduced. HFire can simulate single-fire events or long-term fire regimes, using the same fire-spread algorithm. This paper describes the HFire algorithm, benchmarks the model using a standard set of tests developed for FARSITE, and compares historical and predicted fire spread perimeters for three southern...

A Forest Fire Sensor Web Concept with UAVSAR

NASA Astrophysics Data System (ADS)

Lou, Y.; Chien, S.; Clark, D.; Doubleday, J.; Muellerschoen, R.; Zheng, Y.

2008-12-01

We developed a forest fire sensor web concept with a UAVSAR-based smart sensor and onboard automated response capability that will allow us to monitor fire progression based on coarse initial information provided by an external source. This autonomous disturbance detection and monitoring system combines the unique capabilities of imaging radar with high throughput onboard processing technology and onboard automated response capability based on specific science algorithms. In this forest fire sensor web scenario, a fire is initially located by MODIS/RapidFire or a ground-based fire observer. This information is transmitted to the UAVSAR onboard automated response system (CASPER). CASPER generates a flight plan to cover the alerted fire area and executes the flight plan. The onboard processor generates the fuel load map from raw radar data, used with wind and elevation information, predicts the likely fire progression. CASPER then autonomously alters the flight plan to track the fire progression, providing this information to the fire fighting team on the ground. We can also relay the precise fire location to other remote sensing assets with autonomous response capability such as Earth Observation-1 (EO-1)'s hyper-spectral imager to acquire the fire data.

Comparing effects of fire modeling methods on simulated fire patterns and succession: a case study in the Missouri Ozarks

Treesearch

Jian Yang; Hong S. He; Brian R. Sturtevant; Brian R. Miranda; Eric J. Gustafson

2008-01-01

We compared four fire spread simulation methods (completely random, dynamic percolation. size-based minimum travel time algorithm. and duration-based minimum travel time algorithm) and two fire occurrence simulation methods (Poisson fire frequency model and hierarchical fire frequency model) using a two-way factorial design. We examined these treatment effects on...

Fire and Smoke Monitoring at NOAA' Satellite Service; Applications to Smoke Forecasting

NASA Astrophysics Data System (ADS)

Stephens, G.; Ruminski, M.

2005-12-01

The Hazard Mapping System (HMS), developed and run operationally by NOAA's Satellite Services Division (SSD), is a multiplatform remote sensing approach to detecting fires and smoke over the US and adjacent areas of Canada and Mexico. The system utilizes sensors on 7 different NOAA and NASA satellites. Automated detection algorithms are employed for each of the satellites for the fire detects while smoke is delineated by an image analyst. Analyses are quality control by an analyst who inspects all available imagery and automated fire detects, deleting suspected false detects and adding fires that the automated routines miss. Graphical, text, and GIS compatible analyses are posted to a web site as soon as updates are performed, and a final product for a given day is posted early the following morning. All products are archived at NOAA's National Geophysical Data Center. Areal extent of detectable smoke is outlined using animated visible imagery, for input to a dispersion and transport model, the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT), developed by NOAA's Air Resources Laboratory (ARL). Resulting smoke forecasts will soon be used as input to NOAA's Air Quality forecasts. The GOES Aerosol and Smoke Product (GASP) is an experimental GOES imagery based aerosol optical depth (AOD) product developed by the NESDIS Office of Research and Applications, being implemented for evaluation by the NESDIS Satellite Analysis Branch for use in smoke and volcanic ash monitoring. Currently, research is underway in NESDIS' Office of Research and Applications to objectivize smoke delineation using GASP and MODIS AOD retrievals. NOAA's Operational Significant Event Imagery (OSEI) program processes satellite imagery of environmentally significant events, including fire, smoke and volcanic ash, visible in operational satellite data. This imagery is often referred to by fire managers and air quality agencies. Future plans include the integration of high resolution global data from the European Space Agency's MetOp satellite and global geostationary satellites.

Remote Sensing of Fires and Smoke from the Earth Observing System MODIS Instrument

NASA Technical Reports Server (NTRS)

Kaufman, Y. J.; Hao, W. M.; Justice, C.; Giglio, L.; Herring, D.; Einaudi, Franco (Technical Monitor)

2001-01-01

The talk will include review of the MODIS (Moderate Resolution Imaging Spectrometer) algorithms and performance e.g. the MODIS algorithm and the changes in the algorithm since launch. Comparison of MODIS and ASTER fire observations. Summary of the fall activity with the Forest Service in use of MODIS data for the fires in the North-West. Validation on the ground of the MODIS fire product.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Burned area detection based on Landsat time series in savannas of southern Burkina Faso

NASA Astrophysics Data System (ADS)

Liu, Jinxiu; Heiskanen, Janne; Maeda, Eduardo Eiji; Pellikka, Petri K. E.

2018-02-01

West African savannas are subject to regular fires, which have impacts on vegetation structure, biodiversity and carbon balance. An efficient and accurate mapping of burned area associated with seasonal fires can greatly benefit decision making in land management. Since coarse resolution burned area products cannot meet the accuracy needed for fire management and climate modelling at local scales, the medium resolution Landsat data is a promising alternative for local scale studies. In this study, we developed an algorithm for continuous monitoring of annual burned areas using Landsat time series. The algorithm is based on burned pixel detection using harmonic model fitting with Landsat time series and breakpoint identification in the time series data. This approach was tested in a savanna area in southern Burkina Faso using 281 images acquired between October 2000 and April 2016. An overall accuracy of 79.2% was obtained with balanced omission and commission errors. This represents a significant improvement in comparison with MODIS burned area product (67.6%), which had more omission errors than commission errors, indicating underestimation of the total burned area. By observing the spatial distribution of burned areas, we found that the Landsat based method misclassified cropland and cloud shadows as burned areas due to the similar spectral response, and MODIS burned area product omitted small and fragmented burned areas. The proposed algorithm is flexible and robust against decreased data availability caused by clouds and Landsat 7 missing lines, therefore having a high potential for being applied in other landscapes in future studies.

A Total Validation Approach for assessing the RST technique in forest fire detection and monitoring

NASA Astrophysics Data System (ADS)

Mazzeo, Giuseppe; Baldassarre, Giuseppe; Corrado, Rosita; Filizzola, Carolina; Genzano, Nicola; Marchese, Francesco; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2010-05-01

Several studies have shown that high temporal resolution sensors such as AVHRR (Advanced Very High Resolution Radiometer) aboard NOAA (National Oceanic and Atmospheric Administration) satellites, MODIS (Moderate Resolution Imaging Spectroradiometer) aboard EOS (Earth Observing System) satellites and, more recently, SEVIRI (Spinning Enhanced Visible and Infrared Imager) aboard MSG (Meteosat Second Generation) platforms, are suitable for detecting and monitoring forest fires. At the same time, many satellite-based techniques have been proposed for fire detection, but most of them, based on single image fixed-thresholds, often generate false alarms mainly due to the contribution of the reflected solar radiation in daytime, atmospheric effects, etc., so that they result to have scarce reliability when applied in an operational scenario. Other algorithms, which are quite reliable thanks to their multitemporal and/or contextual nature, may turn out to be hardly applicable so that they cannot be inserted in whatever operative schemes. An innovative approach, named RST - Robust Satellite Technique, already applied for the monitoring of major natural and environmental risks has been recently used for fire detection and monitoring. The RST approach is based on local (in space and time) thresholds which are automatically computed on the basis of long temporal series of satellite data. It demonstrated already good performances in many cases of applications, but recently for the first time a total validation approach (TVA) was experimented in collaboration with administrators, decision makers and local agencies, in order to evaluate the actual reliability and sensitivity of RST in a pre-operational context. TVA, based on a systematic study of the origin of each hot spot identified by RST, allowed us to recognize most of them as actual thermal anomalies (associated to small fires, to variations of thermal emission in industrial plants, etc.) and not as false alarms simply because not associated to officially documented forest fires. Some results of recent campaigns both of winter and summer fire detection and monitoring in Italy will be shown and discussed.

Linear Aerospike SR-71 Experiment (LASRE): Aerospace Propulsion Hazard Mitigation Systems

NASA Technical Reports Server (NTRS)

Mizukami, Masashi; Corpening, Griffin P.; Ray, Ronald J.; Hass, Neal; Ennix, Kimberly A.; Lazaroff, Scott M.

1998-01-01

A major hazard posed by the propulsion system of hypersonic and space vehicles is the possibility of fire or explosion in the vehicle environment. The hazard is mitigated by minimizing or detecting, in the vehicle environment, the three ingredients essential to producing fire: fuel, oxidizer, and an ignition source. The Linear Aerospike SR-71 Experiment (LASRE) consisted of a linear aerospike rocket engine integrated into one-half of an X-33-like lifting body shape, carried on top of an SR-71 aircraft. Gaseous hydrogen and liquid oxygen were used as propellants. Although LASRE is a one-of-a-kind experimental system, it must be rated for piloted flight, so this test presented a unique challenge. To help meet safety requirements, the following propulsion hazard mitigation systems were incorporated into the experiment: pod inert purge, oxygen sensors, a hydrogen leak detection algorithm, hydrogen sensors, fire detection and pod temperature thermocouples, water misting, and control room displays. These systems are described, and their development discussed. Analyses, ground test, and flight test results are presented, as are findings and lessons learned.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery.

PubMed

Zhao, Yi; Ma, Jiale; Li, Xiaohui; Zhang, Jie

2018-02-27

An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset 'UAV_Fire'. A 15-layered self-learning DCNN architecture named 'Fire_Net' is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, 'Fire_Net' guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.

Coverability graphs for a class of synchronously executed unbounded Petri net

NASA Technical Reports Server (NTRS)

Stotts, P. David; Pratt, Terrence W.

1990-01-01

After detailing a variant of the concurrent-execution rule for firing of maximal subsets, in which the simultaneous firing of conflicting transitions is prohibited, an algorithm is constructed for generating the coverability graph of a net executed under this synchronous firing rule. The omega insertion criteria in the algorithm are shown to be valid for any net on which the algorithm terminates. It is accordingly shown that the set of nets on which the algorithm terminates includes the 'conflict-free' class.

Object-based Forest Fire Analysis for Pedrógão Grande Fire Using Landsat 8 OLI and Sentinel-2A Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2017-12-01

Forest fires are among the most important natural disasters with the damage to the natural habitat and human-life. Mapping damaged forest fires is crucial for assessing ecological effects caused by fire, monitoring land cover changes and modeling atmospheric and climatic effects of fire. In this context, satellite data provides a great advantage to users by providing a rapid process of detecting burning areas and determining the severity of fire damage. Especially, Mediterranean ecosystems countries sets the suitable conditions for the forest fires. In this study, the determination of burnt areas of forest fire in Pedrógão Grande region of Portugal occurred in June 2017 was carried out using Landsat 8 OLI and Sentinel-2A satellite images. The Pedrógão Grande fire was one of the largest fires in Portugal, more than 60 people was killed and thousands of hectares were ravaged. In this study, four pairs of pre-fire and post-fire top of atmosphere (TOA) and atmospherically corrected images were utilized. The red and near infrared (NIR) spectral bands of pre-fire and post-fire images were stacked and multiresolution segmentation algorithm was applied. In the segmentation processes, the image objects were generated with estimated optimum homogeneity criteria. Using eCognition software, rule sets have been created to distinguish unburned areas from burned areas. In constructing the rule sets, NDVI threshold values were determined pre- and post-fire and areas where vegetation loss was detected using the NDVI difference image. The results showed that both satellite images yielded successful results for burned area discrimination with a very high degree of consistency in terms of spatial overlap and total burned area (over 93%). Object based image analysis (OBIA) was found highly effective in delineation of burnt areas.

Orion MPCV Touchdown Detection Threshold Development and Testing

NASA Technical Reports Server (NTRS)

Daum, Jared; Gay, Robert

2013-01-01

A robust method of detecting Orion Multi ]Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post ]landing segment of the Flight Software (FSW). The vehicle crew is the prime input for touchdown detection, followed by an autonomous FSW algorithm, and finally a strictly time based backup timer. RCS thrusters must be inhibited before submersion in water to protect against possible damage due to firing these jets under water. In addition, neglecting to declare touchdown will not allow the vehicle to transition to post ]landing activities such as activating the Crew Module Up ]righting System (CMUS), resulting in possible loss of communication and difficult recovery. A previous AIAA paper gAssessment of an Automated Touchdown Detection Algorithm for the Orion Crew Module h concluded that a strictly Inertial Measurement Unit (IMU) based detection method using an acceleration spike algorithm had the highest safety margins and shortest detection times of other methods considered. That study utilized finite element simulations of vehicle splashdown, generated by LS ]DYNA, which were expanded to a larger set of results using a Kriging surface fit. The study also used the Decelerator Systems Simulation (DSS) to generate flight dynamics during vehicle descent under parachutes. Proto ]type IMU and FSW MATLAB models provided the basis for initial algorithm development and testing. This paper documents an in ]depth trade study, using the same dynamics data and MATLAB simulations as the earlier work, to further develop the acceleration detection method. By studying the combined effects of data rate, filtering on the rotational acceleration correction, data persistence limits and values of acceleration thresholds, an optimal configuration was determined. The lever arm calculation, which removes the centripetal acceleration caused by vehicle rotation, requires that the vehicle angular acceleration be derived from vehicle body rates, necessitating the addition of a 2nd order filter to smooth the data. It was determined that using 200 Hz data directly from the vehicle IMU outperforms the 40 Hz FSW data rate. Data persistence counter values and acceleration thresholds were balanced in order to meet desired safety and performance. The algorithm proved to exhibit ample safety margin against early detection while under parachutes, and adequate performance upon vehicle splashdown. Fall times from algorithm initiation were also studied, and a backup timer length was chosen to provide a large safety margin, yet still trigger detection before CMUS inflation. This timer serves as a backup to the primary acceleration detection method. Additionally, these parameters were tested for safety on actual flight test data, demonstrating expected safety margins.

Forest fire autonomous decision system based on fuzzy logic

NASA Astrophysics Data System (ADS)

Lei, Z.; Lu, Jianhua

2010-11-01

The proposed system integrates GPS / pseudolite / IMU and thermal camera in order to autonomously process the graphs by identification, extraction, tracking of forest fire or hot spots. The airborne detection platform, the graph-based algorithms and the signal processing frame are analyzed detailed; especially the rules of the decision function are expressed in terms of fuzzy logic, which is an appropriate method to express imprecise knowledge. The membership function and weights of the rules are fixed through a supervised learning process. The perception system in this paper is based on a network of sensorial stations and central stations. The sensorial stations collect data including infrared and visual images and meteorological information. The central stations exchange data to perform distributed analysis. The experiment results show that working procedure of detection system is reasonable and can accurately output the detection alarm and the computation of infrared oscillations.

AF-DHNN: Fuzzy Clustering and Inference-Based Node Fault Diagnosis Method for Fire Detection

PubMed Central

Jin, Shan; Cui, Wen; Jin, Zhigang; Wang, Ying

2015-01-01

Wireless Sensor Networks (WSNs) have been utilized for node fault diagnosis in the fire detection field since the 1990s. However, the traditional methods have some problems, including complicated system structures, intensive computation needs, unsteady data detection and local minimum values. In this paper, a new diagnosis mechanism for WSN nodes is proposed, which is based on fuzzy theory and an Adaptive Fuzzy Discrete Hopfield Neural Network (AF-DHNN). First, the original status of each sensor over time is obtained with two features. One is the root mean square of the filtered signal (FRMS), the other is the normalized summation of the positive amplitudes of the difference spectrum between the measured signal and the healthy one (NSDS). Secondly, distributed fuzzy inference is introduced. The evident abnormal nodes’ status is pre-alarmed to save time. Thirdly, according to the dimensions of the diagnostic data, an adaptive diagnostic status system is established with a Fuzzy C-Means Algorithm (FCMA) and Sorting and Classification Algorithm to reducing the complexity of the fault determination. Fourthly, a Discrete Hopfield Neural Network (DHNN) with iterations is improved with the optimization of the sensors’ detected status information and standard diagnostic levels, with which the associative memory is achieved, and the search efficiency is improved. The experimental results show that the AF-DHNN method can diagnose abnormal WSN node faults promptly and effectively, which improves the WSN reliability. PMID:26193280

Satellite change detection of forest damage near the Chernobyl accident

DOE Office of Scientific and Technical Information (OSTI.GOV)

McClellan, G.E.; Anno, G.H.

1992-01-01

A substantial amount of forest within a few kilometers of the Chernobyl nuclear reactor station was badly contaminated with radionuclides by the April 26, 1986, explosion and ensuing fire at reactor No. 4. Radiation doses to conifers in some areas were sufficient to cause discoloration of needles within a few weeks. Other areas, receiving smaller doses, showed foliage changes beginning 6 months to a year later. Multispectral imagery available from Landsat sensors is especially suited for monitoring such changes in vegetation. A series of Landsat Thematic Mapper images was developed that span the 2 yr following the accident. Quantitative dosemore » estimation for the exposed conifers requires an objective change detection algorithm and knowledge of the dose-time response of conifers to ionizing radiation. Pacific-Sierra Research Corporation's Hyperscout{trademark} algorithm is based on an advanced, sensitive technique for change detection particularly suited for multispectral images. The Hyperscout algorithm has been used to assess radiation damage to the forested areas around the Chernobyl nuclear power plant.« less

Impacts of Wildfires on Long-term Land Surface Phenology

NASA Astrophysics Data System (ADS)

Wang, J.; Zhang, X.

2016-12-01

Land surface phenology (LSP) detected from satellite data characterizes seasonal dynamics of vegetation communities within a moderate or coarse resolution pixel. Its long-term variation has been widely used to indicate the biological responses to climate changes. However, few studies have focused on the influence of land disturbance on LSP variations. The wildfire is one of the most important drivers of land disturbances across the world, which shows an increasing trend during past decades. To explore the wildfire impacts on LSP, we analyzed post-fire and pre-fire LSP in two forest fire events that are Hayman Fire occurred in 2002 and Mason Fire occurred in 2005 in Colorado. Specifically, we first generated a two band enhanced vegetation index (EVI2) from MODIS daily surface reflectance product (MOD09GQ) at a spatial resolution of 250 m from 2001-2014. The time series of daily EVI2 was then used to detect the start of growing season (SOS) by applying the LSP detection algorithm based on a hybrid piecewise logistic model (HPLM-LSPD). The SOS was further separated for four levels of burn severity obtained from Monitoring Trends in Burn Severity (MTBS) maps for each fire event. The long-term SOS in the burn scars was finally deviated from surrounding areas based on land cover types. Results show that forests were mainly converted to shrubs in both fire events with some grasslands in Hayman. On average, SOS in Hayman burn scar area was advanced 11 days relative to surrounding region while it was delayed 9 days in Mason fire. The deviation also varied with the burn severity spatially. Moreover, the long-term SOS trend in the local area from 2001-2014 was significantly different with and without considerations of the fire influences. This study demonstrates that the long-term LSP SOS trend is significantly influenced by land disturbances in a local and regional scales.

Saliency Detection and Deep Learning-Based Wildfire Identification in UAV Imagery

PubMed Central

Zhao, Yi; Ma, Jiale; Li, Xiaohui

2018-01-01

An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset ‘UAV_Fire’. A 15-layered self-learning DCNN architecture named ‘Fire_Net’ is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, ‘Fire_Net’ guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified. PMID:29495504

A novel approach for fire recognition using hybrid features and manifold learning-based classifier

NASA Astrophysics Data System (ADS)

Zhu, Rong; Hu, Xueying; Tang, Jiajun; Hu, Sheng

2018-03-01

Although image/video based fire recognition has received growing attention, an efficient and robust fire detection strategy is rarely explored. In this paper, we propose a novel approach to automatically identify the flame or smoke regions in an image. It is composed to three stages: (1) a block processing is applied to divide an image into several nonoverlapping image blocks, and these image blocks are identified as suspicious fire regions or not by using two color models and a color histogram-based similarity matching method in the HSV color space, (2) considering that compared to other information, the flame and smoke regions have significant visual characteristics, so that two kinds of image features are extracted for fire recognition, where local features are obtained based on the Scale Invariant Feature Transform (SIFT) descriptor and the Bags of Keypoints (BOK) technique, and texture features are extracted based on the Gray Level Co-occurrence Matrices (GLCM) and the Wavelet-based Analysis (WA) methods, and (3) a manifold learning-based classifier is constructed based on two image manifolds, which is designed via an improve Globular Neighborhood Locally Linear Embedding (GNLLE) algorithm, and the extracted hybrid features are used as input feature vectors to train the classifier, which is used to make decision for fire images or non fire images. Experiments and comparative analyses with four approaches are conducted on the collected image sets. The results show that the proposed approach is superior to the other ones in detecting fire and achieving a high recognition accuracy and a low error rate.

Electric-field sensors for bullet detection systems

NASA Astrophysics Data System (ADS)

Vinci, Stephen; Hull, David; Ghionea, Simon; Ludwig, William; Deligeorges, Socrates; Gudmundsson, Thorkell; Noras, Maciej

2014-06-01

Research and experimental trials have shown that electric-field (E-field) sensors are effective at detecting charged projectiles. E-field sensors can likely complement traditional acoustic sensors, and help provide a more robust and effective solution for bullet detection and tracking. By far, the acoustic sensor is the most prevalent technology in use today for hostile fire defeat systems due to compact size and low cost, yet they come with a number of challenges that include multipath, reverberant environments, false positives and low signal-to-noise. Studies have shown that these systems can benefit from additional sensor modalities such as E-field sensors. However, E-field sensors are a newer technology that is relatively untested beyond basic experimental trials; this technology has not been deployed in any fielded systems. The U.S. Army Research Laboratory (ARL) has conducted live-fire experiments at Aberdeen Proving Grounds (APG) to collect data from E-field sensors. Three types of E-field sensors were included in these experiments: (a) an electric potential gradiometer manufactured by Quasar Federal Systems (QFS), (b) electric charge induction, or "D-dot" sensors designed and built by the Army Research Lab (ARL), and (c) a varactor based E-field sensor prototype designed by University of North Carolina-Charlotte (UNCC). Sensors were placed in strategic locations near the bullet trajectories, and their data were recorded. We analyzed the performance of each E-field sensor type in regard to small-arms bullet detection capability. The most recent experiment in October 2013 allowed demonstration of improved versions of the varactor and D-dot sensor types. Results of new real-time analysis hardware employing detection algorithms were also tested. The algorithms were used to process the raw data streams to determine when bullet detections occurred. Performance among the sensor types and algorithm effectiveness were compared to estimates from acoustics signatures and known ground truth. Results, techniques and configurations that might work best for a given sensor platform are discussed.

Defining pyromes and global syndromes of fire regimes.

PubMed

Archibald, Sally; Lehmann, Caroline E R; Gómez-Dans, Jose L; Bradstock, Ross A

2013-04-16

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes--size, frequency, intensity, season, and extent--and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict.

Defining pyromes and global syndromes of fire regimes

PubMed Central

Archibald, Sally; Lehmann, Caroline E. R.; Gómez-Dans, Jose L.; Bradstock, Ross A.

2013-01-01

Fire is a ubiquitous component of the Earth system that is poorly understood. To date, a global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites. This is problematic because fire is multidimensional, and focus on a single metric belies its complexity and importance within the Earth system. To address this, we identified five key characteristics of fire regimes—size, frequency, intensity, season, and extent—and combined new and existing global datasets to represent each. We assessed how these global fire regime characteristics are related to patterns of climate, vegetation (biomes), and human activity. Cross-correlations demonstrate that only certain combinations of fire characteristics are possible, reflecting fundamental constraints in the types of fire regimes that can exist. A Bayesian clustering algorithm identified five global syndromes of fire regimes, or pyromes. Four pyromes represent distinctions between crown, litter, and grass-fueled fires, and the relationship of these to biomes and climate are not deterministic. Pyromes were partially discriminated on the basis of available moisture and rainfall seasonality. Human impacts also affected pyromes and are globally apparent as the driver of a fifth and unique pyrome that represents human-engineered modifications to fire characteristics. Differing biomes and climates may be represented within the same pyrome, implying that pathways of change in future fire regimes in response to changes in climate and human activity may be difficult to predict. PMID:23559374

Improvement in detection of small wildfires

NASA Astrophysics Data System (ADS)

Sleigh, William J.

1991-12-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

Improvement in detection of small wildfires

NASA Technical Reports Server (NTRS)

Sleigh, William J.

1991-01-01

Detecting and imaging small wildfires with an Airborne Scanner is done against generally high background levels. The Airborne Scanner System used is a two-channel thermal IR scanner, with one channel selected for imaging the terrain and the other channel sensitive to hotter targets. If a relationship can be determined between the two channels that quantifies the background signal for hotter targets, then an algorithm can be determined that removes the background signal in that channel leaving only the fire signal. The relationship can be determined anywhere between various points in the signal processing of the radiometric data from the radiometric input to the quantized output of the system. As long as only linear operations are performed on the signal, the relationship will only depend on the system gain and offsets within the range of interest. The algorithm can be implemented either by using a look-up table or performing the calculation in the system computer. The current presentation will describe the algorithm, its derivation, and its implementation in the Firefly Wildfire Detection System by means of an off-the-shelf commercial scanner. Improvement over the previous algorithm used and the margin gained for improving the imaging of the terrain will be demonstrated.

An Accurate Fire-Spread Algorithm in the Weather Research and Forecasting Model Using the Level-Set Method

NASA Astrophysics Data System (ADS)

Muñoz-Esparza, Domingo; Kosović, Branko; Jiménez, Pedro A.; Coen, Janice L.

2018-04-01

The level-set method is typically used to track and propagate the fire perimeter in wildland fire models. Herein, a high-order level-set method using fifth-order WENO scheme for the discretization of spatial derivatives and third-order explicit Runge-Kutta temporal integration is implemented within the Weather Research and Forecasting model wildland fire physics package, WRF-Fire. The algorithm includes solution of an additional partial differential equation for level-set reinitialization. The accuracy of the fire-front shape and rate of spread in uncoupled simulations is systematically analyzed. It is demonstrated that the common implementation used by level-set-based wildfire models yields to rate-of-spread errors in the range 10-35% for typical grid sizes (Δ = 12.5-100 m) and considerably underestimates fire area. Moreover, the amplitude of fire-front gradients in the presence of explicitly resolved turbulence features is systematically underestimated. In contrast, the new WRF-Fire algorithm results in rate-of-spread errors that are lower than 1% and that become nearly grid independent. Also, the underestimation of fire area at the sharp transition between the fire front and the lateral flanks is found to be reduced by a factor of ≈7. A hybrid-order level-set method with locally reduced artificial viscosity is proposed, which substantially alleviates the computational cost associated with high-order discretizations while preserving accuracy. Simulations of the Last Chance wildfire demonstrate additional benefits of high-order accurate level-set algorithms when dealing with complex fuel heterogeneities, enabling propagation across narrow fuel gaps and more accurate fire backing over the lee side of no fuel clusters.

MUSIC-Expected maximization gaussian mixture methodology for clustering and detection of task-related neuronal firing rates.

PubMed

Ortiz-Rosario, Alexis; Adeli, Hojjat; Buford, John A

2017-01-15

Researchers often rely on simple methods to identify involvement of neurons in a particular motor task. The historical approach has been to inspect large groups of neurons and subjectively separate neurons into groups based on the expertise of the investigator. In cases where neuron populations are small it is reasonable to inspect these neuronal recordings and their firing rates carefully to avoid data omissions. In this paper, a new methodology is presented for automatic objective classification of neurons recorded in association with behavioral tasks into groups. By identifying characteristics of neurons in a particular group, the investigator can then identify functional classes of neurons based on their relationship to the task. The methodology is based on integration of a multiple signal classification (MUSIC) algorithm to extract relevant features from the firing rate and an expectation-maximization Gaussian mixture algorithm (EM-GMM) to cluster the extracted features. The methodology is capable of identifying and clustering similar firing rate profiles automatically based on specific signal features. An empirical wavelet transform (EWT) was used to validate the features found in the MUSIC pseudospectrum and the resulting signal features captured by the methodology. Additionally, this methodology was used to inspect behavioral elements of neurons to physiologically validate the model. This methodology was tested using a set of data collected from awake behaving non-human primates. Copyright © 2016 Elsevier B.V. All rights reserved.

Ancient village fire escape path planning based on improved ant colony algorithm

NASA Astrophysics Data System (ADS)

Xia, Wei; Cao, Kang; Hu, QianChuan

2017-06-01

The roadways are narrow and perplexing in ancient villages, it brings challenges and difficulties for people to choose route to escape when a fire occurs. In this paper, a fire escape path planning method based on ant colony algorithm is presented according to the problem. The factors in the fire environment which influence the escape speed is introduced to improve the heuristic function of the algorithm, optimal transfer strategy, and adjustment pheromone volatile factor to improve pheromone update strategy adaptively, improve its dynamic search ability and search speed. Through simulation, the dynamic adjustment of the optimal escape path is obtained, and the method is proved to be feasible.

Efficient Constant-Time Complexity Algorithm for Stochastic Simulation of Large Reaction Networks.

PubMed

Thanh, Vo Hong; Zunino, Roberto; Priami, Corrado

2017-01-01

Exact stochastic simulation is an indispensable tool for a quantitative study of biochemical reaction networks. The simulation realizes the time evolution of the model by randomly choosing a reaction to fire and update the system state according to a probability that is proportional to the reaction propensity. Two computationally expensive tasks in simulating large biochemical networks are the selection of next reaction firings and the update of reaction propensities due to state changes. We present in this work a new exact algorithm to optimize both of these simulation bottlenecks. Our algorithm employs the composition-rejection on the propensity bounds of reactions to select the next reaction firing. The selection of next reaction firings is independent of the number reactions while the update of propensities is skipped and performed only when necessary. It therefore provides a favorable scaling for the computational complexity in simulating large reaction networks. We benchmark our new algorithm with the state of the art algorithms available in literature to demonstrate its applicability and efficiency.

A multi-sensor burned area algorithm for crop residue burning in northwestern India: validation and sources of error

NASA Astrophysics Data System (ADS)

Liu, T.; Marlier, M. E.; Karambelas, A. N.; Jain, M.; DeFries, R. S.

2017-12-01

A leading source of outdoor emissions in northwestern India comes from crop residue burning after the annual monsoon (kharif) and winter (rabi) crop harvests. Agricultural burned area, from which agricultural fire emissions are often derived, can be poorly quantified due to the mismatch between moderate-resolution satellite sensors and the relatively small size and short burn period of the fires. Many previous studies use the Global Fire Emissions Database (GFED), which is based on the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MCD64A1, as an outdoor fires emissions dataset. Correction factors with MODIS active fire detections have previously attempted to account for small fires. We present a new burned area classification algorithm that leverages more frequent MODIS observations (500 m x 500 m) with higher spatial resolution Landsat (30 m x 30 m) observations. Our approach is based on two-tailed Normalized Burn Ratio (NBR) thresholds, abbreviated as ModL2T NBR, and results in an estimated 104 ± 55% higher burned area than GFEDv4.1s (version 4, MCD64A1 + small fires correction) in northwestern India during the 2003-2014 winter (October to November) burning seasons. Regional transport of winter fire emissions affect approximately 63 million people downwind. The general increase in burned area (+37% from 2003-2007 to 2008-2014) over the study period also correlates with increased mechanization (+58% in combine harvester usage from 2001-2002 to 2011-2012). Further, we find strong correlation between ModL2T NBR-derived burned area and results of an independent survey (r = 0.68) and previous studies (r = 0.92). Sources of error arise from small median landholding sizes (1-3 ha), heterogeneous spatial distribution of two dominant burning practices (partial and whole field), coarse spatio-temporal satellite resolution, cloud and haze cover, and limited Landsat scene availability. The burned area estimates of this study can be used to build a new agricultural fire emissions inventory to re-evaluate the contributions of winter agricultural fires to rural and urban air quality degradation.

Basis for a neuronal version of Grover's quantum algorithm

PubMed Central

Clark, Kevin B.

2014-01-01

Grover's quantum (search) algorithm exploits principles of quantum information theory and computation to surpass the strong Church–Turing limit governing classical computers. The algorithm initializes a search field into superposed N (eigen)states to later execute nonclassical “subroutines” involving unitary phase shifts of measured states and to produce root-rate or quadratic gain in the algorithmic time (O(N1/2)) needed to find some “target” solution m. Akin to this fast technological search algorithm, single eukaryotic cells, such as differentiated neurons, perform natural quadratic speed-up in the search for appropriate store-operated Ca2+ response regulation of, among other processes, protein and lipid biosynthesis, cell energetics, stress responses, cell fate and death, synaptic plasticity, and immunoprotection. Such speed-up in cellular decision making results from spatiotemporal dynamics of networked intracellular Ca2+-induced Ca2+ release and the search (or signaling) velocity of Ca2+ wave propagation. As chemical processes, such as the duration of Ca2+ mobilization, become rate-limiting over interstore distances, Ca2+ waves quadratically decrease interstore-travel time from slow saltatory to fast continuous gradients proportional to the square-root of the classical Ca2+ diffusion coefficient, D1/2, matching the computing efficiency of Grover's quantum algorithm. In this Hypothesis and Theory article, I elaborate on these traits using a fire-diffuse-fire model of store-operated cytosolic Ca2+ signaling valid for glutamatergic neurons. Salient model features corresponding to Grover's quantum algorithm are parameterized to meet requirements for the Oracle Hadamard transform and Grover's iteration. A neuronal version of Grover's quantum algorithm figures to benefit signal coincidence detection and integration, bidirectional synaptic plasticity, and other vital cell functions by rapidly selecting, ordering, and/or counting optional response regulation choices. PMID:24860419

Cerebellar supervised learning revisited: biophysical modeling and degrees-of-freedom control.

PubMed

Kawato, Mitsuo; Kuroda, Shinya; Schweighofer, Nicolas

2011-10-01

The biophysical models of spike-timing-dependent plasticity have explored dynamics with molecular basis for such computational concepts as coincidence detection, synaptic eligibility trace, and Hebbian learning. They overall support different learning algorithms in different brain areas, especially supervised learning in the cerebellum. Because a single spine is physically very small, chemical reactions at it are essentially stochastic, and thus sensitivity-longevity dilemma exists in the synaptic memory. Here, the cascade of excitable and bistable dynamics is proposed to overcome this difficulty. All kinds of learning algorithms in different brain regions confront with difficult generalization problems. For resolution of this issue, the control of the degrees-of-freedom can be realized by changing synchronicity of neural firing. Especially, for cerebellar supervised learning, the triangle closed-loop circuit consisting of Purkinje cells, the inferior olive nucleus, and the cerebellar nucleus is proposed as a circuit to optimally control synchronous firing and degrees-of-freedom in learning. Copyright © 2011 Elsevier Ltd. All rights reserved.

An Overview of Recent Geostationary Fire Monitoring Activities and Applications in the Western Hemisphere

NASA Astrophysics Data System (ADS)

McRae, D. J.; Conard, S. G.; Ivanova, G. A.; Sukhinin, A. I.; Hao, W. M.; Koutzenogii, K. P.; Prins, E. M.; Schmidt, C. C.; Feltz, J. M.

2002-05-01

Over the past twenty years the international scientific research and environmental monitoring communities have recognized the vital role environmental satellites can play in detecting and monitoring active fires both regionally and around the globe for hazards applications and to better understand the extent and impact of biomass burning on the global environment. Both groups have stressed the importance of utilizing operational satellites to produce routine fire products and to ensure long-term stable records of fire activity for applications such as land-use/land cover change analyses and global climate change research. The current NOAA GOES system provides the unique opportunity to detect fires throughout the Western Hemisphere every half-hour from a series of nearly identical satellites for a period of 15+ years. This presentation will provide an overview of the GOES biomass burning monitoring program at UW-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) with an emphasis on recent applications of the new GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA). For the past 8 years, CIMSS has utilized the GOES-8 imager to monitor biomass burning trends in South America. Since September 2000, CIMSS has been producing half-hourly fire products in real-time for most of the Western Hemisphere. The WF_ABBA half-hourly fire product is providing new insights into diurnal, spatial, seasonal and interannual fire dynamics in North, Central, and South America. In North America these products are utilized to detect and monitor wildfires in northerly and remote locations. In South America the diurnal GOES fire product is being used as an indicator of land-use and land-cover change and carbon dynamics along the borders between Brazil, Peru, and Bolivia. The Navy is assimilating the Wildfire ABBA fire product into the Navy Aerosol Analysis and Prediction System (NAAPS) to analyze and predict aerosol loading and transport as part of the NASA-ESE Fire Locating And Mapping of Burning Emissions (FLAMBE) project. Furthermore, the dissemination and use of geostationary imagery and derived fire products in the Western Hemisphere provide a glimpse of future global geostationary fire monitoring capabilities. Global geostationary active fire monitoring will be possible with the launch of the European METEOSAT (METEOrological SATellite) Second Generation (MSG) and the replacement Japanese Multi-functional Transport Satellite (MTSAT-1R) over the next two years. This global network of geostationary satellites will complement the U.S. and international suite of environmental polar-orbiting satellites.

Single vs. dual color fire detection systems: operational tradeoffs

NASA Astrophysics Data System (ADS)

Danino, Meir; Danan, Yossef; Sinvani, Moshe

2017-10-01

In attempt to supply a reasonable fire plume detection, multinational cooperation with significant capital is invested in the development of two major Infra-Red (IR) based fire detection alternatives, single-color IR (SCIR) and dual-color IR (DCIR). False alarm rate was expected to be high not only as a result of real heat sources but mainly due to the IR natural clutter especially solar reflections clutter. SCIR uses state-of-the-art technology and sophisticated algorithms to filter out threats from clutter. On the other hand, DCIR are aiming at using additional spectral band measurements (acting as a guard), to allow the implementation of a simpler and more robust approach for performing the same task. In this paper we present the basics of SCIR & DCIR architecture and the main differences between them. In addition, we will present the results from a thorough study conducted for the purpose of learning about the added value of the additional data available from the second spectral band. Here we consider the two CO2 bands of 4-5 micron and of 2.5-3 micron band as well as off peak band (guard). The findings of this study refer also to Missile warning systems (MWS) efficacy, in terms of operational value. We also present a new approach for tunable filter to such sensor.

Sociable Interfaces

DTIC Science & Technology

2005-01-01

Interface Compatibility); the tool is written in Ocaml [10], and the symbolic algorithms for interface compatibility and refinement are built on top...automata for a fire detection and reporting system. be encoded in the input language of the tool TIC. The refinement of sociable interfaces is discussed...are closely related to the I/O Automata Language (IOA) of [11]. Interface models are games between Input and Output, and in the models, it is es

A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2015-01-01

The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.

Detection rates of the MODIS active fire product in the United States

USGS Publications Warehouse

Hawbaker, T.J.; Radeloff, V.C.; Syphard, A.D.; Zhu, Z.; Stewart, S.I.

2008-01-01

MODIS active fire data offer new information about global fire patterns. However, uncertainties in detection rates can render satellite-derived fire statistics difficult to interpret. We evaluated the MODIS 1??km daily active fire product to quantify detection rates for both Terra and Aqua MODIS sensors, examined how cloud cover and fire size affected detection rates, and estimated how detection rates varied across the United States. MODIS active fire detections were compared to 361 reference fires (??? 18??ha) that had been delineated using pre- and post-fire Landsat imagery. Reference fires were considered detected if at least one MODIS active fire pixel occurred within 1??km of the edge of the fire. When active fire data from both Aqua and Terra were combined, 82% of all reference fires were found, but detection rates were less for Aqua and Terra individually (73% and 66% respectively). Fires not detected generally had more cloudy days, but not when the Aqua data were considered exclusively. MODIS detection rates decreased with fire size, and the size at which 50% of all fires were detected was 105??ha when combining Aqua and Terra (195??ha for Aqua and 334??ha for Terra alone). Across the United States, detection rates were greatest in the West, lower in the Great Plains, and lowest in the East. The MODIS active fire product captures large fires in the U.S. well, but may under-represent fires in areas with frequent cloud cover or rapidly burning, small, and low-intensity fires. We recommend that users of the MODIS active fire data perform individual validations to ensure that all relevant fires are included. ?? 2008 Elsevier Inc. All rights reserved.

An update on The Hazard Mapping System (HMS) - a multiplatform remote sensing approach to fire and smoke detection

NASA Astrophysics Data System (ADS)

Kibler, J. M.; Ruminski, M. G.; Simko, J. J.; McNamara, D. P.; Kasheta, T.

2004-12-01

The Hazard Mapping System (HMS) is a multiplatform remote sensing approach to detecting fires and smoke over the US, Canada, Mexico and Central America. This system is an integral part of the Satellite Services Division's near realtime hazards detection and mitigation efforts. The system utilizes NOAA's Geostationary Operational Environmental Satellites (GOES), Polar Operational Environmental Satellites (POES), the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Terra and Aqua spacecraft and the Defense Meteorological Satellite Program Operational Linescan System (OLS) sensor, (F14 and F15). Automated detection algorithms are employed for each of the satellites (except DMSP OLS) for the fire detects while smoke is annotated by a satellite analyst. Fire detects can also be added by the satellite analyst. Major customers for this product include the National Weather Service, Storm Prediction Center, US Forest Service, Environmental Protection Agency, research science teams, as well as numerous federal, state and local land and air quality managers. In 2004 the HMS was upgraded by adding the Canadian, Mexican, and Central American sectors for hotspot and smoke detection. These sectors can be easily turned off or on by changing flags in the system configuration file. This enables analysis in sectors only during their respective burning seasons. The Alaskan and Canadian sectors are typically turned off in the winter season and the Mexican sector is cut off after the March-May burning season. But sectors can also be easily added or restarted if, for instance, smoke from a region is affecting the United States. Various ancillary data sources are used in the HMS to aid the analysis. Stable Lights is a static product that identifies stable sources of light from the OLS sensor and is usually associated with cities and urban areas. It appears on the screen as a transparent overlay on the satellite imagery being displayed. This capability can assist the analyst by screening out heat sources where stable lights are present. Vegetation type and water overlays aid in the decision to add or delete a fire point. Water sources many times may cause false detects due to low sun zenith angles during sunrise and sunset or due to temperature contrast between land and water at night. This overlay aides in quickly finding these false detects. Vegetation overlays enable the analyst by showing what type of land is present near the hotspot in question. For example, fires are more likely in forest or grassland than desert or barren lands. The SSD fire team is currently assessing the feasibility of a descriptive smoke text product and would like to incorporate additional datasets for the monitoring of fires, smoke, dust, and air pollution. The HMS is a dynamic product that changes with the needs of our analysts and customers.

Mapping burned areas using dense time-series of Landsat data

USGS Publications Warehouse

Hawbaker, Todd J.; Vanderhoof, Melanie; Beal, Yen-Ju G.; Takacs, Joshua; Schmidt, Gail L.; Falgout, Jeff T.; Williams, Brad; Brunner, Nicole M.; Caldwell, Megan K.; Picotte, Joshua J.; Howard, Stephen M.; Stitt, Susan; Dwyer, John L.

2017-01-01

Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, in many areas existing fire occurrence datasets are known to be incomplete. Consequently, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables (ECVs), including information about burned area. In this paper, we present an algorithm that identifies burned areas in dense time-series of Landsat data to produce the Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm uses gradient boosted regression models to generate burn probability surfaces using band values and spectral indices from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Burn classifications are generated from the burn probability surfaces using pixel-level thresholding in combination with a region growing process. The algorithm can be applied anywhere Landsat and training data are available. For this study, BAECV products were generated for the conterminous United States from 1984 through 2015. These products consist of pixel-level burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability and a burn classification. We compared the BAECV burn classification products to the existing Global Fire Emissions Database (GFED; 1997–2015) and Monitoring Trends in Burn Severity (MTBS; 1984–2013) data. We found that the BAECV products mapped 36% more burned area than the GFED and 116% more burned area than MTBS. Differences between the BAECV products and the GFED were especially high in the West and East where the BAECV products mapped 32% and 88% more burned area, respectively. However, the BAECV products found less burned area than the GFED in regions with frequent agricultural fires. Compared to the MTBS data, the BAECV products identified 31% more burned area in the West, 312% more in the Great Plains, and 233% more in the East. Most pixels in the MTBS data were detected by the BAECV, regardless of burn severity. The BAECV products document patterns of fire similar to those in the GFED but also showed patterns of fire that are not well characterized by the existing MTBS data. We anticipate the BAECV products will be useful to studies that seek to understand past patterns of fire occurrence, the drivers that created them, and the impacts fires have on natural and human systems.

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

Investigation of a novel image segmentation method dedicated to forest fire applications

NASA Astrophysics Data System (ADS)

Rudz, S.; Chetehouna, K.; Hafiane, A.; Laurent, H.; Séro-Guillaume, O.

2013-07-01

To face fire it is crucial to understand its behaviour in order to maximize fighting means. To achieve this task, the development of a metrological tool is necessary for estimating both geometrical and physical parameters involved in forest fire modelling. A key parameter is to estimate fire positions accurately. In this paper an image processing tool especially dedicated to an accurate extraction of fire from an image is presented. In this work, the clustering on several colour spaces is investigated and it appears that the blue chrominance Cb from the YCbCr colour space is the most appropriate. As a consequence, a new segmentation algorithm dedicated to forest fire applications has been built using first an optimized k-means clustering in the Cb-channel and then some properties of fire pixels in the RGB colour space. Next, the performance of the proposed method is evaluated using three supervised evaluation criteria and then compared to other existing segmentation algorithms in the literature. Finally a conclusion is drawn, assessing the good behaviour of the developed algorithm. This paper is dedicated to the memory of Dr Olivier Séro-Guillaume (1950-2013), CNRS Research Director.

Geometry-Of-Fire Tracking Algorithm for Direct-Fire Weapon Systems

DTIC Science & Technology

2015-09-01

this specific application. A scaled-down version for a fire team was created with XBee Pro radios, Arduino Uno microcontrollers, Raspberry Pi computers...constructed with XBee Pro radios, Arduino Uno microcontrollers, Raspberry Pi computers and ROS [5]. The XBee Pro radios and Arduino Uno microcontrollers...communicated the positional data of each node as shown in Figure 4, and the Raspberry Pi computers and ROS executed the tracking algorithm and allowed

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-05-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: a level-set-based fire propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the non-linearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially-uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based data assimilation algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically-generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of data assimilation strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 7 2013-10-01 2013-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 7 2012-10-01 2012-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 7 2011-10-01 2011-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 7 2014-10-01 2014-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 193.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 7 2010-10-01 2010-10-01 false Fire detecting, manual alarm, and supervised patrol...) OCEANOGRAPHIC RESEARCH VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 193.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Fire detecting, manual alarm, and supervised patrol... AND MISCELLANEOUS VESSELS FIRE PROTECTION EQUIPMENT Fire Detecting and Extinguishing Equipment, Where Required § 95.05-1 Fire detecting, manual alarm, and supervised patrol systems. (a) Fire detecting, manual...

Fire Fighting Task Force (FIRE)

DTIC Science & Technology

1989-04-01

and fdenify by block number) ~’This study is part of ~a contining effort to develop soldier data and performance algorithms (pergorithus) needed to...similar to combat, results will be useful in developing algorithms and data for use in US Army Concepts Analysis Agency (CAA) combat models. THE...dimensions. The US Army Concepts Analysis Agency (CAA) is committed to adding the soldier variables and algorithms that are necessary to fully represent

Climate Impacts of Fire-Induced Land-Surface Changes

NASA Astrophysics Data System (ADS)

Liu, Y.; Hao, X.; Qu, J. J.

2017-12-01

One of the consequences of wildfires is the changes in land-surface properties such as removal of vegetation. This will change local and regional climate through modifying the land-air heat and water fluxes. This study investigates mechanism by developing and a parameterization of fire-induced land-surface property changes and applying it to modeling of the climate impacts of large wildfires in the United States. Satellite remote sensing was used to quantitatively evaluate the land-surface changes from large fires provided from the Monitoring Trends in Burning Severity (MTBS) dataset. It was found that the changes in land-surface properties induced by fires are very complex, depending on vegetation type and coverage, climate type, season and time after fires. The changes in LAI are remarkable only if the actual values meet a threshold. Large albedo changes occur in winter for fires in cool climate regions. The signs are opposite between the first post-fire year and the following years. Summer day-time temperature increases after fires, while nigh-time temperature changes in various patterns. The changes are larger in forested lands than shrub / grassland lands. In the parameterization scheme, the detected post-fire changes are decomposed into trends using natural exponential functions and fluctuations of periodic variations with the amplitudes also determined by natural exponential functions. The final algorithm is a combination of the trends, periods, and amplitude functions. This scheme is used with Earth system models to simulate the local and regional climate effects of wildfires.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer

NASA Astrophysics Data System (ADS)

Bredfeldt, Jeremy S.; Liu, Yuming; Pehlke, Carolyn A.; Conklin, Matthew W.; Szulczewski, Joseph M.; Inman, David R.; Keely, Patricia J.; Nowak, Robert D.; Mackie, Thomas R.; Eliceiri, Kevin W.

2014-01-01

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.

Spatio-temporal clustering of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.

2012-04-01

Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.

Fire Monitoring from the New Generation of US Polar and Geostationary Satellites

NASA Astrophysics Data System (ADS)

Csiszar, I.; Justice, C. O.; Prins, E.; Schroeder, W.; Schmidt, C.; Giglio, L.

2012-04-01

Sensors on the new generation of US operational environmental satellites will provide measurements suitable for active fire detection and characterization. The NPOESS Preparatory Project (NPP) satellite, launched on October 28, 2011, carries the Visible Infrared Imager Radiometer Suite (VIIRS), which is expected to continue the active fire data record from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Terra and Aqua Satellites. Early evaluation of the VIIRS active fire product, including comparison to near-simultaneous MODIS data, is underway. The new generation of Geostationary Operational Environmental Satellite (GOES) series, starting with GOES-R to be launched in 2015, will carry the Advanced Baseline Imager (ABI), providing higher spatial and temporal resolution than the current GOES imager. The ABI will also include a dedicated band to provide radiance observations over a wider dynamic range to detect and characterize hot targets. In this presentation we discuss details of the monitoring capabilities from both VIIRS and ABI and the current status of the corresponding algorithm development and testing efforts. An integral part of this activity is explicit product validation, utilizing high resolution satellite and airborne imagery as reference data. The new capabilities also represent challenges to establish continuity with data records from heritage missions, and to coordinate compatible international missions towards a global multi-platform fire monitoring system. These objectives are pursued by the Fire Mapping and Monitoring Implementation Team of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) program, which also provides coordinated contribution to relevant initiatives by the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS) and the Global Climate Observing System (GCOS).

Wildland fire management. Volume 2: Wildland fire control 1985-1995. [satellite information system for California fire problems

NASA Technical Reports Server (NTRS)

Saveker, D. R. (Editor)

1973-01-01

The preliminary design of a satellite plus computer earth resources information system is proposed for potential uses in fire prevention and control in the wildland fire community. Suggested are satellite characteristics, sensor characteristics, discrimination algorithms, data communication techniques, data processing requirements, display characteristics, and costs in achieving the integrated wildland fire information system.

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

Simulation of biochemical reactions with time-dependent rates by the rejection-based algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thanh, Vo Hong, E-mail: vo@cosbi.eu; Priami, Corrado, E-mail: priami@cosbi.eu; Department of Mathematics, University of Trento, Trento

We address the problem of simulating biochemical reaction networks with time-dependent rates and propose a new algorithm based on our rejection-based stochastic simulation algorithm (RSSA) [Thanh et al., J. Chem. Phys. 141(13), 134116 (2014)]. The computation for selecting next reaction firings by our time-dependent RSSA (tRSSA) is computationally efficient. Furthermore, the generated trajectory is exact by exploiting the rejection-based mechanism. We benchmark tRSSA on different biological systems with varying forms of reaction rates to demonstrate its applicability and efficiency. We reveal that for nontrivial cases, the selection of reaction firings in existing algorithms introduces approximations because the integration of reactionmore » rates is very computationally demanding and simplifying assumptions are introduced. The selection of the next reaction firing by our approach is easier while preserving the exactness.« less

A Novel and Simple Spike Sorting Implementation.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2017-04-01

Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.

Identifying persistent and characteristic features in firearm tool marks on cartridge cases

NASA Astrophysics Data System (ADS)

Ott, Daniel; Soons, Johannes; Thompson, Robert; Song, John

2017-12-01

Recent concerns about subjectivity in forensic firearm identification have motivated the development of algorithms to compare firearm tool marks that are imparted on ammunition and to generate quantitative measures of similarity. In this paper, we describe an algorithm that identifies impressed tool marks on a cartridge case that are both consistent between firings and contribute strongly to a surface similarity metric. The result is a representation of the tool mark topography that emphasizes both significant and persistent features across firings. This characteristic surface map is useful for understanding the variability and persistence of the tool marks created by a firearm and can provide improved discrimination between the comparison scores of samples fired from the same firearm and the scores of samples fired from different firearms. The algorithm also provides a convenient method for visualizing areas of similarity that may be useful in providing quantitative support for visual comparisons by trained examiners.

A General and Efficient Method for Incorporating Precise Spike Times in Globally Time-Driven Simulations

PubMed Central

Hanuschkin, Alexander; Kunkel, Susanne; Helias, Moritz; Morrison, Abigail; Diesmann, Markus

2010-01-01

Traditionally, event-driven simulations have been limited to the very restricted class of neuronal models for which the timing of future spikes can be expressed in closed form. Recently, the class of models that is amenable to event-driven simulation has been extended by the development of techniques to accurately calculate firing times for some integrate-and-fire neuron models that do not enable the prediction of future spikes in closed form. The motivation of this development is the general perception that time-driven simulations are imprecise. Here, we demonstrate that a globally time-driven scheme can calculate firing times that cannot be discriminated from those calculated by an event-driven implementation of the same model; moreover, the time-driven scheme incurs lower computational costs. The key insight is that time-driven methods are based on identifying a threshold crossing in the recent past, which can be implemented by a much simpler algorithm than the techniques for predicting future threshold crossings that are necessary for event-driven approaches. As run time is dominated by the cost of the operations performed at each incoming spike, which includes spike prediction in the case of event-driven simulation and retrospective detection in the case of time-driven simulation, the simple time-driven algorithm outperforms the event-driven approaches. Additionally, our method is generally applicable to all commonly used integrate-and-fire neuronal models; we show that a non-linear model employing a standard adaptive solver can reproduce a reference spike train with a high degree of precision. PMID:21031031

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fire detection system. 108.405 Section 108.405 Shipping... EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and each smoke detection system on a unit must— (1) Be approved by the Commandant; and (2) Have a visual...

Automatic Road Gap Detection Using Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Hashemi, S.; Valadan Zoej, M. J.; Mokhtarzadeh, M.

2011-09-01

Automatic feature extraction from aerial and satellite images is a high-level data processing which is still one of the most important research topics of the field. In this area, most of the researches are focused on the early step of road detection, where road tracking methods, morphological analysis, dynamic programming and snakes, multi-scale and multi-resolution methods, stereoscopic and multi-temporal analysis, hyper spectral experiments, are some of the mature methods in this field. Although most researches are focused on detection algorithms, none of them can extract road network perfectly. On the other hand, post processing algorithms accentuated on the refining of road detection results, are not developed as well. In this article, the main is to design an intelligent method to detect and compensate road gaps remained on the early result of road detection algorithms. The proposed algorithm consists of five main steps as follow: 1) Short gap coverage: In this step, a multi-scale morphological is designed that covers short gaps in a hierarchical scheme. 2) Long gap detection: In this step, the long gaps, could not be covered in the previous stage, are detected using a fuzzy inference system. for this reason, a knowledge base consisting of some expert rules are designed which are fired on some gap candidates of the road detection results. 3) Long gap coverage: In this stage, detected long gaps are compensated by two strategies of linear and polynomials for this reason, shorter gaps are filled by line fitting while longer ones are compensated by polynomials.4) Accuracy assessment: In order to evaluate the obtained results, some accuracy assessment criteria are proposed. These criteria are obtained by comparing the obtained results with truly compensated ones produced by a human expert. The complete evaluation of the obtained results whit their technical discussions are the materials of the full paper.

Towards predictive data-driven simulations of wildfire spread - Part I: Reduced-cost Ensemble Kalman Filter based on a Polynomial Chaos surrogate model for parameter estimation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Ricci, S.; Lucor, D.; Cuenot, B.; Trouvé, A.

2014-11-01

This paper is the first part in a series of two articles and presents a data-driven wildfire simulator for forecasting wildfire spread scenarios, at a reduced computational cost that is consistent with operational systems. The prototype simulator features the following components: an Eulerian front propagation solver FIREFLY that adopts a regional-scale modeling viewpoint, treats wildfires as surface propagating fronts, and uses a description of the local rate of fire spread (ROS) as a function of environmental conditions based on Rothermel's model; a series of airborne-like observations of the fire front positions; and a data assimilation (DA) algorithm based on an ensemble Kalman filter (EnKF) for parameter estimation. This stochastic algorithm partly accounts for the nonlinearities between the input parameters of the semi-empirical ROS model and the fire front position, and is sequentially applied to provide a spatially uniform correction to wind and biomass fuel parameters as observations become available. A wildfire spread simulator combined with an ensemble-based DA algorithm is therefore a promising approach to reduce uncertainties in the forecast position of the fire front and to introduce a paradigm-shift in the wildfire emergency response. In order to reduce the computational cost of the EnKF algorithm, a surrogate model based on a polynomial chaos (PC) expansion is used in place of the forward model FIREFLY in the resulting hybrid PC-EnKF algorithm. The performance of EnKF and PC-EnKF is assessed on synthetically generated simple configurations of fire spread to provide valuable information and insight on the benefits of the PC-EnKF approach, as well as on a controlled grassland fire experiment. The results indicate that the proposed PC-EnKF algorithm features similar performance to the standard EnKF algorithm, but at a much reduced computational cost. In particular, the re-analysis and forecast skills of DA strongly relate to the spatial and temporal variability of the errors in the ROS model parameters.

Optimized scheme in coal-fired boiler combustion based on information entropy and modified K-prototypes algorithm

NASA Astrophysics Data System (ADS)

Gu, Hui; Zhu, Hongxia; Cui, Yanfeng; Si, Fengqi; Xue, Rui; Xi, Han; Zhang, Jiayu

2018-06-01

An integrated combustion optimization scheme is proposed for the combined considering the restriction in coal-fired boiler combustion efficiency and outlet NOx emissions. Continuous attribute discretization and reduction techniques are handled as optimization preparation by E-Cluster and C_RED methods, in which the segmentation numbers don't need to be provided in advance and can be continuously adapted with data characters. In order to obtain results of multi-objections with clustering method for mixed data, a modified K-prototypes algorithm is then proposed. This algorithm can be divided into two stages as K-prototypes algorithm for clustering number self-adaptation and clustering for multi-objective optimization, respectively. Field tests were carried out at a 660 MW coal-fired boiler to provide real data as a case study for controllable attribute discretization and reduction in boiler system and obtaining optimization parameters considering [ maxηb, minyNOx ] multi-objective rule.

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample extraction smoke detection systems, watchman's supervisory systems, and combinations of these systems. (b) Automatic fire detecting systems. For the purpose of this subpart, automatic fire and smoke detecting...

Comparing fire spread algorithms using equivalence testing and neutral landscape models

Treesearch

Brian R. Miranda; Brian R. Sturtevant; Jian Yang; Eric J. Gustafson

2009-01-01

We demonstrate a method to evaluate the degree to which a meta-model approximates spatial disturbance processes represented by a more detailed model across a range of landscape conditions, using neutral landscapes and equivalence testing. We illustrate this approach by comparing burn patterns produced by a relatively simple fire spread algorithm with those generated by...

Soldier detection using unattended acoustic and seismic sensors

NASA Astrophysics Data System (ADS)

Naz, P.; Hengy, S.; Hamery, P.

2012-06-01

During recent military conflicts, as well as for security interventions, the urban zone has taken a preponderant place. Studies have been initiated in national and in international programs to stimulate the technical innovations for these specific scenarios. For example joint field experiments have been organized by the NATO group SET-142 to evaluate the capability for the detection and localization of snipers, mortars or artillery guns using acoustic devices. Another important operational need corresponds to the protection of military sites or buildings. In this context, unattended acoustic and seismic sensors are envisaged to contribute to the survey of specific points by the detection of approaching enemy soldiers. This paper describes some measurements done in an anechoic chamber and in free field to characterize typical sounds generated by the soldier activities (walking, crawling, weapon handling, radio communication, clothing noises...). Footstep, speech and some specific impulsive sounds are detectable at various distances from the source. Such detection algorithms may be easily merged with the existing weapon firing detection algorithms to provide a more generic "battlefield acoustic" early warning system. Results obtained in various conditions (grassy terrain, gravel path, road, forest) will be presented. A method to extrapolate the distances of detection has been developed, based on an acoustic propagation model and applied to the laboratory measurements.

Trends in fire risk and burned area in Brazil in the 20th century

NASA Astrophysics Data System (ADS)

Silva, P.; Bastos, A.; DaCamara, C.; Libonati, R.

2016-12-01

Fire has a significant contribution to the global greenhouse gas emissions and vast ecological and climatic impacts. Worldwide, Brazil is one of the areas most affected by fire, which highly influences the state of the vegetation cover, the ecological diversity of the region and has significant consequences to the global CO2 balance [1]. Hence, with the increasing evidence of human induced climate change, it becomes essential to understand the present and future trends of fire risk in Brazil. Although a large number of fires in Brazil are anthropogenic, it has been shown that the burned area is mainly controlled by meteorological conditions [2], therefore being partially determined by fire risk. In this study we use a fire danger index specifically tailored for the Brazilian climate and biome characteristics, the MFDI developed by INPE, to assess the patterns and trends of fire risk in Brazil. The index relies on values of maximum temperature, accumulated precipitation over different periods, minimum relative humidity and vegetation cover to estimate the likelihood of fire occurrence. We test the sensitivity of the index to different climate reanalyses and evaluate the trends in fire risk in Brazil during the past four decades for different biomes. We further assess the link between the calculated fire risk and observed fire occurrence and burned area. Finally, we compare the results with fire risk simulated by a regional climate model (RCA4 forced by EC-Earth from CORDEX) in order to evaluate its suitability for future projections of fire risk and burned area. [1] Bowman, D. M. et al. Fire in the earth system. Science, v. 324, p. 481-484, 24 apr. 2009. [2] Libonati, R. et al. An Algorithm for Burned Area Detection in the Brazilian Cerrado Using 4 μm MODIS Imagery. Remote Sensing, v. 7, p. 15782-15803, 2015.

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

46 CFR 108.405 - Fire detection system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Fire detection system. 108.405 Section 108.405 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.405 Fire detection system. (a) Each fire detection system and...

46 CFR 108.404 - Selection of fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Selection of fire detection system. 108.404 Section 108... DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.404 Selection of fire detection system. (a) If a... space. (b) The fire detection system must be designed to minimize false alarms. ...

46 CFR 108.413 - Fusible element fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Fusible element fire detection system. 108.413 Section... UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.413 Fusible element fire detection system. (a) A fusible element fire detection system may be installed. (b) The arrangements for the system...

46 CFR 71.25-20 - Fire-detecting and extinguishing equipment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 3 2010-10-01 2010-10-01 false Fire-detecting and extinguishing equipment. 71.25-20... INSPECTION AND CERTIFICATION Annual Inspection § 71.25-20 Fire-detecting and extinguishing equipment. (a) At... detecting and extinguishing equipment: (1) All hand portable fire extinguishers and semiportable fire...

Miss-distance indicator for tank main guns

NASA Astrophysics Data System (ADS)

Bornstein, Jonathan A.; Hillis, David B.

1996-06-01

Tank main gun systems must possess extremely high levels of accuracy to perform successfully in battle. Under some circumstances, the first round fired in an engagement may miss the intended target, and it becomes necessary to rapidly correct fire. A breadboard automatic miss-distance indicator system was previously developed to assist in this process. The system, which would be mounted on a 'wingman' tank, consists of a charged-coupled device (CCD) camera and computer-based image-processing system, coupled with a separate infrared sensor to detect muzzle flash. For the system to be successfully employed with current generation tanks, it must be reliable, be relatively low cost, and respond rapidly maintaining current firing rates. Recently, the original indicator system was developed further in an effort to assist in achieving these goals. Efforts have focused primarily upon enhanced image-processing algorithms, both to improve system reliability and to reduce processing requirements. Intelligent application of newly refined trajectory models has permitted examination of reduced areas of interest and enhanced rejection of false alarms, significantly improving system performance.

Wildfire monitoring via the integration of remote sensing with innovative information technologies

NASA Astrophysics Data System (ADS)

Kontoes, C.; Papoutsis, I.; Michail, D.; Herekakis, Th.; Koubarakis, M.; Kyzirakos, K.; Karpathiotakis, M.; Nikolaou, C.; Sioutis, M.; Garbis, G.; Vassos, S.; Keramitsoglou, I.; Kersten, M.; Manegold, S.; Pirk, H.

2012-04-01

In the Institute for Space Applications and Remote Sensing of the National Observatory of Athens (ISARS/NOA) volumes of Earth Observation images of different spectral and spatial resolutions are being processed on a systematic basis to derive thematic products that cover a wide spectrum of applications during and after wildfire crisis, from fire detection and fire-front propagation monitoring, to damage assessment in the inflicted areas. The processed satellite imagery is combined with auxiliary geo-information layers, including land use/land cover, administrative boundaries, road and rail network, points of interest, and meteorological data to generate and validate added-value fire-related products. The service portfolio has become available to institutional End Users with a mandate to act on natural disasters and that have activated Emergency Support Services at a European level in the framework of the operational GMES projects SAFER and LinkER. Towards the goal of delivering integrated services for fire monitoring and management, ISARS/NOA employs observational capacities which include the operation of MSG/SEVIRI and NOAA/AVHRR receiving stations, NOA's in-situ monitoring networks for capturing meteorological parameters to generate weather forecasts, and datasets originating from the European Space Agency and third party satellite operators. The qualified operational activity of ISARS/NOA in the domain of wildfires management is highly enhanced by the integration of state-of-the-art Information Technologies that have become available in the framework of the TELEIOS (EC/ICT) project. TELEIOS aims at the development of fully automatic processing chains reliant on a) the effective storing and management of the large amount of EO and GIS data, b) the post-processing refinement of the fire products using semantics, and c) the creation of thematic maps and added-value services. The first objective is achieved with the use of advanced Array Database technologies, such as MonetDB, to enable efficiency in accessing large archives of image data and metadata in a fully transparent way, without worrying for their format, size, and location, as well as efficiency in processing such data using state-of-the-art implementations of image processing algorithms expressed in a high-level Scientific Query Language (SciQL). The product refinement is realized through the application of update operations that incorporate human evidence and human logic, with semantic content extracted from thematic information coming from auxiliary geo-information layers and sources, for reducing considerably the number of false alarms in fire detection, and improving the credibility of the burnt area assessment. The third objective is approached via the combination of the derived fire-products with Linked Geospatial Data, structured accordingly and freely available in the web, using Semantic Web technologies. These technologies are built on top of a robust and modular computational environment, to facilitate several wildfire applications to run efficiently, such as real-time fire detection, fire-front propagation monitoring, rapid burnt area mapping, after crisis detailed burnt scar mapping, and time series analysis of burnt areas. The approach adopted allows ISARS/NOA to routinely serve requests from the end-user community, irrespective of the area of interest and its extent, the observation time period, or the data volume involved, granting the opportunity to combine innovative IT solutions with remote sensing techniques and algorithms for wildfire monitoring and management.

46 CFR 108.407 - Detectors for electric fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 4 2010-10-01 2010-10-01 false Detectors for electric fire detection system. 108.407... DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.407 Detectors for electric fire detection system. (a) Each detector in an electric fire detection system must be located where— (1) No...

Neurofeedback Training for BCI Control

NASA Astrophysics Data System (ADS)

Neuper, Christa; Pfurtscheller, Gert

Brain-computer interface (BCI) systems detect changes in brain signals that reflect human intention, then translate these signals to control monitors or external devices (for a comprehensive review, see [1]). BCIs typically measure electrical signals resulting from neural firing (i.e. neuronal action potentials, Electroencephalogram (ECoG), or Electroencephalogram (EEG)). Sophisticated pattern recognition and classification algorithms convert neural activity into the required control signals. BCI research has focused heavily on developing powerful signal processing and machine learning techniques to accurately classify neural activity [2-4].

The use of satellite data for monitoring temporal and spatial patterns of fire: a comprehensive review

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2009-04-01

Remotely sensed (RS) data can fruitfully support both research activities and operative monitoring of fire at different temporal and spatial scales with a synoptic view and cost effective technologies. "The contribution of remote sensing (RS) to forest fires may be grouped in three categories, according to the three phases of fire management: (i) risk estimation (before fire), (ii) detection (during fire) and (iii) assessment (after fire)" Chuvieco (2006). Relating each phase, wide research activities have been conducted over the years. (i) Risk estimation (before fire) has been mainly based on the use of RS data for (i) monitoring vegetation stress and assessing variations in vegetation moisture content, (ii) fuel type mapping, at different temporal and spatial scales from global, regional down to a local scale (using AVHRR, MODIS, TM, ASTER, Quickbird images and airborne hyperspectral and LIDAR data). Danger estimation has been mainly based on the use of AVHRR (onborad NOAA), MODIS (onboard TERRA and AQUA), VEGETATION (onboard SPOT) due to the technical characteristics (i.e. spectral, spatial and temporal resolution). Nevertheless microwave data have been also used for vegetation monitoring. (ii) Detection: identification of active fires, estimation of fire radiative energy and fire emission. AVHRR was one of the first satellite sensors used for setting up fire detection algorithms. The availbility of MODIS allowed us to obtain global fire products free downloaded from NASA web site. Sensors onboard geostationary satellite platforms, such as GOES, SEVIRI, have been used for fire detection, to obtain a high temporal resolution (at around 15 minutes) monitoring of active fires. (iii) Post fire damage assessment includes: burnt area mapping, fire emission, fire severity, vegetation recovery, fire resilience estimation, and, more recently, fire regime characterization. Chuvieco E. L. Giglio, C. Justice, 2008 Global charactrerization of fire activity: toward defining fire regimes from Earth observation data Global Change Biology vo. 14. doi: 10.1111/j.1365-2486.2008.01585.x 1-15, Chuvieco E., P. Englefield, Alexander P. Trishchenko, Yi Luo Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2381-2396 Chuvieco Emilio 2006, Remote Sensing of Forest Fires: Current limitations and future prospects in Observing Land from Space: Science, Customers and Technology, Advances in Global Change Research Vol. 4 pp 47-51 De Santis A., E. Chuvieco Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models, Remote Sensing of Environment, Volume 108, Issue 4, 29 June 2007, Pages 422-435. De Santis A., E. Chuvieco, Patrick J. Vaughan, Short-term assessment of burn severity using the inversion of PROSPECT and GeoSail models, Remote Sensing of Environment, Volume 113, Issue 1, 15 January 2009, Pages 126-136 García M., E. Chuvieco, H. Nieto, I. Aguado Combining AVHRR and meteorological data for estimating live fuel moisture content Remote Sensing of Environment, Volume 112, Issue 9, 15 September 2008, Pages 3618-3627 Ichoku C., L. Giglio, M. J. Wooster, L. A. Remer Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2950-2962. Lasaponara R. and Lanorte, On the capability of satellite VHR QuickBird data for fuel type characterization in fragmented landscape Ecological Modelling Volume 204, Issues 1-2, 24 May 2007, Pages 79-84 Lasaponara R., A. Lanorte, S. Pignatti,2006 Multiscale fuel type mapping in fragmented ecosystems: preliminary results from Hyperspectral MIVIS and Multispectral Landsat TM data, Int. J. Remote Sens., vol. 27 (3) pp. 587-593. Lasaponara R., V. Cuomo, M. F. Macchiato, and T. Simoniello, 2003 .A self-adaptive algorithm based on AVHRR multitemporal data analysis for small active fire detection.n International Journal of Remote Sensing, vol. 24, No 8, 1723-1749. Minchella A., F. Del Frate, F. Capogna, S. Anselmi, F. Manes Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas Remote Sensing of Environment, In Press Næsset E., T. Gobakken Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 3079-3090 Peterson S. H, Dar A. Roberts, Philip E. Dennison Mapping live fuel moisture with MODIS data: A multiple regression approach, Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4272-4284. Schroeder Wilfrid, Elaine Prins, Louis Giglio, Ivan Csiszar, Christopher Schmidt, Jeffrey Morisette, Douglas Morton Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2711-2726 Shi J., T. Jackson, J. Tao, J. Du, R. Bindlish, L. Lu, K.S. Chen Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4285-4300 Tansey, K., Grégoire, J-M., Defourny, P., Leigh, R., Pekel, J-F., van Bogaert, E. and Bartholomé, E., 2008 A New, Global, Multi-Annual (2000-2007) Burnt Area Product at 1 km Resolution and Daily Intervals Geophysical Research Letters, VOL. 35, L01401, doi:10.1029/2007GL031567, 2008. Telesca L. and Lasaponara R., 2006; "Pre-and Post- fire Behaviural trends revealed in satellite NDVI time series" Geophysical Research Letters,., 33, L14401, doi:10.1029/2006GL026630 Telesca L. and Lasaponara R 2005 Discriminating Dynamical Patterns in Burned and Unburned Vegetational Covers by Using SPOT-VGT NDVI Data. Geophysical Research Letters,, 32, L21401, doi:10.1029/2005GL024391. Telesca L. and Lasaponara R. Investigating fire-induced behavioural trends in vegetation covers , Communications in Nonlinear Science and Numerical Simulation, 13, 2018-2023, 2008 Telesca L., A. Lanorte and R. Lasaponara, 2007. Investigating dynamical trends in burned and unburned vegetation covers by using SPOT-VGT NDVI data. Journal of Geophysics and Engineering, Vol. 4, pp. 128-138, 2007 Telesca L., R. Lasaponara, and A. Lanorte, Intra-annual dynamical persistent mechanisms in Mediterranean ecosystems revealed SPOT-VEGETATION Time Series, Ecological Complexity, 5, 151-156, 2008 Verbesselt, J., Somers, B., Lhermitte, S., Jonckheere, I., van Aardt, J., and Coppin, P. (2007) Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Remote Sensing of Environment 108: 357-368. Zhang X., S. Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897 Zhang X., Shobha Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897

46 CFR 27.203 - What are the requirements for fire detection on towing vessels?

Code of Federal Regulations, 2010 CFR

2010-10-01

... detection on towing vessels? You must have a fire-detection system installed on your vessel to detect engine... use an existing engine-room-monitoring system (with fire-detection capability) instead of a fire-detection system, if the monitoring system is operable and complies with this section. You must ensure that...

An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Khamukhin, A. A.; Demin, A. Y.; Sonkin, D. M.; Bertoldo, S.; Perona, G.; Kretova, V.

2017-01-01

Crown fires are extremely dangerous as the speed of their distribution is dozen times higher compared to surface fires. Therefore, it is important to classify the fire type as early as possible. A method for forest fires classification exploits their computed acoustic emission spectrum compared with a set of samples of the typical fire acoustic emission spectrum stored in the database. This method implies acquisition acoustic data using Wireless Sensors Networks (WSNs) and their analysis in a central processing and a control center. The paper deals with an algorithm which can be directly implemented on a sensor network node that will allow reducing considerably the network traffic and increasing its efficiency. It is hereby suggested to use the sum of the squares ratio, with regard to amplitudes of low and high frequencies of the wildfire acoustic emission spectrum, as the indicator of a forest fire type. It is shown that the value of the crown fires indicator is several times higher than that of the surface ones. This allows classifying the fire types (crown, surface) in a short time interval and transmitting a fire type indicator code alongside with an alarm signal through the network.

Fire Detection Organizing Questions

NASA Technical Reports Server (NTRS)

2004-01-01

Verified models of fire precursor transport in low and partial gravity: a. Development of models for large-scale transport in reduced gravity. b. Validated CFD simulations of transport of fire precursors. c. Evaluation of the effect of scale on transport and reduced gravity fires. Advanced fire detection system for gaseous and particulate pre-fire and fire signaturesa: a. Quantification of pre-fire pyrolysis products in microgravity. b. Suite of gas and particulate sensors. c. Reduced gravity evaluation of candidate detector technologies. d. Reduced gravity verification of advanced fire detection system. e. Validated database of fire and pre-fire signatures in low and partial gravity.

Muzzle flash localization for the dismounted soldier

NASA Astrophysics Data System (ADS)

Kennedy Scott, Will

2015-05-01

The ability to accurately and rapidly know the precise location of enemy fire would be a substantial capability enhancement to the dismounted soldier. Acoustic gun-shot detections systems can provide an approximate bearing but it is desired to precisely know the location (direction and range) of enemy fire; for example to know from `which window' the fire is coming from. Funded by the UK MOD (via Roke Manor Research) QinetiQ is developing an imaging solution built around an InGaAs camera. This paper presents work that QinetiQ has undertaken on the Muzzle Flash Locator system. Key technical challenges that have been overcome are explained and discussed in this paper. They include; the design of the optical sensor and processing hardware to meet low size, weight and power requirements; the algorithm approach required to maintain sensitivity whilst rejecting false alarms from sources such as close passing insects and sun glint from scene objects; and operation on the move. This work shows that such a sensor can provide sufficient sensitivity to detect muzzle flash events to militarily significant ranges and that such a system can be combined with an acoustic gunshot detection system to minimize the false alarm rate. The muzzle flash sensor developed in this work operates in real-time and has a field of view of approximately 29° (horizontal) by 12° (vertical) with a pixel resolution of 0.13°. The work has demonstrated that extension to a sensor with realistic angular rotation rate is feasible.

A foundation for initial attack simulation: the Fried and Fried fire containment model

Treesearch

Jeremy S. Fried; Burton D. Fried

2010-01-01

The Fried and Fried containment algorithm, which models the effect of suppression efforts on fire growth, allows simulation of any mathematically representable fire shape, provides for "head" and "tail" attack tactics as well as parallel attack (building fireline parallel to but at some offset distance from the free-burning fire perimeter, alone and...

Developing fire management mixes for fire program planning

Treesearch

Armando González-Cabán; Patricia B. Shinkle; Thomas J. Mills

1986-01-01

Evaluating economic efficiency of fire management program options requires information on the firefighting inputs, such as vehicles and crews, that would be needed to execute the program option selected. An algorithm was developed to translate automatically dollars allocated to type of firefighting inputs to numbers of units, using a set of weights for a specific fire...

Accelerating rejection-based simulation of biochemical reactions with bounded acceptance probability

NASA Astrophysics Data System (ADS)

Thanh, Vo Hong; Priami, Corrado; Zunino, Roberto

2016-06-01

Stochastic simulation of large biochemical reaction networks is often computationally expensive due to the disparate reaction rates and high variability of population of chemical species. An approach to accelerate the simulation is to allow multiple reaction firings before performing update by assuming that reaction propensities are changing of a negligible amount during a time interval. Species with small population in the firings of fast reactions significantly affect both performance and accuracy of this simulation approach. It is even worse when these small population species are involved in a large number of reactions. We present in this paper a new approximate algorithm to cope with this problem. It is based on bounding the acceptance probability of a reaction selected by the exact rejection-based simulation algorithm, which employs propensity bounds of reactions and the rejection-based mechanism to select next reaction firings. The reaction is ensured to be selected to fire with an acceptance rate greater than a predefined probability in which the selection becomes exact if the probability is set to one. Our new algorithm improves the computational cost for selecting the next reaction firing and reduces the updating the propensities of reactions.

Accelerating rejection-based simulation of biochemical reactions with bounded acceptance probability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thanh, Vo Hong, E-mail: vo@cosbi.eu; Priami, Corrado, E-mail: priami@cosbi.eu; Department of Mathematics, University of Trento, Trento

Stochastic simulation of large biochemical reaction networks is often computationally expensive due to the disparate reaction rates and high variability of population of chemical species. An approach to accelerate the simulation is to allow multiple reaction firings before performing update by assuming that reaction propensities are changing of a negligible amount during a time interval. Species with small population in the firings of fast reactions significantly affect both performance and accuracy of this simulation approach. It is even worse when these small population species are involved in a large number of reactions. We present in this paper a new approximatemore » algorithm to cope with this problem. It is based on bounding the acceptance probability of a reaction selected by the exact rejection-based simulation algorithm, which employs propensity bounds of reactions and the rejection-based mechanism to select next reaction firings. The reaction is ensured to be selected to fire with an acceptance rate greater than a predefined probability in which the selection becomes exact if the probability is set to one. Our new algorithm improves the computational cost for selecting the next reaction firing and reduces the updating the propensities of reactions.« less

34 CFR 668.49 - Institutional fire safety policies and fire statistics.

Code of Federal Regulations, 2011 CFR

2011-07-01

... fire. Fire safety system: Any mechanism or system related to the detection of a fire, the warning resulting from a fire, or the control of a fire. This may include sprinkler systems or other fire extinguishing systems, fire detection devices, stand-alone smoke alarms, devices that alert one to the presence...

34 CFR 668.49 - Institutional fire safety policies and fire statistics.

Code of Federal Regulations, 2012 CFR

2012-07-01

... fire. Fire safety system: Any mechanism or system related to the detection of a fire, the warning resulting from a fire, or the control of a fire. This may include sprinkler systems or other fire extinguishing systems, fire detection devices, stand-alone smoke alarms, devices that alert one to the presence...

34 CFR 668.49 - Institutional fire safety policies and fire statistics.

Code of Federal Regulations, 2014 CFR

2014-07-01

... fire. Fire safety system: Any mechanism or system related to the detection of a fire, the warning resulting from a fire, or the control of a fire. This may include sprinkler systems or other fire extinguishing systems, fire detection devices, stand-alone smoke alarms, devices that alert one to the presence...

34 CFR 668.49 - Institutional fire safety policies and fire statistics.

Code of Federal Regulations, 2013 CFR

2013-07-01

... fire. Fire safety system: Any mechanism or system related to the detection of a fire, the warning resulting from a fire, or the control of a fire. This may include sprinkler systems or other fire extinguishing systems, fire detection devices, stand-alone smoke alarms, devices that alert one to the presence...

Development of gas fire detection system using tunable diode laser absorption spectroscopy

NASA Astrophysics Data System (ADS)

Jiang, Y. L.; Li, G.; Yang, T.; Wang, J. J.

2017-01-01

The conventional fire detection methods mainly produce an alarm through detecting the changes in smoke concentration, flame radiation, heat and other physical parameters in the environment, but are unable to provide an early warning of a fire emergency. We have designed a gas fire detection system with a high detection sensitivity and high selectivity using the tunable semiconductor diode laser as a light source and combining wavelength modulation and harmonic detection technology. This system can invert the second harmonic signal obtained to obtain the concentration of carbon monoxide gas (a fire characteristic gas) so as to provide an early warning of fire. We reduce the system offset noise and the background noise generated due to the laser interference by deducting the system background spectrum lines from the second harmonic signal. This can also eliminate the interference of other gas spectral lines to a large extent. We detected the concentration of the carbon monoxide gas generated in smoldering sandalwood fire and open beech wood fire with the homemade fire simulator, and tested the lowest detectable limit of system. The test results show that the lowest detectable limit can reach 5×10-6 the system can maintain stable operation for a long period of time and can automatically trigger a water mist fire extinguishing system, which can fully meet the needs of early fire warning.

Active Fire Mapping Program

MedlinePlus

Active Fire Mapping Program Current Large Incidents (Home) New Large Incidents Fire Detection Maps MODIS Satellite Imagery VIIRS Satellite Imagery Fire Detection GIS Data Fire Data in Google Earth ...

An algorithm to help design fire simulation and other data base work

Treesearch

Romain Mees

1974-01-01

The data necessary for fire simulation may be made available through an algorithm based on tracing of boundaries composed of straight-line segments. Useful assumptions are that if a closed boundary does not contain a given point, then any other closed boundary contained within the former one does not contain the location; and that a given location will be contained in...

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2010 CFR

2010-10-01

... detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED... and spacing of tubing in pneumatic fire detection system. (a) All tubing in a pneumatic fire detection... exposed in the space. (c) A pneumatic fire detection system must be set to activate after approximately a...

Optical bullet-tracking algorithms for weapon localization in urban environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roberts, R S; Breitfeller, E F

2006-03-31

Localization of the sources of small-arms fire, mortars, and rocket propelled grenades is an important problem in urban combat. Weapons of this type produce characteristic signatures, such as muzzle flashes, that are visible in the infrared. Indeed, several systems have been developed that exploit the infrared signature of muzzle flash to locate the positions of shooters. However, systems based on muzzle flash alone can have difficulty localizing weapons if the muzzle flash is obscured or suppressed. Moreover, optical clutter can be problematic to systems that rely on muzzle flash alone. Lawrence Livermore National Laboratory (LLNL) has developed a projectile trackingmore » system that detects and localizes sources of small-arms fire, mortars and similar weapons using the thermal signature of the projectile rather than a muzzle flash. The thermal signature of a projectile, caused by friction as the projectile travels along its trajectory, cannot be concealed and is easily discriminated from optical clutter. The LLNL system was recently demonstrated at the MOUT facility of the Aberdeen Test Center [1]. In the live-fire demonstration, shooters armed with a variety of small-arms, including M-16s, AK-47s, handguns, mortars and rockets, were arranged at several positions in around the facility. Experiments ranged from a single-weapon firing a single-shot to simultaneous fire of all weapons on full automatic. The LLNL projectile tracking system was demonstrated to localize multiple shooters at ranges up to 400m, far greater than previous demonstrations. Furthermore, the system was shown to be immune to optical clutter that is typical in urban combat. This paper describes the image processing and localization algorithms designed to exploit the thermal signature of projectiles for shooter localization. The paper begins with a description of the image processing that extracts projectile information from a sequence of infrared images. Key to the processing is an adaptive spatio-temporal filter developed to suppress scene clutter. The filtered image sequence is further processed to produce a set of parameterized regions, which are classified using several discriminate functions. Regions that are classified as projectiles are passed to a data association algorithm that matches features from these regions with existing tracks, or initializes new tracks as needed. A Kalman filter is used to smooth and extrapolate existing tracks. Shooter locations are determined by solving a combinatorial least-squares solution for all bullet tracks. It also provides an error ellipse for each shooter, quantifying the uncertainty of shooter location. The paper concludes with examples from the live-fire exercise at the Aberdeen Test Center.« less

14 CFR 460.13 - Smoke detection and fire suppression.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 4 2013-01-01 2013-01-01 false Smoke detection and fire suppression. 460... Crew § 460.13 Smoke detection and fire suppression. An operator or crew must have the ability to detect smoke and suppress a cabin fire to prevent incapacitation of the flight crew. ...

14 CFR 460.13 - Smoke detection and fire suppression.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Smoke detection and fire suppression. 460... Crew § 460.13 Smoke detection and fire suppression. An operator or crew must have the ability to detect smoke and suppress a cabin fire to prevent incapacitation of the flight crew. ...

14 CFR 460.13 - Smoke detection and fire suppression.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Smoke detection and fire suppression. 460... Crew § 460.13 Smoke detection and fire suppression. An operator or crew must have the ability to detect smoke and suppress a cabin fire to prevent incapacitation of the flight crew. ...

14 CFR 460.13 - Smoke detection and fire suppression.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 4 2014-01-01 2014-01-01 false Smoke detection and fire suppression. 460... Crew § 460.13 Smoke detection and fire suppression. An operator or crew must have the ability to detect smoke and suppress a cabin fire to prevent incapacitation of the flight crew. ...

14 CFR 460.13 - Smoke detection and fire suppression.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Smoke detection and fire suppression. 460... Crew § 460.13 Smoke detection and fire suppression. An operator or crew must have the ability to detect smoke and suppress a cabin fire to prevent incapacitation of the flight crew. ...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Automatic fire detecting system, power supply. 161.002-9 Section 161.002-9 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) EQUIPMENT...-9 Automatic fire detecting system, power supply. The power supply for an automatic fire detecting...

Fire detection from hyperspectral data using neural network approach

NASA Astrophysics Data System (ADS)

Piscini, Alessandro; Amici, Stefania

2015-10-01

This study describes an application of artificial neural networks for the recognition of flaming areas using hyper- spectral remote sensed data. Satellite remote sensing is considered an effective and safe way to monitor active fires for environmental and people safeguarding. Neural networks are an effective and consolidated technique for the classification of satellite images. Moreover, once well trained, they prove to be very fast in the application stage for a rapid response. At flaming temperature, thanks to its low excitation energy (about 4.34 eV), potassium (K) ionize with a unique doublet emission features. This emission features can be detected remotely providing a detection map of active fire which allows in principle to separate flaming from smouldering areas of vegetation even in presence of smoke. For this study a normalised Advanced K Band Difference (AKBD) has been applied to airborne hyper spectral sensor covering a range of 400-970 nm with resolution 2.9 nm. A back propagation neural network was used for the recognition of active fires affecting the hyperspectral image. The network was trained using all channels of sensor as inputs, and the corresponding AKBD indexes as target output. In order to evaluate its generalization capabilities, the neural network was validated on two independent data sets of hyperspectral images, not used during neural network training phase. The validation results for the independent data-sets had an overall accuracy round 100% for both image and a few commission errors (0.1%), therefore demonstrating the feasibility of estimating the presence of active fires using a neural network approach. Although the validation of the neural network classifier had a few commission errors, the producer accuracies were lower due to the presence of omission errors. Image analysis revealed that those false negatives lie in "smoky" portion fire fronts, and due to the low intensity of the signal. The proposed method can be considered effective both in terms of classification accuracy and generalization capability. In particular our approach proved to be robust in the rejection of false positives, often corresponding to noisy or smoke pixels, whose presence in hyperspectral images can often undermine the performance of traditional classification algorithms. In order to improve neural network performance, future activities will include also the exploiting of hyperspectral images in the shortwave infrared region of the electromagnetic spectrum, covering wavelengths from 1400 to 2500 nm, which include significant emitted radiance from fire.

Using JPSS VIIRS Fire Radiative Power Data to Forecast Biomass Burning Emissions and Smoke Transport by the High Resolution Rapid Refresh Model

NASA Astrophysics Data System (ADS)

Ahmadov, R.; Grell, G. A.; James, E.; Alexander, C.; Stewart, J.; Benjamin, S.; McKeen, S. A.; Csiszar, I. A.; Tsidulko, M.; Pierce, R. B.; Pereira, G.; Freitas, S. R.; Goldberg, M.

2017-12-01

We present a new real-time smoke modeling system, the High Resolution Rapid Refresh coupled with smoke (HRRR-Smoke), to simulate biomass burning (BB) emissions, plume rise and smoke transport in real time. The HRRR is the NOAA Earth System Research Laboratory's 3km grid spacing version of the Weather Research and Forecasting (WRF) model used for weather forecasting. Here we make use of WRF-Chem (the WRF model coupled with chemistry) and simulate fine particulate matter (smoke) emissions emitted by BB. The HRRR-Smoke modeling system ingests fire radiative power (FRP) data from the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (S-NPP) satellite to calculate BB emissions. The FRP product is based on processing 750m resolution "M" bands. The algorithms for fire detection and FRP retrieval are consistent with those used to generate the MODIS fire detection data. For the purpose of ingesting VIIRS fire data into the HRRR-Smoke model, text files are generated to provide the location and detection confidence of fire pixels, as well as FRP. The VIIRS FRP data from the text files are processed and remapped over the HRRR-Smoke model domains. We process the FRP data to calculate BB emissions (smoldering part) and fire size for the model input. In addition, HRRR-Smoke uses the FRP data to simulate the injection height for the flaming emissions using concurrently simulated meteorological fields by the model. Currently, there are two 3km resolution domains covering the contiguous US and Alaska which are used to simulate smoke in real time. In our presentation, we focus on the CONUS domain. HRRR-Smoke is initialized 4 times per day to forecast smoke concentrations for the next 36 hours. The VIIRS FRP data, as well as near-surface and vertically integrated smoke mass concentrations are visualized for every forecast hour. These plots are provided to the public via the HRRR-Smoke web-page: https://rapidrefresh.noaa.gov/HRRRsmoke/. Model evaluations for a case study are presented, where simulated smoke concentrations are compared with hourly PM2.5 measurements from EPA's Air Quality System network. These comparisons demonstrate the model's ability in simulating high aerosol loadings during major wildfire events in the western US.

Fire Detection Using tin Oxide Gas Sensors Installed in an Indoor Space

NASA Astrophysics Data System (ADS)

Shibata, Shin-Ichi; Higashino, Tsubasa; Sawada, Ayako; Oyabu, Takashi; Takei, Yoshinori; Nanto, Hidehito; Toko, Kiyoshi

Many lives and facilities were lost by fire. Especially, there are many damages to elderly, toddlers and babies. In Japan, number of deaths over 65 years old reached to 53% in 2004. Number of over 81 years olds went to 20%. It takes for the elderly person more time to sense fire and also to evacuate to safe places. Although it is important to prevent the fire, it also needs to inform the fire breaking as early as possible. Human sense decreases with age and it is difficult to perceive the fire at an early stage. It is desired to develop a higher sensitive element for fire and its system which can detect fire at an early stage. In this experiment, tin oxide gas sensors were adopted to detect a smoldering fire at the early stage. Most common case of fire is the smoldering fire. The reliability of the sensor is higher and it is adopted in a gas alarm detector. The sensor can also detect slight amount of odor molecule. In our previous experiment, it became obvious that it was better to install the sensor to the ceiling to detect odor components generating from smoldering fire. Therefore, five sensors were installed in the ceiling away from each other and the method to detect the fire was examined. As a result, a characteristic was newly derived by adding the sensor outputs for one minute. The sensor output was input every 0.1s. The characteristic is called as the integrated characteristic. After that, the differential characteristic was derived using the integrated characteristic. The fire was determined using the differential characteristics. The materials causing a smoldering fire were woodchip, wallpaper and carpet as subjects. The system could detect the fire in several minutes for whole materials. The sensor is effective to detect the smoldering fire at an early stage. It is necessary to detect a cigarette smoke to distinguish as non fire. In this study, the discrimination was also examined using a quadratic function (ax2+b). The coefficients a and b were effective to identify smoldering fire and cigarette smoke. Principal component analysis for the arrival speed S which meant a kind of odor-speed was also useful to distinguish fire from non fire.

The Geoland2 BioPar burned area product

NASA Astrophysics Data System (ADS)

Tansey, K.; Bradley, A.; Smets, B.; van Best, C.; Lacaze, R.

2012-04-01

The European Commission Geoland2 project intends to constitute a major step forward to the implementation of the GMES Land Monitoring Core Service (LMCS). The Bio-geophysical Parameters (BioPar) Core Monitoring Service aims at setting-up pre-operational infrastructures for providing regional, European, and global bio-geophysical variables, both in near real time and off-line mode, for describing the vegetation state, the radiation budget at the surface, and the water cycle. The burned area product is part of the BioPar portfolio. The burned area product further builds on the experience of the Global Burned Area (GBA2000) and L3JRC projects. In the GBA2000 project, several algorithms were developed for different geographical regions of the world, and applied to a 1-year time series (the year 2000) of SPOT-VEGETATION data. In the L3JRC project, a single algorithm was improved and applied to a 7-year global dataset of SPOT-VEGETATION data. Since the conception of the Geoland2 project, work has been undertaken to improve the L3JRC algorithm, mainly based on user comments and feedback. Furthermore, the Geoland2 burned area product specification has been developed to meet the requirements of the Core Information Service, specifically LandCarbon and Natural Resource Monitoring in Africa (Narma). The Geoland2 burned area product has the following improvements over the L3JRC product: • It resolves issues with users extracting statistics and burned area estimates for time periods considered to be outside the main seasons for burning. Specifically, this deals with issues in northern latitude winters. • The number of pre-processing steps has been shortened, reducing processing time. • An improved land-water mask has been used. This resolves a problem around the coastlines of land masses which were frequently being detected as being burned. • A season metric calculation is performed over a 1x1 degree grid. For each grid cell, a date is logged against the start of the fire season, peak of the fire season and then the end of the fire season. Once a fire season has been confirmed as being finished, the region effectively resets itself, which means that the land surface can burn again when the next fire season starts. This automated season reset feature enables multiple fire seasons to be analysed. • Provides easy to interpret seasonality tables every 10 days (the reporting period for the product). It is intended that the product will be validated using CEOS-approved protocols and data sets currently being developed through the European Space Agency Fire-CCI project. In this paper, initial results being produced operationally and will be presented along with examples highlighting the performance of the seasonality metric.

How to model supernovae in simulations of star and galaxy formation

NASA Astrophysics Data System (ADS)

Hopkins, Philip F.; Wetzel, Andrew; Kereš, Dušan; Faucher-Giguère, Claude-André; Quataert, Eliot; Boylan-Kolchin, Michael; Murray, Norman; Hayward, Christopher C.; El-Badry, Kareem

2018-06-01

We study the implementation of mechanical feedback from supernovae (SNe) and stellar mass loss in galaxy simulations, within the Feedback In Realistic Environments (FIRE) project. We present the FIRE-2 algorithm for coupling mechanical feedback, which can be applied to any hydrodynamics method (e.g. fixed-grid, moving-mesh, and mesh-less methods), and black hole as well as stellar feedback. This algorithm ensures manifest conservation of mass, energy, and momentum, and avoids imprinting `preferred directions' on the ejecta. We show that it is critical to incorporate both momentum and thermal energy of mechanical ejecta in a self-consistent manner, accounting for SNe cooling radii when they are not resolved. Using idealized simulations of single SN explosions, we show that the FIRE-2 algorithm, independent of resolution, reproduces converged solutions in both energy and momentum. In contrast, common `fully thermal' (energy-dump) or `fully kinetic' (particle-kicking) schemes in the literature depend strongly on resolution: when applied at mass resolution ≳100 M⊙, they diverge by orders of magnitude from the converged solution. In galaxy-formation simulations, this divergence leads to orders-of-magnitude differences in galaxy properties, unless those models are adjusted in a resolution-dependent way. We show that all models that individually time-resolve SNe converge to the FIRE-2 solution at sufficiently high resolution (<100 M⊙). However, in both idealized single-SN simulations and cosmological galaxy-formation simulations, the FIRE-2 algorithm converges much faster than other sub-grid models without re-tuning parameters.

Objective analysis of toolmarks in forensics

NASA Astrophysics Data System (ADS)

Grieve, Taylor N.

Since the 1993 court case of Daubert v. Merrell Dow Pharmaceuticals, Inc. the subjective nature of toolmark comparison has been questioned by attorneys and law enforcement agencies alike. This has led to an increased drive to establish objective comparison techniques with known error rates, much like those that DNA analysis is able to provide. This push has created research in which the 3-D surface profile of two different marks are characterized and the marks' cross-sections are run through a comparative statistical algorithm to acquire a value that is intended to indicate the likelihood of a match between the marks. The aforementioned algorithm has been developed and extensively tested through comparison of evenly striated marks made by screwdrivers. However, this algorithm has yet to be applied to quasi-striated marks such as those made by the shear edge of slip-joint pliers. The results of this algorithm's application to the surface of copper wire will be presented. Objective mark comparison also extends to comparison of toolmarks made by firearms. In an effort to create objective comparisons, microstamping of firing pins and breech faces has been introduced. This process involves placing unique alphanumeric identifiers surrounded by a radial code on the surface of firing pins, which transfer to the cartridge's primer upon firing. Three different guns equipped with microstamped firing pins were used to fire 3000 cartridges. These cartridges are evaluated based on the clarity of their alphanumeric transfers and the clarity of the radial code surrounding the alphanumerics.

14 CFR 25.858 - Cargo or baggage compartment smoke or fire detection systems.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Cargo or baggage compartment smoke or fire... Construction Fire Protection § 25.858 Cargo or baggage compartment smoke or fire detection systems. If certification with cargo or baggage compartment smoke or fire detection provisions is requested, the following...

14 CFR 25.858 - Cargo or baggage compartment smoke or fire detection systems.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Cargo or baggage compartment smoke or fire... Construction Fire Protection § 25.858 Cargo or baggage compartment smoke or fire detection systems. If certification with cargo or baggage compartment smoke or fire detection provisions is requested, the following...

14 CFR 25.858 - Cargo or baggage compartment smoke or fire detection systems.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Cargo or baggage compartment smoke or fire... Construction Fire Protection § 25.858 Cargo or baggage compartment smoke or fire detection systems. If certification with cargo or baggage compartment smoke or fire detection provisions is requested, the following...

14 CFR 25.858 - Cargo or baggage compartment smoke or fire detection systems.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Cargo or baggage compartment smoke or fire... Construction Fire Protection § 25.858 Cargo or baggage compartment smoke or fire detection systems. If certification with cargo or baggage compartment smoke or fire detection provisions is requested, the following...

[Detecting fire smoke based on the multispectral image].

PubMed

Wei, Ying-Zhuo; Zhang, Shao-Wu; Liu, Yan-Wei

2010-04-01

Smoke detection is very important for preventing forest-fire in the fire early process. Because the traditional technologies based on video and image processing are easily affected by the background dynamic information, three limitations exist in these technologies, i. e. lower anti-interference ability, higher false detection rate and the fire smoke and water fog being not easily distinguished. A novel detection method for detecting smoke based on the multispectral image was proposed in the present paper. Using the multispectral digital imaging technique, the multispectral image series of fire smoke and water fog were obtained in the band scope of 400 to 720 nm, and the images were divided into bins. The Euclidian distance among the bins was taken as a measurement for showing the difference of spectrogram. After obtaining the spectral feature vectors of dynamic region, the regions of fire smoke and water fog were extracted according to the spectrogram feature difference between target and background. The indoor and outdoor experiments show that the smoke detection method based on multispectral image can be applied to the smoke detection, which can effectively distinguish the fire smoke and water fog. Combined with video image processing method, the multispectral image detection method can also be applied to the forest fire surveillance, reducing the false alarm rate in forest fire detection.

Vulnerability of North American Boreal Peatlands to Interactions between Climate, Hydrology, and Wildland Fires

NASA Astrophysics Data System (ADS)

Bourgeau-Chavez, L. L.; Jenkins, L. K.; Kasischke, E. S.; Turetsky, M.; Benscoter, B.; Banda, E. J.; Boren, E. J.; Endres, S. L.; Billmire, M.

2013-12-01

North American boreal peatland sites of Alaska, Alberta Canada, and the southern limit of the boreal ecoregion (Michigan's Upper Peninsula) are the focus of an ongoing project to better understand the fire weather, hydrology, and climatic controls on boreal peatland fires. The overall goal of the research project is to reduce uncertainties of the role of northern high latitude ecosystems in the global carbon cycle and to improve carbon emission estimates from boreal fires. Boreal peatlands store tremendous reservoirs of soil carbon that are likely to become increasingly vulnerable to fire as climate change lowers water tables and exposes C-rich peat to burning. Increasing fire activity in peatlands could cause these ecosystems to become net sources of C to the atmosphere, which is likely to have large influences on atmospheric carbon concentrations through positive feedbacks that enhance climate warming. Remote sensing is key to monitoring, understanding and quantifying changes occurring in boreal peatlands. Remote sensing methods are being developed to: 1) map and classify peatland cover types; 2) characterize seasonal and inter-annual variations in the moisture content of surface peat (fuel) layers; 3) map the extent and seasonal timing of fires in peatlands; and 4) discriminate different levels of fuel consumption/burn severity in peat fires. A hybrid radar and optical infrared methodology has been developed to map peatland types (bog vs. fen) and level of biomass (open herbaceous, shrubby, forested). This methodology relies on multi-season data to detect phenological changes in hydrology which characterize the different ecosystem types. Landsat data are being used to discriminate burn severity classes in the peatland types using standard dNBR methods as well as individual bands. Cross referencing the peatland maps and burn severity maps will allow for assessment of the distribution of upland and peatland ecosystems affected by fire and quantitative analysis of emissions. Radar imagery from multiple platforms (L-band PALSAR, C-band ERS-2, Envisat, and Radarsat-2) is being used to develop soil moisture extraction algorithms to monitor changes (drying - wetting) through time and to develop a standard method for soil moisture assessment. Using data from the 1990s (ERS-1 and 2) through the present (Radarsat-2) will allow for determination of patterns of wetting and drying across the landscape. All the remote sensing analysis is supported with field work which has been coordinated with that of Canadian scientists. Field collection includes vegetation and hydrology data to validate peatland distribution maps, collection of water table depths and peat moisture content data to aid in algorithm development for radar organic soil moisture retrieval, and characterization of variations in depth of burning and carbon consumption during peatland fires to use in burn severity mapping and fire emissions modeling.

Infrared video based gas leak detection method using modified FAST features

NASA Astrophysics Data System (ADS)

Wang, Min; Hong, Hanyu; Huang, Likun

2018-03-01

In order to detect the invisible leaking gas that is usually dangerous and easily leads to fire or explosion in time, many new technologies have arisen in the recent years, among which the infrared video based gas leak detection is widely recognized as a viable tool. However, all the moving regions of a video frame can be detected as leaking gas regions by the existing infrared video based gas leak detection methods, without discriminating the property of each detected region, e.g., a walking person in a video frame may be also detected as gas by the current gas leak detection methods.To solve this problem, we propose a novel infrared video based gas leak detection method in this paper, which is able to effectively suppress strong motion disturbances.Firstly, the Gaussian mixture model(GMM) is used to establish the background model.Then due to the observation that the shapes of gas regions are different from most rigid moving objects, we modify the Features From Accelerated Segment Test (FAST) algorithm and use the modified FAST (mFAST) features to describe each connected component. In view of the fact that the statistical property of the mFAST features extracted from gas regions is different from that of other motion regions, we propose the Pixel-Per-Points (PPP) condition to further select candidate connected components.Experimental results show that the algorithm is able to effectively suppress most strong motion disturbances and achieve real-time leaking gas detection.

Spatial and temporal patterns of burned area over Brazilian Cerrado from 2005 to 2015 using remote sensing data

NASA Astrophysics Data System (ADS)

Libonati, Renata; DaCamara, Carlos; Setzer, Alberto

2016-04-01

Although Cerrado is a fire-dependent biome, current agriculture practices have significantly modified the native fire regime. Moreover, over the last decades, climate conditions, such as intensive droughts, have contributed to enhance the effects of anthropogenic activities, and consequently fire, over the region. For instance, during the 2010 extreme drought there was an increase of 100% in the number of fire pixels detected by just one polar orbiting satellite (information online at http://www.cptec.inpe.br/queimadas). A better characterization of spatial and temporal fire patterns over Cerrado is therefore crucial to uncover both climate and anthropogenic influences in this ecosystem. Additionally, information about the extent, location and time of burned areas (BA) over Cerrado is especially useful to a wide range of users, from government agencies, research groups and ecologists, to fire managers and NGOs. Instruments on-board satellites are the only available operational means to collect BA data at appropriated spatial and temporal scales and in a cost-effective way. Several global BA products derived from remote sensed information have been developed over the last years using a variety of techniques based on different spatial, spectral and temporal resolutions. Although presenting similar inter-annual variability, there are marked differences among the products both in magnitude and location of the area burnt. The development of regional algorithms which take into account local characteristics such as vegetation type, soil and climate is therefore an added value to the existing information. We present a monthly BA product (AQM) for Brazil based on information from MODIS 1km. The algorithm was specifically designed for ecosystems in Brazil and the procedure represents the first initiative of an automated method for BA monitoring using remote sensing information in the country. The product relies on an algorithm that takes advantage of the ability of MIR reflectances to discriminate BA. Validation over Cerrado biome indicates that the product is in accordance with BA maps from reference data, making the product suitable for applications in fire emission studies and ecosystem management. The AQM regional database covers the 11-year period 2005-2015 over Cerrado and allows analyzing the overall temporal and spatial distribution patterns of BA for the last decade. The highest monthly mean amount is observed in September, followed by October, and March presents the lowest amount. The most severe year is 2007, followed by 2005 and 2010; 2006 and 2009 are the years with less area burned, followed by 2008. The spatial pattern of BA shows that the north region of Cerrado presents the highest frequency of occurrence. The intra and inter-annual variability of BA over Cerrado are closely related to variability of precipitation but it is worth emphasizing that, despite the major role played by climate conditions, the human factor has also a prominent role on fire dynamics in this region and cannot be disregarded.

33 CFR 149.414 - What are the requirements for a fire detection and alarm system?

Code of Federal Regulations, 2011 CFR

2011-07-01

... national consensus standard, as that term is defined in 29 CFR 1910.2, for fire detection and fire alarm... fire detection and alarm system? 149.414 Section 149.414 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Firefighting and Fire Protection Equipment Firefighting Requirements § 149.414 What are the...

33 CFR 149.414 - What are the requirements for a fire detection and alarm system?

Code of Federal Regulations, 2013 CFR

2013-07-01

... national consensus standard, as that term is defined in 29 CFR 1910.2, for fire detection and fire alarm... fire detection and alarm system? 149.414 Section 149.414 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Firefighting and Fire Protection Equipment Firefighting Requirements § 149.414 What are the...

33 CFR 149.414 - What are the requirements for a fire detection and alarm system?

Code of Federal Regulations, 2012 CFR

2012-07-01

... national consensus standard, as that term is defined in 29 CFR 1910.2, for fire detection and fire alarm... fire detection and alarm system? 149.414 Section 149.414 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Firefighting and Fire Protection Equipment Firefighting Requirements § 149.414 What are the...

33 CFR 149.414 - What are the requirements for a fire detection and alarm system?

Code of Federal Regulations, 2014 CFR

2014-07-01

... national consensus standard, as that term is defined in 29 CFR 1910.2, for fire detection and fire alarm... fire detection and alarm system? 149.414 Section 149.414 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Firefighting and Fire Protection Equipment Firefighting Requirements § 149.414 What are the...

Estimation of key parameters in adaptive neuron model according to firing patterns based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yuan, Chunhua; Wang, Jiang; Yi, Guosheng

2017-03-01

Estimation of ion channel parameters is crucial to spike initiation of neurons. The biophysical neuron models have numerous ion channel parameters, but only a few of them play key roles in the firing patterns of the models. So we choose three parameters featuring the adaptation in the Ermentrout neuron model to be estimated. However, the traditional particle swarm optimization (PSO) algorithm is still easy to fall into local optimum and has the premature convergence phenomenon in the study of some problems. In this paper, we propose an improved method that uses a concave function and dynamic logistic chaotic mapping mixed to adjust the inertia weights of the fitness value, effectively improve the global convergence ability of the algorithm. The perfect predicting firing trajectories of the rebuilt model using the estimated parameters prove that only estimating a few important ion channel parameters can establish the model well and the proposed algorithm is effective. Estimations using two classic PSO algorithms are also compared to the improved PSO to verify that the algorithm proposed in this paper can avoid local optimum and quickly converge to the optimal value. The results provide important theoretical foundations for building biologically realistic neuron models.

Burned areas for the conterminous U.S. from 1984 through 2015, an automated approach using dense time-series of Landsat data

NASA Astrophysics Data System (ADS)

Hawbaker, T. J.; Vanderhoof, M.; Beal, Y. J. G.; Takacs, J. D.; Schmidt, G.; Falgout, J.; Brunner, N. M.; Caldwell, M. K.; Picotte, J. J.; Howard, S. M.; Stitt, S.; Dwyer, J. L.

2016-12-01

Complete and accurate burned area data are needed to document patterns of fires, to quantify relationships between the patterns and drivers of fire occurrence, and to assess the impacts of fires on human and natural systems. Unfortunately, many existing fire datasets in the United States are known to be incomplete and that complicates efforts to understand burned area patterns and introduces a large amount of uncertainty in efforts to identify their driving processes and impacts. Because of this, the need to systematically collect burned area information has been recognized by the United Nations Framework Convention on Climate Change and the Intergovernmental Panel on Climate Change, which have both called for the production of essential climate variables. To help meet this need, we developed a novel algorithm that automatically identifies burned areas in temporally-dense time series of Landsat image stacks to produce Landsat Burned Area Essential Climate Variable (BAECV) products. The algorithm makes use of predictors derived from individual Landsat scenes, lagged reference conditions, and change metrics between the scene and reference predictors. Outputs of the BAECV algorithm, generated for the conterminous United States for 1984 through 2015, consist of burn probabilities for each Landsat scene, in addition to, annual composites including: the maximum burn probability, burn classification, and the Julian date of the first Landsat scene a burn was observed. The BAECV products document patterns of fire occurrence that are not well characterized by existing fire datasets in the United States. We anticipate that these data could help to better understand past patterns of fire occurrence, the drivers that created them, and the impacts fires had on natural and human systems.

Automated Studies of Continuing Current in Lightning Flashes

NASA Astrophysics Data System (ADS)

Martinez-Claros, Jose

Continuing current (CC) is a continuous luminosity in the lightning channel that lasts longer than 10 ms following a lightning return stroke to ground. Lightning flashes following CC are associated with direct damage to power lines and are thought to be responsible for causing lightning-induced forest fires. The development of an algorithm that automates continuing current detection by combining NLDN (National Lightning Detection Network) and LEFA (Langmuir Electric Field Array) datasets for CG flashes will be discussed. The algorithm was applied to thousands of cloud-to-ground (CG) flashes within 40 km of Langmuir Lab, New Mexico measured during the 2013 monsoon season. It counts the number of flashes in a single minute of data and the number of return strokes of an individual lightning flash; records the time and location of each return stroke; performs peak analysis on E-field data, and uses the slope of interstroke interval (ISI) E-field data fits to recognize whether continuing current (CC) exists within the interval. Following CC detection, duration and magnitude are measured. The longest observed C in 5588 flashes was 631 ms. The performance of the algorithm (vs. human judgement) was checked on 100 flashes. At best, the reported algorithm is "correct" 80% of the time, where correct means that multiple stations agree with each other and with a human on both the presence and duration of CC. Of the 100 flashes that were validated against human judgement, 62% were hybrid. Automated analysis detects the first but misses the second return stroke in many cases where the second return stroke is followed by long CC. This problem is also present in human interpretation of field change records.

Gaps in Data and Modeling Tools for Understanding Fire and Fire Effects in Tundra Ecosystems

NASA Astrophysics Data System (ADS)

French, N. H.; Miller, M. E.; Loboda, T. V.; Jenkins, L. K.; Bourgeau-Chavez, L. L.; Suiter, A.; Hawkins, S. M.

2013-12-01

As the ecosystem science community learns more about tundra ecosystems and disturbance in tundra, a review of base data sets and ecological field data for the region shows there are many gaps that need to be filled. In this paper we will review efforts to improve our knowledge of the occurrence and impacts of fire in the North American tundra region completed under a NASA Terrestrial Ecology grant. Our main source of information is remote sensing data from satellite sensors and ecological data from past and recent field data collections by our team, collaborators, and others. Past fire occurrence is not well known for this region compared with other North American biomes. In this presentation we review an effort to use a semi-automated detection algorithm to identify past fire occurrence using the Landsat TM/ETM+ archives, pointing out some of the still-unaddressed issues for a full understanding of fire regime for the region. For this task, fires in Landsat scenes were mapped using the Random Forest classifier (Breiman 2001) to automatically detect potential burn scars. Random Forests is an ensemble classifier that employs machine learning to build a large collection of decision trees that are grown from a random selection of user supplied training data. A pixel's classification is then determined by which class receives the most 'votes' from each tree. We also review the use fire location records and existing modeling methods to quantify emissions from these fires. Based on existing maps of vegetation fuels, we used the approach developed for the Wildland Fire Emissions Information System (WFEIS; French et al. 2011) to estimate emissions across the tundra region. WFEIS employs the Consume model (http://www.fs.fed.us/pnw/fera/research/smoke/consume/index.shtml) to estimate emissions by applying empirically developed relationships between fuels, fire conditions (weather-based fire indexes), and emissions. Here again, we will review the gaps in data and modeling capability for accurate estimation of fire emissions in this region. Initial evaluation of Landsat for tundra fire characterization (Loboda et al. 2013) and successful use of the rich archive of Synthetic Aperture Radar imagery for many fire-disturbed sites in the region will be additional topics covered in this poster presentation. References: Breiman, L. 2001. Random forests. Machine Learning, 45:5-32. French, N.H.F., W.J. de Groot, L.K. Jenkins, B.. Rogers, et al. 2011. Model comparisons for estimating carbon emissions from North American wildland fire. J. Geophys. Res. 116:G00K05, doi:10.1029/2010JG001469. Loboda, T L, N H F French, C. Hight-Harf, L. Jenkins, M.E. Miller. 2013. Mapping fire extent and burn severity in Alaskan tussock tundra: An analysis of the spectral response of tundra vegetation to wildland fire. Remote Sens. Enviro. 134:194-209.

Discrete Deterministic and Stochastic Petri Nets

NASA Technical Reports Server (NTRS)

Zijal, Robert; Ciardo, Gianfranco

1996-01-01

Petri nets augmented with timing specifications gained a wide acceptance in the area of performance and reliability evaluation of complex systems exhibiting concurrency, synchronization, and conflicts. The state space of time-extended Petri nets is mapped onto its basic underlying stochastic process, which can be shown to be Markovian under the assumption of exponentially distributed firing times. The integration of exponentially and non-exponentially distributed timing is still one of the major problems for the analysis and was first attacked for continuous time Petri nets at the cost of structural or analytical restrictions. We propose a discrete deterministic and stochastic Petri net (DDSPN) formalism with no imposed structural or analytical restrictions where transitions can fire either in zero time or according to arbitrary firing times that can be represented as the time to absorption in a finite absorbing discrete time Markov chain (DTMC). Exponentially distributed firing times are then approximated arbitrarily well by geometric distributions. Deterministic firing times are a special case of the geometric distribution. The underlying stochastic process of a DDSPN is then also a DTMC, from which the transient and stationary solution can be obtained by standard techniques. A comprehensive algorithm and some state space reduction techniques for the analysis of DDSPNs are presented comprising the automatic detection of conflicts and confusions, which removes a major obstacle for the analysis of discrete time models.

Fire detection and incidents localization based on public information channels and social media

NASA Astrophysics Data System (ADS)

Thanos, Konstantinos-Georgios; Skroumpelou, Katerina; Rizogiannis, Konstantinos; Kyriazanos, Dimitris M.; Astyakopoulos, Alkiviadis; Thomopoulos, Stelios C. A.

2017-05-01

In this paper a solution is presented aiming to assist the early detection and localization of a fire incident by exploiting crowdsourcing and unofficial civilian online reports. It consists of two components: (a) the potential fire incident detection and (b) the visualization component. The first component comprises two modules that run in parallel and aim to collect reports posted on public platforms and conclude to potential fire incident locations. It collects the public reports, distinguishes reports that refer to a potential fire incident and store the corresponding information in a structured way. The second module aggregates all these stored reports and conclude to a probable fire location, based on the amount of reports per area, the time and location of these reports. In further the result is entered to a fusion module which combines it with information collected by sensors if available in order to provide a more accurate fire event detection capability. The visualization component is a fully - operational public information channel which provides accurate and up-to-date information about active and past fires, raises awareness about forest fires and the relevant hazards among citizens. The channel has visualization capabilities for presenting in an efficient way information regarding detected fire incidents fire expansion areas, and relevant information such as detecting sensors and reporting origin. The paper concludes with insight to current CONOPS end user with regards to the inclusion of the proposed solution to the current CONOPS of fire detection.

Microfabricated Chemical Sensors for Aerospace Fire Detection Applications

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Neudeck, Philip G.; Fralick, Gustave; Thomas, Valarie; Makel, D.; Liu, C. C.; Ward, B.; Wu, Q. H.

2001-01-01

The detection of fires on-board commercial aircraft is extremely important for safety reasons. Although dependable fire detection equipment presently exists within the cabin, detection of fire within the cargo hold has been less reliable and susceptible to false alarms. A second, independent method of fire detection to complement the conventional smoke detection techniques, such as the measurement of chemical species indicative of a fire, will help reduce false alarms and improve aircraft safety. Although many chemical species are indicative of a fire, two species of particular interest are CO and CO2. This paper discusses microfabricated chemical sensor development tailored to meet the needs of fire safety applications. This development is based on progress in three types of technology: 1) Micromachining and microfabrication (Microsystem) technology to fabricate miniaturized sensors. 2) The use of nanocrystalline materials to develop sensors with improved stability combined with higher sensitivity. 3) The development of high temperature semiconductors, especially silicon carbide. The individual sensor being developed and their level of maturity will be presented.

Orion MPCV Touchdown Detection Threshold Development and Testing

NASA Technical Reports Server (NTRS)

Daum, Jared; Gay, Robert

2013-01-01

A robust method of detecting Orion Multi-Purpose Crew Vehicle (MPCV) splashdown is necessary to ensure crew and hardware safety during descent and after touchdown. The proposed method uses a triple redundant system to inhibit Reaction Control System (RCS) thruster firings, detach parachute risers from the vehicle, and transition to the post-landing segment of the Flight Software (FSW). An in-depth trade study was completed to determine optimal characteristics of the touchdown detection method resulting in an algorithm monitoring filtered, lever-arm corrected, 200 Hz Inertial Measurement Unit (IMU) vehicle acceleration magnitude data against a tunable threshold using persistence counter logic. Following the design of the algorithm, high fidelity environment and vehicle simulations, coupled with the actual vehicle FSW, were used to tune the acceleration threshold and persistence counter value to result in adequate performance in detecting touchdown and sufficient safety margin against early detection while descending under parachutes. An analytical approach including Kriging and adaptive sampling allowed for a sufficient number of finite element analysis (FEA) impact simulations to be completed using minimal computation time. The combination of a persistence counter of 10 and an acceleration threshold of approximately 57.3 ft/s2 resulted in an impact performance factor of safety (FOS) of 1.0 and a safety FOS of approximately 2.6 for touchdown declaration. An RCS termination acceleration threshold of approximately 53.1 ft/s(exp)2 with a persistence counter of 10 resulted in an increased impact performance FOS of 1.2 at the expense of a lowered under-parachutes safety factor of 2.2. The resulting tuned algorithm was then tested on data from eight Capsule Parachute Assembly System (CPAS) flight tests, showing an experimental minimum safety FOS of 6.1. The formulated touchdown detection algorithm will be flown on the Orion MPCV FSW during the Exploration Flight Test 1 (EFT-1) mission in the second half of 2014.

Application of data fusion technology based on D-S evidence theory in fire detection

NASA Astrophysics Data System (ADS)

Cai, Zhishan; Chen, Musheng

2015-12-01

Judgment and identification based on single fire characteristic parameter information in fire detection is subject to environmental disturbances, and accordingly its detection performance is limited with the increase of false positive rate and false negative rate. The compound fire detector employs information fusion technology to judge and identify multiple fire characteristic parameters in order to improve the reliability and accuracy of fire detection. The D-S evidence theory is applied to the multi-sensor data-fusion: first normalize the data from all sensors to obtain the normalized basic probability function of the fire occurrence; then conduct the fusion processing using the D-S evidence theory; finally give the judgment results. The results show that the method meets the goal of accurate fire signal identification and increases the accuracy of fire alarm, and therefore is simple and effective.

The Detection Method of Fire Abnormal Based on Directional Drilling in Complex Conditions of Mine

NASA Astrophysics Data System (ADS)

Huijun, Duan; Shijun, Hao; Jie, Feng

2018-06-01

In the light of more and more urgent hidden fire abnormal detection problem in complex conditions of mine, a method which is used directional drilling technology is put forward. The method can avoid the obstacles in mine, and complete the fire abnormal detection. This paper based on analyzing the trajectory control of directional drilling, measurement while drilling and the characteristic of open branch process, the project of the directional drilling is formulated combination with a complex condition mine, and the detection of fire abnormal is implemented. This method can provide technical support for fire prevention, which also can provide a new way for fire anomaly detection in the similar mine.

Research Plan for Fire Signatures and Detection

NASA Technical Reports Server (NTRS)

2004-01-01

Viewgraphs on the prevention, suppression, and detection of fires aboard a spacecraft is presented. The topics include: 1) Fire Prevention, Detection, and Suppression Sub-Element Products; 2) FPDS Organizing Questions; 3) FPDS Organizing Questions; 4) Signatures, Sensors, and Simulations; 5) Quantification of Fire and Pre-Fire Signatures; 6) Smoke; 7) DAFT Hardware; 8) Additional Benefits of DAFT; 9) Development and Characterization of Sensors 10) Simulation of the Transport of Smoke and Fire Precursors; and 11) FPDS Organizing Questions.

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

46 CFR 95.05-1 - Fire detecting, manual alarm, and supervised patrol systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... provided a smoke detecting or other suitable type fire detecting system. (c) Enclosed spaces which are “specially suitable for vehicles” shall be fitted with an approved fire or smoke detecting system. [CGFR 66...

Use of artificial landscapes to isolate controls on burn probability

Treesearch

Marc-Andre Parisien; Carol Miller; Alan A. Ager; Mark A. Finney

2010-01-01

Techniques for modeling burn probability (BP) combine the stochastic components of fire regimes (ignitions and weather) with sophisticated fire growth algorithms to produce high-resolution spatial estimates of the relative likelihood of burning. Despite the numerous investigations of fire patterns from either observed or simulated sources, the specific influence of...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2011 CFR

2011-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2014 CFR

2014-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

46 CFR 78.47-13 - Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells.

Code of Federal Regulations, 2013 CFR

2013-10-01

..., and smoke detecting alarm bells. 78.47-13 Section 78.47-13 Shipping COAST GUARD, DEPARTMENT OF.... § 78.47-13 Fire detecting and manual alarm, automatic sprinkler, and smoke detecting alarm bells. (a) The fire detecting and manual alarm automatic sprinklers, and smoke detecting alarm bells in the...

Algorithm for Estimating the Plume Centerline Temperature and Ceiling Jet Temperature in the Presence of a Hot Upper Layer

NASA Technical Reports Server (NTRS)

Davis, William D.; Notarianni, Kathy A.; Tapper, Phillip Z.

1998-01-01

The experiments were designed to provide insight into the behavior of jet fuel fires in aircraft hangars and to study the impact of these fires on the design and operation of a variety of fire protection systems. As a result, the test series included small fires designed to investigate the operation of UV/IR detectors and smoke detectors as well as large fires which were used to investigate the operation of ceiling mounted heat detectors and sprinklers. The impact of the presence or absence of draft curtains was also studied in the 15 m hangar. It is shown that in order to predict the plume centerline temperature within experimental uncertainty, the entrainment of the upper layer gas must be modeled. For large fires, the impact of a changing radiation fraction must also be included in the calculation. The dependence of the radial temperature profile of the ceiling jet as a function of layer development is demonstrated and a ceiling jet temperature algorithm which includes the impact of a growing layer is developed.

Wavelet-based Gaussian-mixture hidden Markov model for the detection of multistage seizure dynamics: A proof-of-concept study

PubMed Central

2011-01-01

Background Epilepsy is a common neurological disorder characterized by recurrent electrophysiological activities, known as seizures. Without the appropriate detection strategies, these seizure episodes can dramatically affect the quality of life for those afflicted. The rationale of this study is to develop an unsupervised algorithm for the detection of seizure states so that it may be implemented along with potential intervention strategies. Methods Hidden Markov model (HMM) was developed to interpret the state transitions of the in vitro rat hippocampal slice local field potentials (LFPs) during seizure episodes. It can be used to estimate the probability of state transitions and the corresponding characteristics of each state. Wavelet features were clustered and used to differentiate the electrophysiological characteristics at each corresponding HMM states. Using unsupervised training method, the HMM and the clustering parameters were obtained simultaneously. The HMM states were then assigned to the electrophysiological data using expert guided technique. Minimum redundancy maximum relevance (mRMR) analysis and Akaike Information Criterion (AICc) were applied to reduce the effect of over-fitting. The sensitivity, specificity and optimality index of chronic seizure detection were compared for various HMM topologies. The ability of distinguishing early and late tonic firing patterns prior to chronic seizures were also evaluated. Results Significant improvement in state detection performance was achieved when additional wavelet coefficient rates of change information were used as features. The final HMM topology obtained using mRMR and AICc was able to detect non-ictal (interictal), early and late tonic firing, chronic seizures and postictal activities. A mean sensitivity of 95.7%, mean specificity of 98.9% and optimality index of 0.995 in the detection of chronic seizures was achieved. The detection of early and late tonic firing was validated with experimental intracellular electrical recordings of seizures. Conclusions The HMM implementation of a seizure dynamics detector is an improvement over existing approaches using visual detection and complexity measures. The subjectivity involved in partitioning the observed data prior to training can be eliminated. It can also decipher the probabilities of seizure state transitions using the magnitude and rate of change wavelet information of the LFPs. PMID:21504608

Clinical Predictors of Shigella and Campylobacter Infection in Children in the United States

PubMed Central

Smith, Timothy; Ye, Xiangyang; Stockmann, Chris; Cohen, Daniel; Leber, Amy; Daly, Judy; Jackson, Jami; Selvarangan, Rangaraj; Kanwar, Neena; Bender, Jeffery; Bard, Jennifer Dien; Festekjian, Ara; Duffy, Susan; Larsen, Chari; Baca, Tanya; Holmberg, Kristen; Bourzac, Kevin; Chapin, Kimberle C; Pavia, Andrew; Leung, Daniel

2017-01-01

Abstract Background Infectious gastroenteritis is a major cause of morbidity and mortality among children worldwide. While most episodes are self-limiting, for select pathogens such as Shigella and Campylobacter, etiological diagnosis may allow effective antimicrobial therapy and aid public health interventions. Unfortunately, clinical predictors of such pathogens are not well established and are based on small studies using bacterial culture for identification. Methods We used prospectively collected data from a multi-center study of pediatric gastroenteritis employing multi-pathogen molecular diagnostics to determine clinical predictors associated with 1) Shigella and 2) Shigella or Campylobacter infection. We used machine learning algorithms for clinical predictor identification, then performed logistic regression on features extracted plus pre-selected variables of interest. Results Of 993 children enrolled with acute diarrhea, we detected Shigella spp. in 56 (5.6%) and Campylobacter spp. in 24 (2.4%). Compared with children who had neither pathogen detected (of whom, >70% had ≥1 potential pathogen identified), bloody diarrhea (odds ratio 4.0), headache (OR 2.2), fever (OR 7.1), summer (OR 3.3), and sick contact with GI illness (OR 2.2), were positively associated with Shigella, and out-of-state travel (OR 0.3) and vomiting and/or nausea (OR 0.4) were negatively associated (Table). For Shigella or Campylobacter, predictors were similar but season was no longer significantly associated with infection. Conclusion These results can create prediction models and assist clinicians with identifying patients who would benefit from diagnostic testing and earlier antibiotic treatment. This may curtail unnecessary antibiotic use, and help to direct and target appropriate use of stool diagnostics. Disclosures A. Leber, BioFIre Diagnostics: Research Contractor and Scientific Advisor, Research support, Speaker honorarium and Travel expenses J. Daly, Biofire: Grant Investigator, Grant recipient R. Selvarangan, BioFire Diagnostics: Board Member and Investigator, Consulting fee and Research grant Luminex Diagnostics: Investigator, Research grant J. Dien Bard, BioFire: Consultant and Investigator, Research grant and Speaker honorarium K. Holmberg, BioFire Diagnostics: Employee, Salary K. Bourzac, BioFire Diagnostics: Employee, Salary K. C. Chapin, BioFire Diagnstics: Investigator, Research support A. Pavia, BioFire Diagnostics: Grant Investigator, Research grant

46 CFR 108.404 - Selection of fire detection system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Selection of fire detection system. 108.404 Section 108.404 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.404 Selection of fire detection system. (a) If a...

46 CFR 108.413 - Fusible element fire detection system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Fusible element fire detection system. 108.413 Section 108.413 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.413 Fusible element fire detection system...

46 CFR 108.413 - Fusible element fire detection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Fusible element fire detection system. 108.413 Section 108.413 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.413 Fusible element fire detection system...

46 CFR 108.404 - Selection of fire detection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Selection of fire detection system. 108.404 Section 108.404 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.404 Selection of fire detection system. (a) If a...

46 CFR 108.413 - Fusible element fire detection system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Fusible element fire detection system. 108.413 Section 108.413 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.413 Fusible element fire detection system...

46 CFR 108.404 - Selection of fire detection system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Selection of fire detection system. 108.404 Section 108.404 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.404 Selection of fire detection system. (a) If a...

46 CFR 108.404 - Selection of fire detection system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Selection of fire detection system. 108.404 Section 108.404 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.404 Selection of fire detection system. (a) If a...

46 CFR 108.413 - Fusible element fire detection system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Fusible element fire detection system. 108.413 Section 108.413 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.413 Fusible element fire detection system...

Detection, monitoring, and quantitative analysis of wildfires with the BIRD satellite

NASA Astrophysics Data System (ADS)

Oertel, Dieter A.; Briess, Klaus; Lorenz, Eckehard; Skrbek, Wolfgang; Zhukov, Boris

2004-02-01

Increasing concern about environment and interest to avoid losses led to growing demands on space borne fire detection, monitoring and quantitative parameter estimation of wildfires. The global change research community intends to quantify the amount of gaseous and particulate matter emitted from vegetation fires, peat fires and coal seam fires. The DLR Institute of Space Sensor Technology and Planetary Exploration (Berlin-Adlershof) developed a small satellite called BIRD (Bi-spectral Infrared Detection) which carries a sensor package specially designed for fire detection. BIRD was launched as a piggy-back satellite on October 22, 2001 with ISRO"s Polar Satellite Launch Vehicle (PSLV). It is circling the Earth on a polar and sun-synchronous orbit at an altitude of 572 km and it is providing unique data for detailed analysis of high temperature events on Earth surface. The BIRD sensor package is dedicated for high resolution and reliable fire recognition. Active fire analysis is possible in the sub-pixel domain. The leading channel for fire detection and monitoring is the MIR channel at 3.8 μm. The rejection of false alarms is based on procedures using MIR/NIR (Middle Infra Red/Near Infra Red) and MIR/TIR (Middle Infra Red/Thermal Infra Red) radiance ratio thresholds. Unique results of BIRD wildfire detection and analysis over fire prone regions in Australia and Asia will be presented. BIRD successfully demonstrates innovative fire recognition technology for small satellites which permit to retrieve quantitative characteristics of active burning wildfires, such as the equivalent fire temperature, fire area, radiative energy release, fire front length and fire front strength.

33 CFR 149.421 - What is the requirement for a previously approved fire detection and alarm system on a deepwater...

Code of Federal Regulations, 2010 CFR

2010-07-01

... previously approved fire detection and alarm system on a deepwater port? 149.421 Section 149.421 Navigation... Requirements § 149.421 What is the requirement for a previously approved fire detection and alarm system on a deepwater port? An existing fire detection and alarm system on a deepwater port need not meet the...

33 CFR 149.421 - What is the requirement for a previously approved fire detection and alarm system on a deepwater...

Code of Federal Regulations, 2011 CFR

2011-07-01

... previously approved fire detection and alarm system on a deepwater port? 149.421 Section 149.421 Navigation... Requirements § 149.421 What is the requirement for a previously approved fire detection and alarm system on a deepwater port? An existing fire detection and alarm system on a deepwater port need not meet the...

33 CFR 149.421 - What is the requirement for a previously approved fire detection and alarm system on a deepwater...

Code of Federal Regulations, 2014 CFR

2014-07-01

... previously approved fire detection and alarm system on a deepwater port? 149.421 Section 149.421 Navigation... Requirements § 149.421 What is the requirement for a previously approved fire detection and alarm system on a deepwater port? An existing fire detection and alarm system on a deepwater port need not meet the...

33 CFR 149.421 - What is the requirement for a previously approved fire detection and alarm system on a deepwater...

Code of Federal Regulations, 2012 CFR

2012-07-01

... previously approved fire detection and alarm system on a deepwater port? 149.421 Section 149.421 Navigation... Requirements § 149.421 What is the requirement for a previously approved fire detection and alarm system on a deepwater port? An existing fire detection and alarm system on a deepwater port need not meet the...

33 CFR 149.421 - What is the requirement for a previously approved fire detection and alarm system on a deepwater...

Code of Federal Regulations, 2013 CFR

2013-07-01

... previously approved fire detection and alarm system on a deepwater port? 149.421 Section 149.421 Navigation... Requirements § 149.421 What is the requirement for a previously approved fire detection and alarm system on a deepwater port? An existing fire detection and alarm system on a deepwater port need not meet the...

Pediatric cyanide poisoning by fire smoke inhalation: a European expert consensus. Toxicology Surveillance System of the Intoxications Working Group of the Spanish Society of Paediatric Emergencies.

PubMed

Mintegi, Santiago; Clerigue, Nuria; Tipo, Vincenzo; Ponticiello, Eduardo; Lonati, Davide; Burillo-Putze, Guillermo; Delvau, Nicolas; Anseeuw, Kurt

2013-11-01

Most fire-related deaths are attributable to smoke inhalation rather than burns. The inhalation of fire smoke, which contains not only carbon monoxide but also a complex mixture of gases, seems to be the major cause of morbidity and mortality in fire victims, mainly in enclosed spaces. Cyanide gas exposure is quite common during smoke inhalation, and cyanide is present in the blood of fire victims in most cases and may play an important role in death by smoke inhalation. Cyanide poisoning may, however, be difficult to diagnose and treat. In these children, hydrogen cyanide seems to be a major source of concern, and the rapid administration of the antidote, hydroxocobalamin, may be critical for these children.European experts recently met to formulate an algorithm for prehospital and hospital management of adult patients with acute cyanide poisoning. Subsequently, a group of European pediatric experts met to evaluate and adopt that algorithm for use in the pediatric population.

Cropland management dynamics as a driver of forest cover change in European Russia (Invited)

NASA Astrophysics Data System (ADS)

Tyukavina, A.; Krylov, A.; Potapov, P.; Turubanova, S.; Hansen, M.; McCarty, J. L.

2013-12-01

The European part of Russia spans over 40% of the European subcontinent and comprises most of Europe's temperate and boreal forests. The region has undergone a socio-economic transition during the last two decades that has resulted in radical changes in land management. Large-scale agriculture land abandonment caused massive afforestation in the Central and Northern parts of the region (Alcantara et al. 2012). Afforestation of former croplands is currently not included in the official forestry statistical reports (Potapov et al. 2012), but is likely to have major impacts on regional carbon budgets (Kuemmerle et al. 2009). We employed a complete archive of Landsat TM and ETM+ imagery and automatic data processing algorithm to create regional time-sequential image composites and multi-temporal metrics for 1985-2012. Spectral metrics were used as independent variables to map forest cover and change with help of supervised machine learning algorithms and trend analysis. Forest cover loss was attributed to fires, harvesting, and wind/disease dynamics, while forest cover gain was disaggregated into reforestation and afforestation using pre-1990 TM imagery as baseline data. Special attention was paid to agricultural abandonment. Fire events of the last decade have been further characterized by ignition place, time, and burning intensity using MODIS fire detection data. Change detection products have been validated using field data collected during summer 2012 and 2013 and high resolution imagery. Massive arable land abandonment caused forest area increase within Central agricultural regions. While total logging area decreased after the USSR breakdown, logging and other forms of clearing increased within the Central and Western parts of the region. Gross forest gain and loss were nearly balanced within region; however, the most populated regions of European Russia featured the highest rate of net forest cover loss during the last decade. The annual burned forest area as well as area of windstorms damage significantly increased, especially in the Central regions. Fires predominantly affected pine forests and drained peatlands prone to summer droughts. Fire date and ignition analysis showed that forest fires are not related to extensive spring-time agricultural burning. References: Alcantara, C., T. Kuemmerle, A. V. Prishchepov & V. C. Radeloff. 2012. Mapping abandoned agriculture with multi-temporal MODIS satellite data. 334-347. Remote Sensing of Environment. Kuemmerle, T., O. Chaskovskyy, J. Knorn, V. C. Radeloff, I. Kruhlov, W. S. Keeton & P. Hostert. 2009. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007. Remote Sensing of Environment, 113, 1194-1207. Potapov, P., S. Turubanova, I. Zhuravleva, M. Hansen, A. Yaroshenko & A. Manisha. 2012. Forest Cover Change within the Russian European North after the Breakdown of Soviet Union (1990-2005) 1-11. International Journal of Forestry Research.

Design and realization of disaster assessment algorithm after forest fire

NASA Astrophysics Data System (ADS)

Xu, Aijun; Wang, Danfeng; Tang, Lihua

2008-10-01

Based on GIS technology, this paper mainly focuses on the application of disaster assessment algorithm after forest fire and studies on the design and realization of disaster assessment based on GIS. After forest fire through the analysis and processing of multi-sources and heterogeneous data, this paper integrates the foundation that the domestic and foreign scholars laid of the research on assessment for forest fire loss with the related knowledge of assessment, accounting and forest resources appraisal so as to study and approach the theory framework and assessment index of the research on assessment for forest fire loss. The technologies of extracting boundary, overlay analysis, and division processing of multi-sources spatial data are available to realize the application of the investigation method of the burnt forest area and the computation of the fire area. The assessment provides evidence for fire cleaning in burnt areas and new policy making on restoration in terms of the direct and the indirect economic loss and ecological and environmental damage caused by forest fire under the condition of different fire danger classes and different amounts of forest accumulation, thus makes forest resources protection operated in a faster, more efficient and more economical way. Finally, this paper takes Lin'an city of Zhejiang province as a test area to confirm the method mentioned in the paper in terms of key technologies.

7 CFR 301.81-11 - Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 5 2014-01-01 2014-01-01 false Imported fire ant detection, control, exclusion, and..., DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant Quarantine and Regulations § 301.81-11 Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

7 CFR 301.81-11 - Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 5 2011-01-01 2011-01-01 false Imported fire ant detection, control, exclusion, and..., DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant Quarantine and Regulations § 301.81-11 Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

7 CFR 301.81-11 - Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 5 2012-01-01 2012-01-01 false Imported fire ant detection, control, exclusion, and..., DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant Quarantine and Regulations § 301.81-11 Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

7 CFR 301.81-11 - Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 5 2013-01-01 2013-01-01 false Imported fire ant detection, control, exclusion, and..., DEPARTMENT OF AGRICULTURE DOMESTIC QUARANTINE NOTICES Imported Fire Ant Quarantine and Regulations § 301.81-11 Imported fire ant detection, control, exclusion, and enforcement program for nurseries producing...

Stratifying Tropical Fires by Land Cover: Insights into Amazonian Fires, Aerosol Loading, and Regional Deforestation

NASA Technical Reports Server (NTRS)

TenHoeve, J. E.; Remer, L. A.; Jacobson, M. Z.

2010-01-01

This study analyzes changes in the number of fires detected on forest, grass, and transition lands during the 2002-2009 biomass burning seasons using fire detection data and co-located land cover classifications from the Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the total number of detected fires correlates well with MODIS mean aerosol optical depth (AOD) from year to year, in accord with other studies. However, we also show that the ratio of forest to savanna fires varies substantially from year to year. Forest fires have trended downward, on average, since the beginning of 2006 despite a modest increase in 2007. Our study suggests that high particulate matter loading detected in 2007 was likely due to a large number of savanna/agricultural fires that year. Finally, we illustrate that the correlation between annual Brazilian deforestation estimates and MODIS fires is considerably higher when fires are stratified by MODIS-derived land cover classifications.

Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967

Integrating models to predict regional haze from wildland fire.

Treesearch

D. McKenzie; S.M. O' Neill; N. Larkin; R.A. Norheim

2006-01-01

Visibility impairment from regional haze is a significant problem throughout the continental United States. A substantial portion of regional haze is produced by smoke from prescribed and wildland fires. Here we describe the integration of four simulation models, an array of GIS raster layers, and a set of algorithms for fire-danger calculations into a modeling...

Thermal weapon sights with integrated fire control computers: algorithms and experiences

NASA Astrophysics Data System (ADS)

Rothe, Hendrik; Graswald, Markus; Breiter, Rainer

2008-04-01

The HuntIR long range thermal weapon sight of AIM is deployed in various out of area missions since 2004 as a part of the German Future Infantryman system (IdZ). In 2007 AIM fielded RangIR as upgrade with integrated laser Range finder (LRF), digital magnetic compass (DMC) and fire control unit (FCU). RangIR fills the capability gaps of day/night fire control for grenade machine guns (GMG) and the enhanced system of the IdZ. Due to proven expertise and proprietary methods in fire control, fast access to military trials for optimisation loops and similar hardware platforms, AIM and the University of the Federal Armed Forces Hamburg (HSU) decided to team for the development of suitable fire control algorithms. The pronounced ballistic trajectory of the 40mm GMG requires most accurate FCU-solutions specifically for air burst ammunition (ABM) and is most sensitive to faint effects like levelling or firing up/downhill. This weapon was therefore selected to validate the quality of the FCU hard- and software under relevant military conditions. For exterior ballistics the modified point mass model according to STANAG 4355 is used. The differential equations of motions are solved numerically, the two point boundary value problem is solved iteratively. Computing time varies according to the precision needed and is typical in the range from 0.1 - 0.5 seconds. RangIR provided outstanding hit accuracy including ABM fuze timing in various trials of the German Army and allied partners in 2007 and is now ready for series production. This paper deals mainly with the fundamentals of the fire control algorithms and shows how to implement them in combination with any DSP-equipped thermal weapon sights (TWS) in a variety of light supporting weapon systems.

[Research on early fire detection with CO-CO2 FTIR-spectroscopy].

PubMed

Du, Jian-hua; Zhang, Ren-cheng; Huang, Xiang-ying; Gong, Xue; Zhang, Xiao-hua

2007-05-01

A new fire detection method is put forward based on the theory of FTIR spectroscopy through analyzing all kinds of detection methods, in which CO and CO2 are chosen as early fire detection objects, and an early fire experiment system has been set up. The concentration characters of CO and CO2 were obtained through early fire experiments including real alarm sources and nuisance alarm sources. In real alarm sources there are abundant CO and CO2 which change regularly. In nuisance alarm sources there is almost no CO. So it's feasible to reduce the false alarms and increase the sensitivity of early fire detectors through analyzing the concentration characters of CO and CO2.

Forest Fire Advanced System Technology (FFAST): A Conceptual Design for Detection and Mapping

Treesearch

J. David Nichols; John R. Warren

1987-01-01

The Forest Fire Advanced System Technology (FFAST) project is developing a data system to provide near-real-time forest fire information to fire management at the fire Incident Command Post (ICP). The completed conceptual design defined an integrated forest fire detection and mapping system that is based upon technology available in the 1990's. System component...

Cost-Effective Fuel Treatment Planning

NASA Astrophysics Data System (ADS)

Kreitler, J.; Thompson, M.; Vaillant, N.

2014-12-01

The cost of fighting large wildland fires in the western United States has grown dramatically over the past decade. This trend will likely continue with growth of the WUI into fire prone ecosystems, dangerous fuel conditions from decades of fire suppression, and a potentially increasing effect from prolonged drought and climate change. Fuel treatments are often considered the primary pre-fire mechanism to reduce the exposure of values at risk to wildland fire, and a growing suite of fire models and tools are employed to prioritize where treatments could mitigate wildland fire damages. Assessments using the likelihood and consequence of fire are critical because funds are insufficient to reduce risk on all lands needing treatment, therefore prioritization is required to maximize the effectiveness of fuel treatment budgets. Cost-effectiveness, doing the most good per dollar, would seem to be an important fuel treatment metric, yet studies or plans that prioritize fuel treatments using costs or cost-effectiveness measures are absent from the literature. Therefore, to explore the effect of using costs in fuel treatment planning we test four prioritization algorithms designed to reduce risk in a case study examining fuel treatments on the Sisters Ranger District of central Oregon. For benefits we model sediment retention and standing biomass, and measure the effectiveness of each algorithm by comparing the differences among treatment and no treat alternative scenarios. Our objective is to maximize the averted loss of net benefits subject to a representative fuel treatment budget. We model costs across the study landscape using the My Fuel Treatment Planner software, tree list data, local mill prices, and GIS-measured site characteristics. We use fire simulations to generate burn probabilities, and estimate fire intensity as conditional flame length at each pixel. Two prioritization algorithms target treatments based on cost-effectiveness and show improvements over those that use only benefits. Variations across the heterogeneous surfaces of costs and benefits create opportunities for fuel treatments to maximize the expected averted loss of benefits. By targeting these opportunities we demonstrate how incorporating costs in fuel treatment prioritization can improve the outcome of fuel treatment planning.

Investigating dynamic underground coal fires by means of numerical simulation

NASA Astrophysics Data System (ADS)

Wessling, S.; Kessels, W.; Schmidt, M.; Krause, U.

2008-01-01

Uncontrolled burning or smoldering of coal seams, otherwise known as coal fires, represents a worldwide natural hazard. Efficient application of fire-fighting strategies and prevention of mining hazards require that the temporal evolution of fire propagation can be sufficiently precise predicted. A promising approach for the investigation of the temporal evolution is the numerical simulation of involved physical and chemical processes. In the context of the Sino-German Research Initiative `Innovative Technologies for Detection, Extinction and Prevention of Coal Fires in North China,' a numerical model has been developed for simulating underground coal fires at large scales. The objective of such modelling is to investigate observables, like the fire propagation rate, with respect to the thermal and hydraulic parameters of adjacent rock. In the model, hydraulic, thermal and chemical processes are accounted for, with the last process complemented by laboratory experiments. Numerically, one key challenge in modelling coal fires is to circumvent the small time steps resulting from the resolution of fast reaction kinetics at high temperatures. In our model, this problem is solved by means of an `operator-splitting' approach, in which transport and reactive processes of oxygen are independently calculated. At high temperatures, operator-splitting has the decisive advantage of allowing the global time step to be chosen according to oxygen transport, so that time-consuming simulation through the calculation of fast reaction kinetics is avoided. Also in this model, because oxygen distribution within a coal fire has been shown to remain constant over long periods, an additional extrapolation algorithm for the coal concentration has been applied. In this paper, we demonstrate that the operator-splitting approach is particularly suitable for investigating the influence of hydraulic parameters of adjacent rocks on coal fire propagation. A study shows that dynamic propagation strongly depends on permeability variations. For the assumed model, no fire exists for permeabilities k < 10-10m2, whereas the fire propagation velocity ranges between 340ma-1 for k = 10-8m2, and drops to lower than 3ma-1 for k = 5 × 10-10m2. Additionally, strong temperature variations are observed for the permeability range 5 × 10-10m2 < k < 10-8m2.

Detection and analysis of high-temperature events in the BIRD mission

NASA Astrophysics Data System (ADS)

Zhukov, Boris; Briess, Klaus; Lorenz, Eckehard; Oertel, Dieter; Skrbek, Wolfgang

2005-01-01

The primary mission objective of a new small Bi-spectral InfraRed Detection (BIRD) satellite is detection and quantitative analysis of high-temperature events like fires and volcanoes. An absence of saturation in the BIRD infrared channels makes it possible to improve false alarm rejection as well as to retrieve quantitative characteristics of hot targets, including their effective fire temperature, area and the radiative energy release. Examples are given of detection and analysis of wild and coal seam fires, of volcanic activity as well as of oil fires in Iraq. The smallest fires detected by BIRD, which were verified on ground, had an area of 12m2 at daytime and 4m2 at night.

33 CFR 149.414 - What are the requirements for a fire detection and alarm system?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 33 Navigation and Navigable Waters 2 2010-07-01 2010-07-01 false What are the requirements for a fire detection and alarm system? 149.414 Section 149.414 Navigation and Navigable Waters COAST GUARD... national consensus standard, as that term is defined in 29 CFR 1910.2, for fire detection and fire alarm...

GIS applied to location of fires detection towers in domain area of tropical forest.

PubMed

Eugenio, Fernando Coelho; Rosa Dos Santos, Alexandre; Fiedler, Nilton Cesar; Ribeiro, Guido Assunção; da Silva, Aderbal Gomes; Juvanhol, Ronie Silva; Schettino, Vitor Roberto; Marcatti, Gustavo Eduardo; Domingues, Getúlio Fonseca; Alves Dos Santos, Gleissy Mary Amaral Dino; Pezzopane, José Eduardo Macedo; Pedra, Beatriz Duguy; Banhos, Aureo; Martins, Lima Deleon

2016-08-15

In most countries, the loss of biodiversity caused by the fires is worrying. In this sense, the fires detection towers are crucial for rapid identification of fire outbreaks and can also be used in environmental inspection, biodiversity monitoring, telecommunications mechanisms, telemetry and others. Currently the methodologies for allocating fire detection towers over large areas are numerous, complex and non-standardized by government supervisory agencies. Therefore, this study proposes and evaluates different methodologies to best location of points to install fire detection towers considering the topography, risk areas, conservation units and heat spots. Were used Geographic Information Systems (GIS) techniques and unaligned stratified systematic sampling for implementing and evaluating 9 methods for allocating fire detection towers. Among the methods evaluated, the C3 method was chosen, represented by 140 fire detection towers, with coverage of: a) 67% of the study area, b) 73.97% of the areas with high risk, c) 70.41% of the areas with very high risk, d) 70.42% of the conservation units and e) 84.95% of the heat spots in 2014. The proposed methodology can be adapted to areas of other countries. Copyright © 2016 Elsevier B.V. All rights reserved.

36 CFR 1234.12 - What are the fire safety requirements that apply to records storage facilities?

Code of Federal Regulations, 2012 CFR

2012-07-01

... records storage facilities? (a) The fire detection and protection systems must be designed or reviewed by a licensed fire protection engineer. If the system was not designed by a licensed fire protection... engineer that describes the design intent of the fire detection and suppression system, detailing the...

36 CFR 1234.12 - What are the fire safety requirements that apply to records storage facilities?

Code of Federal Regulations, 2014 CFR

2014-07-01

... records storage facilities? (a) The fire detection and protection systems must be designed or reviewed by a licensed fire protection engineer. If the system was not designed by a licensed fire protection... engineer that describes the design intent of the fire detection and suppression system, detailing the...

Data Filtering of Western Hemisphere GOES Wildfire ABBA Products

NASA Astrophysics Data System (ADS)

Theisen, M.; Prins, E.; Schmidt, C.; Reid, J. S.; Hunter, J.; Westphal, D.

2002-05-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE') project was developed to model biomass burning emissions, transport, and radiative effects in real time. The model relies on data from the Geostationary Operational Environment Satellites (GOES-8, GOES-10), that is generated by the Wildfire Automated Biomass Burning Algorithm (WF ABBA). In an attempt to develop the most accurate modeling system the data set needs to be filtered to distinguish the true fire pixels from false alarms. False alarms occur due to reflection of solar radiation off of standing water, surface structure variances, and heat anomalies. The Reoccurring Fire Filtering algorithm (ReFF) was developed to address such false alarms by filtering data dependent on reoccurrence, location in relation to region and satellite, as well as heat intensity. WF ABBA data for the year 2000 during the peak of the burning season were analyzed using ReFF. The analysis resulted in a 45% decrease in North America and only a 15% decrease in South America, respectively, in total fire pixel occurrence. The lower percentage decrease in South America is a result of fires burning for longer periods of time, less surface variance, as well as an increase in heat intensity of fires for that region. Also fires are so prevalent in the region that multiple fires may coexist in the same 4-kilometer pixel.

Flame filtering and perimeter localization of wildfires using aerial thermal imagery

NASA Astrophysics Data System (ADS)

Valero, Mario M.; Verstockt, Steven; Rios, Oriol; Pastor, Elsa; Vandecasteele, Florian; Planas, Eulàlia

2017-05-01

Airborne thermal infrared (TIR) imaging systems are being increasingly used for wild fire tactical monitoring since they show important advantages over spaceborne platforms and visible sensors while becoming much more affordable and much lighter than multispectral cameras. However, the analysis of aerial TIR images entails a number of difficulties which have thus far prevented monitoring tasks from being totally automated. One of these issues that needs to be addressed is the appearance of flame projections during the geo-correction of off-nadir images. Filtering these flames is essential in order to accurately estimate the geographical location of the fuel burning interface. Therefore, we present a methodology which allows the automatic localisation of the active fire contour free of flame projections. The actively burning area is detected in TIR georeferenced images through a combination of intensity thresholding techniques, morphological processing and active contours. Subsequently, flame projections are filtered out by the temporal frequency analysis of the appropriate contour descriptors. The proposed algorithm was tested on footages acquired during three large-scale field experimental burns. Results suggest this methodology may be suitable to automatise the acquisition of quantitative data about the fire evolution. As future work, a revision of the low-pass filter implemented for the temporal analysis (currently a median filter) was recommended. The availability of up-to-date information about the fire state would improve situational awareness during an emergency response and may be used to calibrate data-driven simulators capable of emitting short-term accurate forecasts of the subsequent fire evolution.

Individual Combatant’s Weapons Firing Algorithm

DTIC Science & Technology

2010-04-01

target selection prioritization scheme, aim point, mode of fire, and estimates on Phit /Pmiss for a single SME. Also undertaken in this phase of the...5 APPENDIX A: SME FUZZY ESTIMATES ON FACTORS AND ESTIMATES ON PHIT /PMISS.....6...influencing the target selection prioritization scheme, aim point, mode of fire, and estimates on Phit /Pmiss for a single SME. Also undertaken in this

A generalized linear integrate-and-fire neural model produces diverse spiking behaviors.

PubMed

Mihalaş, Stefan; Niebur, Ernst

2009-03-01

For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model's rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation.

A Generalized Linear Integrate-and-Fire Neural Model Produces Diverse Spiking Behaviors

PubMed Central

Mihalaş, Ştefan; Niebur, Ernst

2010-01-01

For simulations of neural networks, there is a trade-off between the size of the network that can be simulated and the complexity of the model used for individual neurons. In this study, we describe a generalization of the leaky integrate-and-fire model that produces a wide variety of spiking behaviors while still being analytically solvable between firings. For different parameter values, the model produces spiking or bursting, tonic, phasic or adapting responses, depolarizing or hyperpolarizing after potentials and so forth. The model consists of a diagonalizable set of linear differential equations describing the time evolution of membrane potential, a variable threshold, and an arbitrary number of firing-induced currents. Each of these variables is modified by an update rule when the potential reaches threshold. The variables used are intuitive and have biological significance. The model’s rich behavior does not come from the differential equations, which are linear, but rather from complex update rules. This single-neuron model can be implemented using algorithms similar to the standard integrate-and-fire model. It is a natural match with event-driven algorithms for which the firing times are obtained as a solution of a polynomial equation. PMID:18928368

Ultraviolet Source For Testing Hydrogen-Fire Detectors

NASA Technical Reports Server (NTRS)

Hall, Gregory A.; Larson, William E.; Youngquist, Robert C.; Moerk, John S.; Haskell, William D.; Cox, Robert B.; Polk, Jimmy D.; Stout, Stephen J.; Strobel, James P.

1995-01-01

Hand-held portable unit emits ultraviolet light similar to that emitted by hydrogen burning in air. Developed for use in testing optoelectronic hydrogen-fire detectors, which respond to ultraviolet light at wavelengths from 180 to 240 nanometers. Wavelength range unique in that within it, hydrogen fires emit small but detectable amounts of radiation, light from incandescent lamps and Sun almost completely absent, and air sufficiently transmissive to enable detection of hydrogen fire from distance. Consequently, this spectral region favorable for detecting hydrogen fires while minimizing false alarms.

Evaluation and Testing of Rail Transit Undercar Fire Detection and Suppression Systems

DOT National Transportation Integrated Search

1989-08-01

This document presents the results of a comprehensive review and evaluation of transit undercar fire detection and suppression methods. The evaluation of fire detection method resulted in a recommendation that continuous wire type linear thermal dete...

14 CFR 25.858 - Cargo or baggage compartment smoke or fire detection systems.

Code of Federal Regulations, 2010 CFR

2010-01-01

... detection systems. 25.858 Section 25.858 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT... Construction Fire Protection § 25.858 Cargo or baggage compartment smoke or fire detection systems. If... must be met for each cargo or baggage compartment with those provisions: (a) The detection system must...

Multivariate statistical analysis strategy for multiple misfire detection in internal combustion engines

NASA Astrophysics Data System (ADS)

Hu, Chongqing; Li, Aihua; Zhao, Xingyang

2011-02-01

This paper proposes a multivariate statistical analysis approach to processing the instantaneous engine speed signal for the purpose of locating multiple misfire events in internal combustion engines. The state of each cylinder is described with a characteristic vector extracted from the instantaneous engine speed signal following a three-step procedure. These characteristic vectors are considered as the values of various procedure parameters of an engine cycle. Therefore, determination of occurrence of misfire events and identification of misfiring cylinders can be accomplished by a principal component analysis (PCA) based pattern recognition methodology. The proposed algorithm can be implemented easily in practice because the threshold can be defined adaptively without the information of operating conditions. Besides, the effect of torsional vibration on the engine speed waveform is interpreted as the presence of super powerful cylinder, which is also isolated by the algorithm. The misfiring cylinder and the super powerful cylinder are often adjacent in the firing sequence, thus missing detections and false alarms can be avoided effectively by checking the relationship between the cylinders.

Accommodation of practical constraints by a linear programming jet select. [for Space Shuttle

NASA Technical Reports Server (NTRS)

Bergmann, E.; Weiler, P.

1983-01-01

An experimental spacecraft control system will be incorporated into the Space Shuttle flight software and exercised during a forthcoming mission to evaluate its performance and handling qualities. The control system incorporates a 'phase space' control law to generate rate change requests and a linear programming jet select to compute jet firings. Posed as a linear programming problem, jet selection must represent the rate change request as a linear combination of jet acceleration vectors where the coefficients are the jet firing times, while minimizing the fuel expended in satisfying that request. This problem is solved in real time using a revised Simplex algorithm. In order to implement the jet selection algorithm in the Shuttle flight control computer, it was modified to accommodate certain practical features of the Shuttle such as limited computer throughput, lengthy firing times, and a large number of control jets. To the authors' knowledge, this is the first such application of linear programming. It was made possible by careful consideration of the jet selection problem in terms of the properties of linear programming and the Simplex algorithm. These modifications to the jet select algorithm may by useful for the design of reaction controlled spacecraft.

Comparison of Available Technologies for Fire Spots Detection via Linear Heat Detector

NASA Astrophysics Data System (ADS)

Miksa, František; Nemlaha, Eduard

2016-12-01

It is very demanding to detect fire spots under difficult conditions with high occurrence of interfering external factors such as large distances, airflow difficultly, high dustiness, high humidity, etc. Spot fire sensors do not meet the requirements due to the aforementioned conditions as well as large distances. Therefore, the detection of a fire spot via linear heat sensing cables is utilized.

The Feasibility of Using a Galvanic Cell Array for Corrosion Detection and Solution Monitoring

NASA Technical Reports Server (NTRS)

Kolody, Mark; Calle, Luz-Marina; Zeitlin, Nancy P. (Technical Monitor)

2003-01-01

An initial investigation into the response of the individual galvanic couples was conducted using potentiodynamic polarization measurements of solutions under conditions of varying corrosivity. It is hypothesized that the differing electrodes may provide a means to further investigate the corrosive nature of the analyte through genetic algorithms and pattern recognition techniques. The robust design of the electrochemical sensor makes its utilization in space exploration particularly attractive. Since the electrodes are fired on a ceramic substrate at 900 C, they may be one of the most rugged sensors available for the anticipated usage.

36 CFR § 1234.12 - What are the fire safety requirements that apply to records storage facilities?

Code of Federal Regulations, 2013 CFR

2013-07-01

... records storage facilities? (a) The fire detection and protection systems must be designed or reviewed by a licensed fire protection engineer. If the system was not designed by a licensed fire protection... engineer that describes the design intent of the fire detection and suppression system, detailing the...

Enhancements in Deriving Smoke Emission Coefficients from Fire Radiative Power Measurements

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2011-01-01

Smoke emissions have long been quantified after-the-fact by simple multiplication of burned area, biomass density, fraction of above-ground biomass, and burn efficiency. A new algorithm has been suggested, as described in Ichoku & Kaufman (2005), for use in calculating smoke emissions directly from fire radiative power (FRP) measurements such that the latency and uncertainty associated with the previously listed variables are avoided. Application of this new, simpler and more direct algorithm is automatic, based only on a fire's FRP measurement and a predetermined coefficient of smoke emission for a given location. Attaining accurate coefficients of smoke emission is therefore critical to the success of this algorithm. In the aforementioned paper, an initial effort was made to derive coefficients of smoke emission for different large regions of interest using calculations of smoke emission rates from MODIS FRP and aerosol optical depth (AOD) measurements. Further work had resulted in a first draft of a 1 1 resolution map of these coefficients. This poster will present the work done to refine this algorithm toward the first production of global smoke emission coefficients. Main updates in the algorithm include: 1) inclusion of wind vectors to help refine several parameters, 2) defining new methods for calculating the fire-emitted AOD fractions, and 3) calculating smoke emission rates on a per-pixel basis and aggregating to grid cells instead of doing so later on in the process. In addition to a presentation of the methodology used to derive this product, maps displaying preliminary results as well as an outline of the future application of such a product into specific research opportunities will be shown.

Fuel models and fire potential from satellite and surface observations

USGS Publications Warehouse

Burgan, R.E.; Klaver, R.W.; Klarer, J.M.

1998-01-01

A national 1-km resolution fire danger fuel model map was derived through use of previously mapped land cover classes and ecoregions, and extensive ground sample data, then refined through review by fire managers familiar with various portions of the U.S. The fuel model map will be used in the next generation fire danger rating system for the U.S., but it also made possible immediate development of a satellite and ground based fire potential index map. The inputs and algorithm of the fire potential index are presented, along with a case study of the correlation between the fire potential index and fire occurrence in California and Nevada. Application of the fire potential index in the Mediterranean ecosystems of Spain, Chile, and Mexico will be tested.

Initial estimates of the temperature and fractional areas of fires at the World Trade Center Disaster from AVIRIS

NASA Technical Reports Server (NTRS)

Green, R. O.; Clark, R. N.; Boardman, J.; Pavri, B.; Sarture, C.

2003-01-01

This paper reports the measurements, algorithms, analyses, and results of the fire temperature and fractional area determinations with AVIRIS calibrated spectra at the World Trade Center site in September 2001.

Managed traffic evacuation using distributed sensor processing

NASA Astrophysics Data System (ADS)

Ramuhalli, Pradeep; Biswas, Subir

2005-05-01

This paper presents an integrated sensor network and distributed event processing architecture for managed in-building traffic evacuation during natural and human-caused disasters, including earthquakes, fire and biological/chemical terrorist attacks. The proposed wireless sensor network protocols and distributed event processing mechanisms offer a new distributed paradigm for improving reliability in building evacuation and disaster management. The networking component of the system is constructed using distributed wireless sensors for measuring environmental parameters such as temperature, humidity, and detecting unusual events such as smoke, structural failures, vibration, biological/chemical or nuclear agents. Distributed event processing algorithms will be executed by these sensor nodes to detect the propagation pattern of the disaster and to measure the concentration and activity of human traffic in different parts of the building. Based on this information, dynamic evacuation decisions are taken for maximizing the evacuation speed and minimizing unwanted incidents such as human exposure to harmful agents and stampedes near exits. A set of audio-visual indicators and actuators are used for aiding the automated evacuation process. In this paper we develop integrated protocols, algorithms and their simulation models for the proposed sensor networking and the distributed event processing framework. Also, efficient harnessing of the individually low, but collectively massive, processing abilities of the sensor nodes is a powerful concept behind our proposed distributed event processing algorithms. Results obtained through simulation in this paper are used for a detailed characterization of the proposed evacuation management system and its associated algorithmic components.

Overview of ISS U.S. Fire Detection and Suppression System

NASA Technical Reports Server (NTRS)

Whitaker, Alana

2003-01-01

This paper presents a general overview of the International Space Station's Fire Detection and Suppression System. The topics include: 1) Introduction to Fire Detection and Suppression (FDS); 2) Description of (FDS) Subsystems; 3) FDS System Component Location and Status; 4) FDS System Capabilities; 5) FDS Automatic and Manual Response; 6) Post Fire Atmosphere Restoration and Air Quality Assessment; and 7) FDS Research Needs. This paper is in viewgraph form.

Sensor data monitoring and decision level fusion scheme for early fire detection

NASA Astrophysics Data System (ADS)

Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2017-05-01

The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.

Objective analysis of toolmarks in forensics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grieve, Taylor N.

2013-01-01

Since the 1993 court case of Daubert v. Merrell Dow Pharmaceuticals, Inc. the subjective nature of toolmark comparison has been questioned by attorneys and law enforcement agencies alike. This has led to an increased drive to establish objective comparison techniques with known error rates, much like those that DNA analysis is able to provide. This push has created research in which the 3-D surface profile of two different marks are characterized and the marks’ cross-sections are run through a comparative statistical algorithm to acquire a value that is intended to indicate the likelihood of a match between the marks. Themore » aforementioned algorithm has been developed and extensively tested through comparison of evenly striated marks made by screwdrivers. However, this algorithm has yet to be applied to quasi-striated marks such as those made by the shear edge of slip-joint pliers. The results of this algorithm’s application to the surface of copper wire will be presented. Objective mark comparison also extends to comparison of toolmarks made by firearms. In an effort to create objective comparisons, microstamping of firing pins and breech faces has been introduced. This process involves placing unique alphanumeric identifiers surrounded by a radial code on the surface of firing pins, which transfer to the cartridge’s primer upon firing. Three different guns equipped with microstamped firing pins were used to fire 3000 cartridges. These cartridges are evaluated based on the clarity of their alphanumeric transfers and the clarity of the radial code surrounding the alphanumerics.« less

"Smoke": Characterization Of Smoke Particulate For Spacecraft Fire Detection

NASA Technical Reports Server (NTRS)

Urban, David L.; Mulholland, George W.; Yang, Jiann; Cleary, Thomas G.; Yuan, Zeng-Guang

2003-01-01

The "Smoke" experiment is a flight definition investigation that seeks to increase our understanding of spacecraft fire detection through measurements of particulate size distributions of preignition smokes from typical spacecraft materials. Owing to the catastrophic risk posed by even a very small fire in a spacecraft, the design goal for spacecraft fire detection is to detect the fire as quickly as possible, preferably in the preignition phase before a real flaming fire has developed. Consequently the target smoke for detection is typically not soot (typical of established hydrocarbon fires) but instead, pyrolysis products, and recondensed polymer particles. At the same time, false alarms are extremely costly as the crew and the ground team must respond quickly to every alarm. The U.S. Space Shuttle (STS: Space Transportation System) and the International Space Station (ISS) both use smoke detection as the primary means of fire detection. These two systems were designed in the absence of any data concerning low-gravity smoke particle (and background dust) size distributions. The STS system uses an ionization detector coupled with a sampling pump and the ISS system is a forward light scattering detector operating in the near IR. These two systems have significantly different sensitivities with the ionization detector being most sensitive (on a mass concentration basis) to smaller particulate and the light scattering detector being most sensitive to particulate that is larger than 1 micron. Since any smoke detection system has inherent size sensitivity characteristics, proper design of future smoke detection systems will require an understanding of the background and alarm particle size distributions that can be expected in a space environment.

Fire protection for launch facilities using machine vision fire detection

NASA Astrophysics Data System (ADS)

Schwartz, Douglas B.

1993-02-01

Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.

Fire protection for launch facilities using machine vision fire detection

NASA Technical Reports Server (NTRS)

Schwartz, Douglas B.

1993-01-01

Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.

Development and Application of Version 2.1 of the Fire INventory from NCAR (FINN)

NASA Astrophysics Data System (ADS)

McDonald-Buller, E.; Wiedinmyer, C.; Kimura, Y.

2016-12-01

The Fire INventory from the National Center for Atmospheric Research (FINN) generates global daily emissions estimates of trace gases and particles from open biomass burning, including wildfires, agricultural fires, and prescribed burning. FINN has been widely used for global and regional air quality studies, offering high spatial and temporal resolution necessary for capturing daily variations in emissions and chemistry, consistency across geopolitical boundaries, and chemical speciation profiles for volatile organic compound (VOC) emissions for the GEOS-Chem, SAPRC99, MOZART-4, and Carbon Bond mechanisms. FINN v.1 was first released in 2010 and updated in 2011. FINN v. 1.5 was released in 2014. The work presented here focuses on a collaborative effort between NCAR and the University of Texas at Austin to develop the next generation of the public release of the model, FINN v.2.1, to benefit air quality management and research initiatives within the U.S. and internationally. Specific objectives have included developing a new algorithm for estimating area burned from satellite-derived fire detections, distinguishing major crop types typically found in the U.S., improving the spatial resolution of fuel loading in the United States, and providing flexibility for applying alternative land cover representations from emerging global, U.S. national, and regional land cover products. A case study applies FINN2.1 for regional emission estimates and air quality predictions in Texas during 2012.

46 CFR 108.407 - Detectors for electric fire detection system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Detectors for electric fire detection system. 108.407 Section 108.407 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.407 Detectors for electric fire...

46 CFR 108.407 - Detectors for electric fire detection system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Detectors for electric fire detection system. 108.407 Section 108.407 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.407 Detectors for electric fire...

46 CFR 108.407 - Detectors for electric fire detection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Detectors for electric fire detection system. 108.407 Section 108.407 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.407 Detectors for electric fire...

46 CFR 108.407 - Detectors for electric fire detection system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Detectors for electric fire detection system. 108.407 Section 108.407 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.407 Detectors for electric fire...

29 CFR 1910.164 - Fire detection systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... fire detectors and fire detection systems are tested and adjusted as often as needed to maintain proper reliability and operating condition except that factory calibrated detectors need not be adjusted after...) The employer shall also assure that fire detectors that need to be cleaned of dirt, dust, or other...

29 CFR 1910.164 - Fire detection systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... fire detectors and fire detection systems are tested and adjusted as often as needed to maintain proper reliability and operating condition except that factory calibrated detectors need not be adjusted after...) The employer shall also assure that fire detectors that need to be cleaned of dirt, dust, or other...

29 CFR 1910.164 - Fire detection systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... fire detectors and fire detection systems are tested and adjusted as often as needed to maintain proper reliability and operating condition except that factory calibrated detectors need not be adjusted after...) The employer shall also assure that fire detectors that need to be cleaned of dirt, dust, or other...

29 CFR 1910.164 - Fire detection systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... fire detectors and fire detection systems are tested and adjusted as often as needed to maintain proper reliability and operating condition except that factory calibrated detectors need not be adjusted after...) The employer shall also assure that fire detectors that need to be cleaned of dirt, dust, or other...

29 CFR 1910.164 - Fire detection systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... fire detectors and fire detection systems are tested and adjusted as often as needed to maintain proper reliability and operating condition except that factory calibrated detectors need not be adjusted after...) The employer shall also assure that fire detectors that need to be cleaned of dirt, dust, or other...

30 CFR 250.1629 - Additional production and fuel gas system requirements.

Code of Federal Regulations, 2014 CFR

2014-07-01

... structure. (4) Fire- and gas-detection system. (i) Fire (flame, heat, or smoke) sensors shall be installed... explosive limit. One approved method of providing adequate ventilation is a change of air volume each 5... detection systems shall be capable of continuous monitoring. Fire-detection systems and portions of...

30 CFR 250.1629 - Additional production and fuel gas system requirements.

Code of Federal Regulations, 2013 CFR

2013-07-01

... structure. (4) Fire- and gas-detection system. (i) Fire (flame, heat, or smoke) sensors shall be installed... explosive limit. One approved method of providing adequate ventilation is a change of air volume each 5... detection systems shall be capable of continuous monitoring. Fire-detection systems and portions of...

46 CFR 28.155 - Excess fire detection and protection equipment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Excess fire detection and protection equipment. 28.155... protection equipment. Installation of fire detection and protection equipment in excess of that required by the regulations in this subchapter is permitted provided that the excess equipment does not endanger...

Determine Neuronal Tuning Curves by Exploring Optimum Firing Rate Distribution for Information Efficiency

PubMed Central

Han, Fang; Wang, Zhijie; Fan, Hong

2017-01-01

This paper proposed a new method to determine the neuronal tuning curves for maximum information efficiency by computing the optimum firing rate distribution. Firstly, we proposed a general definition for the information efficiency, which is relevant to mutual information and neuronal energy consumption. The energy consumption is composed of two parts: neuronal basic energy consumption and neuronal spike emission energy consumption. A parameter to model the relative importance of energy consumption is introduced in the definition of the information efficiency. Then, we designed a combination of exponential functions to describe the optimum firing rate distribution based on the analysis of the dependency of the mutual information and the energy consumption on the shape of the functions of the firing rate distributions. Furthermore, we developed a rapid algorithm to search the parameter values of the optimum firing rate distribution function. Finally, we found with the rapid algorithm that a combination of two different exponential functions with two free parameters can describe the optimum firing rate distribution accurately. We also found that if the energy consumption is relatively unimportant (important) compared to the mutual information or the neuronal basic energy consumption is relatively large (small), the curve of the optimum firing rate distribution will be relatively flat (steep), and the corresponding optimum tuning curve exhibits a form of sigmoid if the stimuli distribution is normal. PMID:28270760

MISR Stereo-heights of Grassland Fire Smoke Plumes in Australia

NASA Astrophysics Data System (ADS)

Mims, S. R.; Kahn, R. A.; Moroney, C. M.; Gaitley, B. J.; Nelson, D. L.; Garay, M. J.

2008-12-01

Plume heights from wildfires are used in climate modeling to predict and understand trends in aerosol transport. This study examines whether smoke from grassland fires in the desert region of Western and central Australia ever rises above the relatively stable atmospheric boundary layer and accumulates in higher layers of relative atmospheric stability. Several methods for deriving plume heights from the Multi-angle Imaging SpectroRadiometer (MISR) instrument are examined for fire events during the summer 2000 and 2002 burning seasons. Using MISR's multi-angle stereo-imagery from its three near-nadir-viewing cameras, an automatic algorithm routinely derives the stereo-heights above the geoid of the level-of-maximum-contrast for the entire global data set, which often correspond to the heights of clouds and aerosol plumes. Most of the fires that occur in the cases studied here are small, diffuse, and difficult to detect. To increase the signal from these thin hazes, the MISR enhanced stereo product that computes stereo heights from the most steeply viewing MISR cameras is used. For some cases, a third approach to retrieving plume heights from MISR stereo imaging observations, the MISR Interactive Explorer (MINX) tool, is employed to help differentiate between smoke and cloud. To provide context and to search for correlative factors, stereo-heights are combined with data providing fire strength from the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument, atmospheric structure from the NCEP/NCAR Reanalysis Project, surface cover from the Australia National Vegetation Information System, and forward and backward trajectories from the NOAA HYSPLIT model. Although most smoke plumes concentrate in the near-surface boundary layer, as expected, some appear to rise higher. These findings suggest that a closer examination of grassland fire energetics may be warranted.

Application of a CO2 dial system for infrared detection of forest fire and reduction of false alarm

NASA Astrophysics Data System (ADS)

Bellecci, C.; Francucci, M.; Gaudio, P.; Gelfusa, M.; Martellucci, S.; Richetta, M.; Lo Feudo, T.

2007-04-01

Forest fires can be the cause of serious environmental and economic damages. For this reason considerable effort has been directed toward forest protection and fire fighting. The means traditionally used for early fire detection mainly consist in human observers dispersed over forest regions. A significant improvement in early warning capabilities could be obtained by using automatic detection apparatus. In order to early detect small forest fires and minimize false alarms, the use of a lidar system and dial technique will be considered. A first evaluation of the lowest detectable concentration will be estimated by numerical simulation. The theoretical model will also be used to get the capability of the dial system to control wooded areas. Fixing the burning rate for several fuels, the maximum range of detection will be evaluated. Finally results of simulations will be reported.

Emergence of Alpha and Gamma Like Rhythms in a Large Scale Simulation of Interacting Neurons

NASA Astrophysics Data System (ADS)

Gaebler, Philipp; Miller, Bruce

2007-10-01

In the normal brain, at first glance the electrical activity appears very random. However, certain frequencies emerge during specific stages of sleep or between quiet wake states. This raises the question of whether current mathematical and computational models of interacting neurons can display similar behavior. A recent model developed by Eugene Izhikevich appears to succeed. However, early dynamical simulations used to detect these patterns were possibly compromised by an over-simplified initial condition and evolution algorithm. Utilizing the same model, but a more robust algorithm, here we present our initial results, showing that these patterns persist under a wide range of initial conditions. We employ spectral analysis of the firing patterns of a system of interacting excitatory and inhibitory neurons to demonstrate a bimodal spectrum centered on two frequencies in the range characteristic of alpha and gamma rhythms in the human brain.

NEW IMPROVEMENTS TO MFIRE TO ENHANCE FIRE MODELING CAPABILITIES.

PubMed

Zhou, L; Smith, A C; Yuan, L

2016-06-01

NIOSH's mine fire simulation program, MFIRE, is widely accepted as a standard for assessing and predicting the impact of a fire on the mine ventilation system and the spread of fire contaminants in coal and metal/nonmetal mines, which has been used by U.S. and international companies to simulate fires for planning and response purposes. MFIRE is a dynamic, transient-state, mine ventilation network simulation program that performs normal planning calculations. It can also be used to analyze ventilation networks under thermal and mechanical influence such as changes in ventilation parameters, external influences such as changes in temperature, and internal influences such as a fire. The program output can be used to analyze the effects of these influences on the ventilation system. Since its original development by Michigan Technological University for the Bureau of Mines in the 1970s, several updates have been released over the years. In 2012, NIOSH completed a major redesign and restructuring of the program with the release of MFIRE 3.0. MFIRE's outdated FORTRAN programming language was replaced with an object-oriented C++ language and packaged into a dynamic link library (DLL). However, the MFIRE 3.0 release made no attempt to change or improve the fire modeling algorithms inherited from its previous version, MFIRE 2.20. This paper reports on improvements that have been made to the fire modeling capabilities of MFIRE 3.0 since its release. These improvements include the addition of fire source models of the t-squared fire and heat release rate curve data file, the addition of a moving fire source for conveyor belt fire simulations, improvement of the fire location algorithm, and the identification and prediction of smoke rollback phenomena. All the improvements discussed in this paper will be termed as MFIRE 3.1 and released by NIOSH in the near future.

TRMM Fire Algorithm, Product and Applications

NASA Technical Reports Server (NTRS)

Ji, Yi-Min; Stocker, Erich

2003-01-01

Land fires are frequent menaces to human lives and property. They also change the state of the vegetation and contribute to the climate forcing by releasing large amount of aerosols and greenhouse gases into the atmosphere. This paper summarizes methodologies of detecting global land fires from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner FIRS) measurements. The TRMM Science Data and Information System (TSDIS) fire products include global images of daily hot spots and monthly fire counts at 0.5 deg. x 0.5 deg. resolution, as well as text fiies that details necessary information of all fire pixels. The information includes date, orbit number, pixel number, local time, solar zenith angle, latitude, longitude, reflectance of visible/near infrared channels, brightness temperatures of infrared channels, as well as background brightness temperatures of infrared channels. These products have been archived since January 1998. The TSDIS fire products are compared with the coincidental European Commission (EC) Joint Research Center (JRC) 1 km AVHRR fire products. Analyses of the TSDIS monthly fire products during the period from 1998 to 2003 manifested seasonal cycles of biomass fires over Southeast Asia, Africa, North America and South America. The data also showed interannual variations associated with the 98/99 ENS0 cycle in Central America and the Indonesian region. In order to understand the variability of global land fires and their effects on the distribution of atmospheric aerosols, statistical methods were applied to the TSDIS fire products as well as to the Total Ozone Mapping Spectrometer (TOMS) aerosol index products for a period of five years from January 1998 to December 2002. The variability of global atmospheric aerosol is consistent with the fire variations over these regions during this period. The correlation between fire count and TOMS aerosol index is about 0.55 for fire pixels in Southeast Asia, Indonesia, and Africa. Parallel statistical analyses such as Empirical Orthogonal Function (EOF) analysis and Singular Spectrum Analysis (SSA) methods were applied to pentad TRMM fire data and TOMS aerosol data. The EOF analyses showed contrast between North and South hemispheres and also inter- continental transitions in Africa and America. EOF and SSA analyses also identified 25-60 day intra-seasonal oscillations that were superimposed on the annual cycles of both fire and aerosol data. The intra-seasonal variability of fires showed similarity of tropical rainfall oscillation modes. The TRMM fire products were also compared to the coincident TRMh4 rainfall and other rainfall products to investigate the interaction between rainfall and fire. The results indicate that the annual, interannual and intraseasonal variability of fire are dominated by global rainfall variations. However, the feedback of fire to the rainfall occurrence at regional scale for certain regions is also evident.

Fire Distribution in Peninsular Malaysia, Sumatra and Borneo in 2015 with Special Emphasis on Peatland Fires.

PubMed

Miettinen, Jukka; Shi, Chenghua; Liew, Soo Chin

2017-10-01

In this paper, we analyze the spatio-temporal distribution of vegetation fires in Peninsular Malaysia, Sumatra, and Borneo in the severe El Niño year of 2015, concentrating on the distribution of fires between mineral soils and peatland areas, and between land cover types in peatland areas. The results reveal that 53% of all Moderate Resolution Imaging Spectroradiometer (MODIS) fire detections were recorded in peatlands that cover only 12% of the study area. However, fire occurrence in the peatland areas was highly dependent on land cover type. Pristine peat swamp forests (PSF) experienced only marginal fire activity (30 fire detections per 1000 km 2 ) compared to deforested undeveloped peatlands (831-915 fire detections per 1000 km 2 ). Our results also highlight the extreme fire vulnerability of the southern Sumatran and Bornean peatlands under strong El Niño conditions: 71% of all peatland hotspots were detected in the provinces of South Sumatra and Central Kalimantan, which contain 29% of peatlands in the study area. Degraded PSF and all deforested peatland land cover types, including managed areas, in the two provinces were severely affected, demonstrating how difficult it is to protect even managed drained agricultural areas from unwanted fires during dry periods. Our results thereby advocate rewetting and rehabilitation as the primary management option for highly fire prone degraded undeveloped peatland areas, whenever feasible, as a means to reduce fire risk during future dry episodes.

Fire Distribution in Peninsular Malaysia, Sumatra and Borneo in 2015 with Special Emphasis on Peatland Fires

NASA Astrophysics Data System (ADS)

Miettinen, Jukka; Shi, Chenghua; Liew, Soo Chin

2017-10-01

In this paper, we analyze the spatio-temporal distribution of vegetation fires in Peninsular Malaysia, Sumatra, and Borneo in the severe El Niño year of 2015, concentrating on the distribution of fires between mineral soils and peatland areas, and between land cover types in peatland areas. The results reveal that 53% of all Moderate Resolution Imaging Spectroradiometer (MODIS) fire detections were recorded in peatlands that cover only 12% of the study area. However, fire occurrence in the peatland areas was highly dependent on land cover type. Pristine peat swamp forests (PSF) experienced only marginal fire activity (30 fire detections per 1000 km2) compared to deforested undeveloped peatlands (831-915 fire detections per 1000 km2). Our results also highlight the extreme fire vulnerability of the southern Sumatran and Bornean peatlands under strong El Niño conditions: 71% of all peatland hotspots were detected in the provinces of South Sumatra and Central Kalimantan, which contain 29% of peatlands in the study area. Degraded PSF and all deforested peatland land cover types, including managed areas, in the two provinces were severely affected, demonstrating how difficult it is to protect even managed drained agricultural areas from unwanted fires during dry periods. Our results thereby advocate rewetting and rehabilitation as the primary management option for highly fire prone degraded undeveloped peatland areas, whenever feasible, as a means to reduce fire risk during future dry episodes.

Increased Fire and Toxic Contaminant Detection Responsibility by Use of Distributed, Aspirating Sensors

NASA Technical Reports Server (NTRS)

Youngblood, Wallace W.

1990-01-01

Viewgraphs of increased fire and toxic contaminant detection responsivity by use of distributed, aspirating sensors for space station are presented. Objectives of the concept described are (1) to enhance fire and toxic contaminant detection responsivity in habitable regions of space station; (2) to reduce system weight and complexity through centralized detector/monitor systems; (3) to increase fire signature information from selected locations in a space station module; and (4) to reduce false alarms.

46 CFR 28.825 - Excess fire detection and protection equipment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 1 2010-10-01 2010-10-01 false Excess fire detection and protection equipment. 28.825... equipment. Instead of meeting the requirements of § 28.155, each vessel to which this subpart applies must meet the following requirements: (a) Installation of fire detection and protection equipment in excess...

Forest Fire Mapping

NASA Technical Reports Server (NTRS)

1990-01-01

The Fire Logistics Airborne Mapping Equipment (FLAME) system, mounted in a twin-engine and airplane operated by the U.S. Forest Service (USFS) of the U.S. Department of Agriculture (USDA), is an airborne instrument for detecting and pinpointing forest fires that might escape ground detection. The FLAME equipment rack includes the operator interface, a video monitor, the system's control panel and film output. FLAME's fire detection sensor is an infrared line scanner system that identifies fire boundaries. Sensor's information is correlated with the aircraft's position and altitude at the time the infrared imagery is acquired to fix the fire's location on a map. System can be sent to a fire locale anywhere in the U.S. at the request of a regional forester. USFS felt a need for a more advanced system to deliver timely fire information to fire management personnel in the decade of the 1990s. The Jet Propulsion Laboratory (JPL) conducted a study, jointly sponsored by NASA and USDA, on what advanced technologies might be employed to produce an end-to-end thermal infrared fire detection and mapping system. That led to initiation of the Firefly system, currently in development at JPL and targeted for operational service beginning in 1992. Firefly will employ satellite-reference position fixing and provide performance superior to FLAME.

Modelling a historic oil-tank fire allows an estimation of the sensitivity of the infrared receptors in pyrophilous Melanophila beetles.

PubMed

Schmitz, Helmut; Bousack, Herbert

2012-01-01

Pyrophilous jewel beetles of the genus Melanophila approach forest fires and there is considerable evidence that these beetles can detect fires from great distances of more than 60 km. Because Melanophila beetles are equipped with infrared receptors and are also attracted by hot surfaces it can be concluded that these infrared receptors are used for fire detection.The sensitivity of the IR receptors is still unknown. The lowest threshold published so far is 0.6 W/m(2) which, however, cannot explain the detection of forest fires by IR radiation from distances larger than approximately 10 km. To investigate the possible sensitivity of the IR receptors we assumed that beetles use IR radiation for remote fire detection and we made use of a historic report about a big oil-tank fire in Coalinga, California, in 1924. IR emission of an oil-tank fire can be calculated by "pool fire" simulations which now are used for fire safety and risk analysis. Assuming that beetles were lured to the fire from the nearest forests 25 and 130 km away, our results show that detection from a distance of 25 km requires a threshold of the IR receptors of at least 3×10(-2) W/m(2). According to our investigations most beetles became aware of the fire from a distance of 130 km. In this case the threshold has to be 1.3×10(-4) W/m(2). Because such low IR intensities are buried in thermal noise we suggest that the infrared sensory system of Melanophila beetles utilizes stochastic resonance for the detection of weak IR radiation. Our simulations also suggest that the biological IR receptors might be even more sensitive than uncooled technical IR sensors. Thus a closer look into the mode of operation of the Melanophila IR receptors seems promising for the development of novel IR sensors.

Numerical simulation study on the distribution law of smoke flow velocity in horizontal tunnel fire

NASA Astrophysics Data System (ADS)

Liu, Yejiao; Tian, Zhichao; Xue, Junhua; Wang, Wencai

2018-02-01

According to the fluid similarity theory, the simulation experiment system of mining tunnel fire is established. The grid division of experimental model roadway is carried on by GAMBIT software. By setting the boundary and initial conditions of smoke flow during fire period in FLUENT software, using RNG k-Ɛ two-equation turbulence model, energy equation and SIMPLE algorithm, the steady state numerical simulation of smoke flow velocity in mining tunnel is done to obtain the distribution law of smoke flow velocity in tunnel during fire period.

Fire monitoring capability of the joint Landsat and Sentinel 2 constellation

NASA Astrophysics Data System (ADS)

Murphy, S.; Wright, R.

2017-12-01

Fires are a global hazard. Landsat and Sentinel 2 can monitor the Earth's surface every 2 - 4 days. This provides an important opportunity to complement the operational (lower resolution) fire monitoring systems. Landsat-class sensors can detect small fires that would be missed by MODIS-classed sensors. All large fires start out as small fires. We analyze fire patterns in California from 1984 to 2017 and compare the performance of Landsat-type and MODIS-type sensors. Had an operational Landsat-Sentinel 2 fire detection system been in place at the time of the Soberanes fire last year (i.e. August 2016), the cost of suppressing of this fire event (US $236 million) could potentially have been reduced by an order of magnitude.

Spacecraft Fire Safety

NASA Technical Reports Server (NTRS)

Margle, Janice M. (Editor)

1987-01-01

Fire detection, fire standards and testing, fire extinguishment, inerting and atmospheres, fire-related medical science, aircraft fire safety, Space Station safety concerns, microgravity combustion, spacecraft material flammability testing, and metal combustion are among the topics considered.

Monitoring Of Air Quality Parameters For Construction Of Fire Risk Detection Systems

NASA Astrophysics Data System (ADS)

Romancov, I. I.; Dashkovky, A. G.; Panin, V. F.; Melkov, D. N.

2017-01-01

The analysis of fire developmental process is given, which showed that there are seven stages of fire development, a set of phenomena (factors, signs) of fire risk condition, characterized by a set of defined parameters, corresponds to each stage. Observed that the registration of high staging factors (high ambient temperature, content of CO2, etc.) means the registration of actual low staging fire (thermal destruction of materials gases, fumes, etc.) - fire risk situation. It is shown that the decrease of registered factor staging leads to construction of fire preventive and diagnostic systems as the lower is registered stage, the more uncertain is connection between the fact of its detection and a fire. It is indicated that with development of electronic equipment the staging of fire situations factors used for detection is reducing in whole, and also it is noted that for each control object it is necessary to choose (identify) the optimal factor, in particular, in many ways the optimal factor for aircrafts are smokes and their TV image.

How many neurons can we see with current spike sorting algorithms?

PubMed Central

Pedreira, Carlos; Martinez, Juan; Ison, Matias J.; Quian Quiroga, Rodrigo

2012-01-01

Recent studies highlighted the disagreement between the typical number of neurons observed with extracellular recordings and the ones to be expected based on anatomical and physiological considerations. This disagreement has been mainly attributed to the presence of sparsely firing neurons. However, it is also possible that this is due to limitations of the spike sorting algorithms used to process the data. To address this issue, we used realistic simulations of extracellular recordings and found a relatively poor spike sorting performance for simulations containing a large number of neurons. In fact, the number of correctly identified neurons for single-channel recordings showed an asymptotic behavior saturating at about 8–10 units, when up to 20 units were present in the data. This performance was significantly poorer for neurons with low firing rates, as these units were twice more likely to be missed than the ones with high firing rates in simulations containing many neurons. These results uncover one of the main reasons for the relatively low number of neurons found in extracellular recording and also stress the importance of further developments of spike sorting algorithms. PMID:22841630

Fail-safe fire detection system

NASA Technical Reports Server (NTRS)

Bloam, E. T.

1974-01-01

Fire detection control system continually monitors its own integrity, automatically signals any malfunction, and separately signals fire in any zone being monitored. Should be of interest in fields of chemical and petroleum processing, power generation, equipment testing, and building protection.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, Kostas; Ager, Alan; Finney, Mark; Athanasis, Nikos; Palaiologou, Palaiologos; Vasilakos, Christos

2016-03-01

We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

Using the NASA NEESPI Portal Data to Study Land, Climate, and Socio-Economic Changes in Northern Eurasia

NASA Technical Reports Server (NTRS)

Leptoukh, Gregory; Shen, Suhung; Csiszar, Ivan; Romanov, Peter; Loboda, Tatiana; Gerasimov, Irina

2008-01-01

A large number of fires detected in July of 2003 - a nearly 200-time increase in fire detections compared to other years during 2001-2006. despite the summer monsoon suppression of large fire occurrence. Traditional vegetation indices (NDVI and EVI) included in operational fire danger assessment provide little information on the fuel state in this ecosystem pre- or post-fire. No considerable differences in surface temperature and soil moisture in July were observed between the catastrophic year of 2003 and the two subsequent years of low summer fire occurrence of 2004 and 2005. However, the temporal analysis indicates that dry spring conditions in 2003 (detected through low soil moisture measurements in April and May) may have led to a stressed vegetative state and created conditions conducive to catastrophic fire occurrence.

Glare-reducing goggles for lookouts.

Treesearch

Richard E. McArdle; William G. Morris; Thornton T. Munger

1936-01-01

Detection of forest fires while they are still small is so important in forest protection that studies of the visibility of forest fire smokes from lookout points has been one of the principal phases of the fire studies program of the Pacific Northwest Forest Experiment Station. One phase of fire detection is the personal efficiency of the lookout. The Station has...

Computer evaluation of existing and proposed fire lookouts

Treesearch

Romain M. Mees

1976-01-01

A computer simulation model has been developed for evaluating the fire detection capabilities of existing and proposed lookout stations. The model uses coordinate location of fires and lookouts, tower elevation, and topographic data to judge location of stations, and to determine where a fire can be seen. The model was tested by comparing it with manual detection on a...

A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.1

NASA Astrophysics Data System (ADS)

Rabin, Sam S.; Ward, Daniel S.; Malyshev, Sergey L.; Magi, Brian I.; Shevliakova, Elena; Pacala, Stephen W.

2018-03-01

This study describes and evaluates the Fire Including Natural & Agricultural Lands model (FINAL) which, for the first time, explicitly simulates cropland and pasture management fires separately from non-agricultural fires. The non-agricultural fire module uses empirical relationships to simulate burned area in a quasi-mechanistic framework, similar to past fire modeling efforts, but with a novel optimization method that improves the fidelity of simulated fire patterns to new observational estimates of non-agricultural burning. The agricultural fire components are forced with estimates of cropland and pasture fire seasonality and frequency derived from observational land cover and satellite fire datasets. FINAL accurately simulates the amount, distribution, and seasonal timing of burned cropland and pasture over 2001-2009 (global totals: 0.434×106 and 2.02×106 km2 yr-1 modeled, 0.454×106 and 2.04×106 km2 yr-1 observed), but carbon emissions for cropland and pasture fire are overestimated (global totals: 0.295 and 0.706 PgC yr-1 modeled, 0.194 and 0.538 PgC yr-1 observed). The non-agricultural fire module underestimates global burned area (1.91×106 km2 yr-1 modeled, 2.44×106 km2 yr-1 observed) and carbon emissions (1.14 PgC yr-1 modeled, 1.84 PgC yr-1 observed). The spatial pattern of total burned area and carbon emissions is generally well reproduced across much of sub-Saharan Africa, Brazil, Central Asia, and Australia, whereas the boreal zone sees underestimates. FINAL represents an important step in the development of global fire models, and offers a strategy for fire models to consider human-driven fire regimes on cultivated lands. At the regional scale, simulations would benefit from refinements in the parameterizations and improved optimization datasets. We include an in-depth discussion of the lessons learned from using the Levenberg-Marquardt algorithm in an interactive optimization for a dynamic global vegetation model.

Use of an Infrared Thermometer with Laser Targeting in Morphological Scene Change Detection for Fire Detection

NASA Astrophysics Data System (ADS)

Tickle, Andrew J.; Singh, Harjap; Grindley, Josef E.

2013-06-01

Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial threshold setting. This is a robust technique and can be applied many areas from leak detection to movement tracking, and further augmented to perform additional functions such as watermarking and facial detection. Fire is a severe problem, and in areas where traditional fire alarm systems are not installed or feasible, it may not be detected until it is too late. Shown here is a way of adapting the traditional Morphological Scene Change Detector (MSCD) with a temperature sensor so if both the temperature sensor and scene change detector are triggered, there is a high likelihood of fire present. Such a system would allow integration into autonomous mobile robots so that not only security patrols could be undertaken, but also fire detection.

An approach to the real time risk evaluation system of boreal forest fire

NASA Astrophysics Data System (ADS)

Nakau, K.; Fukuda, M.; Kimura, K.; Hayasaka, H.; Tani, H.; Kushida, K.

2005-12-01

Huge boreal forest fire may cause massive impacts not only on global warming gas emission but also local communities. Thus, it is important to control forest fire. We collected data about boreal forest fire as satellite imagery and fire observation simultaneously in Alaska and east Siberia in summer fire seasons for these three years. Fire observation data was collected from aircraft flying between Japan and Europe. Fire detection results were compared with observed data to evaluate the accuracy and earliness of automatic detection. NOAA and MODIS satellite images covering Alaska and East Siberia are collected. We are also developing fire expansion simulation model to forecast the possible fire expansion area. On the basis of fire expansion forecast, risk analysis of possible fire expansion for decision aid of fire-fighting activities will be analyzed. To identify the risk of boreal forest fire and public concern about forest fire, we collected local news paper in Fairbanks, AK and discuss the statistics of articles related to forest fire on the newspaper.

[Digital signal processing of a novel neuron discharge model stimulation strategy for cochlear implants].

PubMed

Yang, Yiwei; Xu, Yuejin; Miu, Jichang; Zhou, Linghong; Xiao, Zhongju

2012-10-01

To apply the classic leakage integrate-and-fire models, based on the mechanism of the generation of physiological auditory stimulation, in the information processing coding of cochlear implants to improve the auditory result. The results of algorithm simulation in digital signal processor (DSP) were imported into Matlab for a comparative analysis. Compared with CIS coding, the algorithm of membrane potential integrate-and-fire (MPIF) allowed more natural pulse discharge in a pseudo-random manner to better fit the physiological structures. The MPIF algorithm can effectively solve the problem of the dynamic structure of the delivered auditory information sequence issued in the auditory center and allowed integration of the stimulating pulses and time coding to ensure the coherence and relevance of the stimulating pulse time.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, K.; Ager, A.; Finney, M.; Athanasis, N.; Palaiologou, P.; Vasilakos, C.

2015-10-01

A Web-GIS wildfire prevention and management platform (AEGIS) was developed as an integrated and easy-to-use decision support tool (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing access to information that is essential for wildfire management. Databases were created with spatial and non-spatial data to support key system functionalities. Updated land use/land cover maps were produced by combining field inventory data with high resolution multispectral satellite images (RapidEye) to be used as inputs in fire propagation modeling with the Minimum Travel Time algorithm. End users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations; i.e. single-fire propagations, conditional burn probabilities and at the landscape-level, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANN) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps produced an integrated output map for fire danger prediction. The system also incorporates weather measurements from remote automatic weather stations and weather forecast maps. The structure of the algorithms relies on parallel processing techniques (i.e. High Performance Computing and Cloud Computing) that ensure computational power and speed. All AEGIS functionalities are accessible to authorized end users through a web-based graphical user interface. An innovative mobile application, AEGIS App, acts as a complementary tool to the web-based version of the system.

Modelling a Historic Oil-Tank Fire Allows an Estimation of the Sensitivity of the Infrared Receptors in Pyrophilous Melanophila Beetles

PubMed Central

Schmitz, Helmut; Bousack, Herbert

2012-01-01

Pyrophilous jewel beetles of the genus Melanophila approach forest fires and there is considerable evidence that these beetles can detect fires from great distances of more than 60 km. Because Melanophila beetles are equipped with infrared receptors and are also attracted by hot surfaces it can be concluded that these infrared receptors are used for fire detection. The sensitivity of the IR receptors is still unknown. The lowest threshold published so far is 0.6 W/m2 which, however, cannot explain the detection of forest fires by IR radiation from distances larger than approximately 10 km. To investigate the possible sensitivity of the IR receptors we assumed that beetles use IR radiation for remote fire detection and we made use of a historic report about a big oil-tank fire in Coalinga, California, in 1924. IR emission of an oil-tank fire can be calculated by “pool fire” simulations which now are used for fire safety and risk analysis. Assuming that beetles were lured to the fire from the nearest forests 25 and 130 km away, our results show that detection from a distance of 25 km requires a threshold of the IR receptors of at least 3×10−2 W/m2. According to our investigations most beetles became aware of the fire from a distance of 130 km. In this case the threshold has to be 1.3×10−4 W/m2. Because such low IR intensities are buried in thermal noise we suggest that the infrared sensory system of Melanophila beetles utilizes stochastic resonance for the detection of weak IR radiation. Our simulations also suggest that the biological IR receptors might be even more sensitive than uncooled technical IR sensors. Thus a closer look into the mode of operation of the Melanophila IR receptors seems promising for the development of novel IR sensors. PMID:22629433

Progress in Fire Detection and Suppression Technology for Future Space Missions

NASA Technical Reports Server (NTRS)

Friedman, Robert; Urban, David L.

2000-01-01

Fire intervention technology (detection and suppression) is a critical part of the strategy of spacecraft fire safety. This paper reviews the status, trends, and issues in fire intervention, particularly the technology applied to the protection of the International Space Station and future missions beyond Earth orbit. An important contribution to improvements in spacecraft fire safety is the understanding of the behavior of fires in the non-convective (microgravity) environment of Earth-orbiting and planetary-transit spacecraft. A key finding is the strong influence of ventilation flow on flame characteristics, flammability limits and flame suppression in microgravity. Knowledge of these flow effects will aid the development of effective processes for fire response and technology for fire suppression.

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2012 CFR

2012-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2014 CFR

2014-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

36 CFR Appendix B to Part 1234 - Alternative Certified Fire-Safety Detection and Suppression System(s)

Code of Federal Regulations, 2013 CFR

2013-07-01

... the system at the base of the main sprinkler riser. l. Fire hydrants must be located within 250 feet... Suppression System(s) 1. General. This Appendix B contains information on the Fire-safety Detection and Suppression System(s) tested by NARA through independent live fire testing that are certified to meet the...

Sprinklers/Standpipes/Detection Systems. Fire Service Certification Series. Unit FSCS-FF-11-80.

ERIC Educational Resources Information Center

Pribyl, Paul F.

This training unit on sprinklers, standpipes, and detection systems is part of a 17-unit course package written to aid instructors in the development, teaching, and evaluation of fire fighters in the Wisconsin Fire Service Certification Series. The purpose stated for the 6-hour unit is to provide the fire fighter with an understanding of the…

Infrared-enhanced TV for fire detection

NASA Technical Reports Server (NTRS)

Hall, J. R.

1978-01-01

Closed-circuit television is superior to conventional smoke or heat sensors for detecting fires in large open spaces. Single TV camera scans entire area, whereas many conventional sensors and maze of interconnecting wiring might be required to get same coverage. Camera is monitored by person who would trip alarm if fire were detected, or electronic circuitry could process camera signal for fully-automatic alarm system.

Improvement of retrieval algorithms for severe air pollution

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

2016-10-01

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. Furthermore, dust storms or biomass burning plumes can cause serious environmental hazards, yet their aerosol properties are poorly understood. Our research group has worked on the development of an efficient algorithm for aerosol retrieval during hazy episodes (dense concentrations of atmospheric aerosols). It is noted that near UV measurements are available for detection of carbonaceous aerosols. The biomass burning aerosols (BBA) due to large-scale forest fires and/or burn agriculture exacerbated the severe air pollution. It is known that global warming and climate change have caused increasing instances of forest fires, which have in turn accelerated climate change. It is well known that this negative cycle decreases the quality of the global environment and human health. The Japan Aerospace Exploration Agency (JAXA) has been developing a new Earth observing system, the GCOM (Global Change Observation Mission) project, which consists of two satellite series: GCOM-W1 and GCOM-C1. The first GCOM-C satellite will board the SGLI (second generation GLI [global imager]) to be launched in early 2017. The SGLI is capable of multi-channel (19) observation, including a near UV channel (0.380 μm) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87 μm. Thus, global aerosol retrieval will be achieved with simultaneous polarization and total radiance. In this study, algorithm improvement for aerosol remote sensing, especially of BBA episodes, is examined using Terra/MODIS measurements from 2003, when the GLI and POLDER-2 sensors were working onboard the Japanese satellite ADEOS-2.

Poverty and corruption compromise tropical forest reserves.

PubMed

Wright, S Joseph; Sanchez-Azofeifa, G Arturo; Portillo-Quintero, Carlos; Davies, Diane

2007-07-01

We used the global fire detection record provided by the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to determine the number of fires detected inside 823 tropical and subtropical moist forest reserves and for contiguous buffer areas 5, 10, and 15 km wide. The ratio of fire detection densities (detections per square kilometer) inside reserves to their contiguous buffer areas provided an index of reserve effectiveness. Fire detection density was significantly lower inside reserves than in paired, contiguous buffer areas but varied by five orders of magnitude among reserves. The buffer: reserve detection ratio varied by up to four orders of magnitude among reserves within a single country, and median values varied by three orders of magnitude among countries. Reserves tended to be least effective at reducing fire frequency in many poorer countries and in countries beset by corruption. Countries with the most successful reserves include Costa Rica, Jamaica, Malaysia, and Taiwan and the Indonesian island of Java. Countries with the most problematic reserves include Cambodia, Guatemala, Paraguay, and Sierra Leone and the Indonesian portion of Borneo. We provide fire detection density for 3964 tropical and subtropical reserves and their buffer areas in the hope that these data will expedite further analyses that might lead to improved management of tropical reserves.

Final Report: Fire Prevention, Detection, and Suppression Project, Exploration Technology Development Program

NASA Technical Reports Server (NTRS)

Ruff, Gary A.

2011-01-01

The Fire Prevention, Detection, and Suppression (FPDS) project is a technology development effort within the Exploration Technology Development Program of the Exploration System Missions Directorate (ESMD) that addresses all aspects of fire safety aboard manned exploration systems. The overarching goal for work in the FPDS area is to develop technologies that will ensure crew health and safety on exploration missions by reducing the likelihood of a fire, or, if one does occur, minimizing the risk to the crew, mission, or system. This is accomplished by addressing the areas of (1) fire prevention and material flammability, (2) fire signatures and detection, and (3) fire suppression and response. This report describes the outcomes of this project from the formation of the Exploration Technology Development Program (ETDP) in October 2005 to September 31, 2010 when the Exploration Technology Development Program was replaced by the Enabling Technology Development and Demonstration Program. NASA s fire safety work will continue under this new program and will build upon the accomplishments described herein.

HOW TO PROVIDE AUTOMATIC FIRE PROTECTION FOR YOUR BUILDING.

ERIC Educational Resources Information Center

Honeywell, Inc., Minneapolis, Minn.

THE ADVANTAGES OF PROMPT FIRE DETECTION IS DISCUSSED WITH RESPECT TO THE NATURE AND COST OF FIRES. EQUIPMENT IS DESCRIBED, AND DIAGRAMS OF INSTALLATIONS OF DETECTION AND ALARM SYSTEMS ARE GIVEN FOR SCHOOLS, HOSPITALS, COMMERICAL BUILDINGS, INDUSTRIAL PLANTS, AND CAMPUSES. (JT)

Automatic firearm class identification from cartridge cases

NASA Astrophysics Data System (ADS)

Kamalakannan, Sridharan; Mann, Christopher J.; Bingham, Philip R.; Karnowski, Thomas P.; Gleason, Shaun S.

2011-03-01

We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area (PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI. Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of the proposed approach.

Downward shortwave surface irradiance from 17 sites for the FIRE/SRB Wisconsin experiment

NASA Technical Reports Server (NTRS)

Whitlock, Charles H.; Hay, John E.; Robinson, David A.; Cox, Stephen K.; Wardle, David I.; Lecroy, Stuart R.

1990-01-01

A field experiment was conducted in Wisconsin during Oct. to Nov. 1986 for purposes of both intensive cirrus cloud measurments and SRB algorithm validation activities. The cirrus cloud measurements were part of the FIRE. Tables are presented which show data from 17 sites in the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment/Surface Radiation Budget (FIRE/SRB) Wisconsin experiment region. A discussion of intercomparison results and calibration inconsistencies is also included.

The Fire Locating and Modeling of Burning Emissions (FLAMBE) Project

NASA Astrophysics Data System (ADS)

Reid, J. S.; Prins, E. M.; Westphal, D.; Richardson, K.; Christopher, S.; Schmidt, C.; Theisen, M.; Eck, T.; Reid, E. A.

2001-12-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE) project was initiated by NASA, the US Navy and NOAA to monitor biomass burning and burning emissions on a global scale. The idea behind the mission is to integrate remote sensing data with global and regional transport models in real time for the purpose of providing the scientific community with smoke and fire products for planning and research purposes. FLAMBE is currently utilizing real time satellite data from GOES satellites, fire products based on the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) are generated for the Western Hemisphere every 30 minutes with only a 90 minute processing delay. We are currently collaborating with other investigators to gain global coverage. Once generated, the fire products are used to input smoke fluxes into the NRL Aerosol Analysis and Prediction System, where advection forecasts are performed for up to 6 days. Subsequent radiative transfer calculations are used to estimate top of atmosphere and surface radiative forcing as well as surface layer visibility. Near real time validation is performed using field data collected by Aerosol Robotic Network (AERONET) Sun photometers. In this paper we fully describe the FLAMBE project and data availability. Preliminary result from the previous year will also be presented, with an emphasis on the development of algorithms to determine smoke emission fluxes from individual fire products. Comparisons to AERONET Sun photometer data will be made.

Controls on variations in MODIS fire radiative power in Alaskan boreal forests: implications for fire severity conditions

USGS Publications Warehouse

Barrett, Kirsten; Kasischke, Eric S.

2013-01-01

Fire activity in the Alaskan boreal forest, though episodic at annual and intra-annual time scales, has experienced an increase over the last several decades. Increases in burned area and fire severity are not only releasing more carbon to the atmosphere, but likely shifting vegetation composition in the region towards greater deciduous dominance and a reduction in coniferous stands. While some recent studies have addressed qualitative differences between large and small fire years in the Alaskan boreal forest, the ecological effects of a greater proportion of burning occurring during large fire years and during late season fires have not yet been examined. Some characteristics of wildfires that can be detected remotely are related to fire severity and can provide new information on spatial and temporal patterns of burning. This analysis focused on boreal wildfire intensity (fire radiative power, or FRP) contained in the Moderate Resolution Imaging Spectroradiometer (MODIS) daily active fire product from 2003 to 2010. We found that differences in FRP resulted from seasonality and intra-annual variability in fire activity levels, vegetation composition, latitudinal variation, and fire spread behavior. Our studies determined two general categories of active fire detections: new detections associated with the spread of the fire front and residual pixels in areas that had already experienced front burning. Residual pixels had a lower average FRP than front pixels, but represented a high percentage of all pixels during periods of high fire activity (large fire years, late season burning, and seasonal periods of high fire activity). As a result, the FRP from periods of high fire activity was less intense than those from periods of low fire activity. Differences related to latitude were greater than expected, with higher latitudes burning later in the season and at a higher intensity than lower latitudes. Differences in vegetation type indicate that coniferous vegetation is the most fire prone, but deciduous vegetation is not particularly fire resistant, as the proportion of active fire detections in deciduous stands is roughly the same as the fraction of deciduous vegetation in the region. Qualitative differences between periods of high and low fire activity are likely to reflect important differences in fire severity. Large fire years are likely to be more severe, characterized by more late season fires and a greater proportion of residual burning. Given the potential for severe fires to effect changes in vegetation cover, the shift toward a greater proportion of area burning during large fire years may influence vegetation patterns in the region over the medium to long term.

Economic vulnerability of timber resources to forest fires.

PubMed

y Silva, Francisco Rodríguez; Molina, Juan Ramón; González-Cabán, Armando; Machuca, Miguel Ángel Herrera

2012-06-15

The temporal-spatial planning of activities for a territorial fire management program requires knowing the value of forest ecosystems. In this paper we extend to and apply the economic valuation principle to the concept of economic vulnerability and present a methodology for the economic valuation of the forest production ecosystems. The forest vulnerability is analyzed from criteria intrinsically associated to the forest characterization, and to the potential behavior of surface fires. Integrating a mapping process of fire potential and analytical valuation algorithms facilitates the implementation of fire prevention planning. The availability of cartography of economic vulnerability of the forest ecosystems is fundamental for budget optimization, and to help in the decision making process. Published by Elsevier Ltd.

Classification Model for Forest Fire Hotspot Occurrences Prediction Using ANFIS Algorithm

NASA Astrophysics Data System (ADS)

Wijayanto, A. K.; Sani, O.; Kartika, N. D.; Herdiyeni, Y.

2017-01-01

This study proposed the application of data mining technique namely Adaptive Neuro-Fuzzy inference system (ANFIS) on forest fires hotspot data to develop classification models for hotspots occurrence in Central Kalimantan. Hotspot is a point that is indicated as the location of fires. In this study, hotspot distribution is categorized as true alarm and false alarm. ANFIS is a soft computing method in which a given inputoutput data set is expressed in a fuzzy inference system (FIS). The FIS implements a nonlinear mapping from its input space to the output space. The method of this study classified hotspots as target objects by correlating spatial attributes data using three folds in ANFIS algorithm to obtain the best model. The best result obtained from the 3rd fold provided low error for training (error = 0.0093676) and also low error testing result (error = 0.0093676). Attribute of distance to road is the most determining factor that influences the probability of true and false alarm where the level of human activities in this attribute is higher. This classification model can be used to develop early warning system of forest fire.

Application of constraint-based satellite mission planning model in forest fire monitoring

NASA Astrophysics Data System (ADS)

Guo, Bingjun; Wang, Hongfei; Wu, Peng

2017-10-01

In this paper, a constraint-based satellite mission planning model is established based on the thought of constraint satisfaction. It includes target, request, observation, satellite, payload and other elements, with constraints linked up. The optimization goal of the model is to make full use of time and resources, and improve the efficiency of target observation. Greedy algorithm is used in the model solving to make observation plan and data transmission plan. Two simulation experiments are designed and carried out, which are routine monitoring of global forest fire and emergency monitoring of forest fires in Australia. The simulation results proved that the model and algorithm perform well. And the model is of good emergency response capability. Efficient and reasonable plan can be worked out to meet users' needs under complex cases of multiple payloads, multiple targets and variable priorities with this model.

Evolving land cover classification algorithms for multispectral and multitemporal imagery

NASA Astrophysics Data System (ADS)

Brumby, Steven P.; Theiler, James P.; Bloch, Jeffrey J.; Harvey, Neal R.; Perkins, Simon J.; Szymanski, John J.; Young, Aaron C.

2002-01-01

The Cerro Grande/Los Alamos forest fire devastated over 43,000 acres (17,500 ha) of forested land, and destroyed over 200 structures in the town of Los Alamos and the adjoining Los Alamos National Laboratory. The need to measure the continuing impact of the fire on the local environment has led to the application of a number of remote sensing technologies. During and after the fire, remote-sensing data was acquired from a variety of aircraft- and satellite-based sensors, including Landsat 7 Enhanced Thematic Mapper (ETM+). We now report on the application of a machine learning technique to the automated classification of land cover using multi-spectral and multi-temporal imagery. We apply a hybrid genetic programming/supervised classification technique to evolve automatic feature extraction algorithms. We use a software package we have developed at Los Alamos National Laboratory, called GENIE, to carry out this evolution. We use multispectral imagery from the Landsat 7 ETM+ instrument from before, during, and after the wildfire. Using an existing land cover classification based on a 1992 Landsat 5 TM scene for our training data, we evolve algorithms that distinguish a range of land cover categories, and an algorithm to mask out clouds and cloud shadows. We report preliminary results of combining individual classification results using a K-means clustering approach. The details of our evolved classification are compared to the manually produced land-cover classification.

Remote sensing techniques in monitoring areas affected by forest fire

NASA Astrophysics Data System (ADS)

Karagianni, Aikaterini Ch.; Lazaridou, Maria A.

2017-09-01

Forest fire is a part of nature playing a key role in shaping ecosystems. However, fire's environmental impacts can be significant, affecting wildlife habitat and timber, human settlements, man-made technical constructions and various networks (road, power networks) and polluting the air with emissions harmful to human health. Furthermore, fire's effect on the landscape may be long-lasting. Monitoring the development of a fire occurs as an important aspect at the management of natural hazards in general. Among the used methods for monitoring, satellite data and remote sensing techniques can be proven of particular importance. Satellite remote sensing offers a useful tool for forest fire detection, monitoring, management and damage assessment. Especially for fire scars detection and monitoring, satellite data derived from Landsat 8 can be a useful research tool. This paper includes critical considerations of the above and concerns in particular an example of the Greek area (Thasos Island). This specific area was hit by fires several times in the past and recently as well (September 2016). Landsat 8 satellite data are being used (pre and post fire imagery) and digital image processing techniques are applied (enhancement techniques, calculation of various indices) for fire scars detection. Visual interpretation of the example area affected by the fires is also being done, contributing to the overall study.

Radiation and Electromagnetic Induction Data Fusion for Detection of Buried Radioactive Metal Waste - 12282

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Zhiling; Wei, Wei; Turlapaty, Anish

2012-07-01

At the United States Army's test sites, fired penetrators made of Depleted Uranium (DU) have been buried under ground and become hazardous waste. Previously, we developed techniques for detecting buried radioactive targets. We also developed approaches for locating buried paramagnetic metal objects by utilizing the electromagnetic induction (EMI) sensor data. In this paper, we apply data fusion techniques to combine results from both the radiation detection and the EMI detection, so that we can further distinguish among DU penetrators, DU oxide, and non- DU metal debris. We develop a two-step fusion approach for the task, and test it with surveymore » data collected on simulation targets. In this work, we explored radiation and EMI data fusion for detecting DU, oxides, and non-DU metals. We developed a two-step fusion approach based on majority voting and a set of decision rules. With this approach, we fuse results from radiation detection based on the RX algorithm and EMI detection based on a 3-step analysis. Our fusion approach has been tested successfully with data collected on simulation targets. In the future, we will need to further verify the effectiveness of this fusion approach with field data. (authors)« less

Automated method for measuring the extent of selective logging damage with airborne LiDAR data

NASA Astrophysics Data System (ADS)

Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

2018-05-01

Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

Limitations imposed on fire PRA methods as the result of incomplete and uncertain fire event data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nowlen, Steven Patrick; Hyslop, J. S.

2010-04-01

Fire probabilistic risk assessment (PRA) methods utilize data and insights gained from actual fire events in a variety of ways. For example, fire occurrence frequencies, manual fire fighting effectiveness and timing, and the distribution of fire events by fire source and plant location are all based directly on the historical experience base. Other factors are either derived indirectly or supported qualitatively based on insights from the event data. These factors include the general nature and intensity of plant fires, insights into operator performance, and insights into fire growth and damage behaviors. This paper will discuss the potential methodology improvements thatmore » could be realized if more complete fire event reporting information were available. Areas that could benefit from more complete event reporting that will be discussed in the paper include fire event frequency analysis, analysis of fire detection and suppression system performance including incipient detection systems, analysis of manual fire fighting performance, treatment of fire growth from incipient stages to fully-involved fires, operator response to fire events, the impact of smoke on plant operations and equipment, and the impact of fire-induced cable failures on plant electrical circuits.« less

Application of wildfire simulation models for risk analysis

NASA Astrophysics Data System (ADS)

Ager, A.; Finney, M.

2009-04-01

Wildfire simulation models are being widely used by fire and fuels specialists in the U.S. to support tactical and strategic decisions related to the mitigation of wildfire risk. Much of this application has resulted from the development of a minimum travel time (MTT) fire spread algorithm (M. Finney) that makes it computationally feasible to simulate thousands of fires and generate burn probability and intensity maps over large areas (10,000 - 2,000,000 ha). The MTT algorithm is parallelized for multi-threaded processing and is imbedded in a number of research and applied fire modeling applications. High performance computers (e.g., 32-way 64 bit SMP) are typically used for MTT simulations, although the algorithm is also implemented in the 32 bit desktop FlamMap3 program (www.fire.org). Extensive testing has shown that this algorithm can replicate large fire boundaries in the heterogeneous landscapes that typify much of the wildlands in the western U.S. In this paper, we describe the application of the MTT algorithm to understand spatial patterns of burn probability (BP), and to analyze wildfire risk to key human and ecological values. The work is focused on a federally-managed 2,000,000 ha landscape in the central interior region of Oregon State, USA. The fire-prone study area encompasses a wide array of topography and fuel types and a number of highly valued resources that are susceptible to fire. We quantitatively defined risk as the product of the probability of a fire and the resulting consequence. Burn probabilities at specific intensity classes were estimated for each 100 x 100 m pixel by simulating 100,000 wildfires under burn conditions that replicated recent severe wildfire events that occurred under conditions where fire suppression was generally ineffective (97th percentile, August weather). We repeated the simulation under milder weather (70th percentile, August weather) to replicate a "wildland fire use scenario" where suppression is minimized to manage fires for fuel reduction. The average BP was calculated for these scenarios to examine variation within and among a number of key designated management units, including forest-urban interface, conservation areas, protected species habitat, municipal watersheds, recreation areas, and others. To quantify risk, we developed a number of loss-benefit functions using fire effects models that relate fire intensity to tree mortality and biomass consumption. We used these relationships to measure the change in highly-valued old forest, designated wildlife conservation areas, aboveground carbon, surface fuels, and other wildland values. The loss-benefit functions were then coupled with BP's for different intensity classes to estimate expected value change (risk) for each pixel. For a subset of the study area we also measured the change in risk from fuels management for selected resources. Estimates of BP, excluding non burnable fuels (water, rock), fro the simulations ranged from 0.00001 to 0.026 within the study area, with a mean value of 0.007. In comparison, the annual burn probability estimated from fire occurrence data within the study area (1910 - 2003) was 0.0022. The estimate from simulations represents the average probability of a random pixel burning from a single large fire that escapes suppression, hence some difference is expected. Variation in BP among designated conservation and fire protection units was relatively large and illustrated spatial differences in wildfire likelihood among highly values resources. For instance, among the 130 different forest-urban interface areas, average BP varied from 0.0001 to 0.02. Average BP for nesting sites used by the endangered Northern spotted owl averaged 0.04 and varied from 0.001 to 0.01. The marginal BP's for high fire intensities was higher for many of the conservation areas compared the surrounding managed forest. Conservation areas that were located on the lee side of non-burnable fuels such as lava flows and lakes showed markedly reduced BP. When wildfire probabilities were combined with habitat loss functions for the Northern spotted owl, we observed expected loss from a random wildfire event ranging from 0.0 to 9.4% with a mean value of 1.5%. Expected loss was strongly correlated with BP for owl habitat, apparently because fires at very low intensities caused understory mortality and reduced stand canopy closure below minimum levels. The effect of simulating strategic fuel treatments on a subunit of the area resulted in significant decrease in expected loss of owl habitat. The effect of changing weather from a severe to mild (97th to 70th) percentile weather resulted in a dramatic 8-fold drop in BP and reduced the average wildfire size. However, the reduction was not uniform with the departures well correlated with specific fuel models. In total, this work demonstrated the application of wildfire spread models to quantitative risk assessment for fuels management on federally-managed lands in the U.S. The analyses revealed spatial variation in BP that is useful in prioritizing fuels treatments and guiding other wildfire mitigation activities. The work also illuminated the conflict between biodiversity conservation efforts on federally-managed lands and the high wildfire risk on fire-prone landscapes.

Solution of internal ballistic problem for SRM with grain of complex shape during main firing phase

NASA Astrophysics Data System (ADS)

Kiryushkin, A. E.; Minkov, L. L.

2017-10-01

Solid rocket motor (SRM) internal ballistics problems are related to the problems with moving boundaries. The algorithm able to solve similar problems in axisymmetric formulation on Cartesian mesh with an arbitrary order of accuracy is considered in this paper. The base of this algorithm is the ghost point extrapolation using inverse Lax-Wendroff procedure. Level set method is used as an implicit representation of the domain boundary. As an example, the internal ballistics problem for SRM with umbrella type grain was solved during the main firing phase. In addition, flow parameters distribution in the combustion chamber was obtained for different time moments.

Visibility analysis of fire lookout towers in the Boyabat State Forest Enterprise in Turkey.

PubMed

Kucuk, Omer; Topaloglu, Ozer; Altunel, Arif Oguz; Cetin, Mehmet

2017-07-01

For a successful fire suppression, it is essential to detect and intervene forest fires as early as possible. Fire lookout towers are crucial assets in detecting forest fires, in addition to other technological advancements. In this study, we performed a visibility analysis on a network of fire lookout towers currently operating in a relatively fire-prone region in Turkey's Western Black Sea region. Some of these towers had not been functioning properly; it was proposed that these be taken out of the grid and replaced with new ones. The percentage of visible areas under the current network of fire lookout towers was 73%; it could rise to 81% with the addition of newly proposed towers. This study was the first research to conduct a visibility analysis of current and newly proposed fire lookout towers in the Western Black Sea region and focus on its forest fire problem.

How many neurons can we see with current spike sorting algorithms?

PubMed

Pedreira, Carlos; Martinez, Juan; Ison, Matias J; Quian Quiroga, Rodrigo

2012-10-15

Recent studies highlighted the disagreement between the typical number of neurons observed with extracellular recordings and the ones to be expected based on anatomical and physiological considerations. This disagreement has been mainly attributed to the presence of sparsely firing neurons. However, it is also possible that this is due to limitations of the spike sorting algorithms used to process the data. To address this issue, we used realistic simulations of extracellular recordings and found a relatively poor spike sorting performance for simulations containing a large number of neurons. In fact, the number of correctly identified neurons for single-channel recordings showed an asymptotic behavior saturating at about 8-10 units, when up to 20 units were present in the data. This performance was significantly poorer for neurons with low firing rates, as these units were twice more likely to be missed than the ones with high firing rates in simulations containing many neurons. These results uncover one of the main reasons for the relatively low number of neurons found in extracellular recording and also stress the importance of further developments of spike sorting algorithms. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimization of the resources management in fighting wildfires.

PubMed

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Optimization of the Resources Management in Fighting Wildfires

NASA Astrophysics Data System (ADS)

Martin-Fernández, Susana; Martínez-Falero, Eugenio; Pérez-González, J. Manuel

2002-09-01

Wildfires lead to important economic, social, and environmental losses, especially in areas of Mediterranean climate where they are of a high intensity and frequency. Over the past 30 years there has been a dramatic surge in the development and use of fire spread models. However, given the chaotic nature of environmental systems, it is very difficult to develop real-time fire-extinguishing models. This article proposes a method of optimizing the performance of wildfire fighting resources such that losses are kept to a minimum. The optimization procedure includes discrete simulation algorithms and Bayesian optimization methods for discrete and continuous problems (simulated annealing and Bayesian global optimization). Fast calculus algorithms are applied to provide optimization outcomes in short periods of time such that the predictions of the model and the real behavior of the fire, combat resources, and meteorological conditions are similar. In addition, adaptive algorithms take into account the chaotic behavior of wildfire so that the system can be updated with data corresponding to the real situation to obtain a new optimum solution. The application of this method to the Northwest Forest of Madrid (Spain) is also described. This application allowed us to check that it is a helpful tool in the decision-making process.

Evaluation of short-term changes of hydrological response in mountainous basins of the Vitim Plateau (Russia) after forest fires based on data analysis and hydrological modelling

NASA Astrophysics Data System (ADS)

Semenova, O. M.; Lebedeva, L. S.; Nesterova, N. V.; Vinogradova, T. A.

2015-06-01

Twelve mountainous basins of the Vitim Plateau (Eastern Siberia, Russia) with areas ranging from 967 to 18 200 km2 affected by extensive fires in 2003 (from 13 to 78% of burnt area) were delineated based on MODIS Burned Area Product. The studied area is characterized by scarcity of hydrometeorological observations and complex hydrological processes. Combined analysis of monthly series of flow and precipitation was conducted to detect short-term fire impact on hydrological response of the basins. The idea of basin-analogues which have significant correlation of flow with "burnt" watersheds in stationary (pre-fire) period with the assumption that fire impact produced an outlier of established dependence was applied. Available data allowed for qualitative detection of fire-induced changes at two basins from twelve studied. Summer flow at the Amalat and Vitimkan Rivers (22 and 78% proportion of burnt area in 2003, respectively) increased by 40-50% following the fire.The impact of fire on flow from the other basins was not detectable.The hydrological model Hydrograph was applied to simulate runoff formation processes for stationary pre-fire and non-stationary post-fire conditions. It was assumed that landscape properties changed after the fire suggest a flow increase. These changes were used to assess the model parameters which allowed for better model performance in the post-fire period.

Fire Detection Tradeoffs as a Function of Vehicle Parameters

NASA Technical Reports Server (NTRS)

Urban, David L.; Dietrich, Daniel L.; Brooker, John E.; Meyer, Marit E.; Ruff, Gary A.

2016-01-01

Fire survivability depends on the detection of and response to a fire before it has produced an unacceptable environment in the vehicle. This detection time is the result of interplay between the fire burning and growth rates; the vehicle size; the detection system design; the transport time to the detector (controlled by the level of mixing in the vehicle); and the rate at which the life support system filters the atmosphere, potentially removing the detected species or particles. Given the large differences in critical vehicle parameters (volume, mixing rate and filtration rate) the detection approach that works for a large vehicle (e.g. the ISS) may not be the best choice for a smaller crew capsule. This paper examines the impact of vehicle size and environmental control and life support system parameters on the detectability of fires in comparison to the hazard they present. A lumped element model was developed that considers smoke, heat, and toxic product release rates in comparison to mixing and filtration rates in the vehicle. Recent work has quantified the production rate of smoke and several hazardous species from overheated spacecraft polymers. These results are used as the input data set in the lumped element model in combination with the transport behavior of major toxic products released by overheating spacecraft materials to evaluate the necessary alarm thresholds to enable appropriate response to the fire hazard.

MODVOLC2: A Hybrid Time Series Analysis for Detecting Thermal Anomalies Applied to Thermal Infrared Satellite Data

NASA Astrophysics Data System (ADS)

Koeppen, W. C.; Wright, R.; Pilger, E.

2009-12-01

We developed and tested a new, automated algorithm, MODVOLC2, which analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes, fires, and gas flares. MODVOLC2 combines two previously developed algorithms, a simple point operation algorithm (MODVOLC) and a more complex time series analysis (Robust AVHRR Techniques, or RAT) to overcome the limitations of using each approach alone. MODVOLC2 has four main steps: (1) it uses the original MODVOLC algorithm to process the satellite data on a pixel-by-pixel basis and remove thermal outliers, (2) it uses the remaining data to calculate reference and variability images for each calendar month, (3) it compares the original satellite data and any newly acquired data to the reference images normalized by their variability, and it detects pixels that fall outside the envelope of normal thermal behavior, (4) it adds any pixels detected by MODVOLC to those detected in the time series analysis. Using test sites at Anatahan and Kilauea volcanoes, we show that MODVOLC2 was able to detect ~15% more thermal anomalies than using MODVOLC alone, with very few, if any, known false detections. Using gas flares from the Cantarell oil field in the Gulf of Mexico, we show that MODVOLC2 provided results that were unattainable using a time series-only approach. Some thermal anomalies (e.g., Cantarell oil field flares) are so persistent that an additional, semi-automated 12-µm correction must be applied in order to correctly estimate both the number of anomalies and the total excess radiance being emitted by them. Although all available data should be included to make the best possible reference and variability images necessary for the MODVOLC2, we estimate that at least 80 images per calendar month are required to generate relatively good statistics from which to run MODVOLC2, a condition now globally met by a decade of MODIS observations. We also found that MODVOLC2 achieved good results on multiple sensors (MODIS and GOES), which provides confidence that MODVOLC2 can be run on future instruments regardless of their spatial and temporal resolutions. The improved performance of MODVOLC2 over MODVOLC makes possible the detection of lower temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions as well as detect possible low temperature thermal precursors to larger eruptions.

Development and demonstration of a Lagrangian dispersion modeling system for real-time prediction of smoke haze pollution from biomass burning in Southeast Asia

NASA Astrophysics Data System (ADS)

Hertwig, Denise; Burgin, Laura; Gan, Christopher; Hort, Matthew; Jones, Andrew; Shaw, Felicia; Witham, Claire; Zhang, Kathy

2015-12-01

Transboundary smoke haze caused by biomass burning frequently causes extreme air pollution episodes in maritime and continental Southeast Asia. With millions of people being affected by this type of pollution every year, the task to introduce smoke haze related air quality forecasts is urgent. We investigate three severe haze episodes: June 2013 in Maritime SE Asia, induced by fires in central Sumatra, and March/April 2013 and 2014 on mainland SE Asia. Based on comparisons with surface measurements of PM10 we demonstrate that the combination of the Lagrangian dispersion model NAME with emissions derived from satellite-based active-fire detection provides reliable forecasts for the region. Contrasting two fire emission inventories shows that using algorithms to account for fire pixel obscuration by cloud or haze better captures the temporal variations and observed persistence of local pollution levels. Including up-to-date representations of fuel types in the area and using better conversion and emission factors is found to more accurately represent local concentration magnitudes, particularly for peat fires. With both emission inventories the overall spatial and temporal evolution of the haze events is captured qualitatively, with some error attributed to the resolution of the meteorological data driving the dispersion process. In order to arrive at a quantitative agreement with local PM10 levels, the simulation results need to be scaled. Considering the requirements of operational forecasts, we introduce a real-time bias correction technique to the modeling system to address systematic and random modeling errors, which successfully improves the results in terms of reduced normalized mean biases and fractional gross errors.

Earthquake Warning Performance in Vallejo for the South Napa Earthquake

NASA Astrophysics Data System (ADS)

Wurman, G.; Price, M.

2014-12-01

In 2002 and 2003, Seismic Warning Systems, Inc. installed first-generation QuakeGuardTM earthquake warning devices at all eight fire stations in Vallejo, CA. These devices are designed to detect the P-wave of an earthquake and initiate predetermined protective actions if the impending shaking is estimated at approximately Modifed Mercalli Intensity V or greater. At the Vallejo fire stations the devices were set up to sound an audio alert over the public address system and to command the equipment bay doors to open. In August 2014, after more than 11 years of operating in the fire stations with no false alarms, the five units that were still in use triggered correctly on the MW 6.0 South Napa earthquake, less than 16 km away. The audio alert sounded in all five stations, providing fire fighters with 1.5 to 2.5 seconds of warning before the arrival of the S-wave, and the equipment bay doors opened in three of the stations. In one station the doors were disconnected from the QuakeGuard device, and another station lost power before the doors opened completely. These problems highlight just a small portion of the complexity associated with realizing actionable earthquake warnings. The issues experienced in this earthquake have already been addressed in subsequent QuakeGuard product generations, with downstream connection monitoring and backup power for critical systems. The fact that the fire fighters in Vallejo were afforded even two seconds of warning at these epicentral distances results from the design of the QuakeGuard devices, which focuses on rapid false positive rejection and ground motion estimates. We discuss the performance of the ground motion estimation algorithms, with an emphasis on the accuracy and timeliness of the estimates at close epicentral distances.

Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012

NASA Astrophysics Data System (ADS)

Loría-Salazar, S. Marcela; Holmes, Heather A.; Patrick Arnott, W.; Barnard, James C.; Moosmüller, Hans

2016-11-01

Satellite characterization of local aerosol pollution is desirable because of the potential for broad spatial coverage, enabling transport studies of pollution from major sources, such as biomass burning events. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging over land because the underlying surface albedo may be heterogeneous in space and time. Ground-based sunphotometer measurements of AOD are unaffected by surface albedo and are crucial in enabling evaluation, testing, and further development of satellite instruments and retrieval algorithms. Columnar aerosol optical properties from ground-based sunphotometers (Cimel CE-318) as part of AERONET and MODIS aerosol retrievals from Aqua and Terra satellites were compared over semi-arid California and Nevada during the summer season of 2012. Sunphotometer measurements were used as a 'ground truth' to evaluate the current state of satellite retrievals in this spatiotemporal domain. Satellite retrieved (MODIS Collection 6) AOD showed the presence of wildfires in northern California during August. During the study period, the dark-target (DT) retrieval algorithm appears to overestimate AERONET AOD by an average factor of 3.85 in the entire study domain. AOD from the deep-blue (DB) algorithm overestimates AERONET AOD by an average factor of 1.64. Low AOD correlation was also found between AERONET, DT, and DB retrievals. Smoke from fires strengthened the aerosol signal, but MODIS versus AERONET AOD correlation hardly increased during fire events (r2∼0.1-0.2 during non-fire periods and r2∼0-0.31 during fire periods). Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD (NMB∼23%-154% for non-fire periods and NMB∼77%-196% for fire periods). Ångström Extinction Exponent (AEE) from DB for both Terra and Aqua did not correlate with AERONET observations. High surface reflectance and incorrect aerosol physical parametrizations may still be affecting the DT and DB MODIS AOD retrievals in the semi-arid western U.S.

Fire behavior and risk analysis in spacecraft

NASA Technical Reports Server (NTRS)

Friedman, Robert; Sacksteder, Kurt R.

1988-01-01

Practical risk management for present and future spacecraft, including space stations, involves the optimization of residual risks balanced by the spacecraft operational, technological, and economic limitations. Spacecraft fire safety is approached through three strategies, in order of risk: (1) control of fire-causing elements, through exclusion of flammable materials for example; (2) response to incipient fires through detection and alarm; and (3) recovery of normal conditions through extinguishment and cleanup. Present understanding of combustion in low gravity is that, compared to normal gravity behavior, fire hazards may be reduced by the absence of buoyant gas flows yet at the same time increased by ventilation flows and hot particle expulsion. This paper discusses the application of low-gravity combustion knowledge and appropriate aircraft analogies to fire detection, fire fighting, and fire-safety decisions for eventual fire-risk management and optimization in spacecraft.

Efficient Flame Detection and Early Warning Sensors on Combustible Materials Using Hierarchical Graphene Oxide/Silicone Coatings.

PubMed

Wu, Qian; Gong, Li-Xiu; Li, Yang; Cao, Cheng-Fei; Tang, Long-Cheng; Wu, Lianbin; Zhao, Li; Zhang, Guo-Dong; Li, Shi-Neng; Gao, Jiefeng; Li, Yongjin; Mai, Yiu-Wing

2018-01-23

Design and development of smart sensors for rapid flame detection in postcombustion and early fire warning in precombustion situations are critically needed to improve the fire safety of combustible materials in many applications. Herein, we describe the fabrication of hierarchical coatings created by assembling a multilayered graphene oxide (GO)/silicone structure onto different combustible substrate materials. The resulting coatings exhibit distinct temperature-responsive electrical resistance change as efficient early warning sensors for detecting abnormal high environmental temperature, thus enabling fire prevention below the ignition temperature of combustible materials. After encountering a flame attack, we demonstrate extremely rapid flame detection response in 2-3 s and excellent flame self-extinguishing retardancy for the multilayered GO/silicone structure that can be synergistically transformed to a multiscale graphene/nanosilica protection layer. The hierarchical coatings developed are promising for fire prevention and protection applications in various critical fire risk and related perilous circumstances.

Evaluation of detection and response times of fire sensors using an atmospheric monitoring system

PubMed Central

Rowland, J.H.; Litton, C.D.; Thomas, R.A.

2017-01-01

Atmospheric monitoring systems (AMS) are required when using air from conveyor belt entries to ventilate working sections in U.S. underground coal mines. AMS technology has the potential to increase fire safety mine-wide, but research is needed to determine the detection and response times for fires of a variety of combustible materials. To evaluate the potential of an AMS for fire detection in other areas of a coal mine, a series of full-scale fire experiments were conducted to determine detection and response times from fires of different combustible materials that are found in U.S. underground coal mines, including high- and low-volatility coals, conveyor belts, brattice materials, different types of wood, diesel fuel, and a foam sealant. These experiments were conducted in the Safety Research Coal Mine (SRCM) of the U.S. National Institute for Occupational Safety and Health (NIOSH) located in Pittsburgh, PA, using a commercially available AMS that is typical of current technology. The results showed that through proper selection of sensors and their locations, a mine-wide AMS can provide sufficient early fire warning times and improve the health and safety of miners. PMID:28529442

Evaluation of detection and response times of fire sensors using an atmospheric monitoring system.

PubMed

Rowland, J H; Litton, C D; Thomas, R A

2016-01-01

Atmospheric monitoring systems (AMS) are required when using air from conveyor belt entries to ventilate working sections in U.S. underground coal mines. AMS technology has the potential to increase fire safety mine-wide, but research is needed to determine the detection and response times for fires of a variety of combustible materials. To evaluate the potential of an AMS for fire detection in other areas of a coal mine, a series of full-scale fire experiments were conducted to determine detection and response times from fires of different combustible materials that are found in U.S. underground coal mines, including high- and low-volatility coals, conveyor belts, brattice materials, different types of wood, diesel fuel, and a foam sealant. These experiments were conducted in the Safety Research Coal Mine (SRCM) of the U.S. National Institute for Occupational Safety and Health (NIOSH) located in Pittsburgh, PA, using a commercially available AMS that is typical of current technology. The results showed that through proper selection of sensors and their locations, a mine-wide AMS can provide sufficient early fire warning times and improve the health and safety of miners.

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Archeological treasures protection based on early forest wildfire multi-band imaging detection system

NASA Astrophysics Data System (ADS)

Gouverneur, B.; Verstockt, S.; Pauwels, E.; Han, J.; de Zeeuw, P. M.; Vermeiren, J.

2012-10-01

Various visible and infrared cameras have been tested for the early detection of wildfires to protect archeological treasures. This analysis was possible thanks to the EU Firesense project (FP7-244088). Although visible cameras are low cost and give good results during daytime for smoke detection, they fall short under bad visibility conditions. In order to improve the fire detection probability and reduce the false alarms, several infrared bands are tested ranging from the NIR to the LWIR. The SWIR and the LWIR band are helpful to locate the fire through smoke if there is a direct Line Of Sight. The Emphasis is also put on the physical and the electro-optical system modeling for forest fire detection at short and longer ranges. The fusion in three bands (Visible, SWIR, LWIR) is discussed at the pixel level for image enhancement and for fire detection.

Spacecraft Fire Safety Research at NASA Glenn Research Center

NASA Technical Reports Server (NTRS)

Meyer, Marit

2016-01-01

Appropriate design of fire detection systems requires knowledge of both the expected fire signature and the background aerosol levels. Terrestrial fire detection systems have been developed based on extensive study of terrestrial fires. Unfortunately there is no corresponding data set for spacecraft fires and consequently the fire detectors in current spacecraft were developed based upon terrestrial designs. In low gravity, buoyant flow is negligible which causes particles to concentrate at the smoke source, increasing their residence time, and increasing the transport time to smoke detectors. Microgravity fires have significantly different structure than those in 1-g which can change the formation history of the smoke particles. Finally the materials used in spacecraft are different from typical terrestrial environments where smoke properties have been evaluated. It is critically important to detect a fire in its early phase before a flame is established, given the fixed volume of air on any spacecraft. Consequently, the primary target for spacecraft fire detection is pyrolysis products rather than soot. Experimental investigations have been performed at three different NASA facilities which characterize smoke aerosols from overheating common spacecraft materials. The earliest effort consists of aerosol measurements in low gravity, called the Smoke Aerosol Measurement Experiment (SAME), and subsequent ground-based testing of SAME smoke in 55-gallon drums with an aerosol reference instrument. Another set of experiments were performed at NASAs Johnson Space Center White Sands Test Facility (WSTF), with additional fuels and an alternate smoke production method. Measurements of these smoke products include mass and number concentration, and a thermal precipitator was designed for this investigation to capture particles for microscopic analysis. The final experiments presented are from NASAs Gases and Aerosols from Smoldering Polymers (GASP) Laboratory, with selected results focusing on realistic fuel preparations and heating profiles with regards to early detection of smoke. SAFFIRE is the upcoming large-scale fire experiment which will be executed in a Cygnus vehicle after it undocks from the ISS.

Ultrafast detection in particle physics and positron emission tomography using SiPMs

NASA Astrophysics Data System (ADS)

Dolenec, R.; Korpar, S.; Križan, P.; Pestotnik, R.

2017-12-01

Silicon photomultiplier (SiPM) photodetectors perform well in many particle and medical physics applications, especially where good efficiency, insensitivity to magnetic field and precise timing are required. In Cherenkov time-of-flight positron emission tomography the requirements for photodetector performance are especially high. On average only a couple of photons are available for detection and the best possible timing resolution is needed. Using SiPMs as photodetectors enables good detection efficiency, but the large sensitive area devices needed have somewhat limited time resolution for single photons. We have observed an additional degradation of the timing at very low light intensities due to delayed events in distribution of signals resulting from multiple fired micro cells. In this work we present the timing properties of AdvanSiD ASD-NUV3S-P-40 SiPM at single photon level picosecond laser illumination and a simple modification of the time-walk correction algorithm, that resulted in reduced degradation of timing resolution due to the delayed events.

Application of wildfire simulation models for risk analysis

Treesearch

Alan A. Ager; Mark A. Finney

2009-01-01

Wildfire simulation models are being widely used by fire and fuels specialists in the U.S. to support tactical and strategic decisions related to the mitigation of wildfire risk. Much of this application has resulted from the development of a minimum travel time (MTT) fire spread algorithm (M. Finney) that makes it computationally feasible to simulate thousands of...

Advanced FIREFLY Assessment Generalized Mechanization Requirements Report

DTIC Science & Technology

1979-06-01

Systems; Fire Control Computers ; Weapon Control 20. ABSTRACT (Continue on reverse side If necessary end tdentify by blockc number) -The requirements for...airborne digital computer which can be specialized to per- form successfully in a variety of tactical aircraft with differing avionics sensors, fire...AGG ........................................... 27 13 Time of Flight Computation Using a Modified (China Lake) Numerical Integration Algorithm

The analysis of a complex fire event using multispaceborne observations

NASA Astrophysics Data System (ADS)

Andrei, Simona; Carstea, Emil; Marmureanu, Luminita; Ene, Dragos; Binietoglou, Ioannis; Nicolae, Doina; Konsta, Dimitra; Amiridis, Vassilis; Proestakis, Emmanouil

2018-04-01

This study documents a complex fire event that occurred on October 2016, in Middle East belligerent area. Two fire outbreaks were detected by different spacecraft monitoring instruments on board of TERRA, CALIPSO and AURA Earth Observation missions. Link with local weather conditions was examined using ERA Interim Reanalysis and CAMS datasets. The detection of the event by multiple sensors enabled a detailed characterization of fires and the comparison with different observational data.

Systems Engineering Approach To Ground Combat Vehicle Survivability In Urban Operations

DTIC Science & Technology

2016-09-01

extinguishing system (AFES), which uses fire wires to detect the presence of fires. The detection of fire automatically triggers the activation of the fire...corresponding wires and connection points also means that it can be more difficult for engineers to integrate distributed architecture systems onto...command signals to the missile via wires trailing behind the missile or via RF signals. See Figure 29 for an illustration of CLOS guidance. Since CLOS

SAR-based change detection using hypothesis testing and Markov random field modelling

NASA Astrophysics Data System (ADS)

Cao, W.; Martinis, S.

2015-04-01

The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists of two steps: Firstly, an automatic coarse detection step is applied based on a statistical hypothesis test for initializing the classification. The original analytical formula as proposed in the constant false alarm rate (CFAR) edge detector is reviewed and rewritten in a compact form of the incomplete beta function, which is a builtin routine in commercial scientific software such as MATLAB and IDL. Secondly, a post-classification step is introduced to optimize the noisy classification result in the previous step. Generally, an optimization problem can be formulated as a Markov random field (MRF) on which the quality of a classification is measured by an energy function. The optimal classification based on the MRF is related to the lowest energy value. Previous studies provide methods for the optimization problem using MRFs, such as the iterated conditional modes (ICM) algorithm. Recently, a novel algorithm was presented based on graph-cut theory. This method transforms a MRF to an equivalent graph and solves the optimization problem by a max-flow/min-cut algorithm on the graph. In this study this graph-cut algorithm is applied iteratively to improve the coarse classification. At each iteration the parameters of the energy function for the current classification are set by the logarithmic probability density function (PDF). The relevant parameters are estimated by the method of logarithmic cumulants (MoLC). Experiments are performed using two flood events in Germany and Australia in 2011 and a forest fire on La Palma in 2009 using pre- and post-event TerraSAR-X data. The results show convincing coarse classifications and considerable improvement by the graph-cut post-classification step.

Prototype of microbolometer thermal infrared camera for forest fire detection from space

NASA Astrophysics Data System (ADS)

Guerin, Francois; Dantes, Didier; Bouzou, Nathalie; Chorier, Philippe; Bouchardy, Anne-Marie; Rollin, Joël.

2017-11-01

The contribution of the thermal infrared (TIR) camera to the Earth observation FUEGO mission is to participate; to discriminate the clouds and smoke; to detect the false alarms of forest fires; to monitor the forest fires. Consequently, the camera needs a large dynamic range of detectable radiances. A small volume, low mass and power are required by the small FUEGO payload. These specifications can be attractive for other similar missions.

Fire protection for a Martian colony

NASA Astrophysics Data System (ADS)

Beattie, Robert M., Jr.

The fire prevention failures that occurred in Apollo 1 and Challenger accidents are reviewed and used to discuss fire protection measures that should be taken in a Martian colony. Fire detection systems, classes of fire, and suppression agents are described. The organization of fire fighting personnel appropriate for Mars is addressed.

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 4 2013-10-01 2013-10-01 false Location and spacing of tubing in pneumatic fire detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.409 Location...

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 4 2012-10-01 2012-10-01 false Location and spacing of tubing in pneumatic fire detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.409 Location...

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 4 2014-10-01 2014-10-01 false Location and spacing of tubing in pneumatic fire detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.409 Location...

46 CFR 108.409 - Location and spacing of tubing in pneumatic fire detection system.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 4 2011-10-01 2011-10-01 false Location and spacing of tubing in pneumatic fire detection system. 108.409 Section 108.409 Shipping COAST GUARD, DEPARTMENT OF HOMELAND SECURITY (CONTINUED) A-MOBILE OFFSHORE DRILLING UNITS DESIGN AND EQUIPMENT Fire Extinguishing Systems § 108.409 Location...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2013 CFR

2013-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2013-10-01 2013-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2014 CFR

2014-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2014-10-01 2014-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

46 CFR 161.002-9 - Automatic fire detecting system, power supply.

Code of Federal Regulations, 2012 CFR

2012-10-01

... system must meet the requirements of § 113.10-9 of subchapter J (Electrical Engineering Regulations) of... 46 Shipping 6 2012-10-01 2012-10-01 false Automatic fire detecting system, power supply. 161.002-9..., CONSTRUCTION, AND MATERIALS: SPECIFICATIONS AND APPROVAL ELECTRICAL EQUIPMENT Fire-Protective Systems § 161.002...

77 FR 75071 - Special Conditions: Embraer S.A., Model EMB-550 Airplanes; Electrical/Electronic Equipment Bay...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-19

.../Electronic Equipment Bay Fire Detection and Smoke Penetration AGENCY: Federal Aviation Administration (FAA... where the flightcrew could determine the origin of smoke or fire by a straightforward airplane flight.... The FAA has no requirement for smoke and/or fire detection in the electrical/electronic equipment bays...

78 FR 14007 - Special Conditions: Embraer S.A., Model EMB-550 Airplanes; Electrical/Electronic Equipment Bay...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-04

...; Electrical/Electronic Equipment Bay Fire Detection and Smoke Penetration AGENCY: Federal Aviation... where the flight crew could determine the origin of smoke or fire by a straightforward airplane flight.... The FAA has no requirement for smoke and/or fire detection in the electrical/electronic equipment bays...

Use of multi-sensor active fire detections to map fires in the United States: the future of monitoring trends in burn severity

USGS Publications Warehouse

Picotte, Joshua J.; Coan, Michael; Howard, Stephen M.

2014-01-01

The effort to utilize satellite-based MODIS, AVHRR, and GOES fire detections from the Hazard Monitoring System (HMS) to identify undocumented fires in Florida and improve the Monitoring Trends in Burn Severity (MTBS) mapping process has yielded promising results. This method was augmented using regression tree models to identify burned/not-burned pixels (BnB) in every Landsat scene (1984–2012) in Worldwide Referencing System 2 Path/Rows 16/40, 17/39, and 1839. The burned area delineations were combined with the HMS detections to create burned area polygons attributed with their date of fire detection. Within our study area, we processed 88,000 HMS points (2003–2012) and 1,800 Landsat scenes to identify approximately 300,000 burned area polygons. Six percent of these burned area polygons were larger than the 500-acre MTBS minimum size threshold. From this study, we conclude that the process can significantly improve understanding of fire occurrence and improve the efficiency and timeliness of assessing its impacts upon the landscape.

Engineering Software for Interoperability through Use of Enterprise Architecture Techniques

DTIC Science & Technology

2003-03-01

Response Home/ Business Security . To detect flood conditions (i.e. excess water levels) within the monitored area and alert authorities, as necessary...Response; Fire Detection & Response; and Flood Detection & Response. Functional Area Description Intruder Detection & Response Home/ Business ... Security . To monitor and detect unauthorized entry into the secured area and sound alarms/alert authorities, as necessary. Fire Detection

The investigation of identifying method on grass fire by FY-3 VIRR images

NASA Astrophysics Data System (ADS)

Jiang, Youyan; Han, Tao; Wang, Dawei

2018-03-01

Grassland fire has the characteristics of fierce fire and rapid spreading, and many fires occur in sparsely populated places. Satellite remote sensing has the characteristics of fast imaging period and wide coverage, and plays an important role in the rapid monitoring and evaluation of grassland fire. FY-3 satellite has been widely used since its launch in September 2008, and this paper uses the fire information of Gansu grassland from 2011 to 2016, based on the more mature MODIS and NOAA-AVHRR fire identification method. The results show that the accuracy of FY-3/VIRR satellite data fire detection are higher than that of NOAA-AVHRR satellite, and the accuracy of FY-3/VIRR satellite data is described. There is a greater improvement, the ability to identify slightly worse than the MODIS satellite, the region is relatively large fire detection accuracy is higher.

Wildfire Detection using by Multi Dimensional Histogram in Boreal Forest

NASA Astrophysics Data System (ADS)

Honda, K.; Kimura, K.; Honma, T.

2008-12-01

Early detection of wildfires is an issue for reduction of damage to environment and human. There are some attempts to detect wildfires by using satellite imagery, which are mainly classified into three methods: Dozier Method(1981-), Threshold Method(1986-) and Contextual Method(1994-). However, the accuracy of these methods is not enough: some commission and omission errors are included in the detected results. In addition, it is not so easy to analyze satellite imagery with high accuracy because of insufficient ground truth data. Kudoh and Hosoi (2003) developed the detection method by using three-dimensional (3D) histogram from past fire data with the NOAA-AVHRR imagery. But their method is impractical because their method depends on their handworks to pick up past fire data from huge data. Therefore, the purpose of this study is to collect fire points as hot spots efficiently from satellite imagery and to improve the method to detect wildfires with the collected data. As our method, we collect past fire data with the Alaska Fire History data obtained by the Alaska Fire Service (AFS). We select points that are expected to be wildfires, and pick up the points inside the fire area of the AFS data. Next, we make 3D histogram with the past fire data. In this study, we use Bands 1, 21 and 32 of MODIS. We calculate the likelihood to detect wildfires with the three-dimensional histogram. As our result, we select wildfires with the 3D histogram effectively. We can detect the troidally spreading wildfire. This result shows the evidence of good wildfire detection. However, the area surrounding glacier tends to rise brightness temperature. It is a false alarm. Burnt area and bare ground are sometimes indicated as false alarms, so that it is necessary to improve this method. Additionally, we are trying various combinations of MODIS bands as the better method to detect wildfire effectively. So as to adjust our method in another area, we are applying our method to tropical forest in Kalimantan, Indonesia and around Chiang Mai, Thailand. But the ground truth data in these areas is lesser than the one in Alaska. Our method needs lots of accurate observed data to make multi-dimensional histogram in the same area. In this study, we can show the system to select wildfire data efficiently from satellite imagery. Furthermore, the development of multi-dimensional histogram from past fire data makes it possible to detect wildfires accurately.

Ensemble stacking mitigates biases in inference of synaptic connectivity.

PubMed

Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N

2018-01-01

A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

..., but not be limited to, automatic fire and smoke detecting systems, manual fire alarm systems, sample... unit, fire detectors, smoke detectors, and audible and visual alarms distinct in both respects from the alarms of any other system not indicating fire. (c) Manual fire alarm systems. For the purpose of this...

A MODIS direct broadcast algorithm for mapping wildfire burned area in the western United States

Treesearch

S. P. Urbanski; J. M. Salmon; B. L. Nordgren; W. M. Hao

2009-01-01

Improved wildland fire emission inventory methods are needed to support air quality forecasting and guide the development of air shed management strategies. Air quality forecasting requires dynamic fire emission estimates that are generated in a timely manner to support real-time operations. In the regulatory and planning realm, emission inventories are essential for...

Using satellite fire detection to calibrate components of the fire weather index system in Malaysia and Indonesia.

PubMed

Dymond, Caren C; Field, Robert D; Roswintiarti, Orbita; Guswanto

2005-04-01

Vegetation fires have become an increasing problem in tropical environments as a consequence of socioeconomic pressures and subsequent land-use change. In response, fire management systems are being developed. This study set out to determine the relationships between two aspects of the fire problems in western Indonesia and Malaysia, and two components of the Canadian Forest Fire Weather Index System. The study resulted in a new method for calibrating components of fire danger rating systems based on satellite fire detection (hotspot) data. Once the climate was accounted for, a problematic number of fires were related to high levels of the Fine Fuel Moisture Code. The relationship between climate, Fine Fuel Moisture Code, and hotspot occurrence was used to calibrate Fire Occurrence Potential classes where low accounted for 3% of the fires from 1994 to 2000, moderate accounted for 25%, high 26%, and extreme 38%. Further problems arise when there are large clusters of fires burning that may consume valuable land or produce local smoke pollution. Once the climate was taken into account, the hotspot load (number and size of clusters of hotspots) was related to the Fire Weather Index. The relationship between climate, Fire Weather Index, and hotspot load was used to calibrate Fire Load Potential classes. Low Fire Load Potential conditions (75% of an average year) corresponded with 24% of the hotspot clusters, which had an average size of 30% of the largest cluster. In contrast, extreme Fire Load Potential conditions (1% of an average year) corresponded with 30% of the hotspot clusters, which had an average size of 58% of the maximum. Both Fire Occurrence Potential and Fire Load Potential calibrations were successfully validated with data from 2001. This study showed that when ground measurements are not available, fire statistics derived from satellite fire detection archives can be reliably used for calibration. More importantly, as a result of this work, Malaysia and Indonesia have two new sources of information to initiate fire prevention and suppression activities.

Science in 60 – Tabletop Fire Prediction

ScienceCinema

Cary, Lyle

2018-01-16

At the Interagency Fire Center at Los Alamos National Laboratory, experts rely on the state-of-the-art Simtable to help them predict the unpredictable. With algorithms that include camera-based object-tracking and projection developed by the Laboratory, the emergency operations team can simulate a wildland fire spreading across any terrain. The table system, developed and marketed by Simtable, a Santa Fe, N.M., company, takes into account weather, vegetation and fuel conditions. The project also received funding from the LANS Venture Acceleration Fund to improve the user interface.

Science in 60 – Tabletop Fire Prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cary, Lyle

At the Interagency Fire Center at Los Alamos National Laboratory, experts rely on the state-of-the-art Simtable to help them predict the unpredictable. With algorithms that include camera-based object-tracking and projection developed by the Laboratory, the emergency operations team can simulate a wildland fire spreading across any terrain. The table system, developed and marketed by Simtable, a Santa Fe, N.M., company, takes into account weather, vegetation and fuel conditions. The project also received funding from the LANS Venture Acceleration Fund to improve the user interface.

Water vapour emission in vegetable fuel: absorption cell measurements and detection limits of our CO II Dial system

NASA Astrophysics Data System (ADS)

Bellecci, C.; De Leo, L.; Gaudio, P.; Gelfusa, M.; Lo Feudo, T.; Martellucci, S.; Richetta, M.

2006-09-01

Forest fires can be the cause of serious environmental and economic damages. For this reason a considerable effort has been directed toward the forest protection and fire fighting. In the early forest fire detection, Lidar technique present considerable advantages compared to the passive detection methods based on infrared cameras currently in common use, due its higher sensitivity and ability to accurately locate the fire. The combustion phase of the vegetable matter causes a great amount of water vapour emission, thus the water molecule behaviour will be studied to obtain a fire detection system ready and efficient also before the flame propagation. A first evaluation of increment of the water vapour concentration compared to standard one will be estimated by a numerical simulation. These results will be compared with the experimental measurements carried out into a cell with a CO II Dial system, burning different kinds of vegetable fuel. Our results and their comparison will be reported in this paper.

Smoke from Fires in Southern Mexico

NASA Technical Reports Server (NTRS)

2002-01-01

On May 2, 2002, numerous fires in southern Mexico sent smoke drifting northward over the Gulf of Mexico. These views from the Multi-angle Imaging SpectroRadiometer illustrate the smoke extent over parts of the Gulf and the southern Mexican states of Tabasco, Campeche and Chiapas. At the same time, dozens of other fires were also burning in the Yucatan Peninsula and across Central America. A similar situation occurred in May and June of 1998, when Central American fires resulted in air quality warnings for several U.S. States.

The image on the left is a natural color view acquired by MISR's vertical-viewing (nadir) camera. Smoke is visible, but sunglint in some ocean areas makes detection difficult. The middle image, on the other hand, is a natural color view acquired by MISR's 70-degree backward-viewing camera; its oblique view angle simultaneously suppresses sunglint and enhances the smoke. A map of aerosol optical depth, a measurement of the abundance of atmospheric particulates, is provided on the right. This quantity is retrieved using an automated computer algorithm that takes advantage of MISR's multi-angle capability. Areas where no retrieval occurred are shown in black.

The images each represent an area of about 380 kilometers x 1550 kilometers and were captured during Terra orbit 12616.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

Evaluating the impact of improvements to the FLAMBE smoke source model on forecasts of aerosol distribution from NAAPS

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Reid, J. S.

2006-12-01

As more forecast models aim to include aerosol and chemical species, there is a need for source functions for biomass burning emissions that are accurate, robust, and operable in real-time. NAAPS is a global aerosol forecast model running every six hours and forecasting distributions of biomass burning, industrial sulfate, dust, and sea salt aerosols. This model is run operationally by the U.S. Navy as an aid to planning. The smoke emissions used as input to the model are calculated from the data collected by the FLAMBE system, driven by near-real-time active fire data from GOES WF_ABBA and MODIS Rapid Response. The smoke source function uses land cover data to predict properties of detected fires based on literature data from experimental burns. This scheme is very sensitive to the choice of land cover data sets. In areas of rapid land cover change, the use of static land cover data can produce artifactual changes in emissions unrelated to real changes in fire patterns. In South America, this change may be as large as 40% over five years. We demonstrate the impact of a modified land cover scheme on FLAMBE emissions and NAAPS forecasts, including a fire size algorithm developed using MODIS burned area data. We also describe the effects of corrections to emissions estimates for cloud and satellite coverage. We outline areas where existing data sources are incomplete and improvements are required to achieve accurate modeling of biomass burning emissions in real time.

Learning neural connectivity from firing activity: efficient algorithms with provable guarantees on topology.

PubMed

Karbasi, Amin; Salavati, Amir Hesam; Vetterli, Martin

2018-04-01

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network's topology has received a lot of attentions in neuroscience and has been the center of many research initiatives such as Human Connectome Project. Nevertheless, direct and invasive approaches that slice and observe the neural tissue have proven to be time consuming, complex and costly. As a result, the inverse methods that utilize firing activity of neurons in order to identify the (functional) connections have gained momentum recently, especially in light of rapid advances in recording technologies; It will soon be possible to simultaneously monitor the activities of tens of thousands of neurons in real time. While there are a number of excellent approaches that aim to identify the functional connections from firing activities, the scalability of the proposed techniques plays a major challenge in applying them on large-scale datasets of recorded firing activities. In exceptional cases where scalability has not been an issue, the theoretical performance guarantees are usually limited to a specific family of neurons or the type of firing activities. In this paper, we formulate the neural network reconstruction as an instance of a graph learning problem, where we observe the behavior of nodes/neurons (i.e., firing activities) and aim to find the links/connections. We develop a scalable learning mechanism and derive the conditions under which the estimated graph for a network of Leaky Integrate and Fire (LIf) neurons matches the true underlying synaptic connections. We then validate the performance of the algorithm using artificially generated data (for benchmarking) and real data recorded from multiple hippocampal areas in rats.

Regional variation of carbonaceous aerosols from space and simulations

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko; Kokhanovsky, Alexander

2017-04-01

Satellite remote sensing provides us with a systematic monitoring in a global scale. As such, aerosol observation via satellites is known to be useful and effective. However, before attempting to retrieve aerosol properties from satellite data, the efficient algorithms for aerosol retrieval need to be considered. The characteristics and distributions of atmospheric aerosols are known to be complicated, owing to both natural factors and human activities. It is known that the biomass burning aerosols generated by the large-scale forest fires and burn agriculture have influenced the severity of air pollution. Nevertheless the biomass burning episodes increase due to global warming and climate change and vice versa. It is worth noting that the near ultra violet (NUV) measurements are helpful for the detection of carbonaceous particles, which are the main component of aerosols from biomass burning. In this work, improved retrieval algorithms for biomass burning aerosols are shown by using the measurements observed by GLI and POLDER-2 on Japanese short term mission ADEOS-2 in 2003. The GLI sensor has 380nm channel. For detection of biomass burning episodes, the aerosol optical thickness of carbonaceous aerosols simulated with the numerical model simulations (SPRINTARS) is available as well as fire products from satellite imagery. Moreover the algorithm using shorter wavelength data is available for detection of absorbing aerosols. An algorithm based on the combined use of near-UV and violet data has been introduced in our previous work with ADEOS (Advanced Earth Observing Satellite) -2 /GLI measurements [1]. It is well known that biomass burning plume is a seasonal phenomenon peculiar to a particular region. Hence, the mass concentrations of aerosols are frequently governed with spatial and/or temporal variations of biomass burning plumes. Accordingly the satellite data sets for our present study are adopted from the view points of investigation of regional and seasonal effect on carbonaceous aerosols. And then the selected data observed by ADEOS-2/GLI and POLDER in 2003 are treated by using Vector form Method of Successive Order of Scattering (VMSOS) for radiative transfer simulations in the semi-infinite atmosphere [2]. Finally the obtained optical properties of the carbonaceous aerosols are investigated in comparison with the numerical model simulations of SPRINTARS. In spite of the limited case studies, it has been pointed out that NUV-channel data are effective for retrieval of the carbonaceous aerosol properties. Therefore we have to treat with this issue for not only detection of biomass burning plume but also retrieval itself. If that happens, synthetic analysis based on multi-channel and/or polarization measurements become practical, and the proposed procedure and results are available for a feasibility study of coming space missions. [1] Sano, I., Y. Okada, M. Mukai and S. Mukai, "Retrieval algorithm based on combined use of POLDER and GLI data for biomass aerosols," J. RSSJ, vol. 29, no. 1, pp. 54-59, doi:10.11440/rssj.29.54, 2009. [2] Mukai, S., M. Nakata, M. Yasumoto, I. Sano and A. Kokhanovsky, "A study of aerosol pollution episode due to agriculture biomass burning in the east-central China using satellite data," Front. Environ. Sci., vol. 3:57, doi:　10.3389/fenvs.2015.00057, 2015.

Intelligent emissions controller for substance injection in the post-primary combustion zone of fossil-fired boilers

DOEpatents

Reifman, Jaques; Feldman, Earl E.; Wei, Thomas Y. C.; Glickert, Roger W.

2003-01-01

The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate. Based upon the optimal operating conditions from the optimization algorithms, the incremental substance cost per unit of emissions reduction, and the open-market price per unit of emissions reduction, the intelligent emissions controller allows for the determination of whether it is more cost-effective to achieve additional increments in emission reduction through the injection of additional substance or through the purchase of emission credits on the open market. This is of particular interest to fossil-fired electrical power plant operators. The intelligent emission controller is particularly adapted for determining the economical control of such pollutants as oxides of nitrogen (NO.sub.x) and carbon monoxide (CO) emitted by fossil-fired boilers by the selective introduction of multiple inputs of substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea, and combinations of these substances) above the primary combustion zone of fossil-fired boilers.

Improved estimates of biomass burning emissions in the southeast United States

NASA Astrophysics Data System (ADS)

Nowell, H.; Holmes, C.; Elsner, J.; Hiers, J. K.; Robertson, K.

2017-12-01

Biomass burning is a major source of gas and particle emissions that affects air quality, human health, and climate. Prescribed burns in the southeastern United States consume more biomass and cover a larger area than fires in the rest of the United States combined. Although fires can be detected remotely from thermal infrared emission and changes to surface reflectance, there are multiple issues that make satellite detections difficult in the eastern United States. These include small fire sizes, short duration, low intensity, canopy coverage, and rapid vegetation regrowth. Some attempts have been made to compensate for this bias, for example the small fire product in the Global Fire Emission Database (GFED4.1s) product. The accuracy of GFED and other remotely sensed global fire emission inventories are largely unknown, outside of a few field studies, mainly because there are few independent datasets of fire extent. The Florida Forest Service (FFS) has extensive records on fire type, size, location, and time for both prescribed and wild fires, which have not previously been used to evaluate fire area and emissions. For our study period of 2004 to 2016, we compared FFS burn authorization data against GFED4.1s burned area. When averaged across the state of Florida, there is 4 times more land burned than detected from satellite sensors. When comparing FFS data against high quality records from Apalachicola National Forest, Avon Park Air Force Range, Eglin Air Force Base, Tall Timbers Research Station, and Tyndall Air Force base, the areal discrepancy between these records and FFS reports are +/- 15%, well below the 4 times detection discrepancy between satellites and FFS reports. We have developed a method to statistically correct this satellite bias in fire detections. Treating the FFS burn authorizations as accurate, we have found this bias ratio can be predicted from fire size, land cover type, leaf area, and month. The regression model incorporating these factors can predict greater than 80% of variance in bias ratio across Florida during the summer months with correlations around 0.6 on average. This improved estimate of burned area in Florida will be used in global circulation models to determine the true contribution of prescribed wild fires in the southeast United States to gas and particle emissions.

The double slit experiment and the time reversed fire alarm

NASA Astrophysics Data System (ADS)

Halabi, Tarek

2011-03-01

When both slits of the double slit experiment are open, closing one paradoxically increases the detection rate at some points on the detection screen. Feynman famously warned that temptation to "understand" such a puzzling feature only draws us into blind alleys. Nevertheless, we gain insight into this feature by drawing an analogy between the double slit experiment and a time reversed fire alarm. Much as closing the slit increases probability of a future detection, ruling out fire drill scenarios, having heard the fire alarm, increases probability of a past fire (using Bayesian inference). Classically, Bayesian inference is associated with computing probabilities of past events. We therefore identify this feature of the double slit experiment with a time reversed thermodynamic arrow. We believe that much of the enigma of quantum mechanics is simply due to some variation of time's arrow.

Cable tunnel fire experiment study based on linear optical fiber fire detectors

NASA Astrophysics Data System (ADS)

Fan, Dian; Ding, Hongjun

2013-09-01

Aiming at exiting linear temperature fire detection technology including temperature sensing cable, fiber Raman scattering, fiber Bragg grating, this paper establish an experimental platform in cable tunnel, set two different experimental scenes of the fire and record temperature variation and fire detector response time in the processing of fire simulation. Since a small amount of thermal radiation and no flame for the beginning of the small-scale fire, only directly contacting heat detectors can make alarm response and the rest of other non- contact detectors are unable to respond. In large-scale fire, the alarm response time of the fiber Raman temperature sensing fire detector and fiber Bragg grating temperature sensing fire detector is about 30 seconds, and depending on the thermocouples' record the temperature over the fire is less than 35° in first 60 seconds of large-scale fire, while the temperature rising is more than 5°/min within the range of +/- 3m. According to the technical characteristics of the three detectors, the engineering suitability of the typical linear heat detectors in cable tunnels early fire detection is analyzed, which provide technical support for the preparation of norms.

Utilizing multi-sensor fire detections to map fires in the United States

USGS Publications Warehouse

Howard, Stephen M.; Picotte, Joshua J.; Coan, Michael

2014-01-01

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 “unknown” or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.

Utilizing Multi-Sensor Fire Detections to Map Fires in the United States

NASA Astrophysics Data System (ADS)

Howard, S. M.; Picotte, J. J.; Coan, M. J.

2014-11-01

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 "unknown" or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.

DoD Is Not Properly Monitoring the Initiation of Maintenance for Facilities at Kandahar Airfield, Afghanistan (REDACTED)

DTIC Science & Technology

2013-09-30

fire sprinkler system during the initial construction of the RSOI facilities. The construction contract to build the RSOI...International Building Code. Compliant manual and automatic fire alarm and notification systems , portable fire extinguishers, fire sprinkler systems ...automatic fire sprinkler system that was not operational, a fire department connection that was obstructed, and a fire detection system

Thermal particle image velocity estimation of fire plume flow

Treesearch

Xiangyang Zhou; Lulu Sun; Shankar Mahalingam; David R. Weise

2003-01-01

For the purpose of studying wildfire spread in living vegetation such as chaparral in California, a thermal particle image velocity (TPIV) algorithm for nonintrusively measuring flame gas velocities through thermal infrared (IR) imagery was developed. By tracing thermal particles in successive digital IR images, the TPIV algorithm can estimate the velocity field in a...

Single Neuron Optimization as a Basis for Accurate Biophysical Modeling: The Case of Cerebellar Granule Cells.

PubMed

Masoli, Stefano; Rizza, Martina F; Sgritta, Martina; Van Geit, Werner; Schürmann, Felix; D'Angelo, Egidio

2017-01-01

In realistic neuronal modeling, once the ionic channel complement has been defined, the maximum ionic conductance (G i-max ) values need to be tuned in order to match the firing pattern revealed by electrophysiological recordings. Recently, selection/mutation genetic algorithms have been proposed to efficiently and automatically tune these parameters. Nonetheless, since similar firing patterns can be achieved through different combinations of G i-max values, it is not clear how well these algorithms approximate the corresponding properties of real cells. Here we have evaluated the issue by exploiting a unique opportunity offered by the cerebellar granule cell (GrC), which is electrotonically compact and has therefore allowed the direct experimental measurement of ionic currents. Previous models were constructed using empirical tuning of G i-max values to match the original data set. Here, by using repetitive discharge patterns as a template, the optimization procedure yielded models that closely approximated the experimental G i-max values. These models, in addition to repetitive firing, captured additional features, including inward rectification, near-threshold oscillations, and resonance, which were not used as features. Thus, parameter optimization using genetic algorithms provided an efficient modeling strategy for reconstructing the biophysical properties of neurons and for the subsequent reconstruction of large-scale neuronal network models.

Reflexive obstacle avoidance for kinematically-redundant manipulators

NASA Technical Reports Server (NTRS)

Karlen, James P.; Thompson, Jack M., Jr.; Farrell, James D.; Vold, Havard I.

1989-01-01

Dexterous telerobots incorporating 17 or more degrees of freedom operating under coordinated, sensor-driven computer control will play important roles in future space operations. They will also be used on Earth in assignments like fire fighting, construction and battlefield support. A real time, reflexive obstacle avoidance system, seen as a functional requirement for such massively redundant manipulators, was developed using arm-mounted proximity sensors to control manipulator pose. The project involved a review and analysis of alternative proximity sensor technologies for space applications, the development of a general-purpose algorithm for synthesizing sensor inputs, and the implementation of a prototypical system for demonstration and testing. A 7 degree of freedom Robotics Research K-2107HR manipulator was outfitted with ultrasonic proximity sensors as a testbed, and Robotics Research's standard redundant motion control algorithm was modified such that an object detected by sensor arrays located at the elbow effectively applies a force to the manipulator elbow, normal to the axis. The arm is repelled by objects detected by the sensors, causing the robot to steer around objects in the workspace automatically while continuing to move its tool along the commanded path without interruption. The mathematical approach formulated for synthesizing sensor inputs can be employed for redundant robots of any kinematic configuration.

Multiple-Parameter, Low-False-Alarm Fire-Detection Systems

NASA Technical Reports Server (NTRS)

Hunter, Gary W.; Greensburg, Paul; McKnight, Robert; Xu, Jennifer C.; Liu, C. C.; Dutta, Prabir; Makel, Darby; Blake, D.; Sue-Antillio, Jill

2007-01-01

Fire-detection systems incorporating multiple sensors that measure multiple parameters are being developed for use in storage depots, cargo bays of ships and aircraft, and other locations not amenable to frequent, direct visual inspection. These systems are intended to improve upon conventional smoke detectors, now used in such locations, that reliably detect fires but also frequently generate false alarms: for example, conventional smoke detectors based on the blockage of light by smoke particles are also affected by dust particles and water droplets and, thus, are often susceptible to false alarms. In contrast, by utilizing multiple parameters associated with fires, i.e. not only obscuration by smoke particles but also concentrations of multiple chemical species that are commonly generated in combustion, false alarms can be significantly decreased while still detecting fires as reliably as older smoke-detector systems do. The present development includes fabrication of sensors that have, variously, micrometer- or nanometer-sized features so that such multiple sensors can be integrated into arrays that have sizes, weights, and power demands smaller than those of older macroscopic sensors. The sensors include resistors, electrochemical cells, and Schottky diodes that exhibit different sensitivities to the various airborne chemicals of interest. In a system of this type, the sensor readings are digitized and processed by advanced signal-processing hardware and software to extract such chemical indications of fires as abnormally high concentrations of CO and CO2, possibly in combination with H2 and/or hydrocarbons. The system also includes a microelectromechanical systems (MEMS)-based particle detector and classifier device to increase the reliability of measurements of chemical species and particulates. In parallel research, software for modeling the evolution of a fire within an aircraft cargo bay has been developed. The model implemented in the software can describe the concentrations of chemical species and of particulate matter as functions of time. A system of the present developmental type and a conventional fire detector were tested under both fire and false-alarm conditions in a Federal Aviation Administration cargo-compartment- testing facility. Both systems consistently detected fires. However, the conventional fire detector consistently generated false alarms, whereas the developmental system did not generate any false alarms.

Colleges Fight Fire With Electronics.

ERIC Educational Resources Information Center

College & University Business, 1968

1968-01-01

Description of various electronic fire detection and alarm systems is presented. Explanation of detective systems includes--(1) fixed-temperature and rate-of-rise heat sensitive devices, (2) smoke detective devices, (3) ionization systems, and (4) infrared and ultraviolet radiation devices. Each system type is evaluated in terms of operation,…

A wireless sensor network deployment for rural and forest fire detection and verification.

PubMed

Lloret, Jaime; Garcia, Miguel; Bri, Diana; Sendra, Sandra

2009-01-01

Forest and rural fires are one of the main causes of environmental degradation in Mediterranean countries. Existing fire detection systems only focus on detection, but not on the verification of the fire. However, almost all of them are just simulations, and very few implementations can be found. Besides, the systems in the literature lack scalability. In this paper we show all the steps followed to perform the design, research and development of a wireless multisensor network which mixes sensors with IP cameras in a wireless network in order to detect and verify fire in rural and forest areas of Spain. We have studied how many cameras, sensors and access points are needed to cover a rural or forest area, and the scalability of the system. We have developed a multisensor and when it detects a fire, it sends a sensor alarm through the wireless network to a central server. The central server selects the closest wireless cameras to the multisensor, based on a software application, which are rotated to the sensor that raised the alarm, and sends them a message in order to receive real-time images from the zone. The camera lets the fire fighters corroborate the existence of a fire and avoid false alarms. In this paper, we show the test performance given by a test bench formed by four wireless IP cameras in several situations and the energy consumed when they are transmitting. Moreover, we study the energy consumed by each device when the system is set up. The wireless sensor network could be connected to Internet through a gateway and the images of the cameras could be seen from any part of the world.

A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification

PubMed Central

Lloret, Jaime; Garcia, Miguel; Bri, Diana; Sendra, Sandra

2009-01-01

Forest and rural fires are one of the main causes of environmental degradation in Mediterranean countries. Existing fire detection systems only focus on detection, but not on the verification of the fire. However, almost all of them are just simulations, and very few implementations can be found. Besides, the systems in the literature lack scalability. In this paper we show all the steps followed to perform the design, research and development of a wireless multisensor network which mixes sensors with IP cameras in a wireless network in order to detect and verify fire in rural and forest areas of Spain. We have studied how many cameras, sensors and access points are needed to cover a rural or forest area, and the scalability of the system. We have developed a multisensor and when it detects a fire, it sends a sensor alarm through the wireless network to a central server. The central server selects the closest wireless cameras to the multisensor, based on a software application, which are rotated to the sensor that raised the alarm, and sends them a message in order to receive real-time images from the zone. The camera lets the fire fighters corroborate the existence of a fire and avoid false alarms. In this paper, we show the test performance given by a test bench formed by four wireless IP cameras in several situations and the energy consumed when they are transmitting. Moreover, we study the energy consumed by each device when the system is set up. The wireless sensor network could be connected to Internet through a gateway and the images of the cameras could be seen from any part of the world. PMID:22291533

An approach of surface coal fire detection from ASTER and Landsat-8 thermal data: Jharia coal field, India

NASA Astrophysics Data System (ADS)

Roy, Priyom; Guha, Arindam; Kumar, K. Vinod

2015-07-01

Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9 × 9 pixels for ASTER and 27 × 27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold.

Fire Safety's My Job. Eighth Grade. Fire Safety for Texans: Fire and Burn Prevention Curriculum Guide.

ERIC Educational Resources Information Center

Texas State Commission on Fire Protection, Austin.

This booklet comprises the eighth grade component of a series of curriculum guides on fire and burn prevention. Designed to meet the age-specific needs of eighth grade students, its objectives include: (1) focusing on technical aspects of fire hazards and detection, and (2) exploring fire hazards outside the home. Texas essential elements of…

Space station internal environmental and safety concerns

NASA Technical Reports Server (NTRS)

Cole, Matthew B.

1987-01-01

Space station environmental and safety concerns, especially those involving fires, are discussed. Several types of space station modules and the particular hazards associated with each are briefly surveyed. A brief history of fire detection and suppression aboard spacecraft is given. Microgravity fire behavior, spacecraft fire detector systems, space station fire suppression equipment and procedures, and fire safety in hyperbaric chambers are discussed.

Applying genetic algorithms to set the optimal combination of forest fire related variables and model forest fire susceptibility based on data mining models. The case of Dayu County, China.

PubMed

Hong, Haoyuan; Tsangaratos, Paraskevas; Ilia, Ioanna; Liu, Junzhi; Zhu, A-Xing; Xu, Chong

2018-07-15

The main objective of the present study was to utilize Genetic Algorithms (GA) in order to obtain the optimal combination of forest fire related variables and apply data mining methods for constructing a forest fire susceptibility map. In the proposed approach, a Random Forest (RF) and a Support Vector Machine (SVM) was used to produce a forest fire susceptibility map for the Dayu County which is located in southwest of Jiangxi Province, China. For this purpose, historic forest fires and thirteen forest fire related variables were analyzed, namely: elevation, slope angle, aspect, curvature, land use, soil cover, heat load index, normalized difference vegetation index, mean annual temperature, mean annual wind speed, mean annual rainfall, distance to river network and distance to road network. The Natural Break and the Certainty Factor method were used to classify and weight the thirteen variables, while a multicollinearity analysis was performed to determine the correlation among the variables and decide about their usability. The optimal set of variables, determined by the GA limited the number of variables into eight excluding from the analysis, aspect, land use, heat load index, distance to river network and mean annual rainfall. The performance of the forest fire models was evaluated by using the area under the Receiver Operating Characteristic curve (ROC-AUC) based on the validation dataset. Overall, the RF models gave higher AUC values. Also the results showed that the proposed optimized models outperform the original models. Specifically, the optimized RF model gave the best results (0.8495), followed by the original RF (0.8169), while the optimized SVM gave lower values (0.7456) than the RF, however higher than the original SVM (0.7148) model. The study highlights the significance of feature selection techniques in forest fire susceptibility, whereas data mining methods could be considered as a valid approach for forest fire susceptibility modeling. Copyright © 2018 Elsevier B.V. All rights reserved.

Risks and issues in fire safety on the Space Station

NASA Technical Reports Server (NTRS)

Friedman, Robert

1993-01-01

A fire in the inhabited portion of a spacecraft is a greatly feared hazard, but fire protection in space operations is complicated by two factors. First, the spacecraft cabin is an enclosed volume, which limits the resources for fire fighting and the options for crew escape. Second, an orbiting spacecraft experiences a balance of forces, creating a near-zero-gravity (microgravity) environment that profoundly affects the characteristics of fire initiation, spread, and suppression. The current Shuttle Orbiter is protected by a fire-detection and suppression system whose requirements are derived of necessity from accepted terrestrial and aircraft standards. While experience has shown that Shuttle fire safety is adequate, designers recognize that improved systems to respond specifically to microgravity fire characteristics are highly desirable. Innovative technology is particularly advisable for the Space Station, a forthcoming space community with a complex configuration and long-duration orbital missions, in which the effectiveness of current fire-protection systems is unpredictable. The development of risk assessments to evaluate the probabilities and consequences of fire incidents in spacecraft are briefly reviewed. It further discusses the important unresolved issues and needs for improved fire safety in the Space Station, including those of material selection, spacecraft atmospheres, fire detection, fire suppression, and post-fire restoration.

46 CFR 78.45-1 - When required.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the following plans: (1) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 78.45-1 - When required.

Code of Federal Regulations, 2010 CFR

2010-10-01

... the following plans: (1) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 78.45-1 - When required.

Code of Federal Regulations, 2011 CFR

2011-10-01

... the following plans: (1) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 78.45-1 - When required.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the following plans: (1) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 78.45-1 - When required.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the following plans: (1) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

Asynchronous Processing of a Constellation of Geostationary and Polar-Orbiting Satellites for Fire Detection and Smoke Estimation

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Peterson, D. A.; Curtis, C. A.; Schmidt, C. C.; Hoffman, J.; Prins, E. M.

2014-12-01

The Fire Locating and Monitoring of Burning Emissions (FLAMBE) system converts satellite observations of thermally anomalous pixels into spatially and temporally continuous estimates of smoke release from open biomass burning. This system currently processes data from a constellation of 5 geostationary and 2 polar-orbiting sensors. Additional sensors, including NPP VIIRS and the imager on the Korea COMS-1 geostationary satellite, will soon be added. This constellation experiences schedule changes and outages of various durations, making the set of available scenes for fire detection highly variable on an hourly and daily basis. Adding to the complexity, the latency of the satellite data is variable between and within sensors. FLAMBE shares with many fire detection systems the goal of detecting as many fires as possible as early as possible, but the FLAMBE system must also produce a consistent estimate of smoke production with minimal artifacts from the changing constellation. To achieve this, NRL has developed a system of asynchronous processing and cross-calibration that permits satellite data to be used as it arrives, while preserving the consistency of the smoke emission estimates. This talk describes the asynchronous data ingest methodology, including latency statistics for the constellation. We also provide an overview and show results from the system we have developed to normalize multi-sensor fire detection for consistency.

Configuration of electro-optic fire source detection system

NASA Astrophysics Data System (ADS)

Fabian, Ram Z.; Steiner, Zeev; Hofman, Nir

2007-04-01

The recent fighting activities in various parts of the world have highlighted the need for accurate fire source detection on one hand and fast "sensor to shooter cycle" capabilities on the other. Both needs can be met by the SPOTLITE system which dramatically enhances the capability to rapidly engage hostile fire source with a minimum of casualties to friendly force and to innocent bystanders. Modular system design enable to meet each customer specific requirements and enable excellent future growth and upgrade potential. The design and built of a fire source detection system is governed by sets of requirements issued by the operators. This can be translated into the following design criteria: I) Long range, fast and accurate fire source detection capability. II) Different threat detection and classification capability. III) Threat investigation capability. IV) Fire source data distribution capability (Location, direction, video image, voice). V) Men portability. ) In order to meet these design criteria, an optimized concept was presented and exercised for the SPOTLITE system. Three major modular components were defined: I) Electro Optical Unit -Including FLIR camera, CCD camera, Laser Range Finder and Marker II) Electronic Unit -including system computer and electronic. III) Controller Station Unit - Including the HMI of the system. This article discusses the system's components definition and optimization processes, and also show how SPOTLITE designers successfully managed to introduce excellent solutions for other system parameters.

46 CFR 28.325 - Fire detection systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... space must be equipped with an independent modular smoke detector or a smoke actuated fire detecting... detector must meet UL 217 and be listed as a “Single Station Smoke Detector—Also suitable for use in...

46 CFR 28.325 - Fire detection systems.

Code of Federal Regulations, 2013 CFR

2013-10-01

... space must be equipped with an independent modular smoke detector or a smoke actuated fire detecting... detector must meet UL 217 and be listed as a “Single Station Smoke Detector—Also suitable for use in...

46 CFR 28.325 - Fire detection systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... space must be equipped with an independent modular smoke detector or a smoke actuated fire detecting... detector must meet UL 217 and be listed as a “Single Station Smoke Detector—Also suitable for use in...

46 CFR 28.325 - Fire detection systems.

Code of Federal Regulations, 2014 CFR

2014-10-01

... space must be equipped with an independent modular smoke detector or a smoke actuated fire detecting... detector must meet UL 217 and be listed as a “Single Station Smoke Detector—Also suitable for use in...

46 CFR 28.325 - Fire detection systems.

Code of Federal Regulations, 2012 CFR

2012-10-01

... space must be equipped with an independent modular smoke detector or a smoke actuated fire detecting... detector must meet UL 217 and be listed as a “Single Station Smoke Detector—Also suitable for use in...

Estimation of carbon emissions from wildfires in Alaskan boreal forests using AVHRR data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kasischke, E.S.; French, N.H.F.; Bourgeau-Chavez, L.L

1993-06-01

The objectives of this research study were to evaluate the utility of using AVHRR data for locating and measuring the areal extent of wildfires in the boreal forests of Alaska and to estimate the amount of carbon being released during these fires. Techniques were developed to using the normalized difference vegetation signature derived from AVHRR data to detect and measure the area of fires in Alaska. A model was developed to estimate the amount of biomass/carbon being stored in Alaskan boreal forests, and the amount of carbon released during fires. The AVHRR analysis resulted in detection of > 83% ofmore » all forest fires greater than 2,000 ha in size in the years 1990 and 1991. The areal estimate derived from AVHRR data were 75% of the area mapped by the Alaska Fire Service for these years. Using fire areas and locations for 1954 through 1992, it was determined that on average, 13.0 gm-C-m-2 of boreal forest area is released during fires every year. This estimate is two to six times greater than previous reported estimates. Our conclusions are that the analysis of AVHRR data represents a viable means for detecting and mapping fires in boreal regions on a global basis.« less

Intelligent Extruder

DOE Office of Scientific and Technical Information (OSTI.GOV)

AlperEker; Mark Giammattia; Paul Houpt

''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. Themore » project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.« less

46 CFR 97.36-1 - When required.

Code of Federal Regulations, 2012 CFR

2012-10-01

... the vessel the following plans: (a) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 97.36-1 - When required.

Code of Federal Regulations, 2013 CFR

2013-10-01

... the vessel the following plans: (a) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

46 CFR 97.36-1 - When required.

Code of Federal Regulations, 2014 CFR

2014-10-01

... the vessel the following plans: (a) General arrangement plans showing for each deck the fire control stations, the various sections enclosed by fire-resisting bulkheads, together with particulars of the fire alarms, detecting systems, the sprinkler installation (if any), the fire extinguishing appliances, means...

Fire Won't Wait--Plan Your Escape!

ERIC Educational Resources Information Center

PTA Today, 1991

1991-01-01

Discusses the importance of home fire escape drills, detailing fire safety plans. Early detection and warning (smoke detectors) coupled with well-rehearsed escape plans help prevent serious injury. Children need to be taught about fire safety beginning at a very early age. (SM)

Know how to maximize maintenance spending

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carrino, A.J.; Jones, R.B.; Platt, W.E.

Solomon has developed a methodology to determine a large optimum point where availability meets maintenance spending for Powder River Basin (PRB) coal-fired units. Using a database of sufficient size and composition across various operating ranges, Solomon generated an algorithm that predicts the relationship between maintenance spending and availability. Coupling this generalized algorithm with a unit-specific market-loss curve determines the optimum spending for a facility. The article presents the results of the analysis, how this methodology can be applied to develop optimum operating and financial targets for specific units and markets and a process to achieve those targets. It also describesmore » how this methodology can be used for other types of fossil-fired technologies and future enhancements to the analysis. 5 figs.« less

Fire Detections and Fire Radiative Power Intercomparison Using Multiple Sensor Products over a Predominantly Gas Flaring Region

NASA Astrophysics Data System (ADS)

Sharma, A.; Wang, J.

2014-12-01

Gas flaring is a global environmental hazard severely impacting climate, economy and public health. The associated emissions are frequently unreported and have large uncertainties. Prior studies have established a direct relationship between radiative energy released from fires and the biomass burned, making fire radiative power (FRP), i.e., the rate of radiative energy release, an important proxy to characterize emissions. In this study fire properties from four different satellite products were obtained over a 10⁰ x 10⁰ gas flaring region in Russia for all days of May 2013. The target area is part of Russia's biggest gas flaring region, Khanty-Mansiysk autonomous okrug. The objective of the study is to investigate the consistency of fire detections, FRP retrievals and effects of gridding FRP data from the region on a uniform grid. The four products used were: MODIS Terra level2 thermal anomalies (MOD14), MODIS Aqua level2 thermal anomalies (MYD14), VIIRS Active fire product and a recent NOAA Nightfire product. 1 km nominal resolution FRP from MOD14 AND MYD14, subpixel radiant heat (RH) from NOAA Nightfire product and fire detections from all four products were recorded on a 0.25⁰ x 0.25⁰ grid on a daily basis. Results revealed the Nightfire product had maximum detections, almost six times the number of detections by other products, mainly because of the use of M10 (1.6 µm) band as their primary detection band. The M10 band is highly efficient in identifying radiant emissions from hot sources during night-time. The correlation (after omitting outliers) between gridded NOAA Nightfire RH and corresponding MOD14 FRP and MYD14 FRP gave a moderate regression value, with MODIS FRP being mostly higher than RH. As an extension to this work, a comprehensive study for a larger temporal domain also incorporating viewing geometries and cloud cover would advance our understanding of flare detections and associated FRP retrievals not just for the target region but also gas flaring regions globally.

Monitoring system of multiple fire fighting based on computer vision

NASA Astrophysics Data System (ADS)

Li, Jinlong; Wang, Li; Gao, Xiaorong; Wang, Zeyong; Zhao, Quanke

2010-10-01

With the high demand of fire control in spacious buildings, computer vision is playing a more and more important role. This paper presents a new monitoring system of multiple fire fighting based on computer vision and color detection. This system can adjust to the fire position and then extinguish the fire by itself. In this paper, the system structure, working principle, fire orientation, hydrant's angle adjusting and system calibration are described in detail; also the design of relevant hardware and software is introduced. At the same time, the principle and process of color detection and image processing are given as well. The system runs well in the test, and it has high reliability, low cost, and easy nodeexpanding, which has a bright prospect of application and popularization.

Optical Flow Estimation for Flame Detection in Videos

PubMed Central

Mueller, Martin; Karasev, Peter; Kolesov, Ivan; Tannenbaum, Allen

2014-01-01

Computational vision-based flame detection has drawn significant attention in the past decade with camera surveillance systems becoming ubiquitous. Whereas many discriminating features, such as color, shape, texture, etc., have been employed in the literature, this paper proposes a set of motion features based on motion estimators. The key idea consists of exploiting the difference between the turbulent, fast, fire motion, and the structured, rigid motion of other objects. Since classical optical flow methods do not model the characteristics of fire motion (e.g., non-smoothness of motion, non-constancy of intensity), two optical flow methods are specifically designed for the fire detection task: optimal mass transport models fire with dynamic texture, while a data-driven optical flow scheme models saturated flames. Then, characteristic features related to the flow magnitudes and directions are computed from the flow fields to discriminate between fire and non-fire motion. The proposed features are tested on a large video database to demonstrate their practical usefulness. Moreover, a novel evaluation method is proposed by fire simulations that allow for a controlled environment to analyze parameter influences, such as flame saturation, spatial resolution, frame rate, and random noise. PMID:23613042

Analysis of toxic effluents released from PVC carpet under different fire conditions.

PubMed

Stec, A A; Readman, J; Blomqvist, P; Gylestam, D; Karlsson, D; Wojtalewicz, D; Dlugogorski, B Z

2013-01-01

A large number of investigations have been reported on minimising the PAH and PCDD/F yields during controlled combustion, such as incineration. This study is an attempt to quantify acute and chronic toxicants including PAH and PCDD/F in conditions relating to unwanted fires. This paper investigates distribution patterns of fire effluents between gas and aerosol phase, and the different particle size-ranges produced under different fire conditions. PVC carpet was selected as the fuel as a precursor for both PAH and PCDD/F. In order to generate fire effluents under controlled fire conditions, the steady-state tube furnace, was chosen as the physical fire model. Fire scenarios included oxidative pyrolysis, well-ventilated and under-ventilated fires. Fire effluent measurements included: carbon monoxide, carbon dioxide, hydrogen chloride, polycyclic aromatic hydrocarbons, chlorinated dibenzo-dioxins and furans and soot. The distribution patterns between gas and particle phase, and the size-ranges of the particles produced in these fires together with their chemical composition is also reported. Significant quantities of respirable submicron particles were detected, together with a range of PAHs. Lower levels of halogenated dioxins were detected in the fire residue compared with those found in other studies. Nevertheless, the findings do have implications for the health and safety of fire and rescue personnel, fire investigators, and other individuals exposed to the residue from unwanted fires. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-channel, passive, short-range anti-aircraft defence system

NASA Astrophysics Data System (ADS)

Gapiński, Daniel; Krzysztofik, Izabela; Koruba, Zbigniew

2018-01-01

The paper presents a novel method for tracking several air targets simultaneously. The developed concept concerns a multi-channel, passive, short-range anti-aircraft defence system based on the programmed selection of air targets and an algorithm of simultaneous synchronisation of several modified optical scanning seekers. The above system is supposed to facilitate simultaneous firing of several self-guided infrared rocket missiles at many different air targets. From the available information, it appears that, currently, there are no passive self-guided seekers that fulfil such tasks. This paper contains theoretical discussions and simulations of simultaneous detection and tracking of many air targets by mutually integrated seekers of several rocket missiles. The results of computer simulation research have been presented in a graphical form.

The use of network theory to model disparate ship design information

NASA Astrophysics Data System (ADS)

Rigterink, Douglas; Piks, Rebecca; Singer, David J.

2014-06-01

This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

ParamAP: Standardized Parameterization of Sinoatrial Node Myocyte Action Potentials.

PubMed

Rickert, Christian; Proenza, Catherine

2017-08-22

Sinoatrial node myocytes act as cardiac pacemaker cells by generating spontaneous action potentials (APs). Much information is encoded in sinoatrial AP waveforms, but both the analysis and the comparison of AP parameters between studies is hindered by the lack of standardized parameter definitions and the absence of automated analysis tools. Here we introduce ParamAP, a standalone cross-platform computational tool that uses a template-free detection algorithm to automatically identify and parameterize APs from text input files. ParamAP employs a graphic user interface with automatic and user-customizable input modes, and it outputs data files in text and PDF formats. ParamAP returns a total of 16 AP waveform parameters including time intervals such as the AP duration, membrane potentials such as the maximum diastolic potential, and rates of change of the membrane potential such as the diastolic depolarization rate. ParamAP provides a robust AP detection algorithm in combination with a standardized AP parameter analysis over a wide range of AP waveforms and firing rates, owing in part to the use of an iterative algorithm for the determination of the threshold potential and the diastolic depolarization rate that is independent of the maximum upstroke velocity, a parameter that can vary significantly among sinoatrial APs. Because ParamAP is implemented in Python 3, it is also highly customizable and extensible. In conclusion, ParamAP is a powerful computational tool that facilitates quantitative analysis and enables comparison of sinoatrial APs by standardizing parameter definitions and providing an automated work flow. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Detection, mapping and estimation of rate of spread of grass fires from southern African ERTS-1 imagery

NASA Technical Reports Server (NTRS)

Wightman, J. M.

1973-01-01

Sequential band-6 imagery of the Zambesi Basin of southern Africa recorded substantial changes in burn patterns resulting from late dry season grass fires. One example from northern Botswana, indicates that a fire consumed approximately 70 square miles of grassland over a 24-hour period. Another example from western Zambia indicates increased fire activity over a 19-day period. Other examples clearly define the area of widespread grass fires in Angola, Botswana, Rhodesia and Zambia. From the fire patterns visible on the sequential portions of the imagery, and the time intervals involved, the rates of spread of the fires are estimated and compared with estimates derived from experimental burning plots in Zambia and Canada. It is concluded that sequential ERTS-1 imagery, of the quality studied, clearly provides the information needed to detect and map grass fires and to monitor their rates of spread in this region during the late dry season.

Detecting post-fire salvage logging with Landsat change maps and national fire survey data

Treesearch

Todd A. Schroeder; Michael A. Wulder; Sean P. Healey; Gretchen G. Moisen

2012-01-01

In Canadian boreal forests, wildfire is the predominant agent of natural disturbance often with millions of hectares burning annually. In addition to fire, nearly one quarter of Canada's boreal forest is also managed for industrial wood production. Post-fire logging (or salvage harvesting) is increasingly used to minimize economic losses from fire, notwithstanding...

46 CFR 161.002-12 - Manual fire alarm systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

.... (a) General. A manual fire alarm system shall consist of a power supply, a control unit on which are... using manually operated fire alarm boxes. (3) Other types as may be developed. (c) Power supply. The power supply shall be as specified for automatic fire detecting system by § 161.002-9. (d) Manual fire...

46 CFR 161.002-12 - Manual fire alarm systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

.... (a) General. A manual fire alarm system shall consist of a power supply, a control unit on which are... using manually operated fire alarm boxes. (3) Other types as may be developed. (c) Power supply. The power supply shall be as specified for automatic fire detecting system by § 161.002-9. (d) Manual fire...

Management and climate contributions to satellite-derived active fire trends in the contiguous United States

PubMed Central

Lin, Hsiao-Wen; McCarty, Jessica L; Wang, Dongdong; Rogers, Brendan M; Morton, Douglas C; Collatz, G James; Jin, Yufang; Randerson, James T

2014-01-01

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001–2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001–2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems. Key Points Wildland, cropland, and prescribed fires had different trends and patterns Sensitivity to climate varied with fire type Intensity of air quality regulation influenced cropland burning trends PMID:26213662

Management and climate contributions to satellite-derived active fire trends in the contiguous United States.

PubMed

Lin, Hsiao-Wen; McCarty, Jessica L; Wang, Dongdong; Rogers, Brendan M; Morton, Douglas C; Collatz, G James; Jin, Yufang; Randerson, James T

2014-04-01

Fires in croplands, plantations, and rangelands contribute significantly to fire emissions in the United States, yet are often overshadowed by wildland fires in efforts to develop inventories or estimate responses to climate change. Here we quantified decadal trends, interannual variability, and seasonality of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations of active fires (thermal anomalies) as a function of management type in the contiguous U.S. during 2001-2010. We used the Monitoring Trends in Burn Severity database to identify active fires within the perimeter of large wildland fires and land cover maps to identify active fires in croplands. A third class of fires defined as prescribed/other included all residual satellite active fire detections. Large wildland fires were the most variable of all three fire types and had no significant annual trend in the contiguous U.S. during 2001-2010. Active fires in croplands, in contrast, increased at a rate of 3.4% per year. Cropland and prescribed/other fire types combined were responsible for 77% of the total active fire detections within the U.S and were most abundant in the south and southeast. In the west, cropland active fires decreased at a rate of 5.9% per year, likely in response to intensive air quality policies. Potential evaporation was a dominant regulator of the interannual variability of large wildland fires, but had a weaker influence on the other two fire types. Our analysis suggests it may be possible to modify landscape fire emissions within the U.S. by influencing the way fires are used in managed ecosystems. Wildland, cropland, and prescribed fires had different trends and patternsSensitivity to climate varied with fire typeIntensity of air quality regulation influenced cropland burning trends.

Volcano early warning system based on MSG-SEVIRI multispectral data

NASA Astrophysics Data System (ADS)

Ganci, Gaetana; Vicari, Annamaria; Del Negro, Ciro

2010-05-01

Spaceborne remote sensing of high-temperature volcanic features offers an excellent opportunity to monitor the onset and development of new eruptive activity. Particularly, images with lower spatial but higher temporal resolution from meteorological satellites have been proved to be a sound instrument for continuous monitoring of volcanic activity, even though the relevant volcanic characteristics are much smaller than the nominal pixel size. The launch of Spinning Enhanced Visible and Infrared Imager (SEVIRI), on August 2002, onboard the geosynchronous platforms MSG1 and MSG2, has opened a new perspective for near real-time volcano monitoring by providing images at 15 minutes interval. Indeed, in spite of the low spatial resolution (3 km2 at nadir), the high frequency of observations afforded by the MSG SEVIRI was recently applied both for forest fire detection and for the monitoring of effusive volcanoes in Europe and Africa. Our Laboratory of Technologies (TecnoLab) at INGV-CT has been developing methods and know-how for the automated acquisition and management of MSG SEVIRI data. To provide a basis for real-time response during eruptive events, we designed and developed the automated system called HOTSAT. Our algorithm takes advantages from both spectral and spatial comparisons. Firstly, we use an adaptive thresholding procedure based on the computation of the spatial standard deviation derived from the immediately neighboring of each pixel to detect "potential" hot pixels. Secondly, it is required to further assess as true or false hotspot detections base on other thresholds test derived from the SEVIRI middle infrared (MIR, 3.9 μm) brightness temperatures taking into account its statistic behavior. Following these procedures, all the computations are based on dynamic thresholds reducing the number of false alarm due to atmospheric conditions. Our algorithm allows also the derivation of radiative power at all "hot" pixels. This is carried out using the MIR radiance method introduced by Wooster et al. [2003] for forest fires. It's based on an approximation of the Plank's Law as a power law. No assumption is made on the thermal structure of the pixel. The radiant flux, i.e. the fire radiative power, is proportional to the calibrated radiance associated to the hot part of the pixel computed as the difference between the observed hotspot pixel radiance in the SEVIRI MIR channel and the background radiance that would have been observed at the same location in the absence of thermal anomalies. The HOTSAT early warning system based on SEVIRI multispectral data is now suitable to be employed in an operational system of volcano monitoring. To validate and test the system some real cases on Mt Etna are presented.

Automated Burned Area Delineation Using IRS AWiFS satellite data

NASA Astrophysics Data System (ADS)

Singhal, J.; Kiranchand, T. R.; Rajashekar, G.; Jha, C. S.

2014-12-01

India is endowed with a rich forest cover. Over 21% of country's area is covered by forest of varied composition and structure. Out of 67.5 million ha of Indian forests, about 55% of the forest cover is being subjected to fires each year, causing an economic loss of over 440 crores of rupees apart from other ecological effects. Studies carried out by Forest Survey of India reveals that on an average 53% forest cover of the country is prone to fires and 6.17% of the forests are prone to severe fire damage. Forest Survey of India in a countrywide study in 1995 estimated that about 1.45 million hectares of forest are affected by fire annually. According to Forest Protection Division of the Ministry of Environment and Forest (GOI), 3.73 million ha of forests are affected by fire annually in India. Karnataka is one of the southern states of India extending in between latitude 110 30' and 180 25' and longitudes 740 10' and 780 35'. As per Forest Survey of India's State of Forest Report (SFR) 2009, of the total geographic area of 191791sq.km, the state harbors 38284 sq.km of recorded forest area. Major forest types occurring in the study area are tropical evergreen and semi-evergreen, tropical moist and dry deciduous forests along with tropical scrub and dry grasslands. Typical forest fire season in the study area is from February-May with a peak during March-April every year, though sporadic fire episodes occur in other parts of the year sq.km, the state harbors 38284 sq.km of recorded forest area. Major forest types occurring in the study area are tropical evergreen and semi-evergreen, tropical moist and dry deciduous forests along with tropical scrub and dry grasslands. Significant area of the deciduous forests, scrub and grasslands is prone to recurrent forest fires every year. In this study we evaluate the feasibility of burned area mapping over a large area (Karnataka state, India) using a semi-automated detection algorithm applied to medium resolution multi spectral data from the IRS AWiFS sensor. The method is intended to be used by non-specialist users for diagnostic rapid burnt area mapping.

Development of a multiple gas analyzer using cavity ringdown spectroscopy for use in advanced fire detection.

PubMed

Fallows, Eric A; Cleary, Thomas G; Miller, J Houston

2009-02-01

A portable cavity ringdown spectroscopy (CRDS) apparatus was used to detect effluents from small test fires in the Fire Emulator/Detector Evaluator (FE/DE) and a small room in the Building Fire and Research Laboratory at the National Institute of Standards and Technology (NIST). The output from two lasers is combined to detect four combustion gases, CO, CO(2), HCN, and C(2)H(2), near simultaneously using CRDS. The goal of this work was to demonstrate the feasibility of using a CRDS sensor as a fire detector. Fire effluents were extracted from several test facilities and measurements of CO, CO(2), HCN, and C(2)H(2) were obtained every 25-30 s. In the FE/DE test, peak concentrations of the gases from smoldering paper were 420 parts in 10(6) (ppm) CO, 1600 ppm CO(2), 530 parts in 10(9) (ppb) HCN, and 440 ppb C(2)H(2). Peak gas concentrations from the small room were 270 ppm CO, 2100 ppm CO(2), and 310 ppb C(2)H(2).

Avian community responses to post-fire forest structure: Implications for fire management in mixed conifer forests

USGS Publications Warehouse

White, Angela M.; Manley, Patricia N.; Tarbill, Gina; Richardson, T.L.; Russell, Robin E.; Safford, Hugh D.; Dobrowski, Solomon Z.

2015-01-01

Fire is a natural process and the dominant disturbance shaping plant and animal communities in many coniferous forests of the western US. Given that fire size and severity are predicted to increase in the future, it has become increasingly important to understand how wildlife responds to fire and post-fire management. The Angora Fire burned 1243 hectares of mixed conifer forest in South Lake Tahoe, California. We conducted avian point counts for the first 3 years following the fire in burned and unburned areas to investigate which habitat characteristics are most important for re-establishing or maintaining the native avian community in post-fire landscapes. We used a multi-species occurrence model to estimate how avian species are influenced by the density of live and dead trees and shrub cover. While accounting for variations in the detectability of species, our approach estimated the occurrence probabilities of all species detected including those that were rare or observed infrequently. Although all species encountered in this study were detected in burned areas, species-specific modeling results predicted that some species were strongly associated with specific post-fire conditions, such as a high density of dead trees, open-canopy conditions or high levels of shrub cover that occur at particular burn severities or at a particular time following fire. These results indicate that prescribed fire or managed wildfire which burns at low to moderate severity without at least some high-severity effects is both unlikely to result in the species assemblages that are unique to post-fire areas or to provide habitat for burn specialists. Additionally, the probability of occurrence for many species was associated with high levels of standing dead trees indicating that intensive post-fire harvest of these structures could negatively impact habitat of a considerable proportion of the avian community.

Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: the Australian case

NASA Astrophysics Data System (ADS)

Williamson, Grant J.; Prior, Lynda D.; Jolly, W. Matt; Cochrane, Mark A.; Murphy, Brett P.; Bowman, David M. J. S.

2016-03-01

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-derived active fire detections to determine day and night time fire activity, fire season start and end dates, and inter-annual variability, across 61 objectively defined climate regions in three climate zones (monsoon tropics, arid and temperate). We show that geographic patterns of landscape burning (onset and duration) are related to fire weather, resulting in a latitudinal gradient from the monsoon tropics in winter, through the arid zone in all seasons except winter, and then to the temperate zone in summer and autumn. Peak fire activity precedes maximum lightning activity by several months in all regions, signalling the importance of human ignitions in shaping fire seasons. We determined median daily McArthur forest fire danger index (FFDI50) for days and nights when fires were detected: FFDI50 varied substantially between climate zones, reflecting effects of fire management in the temperate zone, fuel limitation in the arid zone and abundance of flammable grasses in the monsoon tropical zone. We found correlations between the proportion of days when FFDI exceeds FFDI50 and the Southern Oscillation index across the arid zone during spring and summer, and Indian Ocean dipole mode index across south-eastern Australia during summer. Our study demonstrates that Australia has a long fire weather season with high inter-annual variability relative to all other continents, making it difficult to detect long term trends. It also provides a way of establishing robust baselines to track changes to fire seasons, and supports a previous conceptual model highlighting multi-temporal scale effects of climate in shaping continental-scale pyrogeography.

Live tree carbon stock equivalence of fire and fuels extension to the Forest Vegetation Simulator and Forest Inventory and Analysis approaches

Treesearch

James E. Smith; Coeli M. Hoover

2017-01-01

The carbon reports in the Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) provide two alternate approaches to carbon estimates for live trees (Rebain 2010). These are (1) the FFE biomass algorithms, which are volumebased biomass equations, and (2) the Jenkins allometric equations (Jenkins and others 2003), which are diameter based. Here, we...

Efficient and accurate time-stepping schemes for integrate-and-fire neuronal networks.

PubMed

Shelley, M J; Tao, L

2001-01-01

To avoid the numerical errors associated with resetting the potential following a spike in simulations of integrate-and-fire neuronal networks, Hansel et al. and Shelley independently developed a modified time-stepping method. Their particular scheme consists of second-order Runge-Kutta time-stepping, a linear interpolant to find spike times, and a recalibration of postspike potential using the spike times. Here we show analytically that such a scheme is second order, discuss the conditions under which efficient, higher-order algorithms can be constructed to treat resets, and develop a modified fourth-order scheme. To support our analysis, we simulate a system of integrate-and-fire conductance-based point neurons with all-to-all coupling. For six-digit accuracy, our modified Runge-Kutta fourth-order scheme needs a time-step of Delta(t) = 0.5 x 10(-3) seconds, whereas to achieve comparable accuracy using a recalibrated second-order or a first-order algorithm requires time-steps of 10(-5) seconds or 10(-9) seconds, respectively. Furthermore, since the cortico-cortical conductances in standard integrate-and-fire neuronal networks do not depend on the value of the membrane potential, we can attain fourth-order accuracy with computational costs normally associated with second-order schemes.

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation. PMID:26958441

An Improved Algorithm of Congruent Matching Cells (CMC) Method for Firearm Evidence Identifications.

PubMed

Tong, Mingsi; Song, John; Chu, Wei

2015-01-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for firearm evidence identifications. The CMC method divides the measured image of a surface area, such as a breech face impression from a fired cartridge case, into small correlation cells and uses four identification parameters to identify correlated cell pairs originating from the same firearm. The CMC method was validated by identification tests using both 3D topography images and optical images captured from breech face impressions of 40 cartridge cases fired from a pistol with 10 consecutively manufactured slides. In this paper, we discuss the processing of the cell correlations and propose an improved algorithm of the CMC method which takes advantage of the cell correlations at a common initial phase angle and combines the forward and backward correlations to improve the identification capability. The improved algorithm is tested by 780 pairwise correlations using the same optical images and 3D topography images as the initial validation.

Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data.

PubMed

Florescu, Dorian; Coca, Daniel

2018-03-01

Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms.

Towards Data-Driven Simulations of Wildfire Spread using Ensemble-based Data Assimilation

NASA Astrophysics Data System (ADS)

Rochoux, M. C.; Bart, J.; Ricci, S. M.; Cuenot, B.; Trouvé, A.; Duchaine, F.; Morel, T.

2012-12-01

Real-time predictions of a propagating wildfire remain a challenging task because the problem involves both multi-physics and multi-scales. The propagation speed of wildfires, also called the rate of spread (ROS), is indeed determined by complex interactions between pyrolysis, combustion and flow dynamics, atmospheric dynamics occurring at vegetation, topographical and meteorological scales. Current operational fire spread models are mainly based on a semi-empirical parameterization of the ROS in terms of vegetation, topographical and meteorological properties. For the fire spread simulation to be predictive and compatible with operational applications, the uncertainty on the ROS model should be reduced. As recent progress made in remote sensing technology provides new ways to monitor the fire front position, a promising approach to overcome the difficulties found in wildfire spread simulations is to integrate fire modeling and fire sensing technologies using data assimilation (DA). For this purpose we have developed a prototype data-driven wildfire spread simulator in order to provide optimal estimates of poorly known model parameters [*]. The data-driven simulation capability is adapted for more realistic wildfire spread : it considers a regional-scale fire spread model that is informed by observations of the fire front location. An Ensemble Kalman Filter algorithm (EnKF) based on a parallel computing platform (OpenPALM) was implemented in order to perform a multi-parameter sequential estimation where wind magnitude and direction are in addition to vegetation properties (see attached figure). The EnKF algorithm shows its good ability to track a small-scale grassland fire experiment and ensures a good accounting for the sensitivity of the simulation outcomes to the control parameters. As a conclusion, it was shown that data assimilation is a promising approach to more accurately forecast time-varying wildfire spread conditions as new airborne-like observations of the fire front location get available. [*] Rochoux, M.C., Delmotte, B., Cuenot, B., Ricci, S., and Trouvé, A. (2012) "Regional-scale simulations of wildland fire spread informed by real-time flame front observations", Proc. Combust. Inst., 34, in press http://dx.doi.org/10.1016/j.proci.2012.06.090 EnKF-based tracking of small-scale grassland fire experiment, with estimation of wind and fuel parameters.

Fire Safety in Extraterrestrial Environments

NASA Technical Reports Server (NTRS)

Friedman, Robert

1998-01-01

Despite rigorous fire-safety policies and practices, fire incidents are possible during lunar and Martian missions. Fire behavior and hence preventive and responsive safety actions in the missions are strongly influenced by the low-gravity environments in flight and on the planetary surfaces. This paper reviews the understanding and key issues of fire safety in the missions, stressing flame spread, fire detection, suppression, and combustion performance of propellants produced from Martian resources.

Comparison of human and algorithmic target detection in passive infrared imagery

NASA Astrophysics Data System (ADS)

Weber, Bruce A.; Hutchinson, Meredith

2003-09-01

We have designed an experiment that compares the performance of human observers and a scale-insensitive target detection algorithm that uses pixel level information for the detection of ground targets in passive infrared imagery. The test database contains targets near clutter whose detectability ranged from easy to very difficult. Results indicate that human observers detect more "easy-to-detect" targets, and with far fewer false alarms, than the algorithm. For "difficult-to-detect" targets, human and algorithm detection rates are considerably degraded, and algorithm false alarms excessive. Analysis of detections as a function of observer confidence shows that algorithm confidence attribution does not correspond to human attribution, and does not adequately correlate with correct detections. The best target detection score for any human observer was 84%, as compared to 55% for the algorithm for the same false alarm rate. At 81%, the maximum detection score for the algorithm, the same human observer had 6 false alarms per frame as compared to 29 for the algorithm. Detector ROC curves and observer-confidence analysis benchmarks the algorithm and provides insights into algorithm deficiencies and possible paths to improvement.

46 CFR 115.810 - Fire protection.

Code of Federal Regulations, 2011 CFR

2011-10-01

... extinguisher, semiportable fire extinguisher, and fixed gas fire extinguishing system to check for excessive... testing of alarms and ventilation shutdowns, for each fixed gas fire extinguishing system and detecting... gas to ensure it has been tested and marked in accordance with § 147.60 in subchapter N of this...

46 CFR 115.810 - Fire protection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... extinguisher, semiportable fire extinguisher, and fixed gas fire extinguishing system to check for excessive... testing of alarms and ventilation shutdowns, for each fixed gas fire extinguishing system and detecting... gas to ensure it has been tested and marked in accordance with § 147.60 in subchapter N of this...

Infrared Instrument for Detecting Hydrogen Fires

NASA Technical Reports Server (NTRS)

Youngquist, Robert; Ihlefeld, Curtis; Immer, Christopher; Oostdyk, Rebecca; Cox, Robert; Taylor, John

2006-01-01

The figure shows an instrument incorporating an infrared camera for detecting small hydrogen fires. The instrument has been developed as an improved replacement for prior infrared and ultraviolet instruments used to detect hydrogen fires. The need for this or any such instrument arises because hydrogen fires (e.g., those associated with leaks from tanks, valves, and ducts) pose a great danger, yet they emit so little visible light that they are mostly undetectable by the unaided human eye. The main performance advantage offered by the present instrument over prior hydrogen-fire-detecting instruments lies in its greater ability to avoid false alarms by discriminating against reflected infrared light, including that originating in (1) the Sun, (2) welding torches, and (3) deliberately ignited hydrogen flames (e.g., ullage-burn-off flames) that are nearby but outside the field of view intended to be monitored by the instrument. Like prior such instruments, this instrument is based mostly on the principle of detecting infrared emission above a threshold level. However, in addition, this instrument utilizes information on the spatial distribution of infrared light from a source that it detects. Because the combination of spatial and threshold information about a flame tends to constitute a unique signature that differs from that of reflected infrared light originating in a source not in the field of view, the incidence of false alarms is reduced substantially below that of related prior threshold- based instruments.

Analysing Forst Fores in China

NASA Astrophysics Data System (ADS)

Casanova, Jose-Luis; Sanz, Julia; Garcia, Miguel; Salvador, Pablo; Quin, Xianlin; Li, Zengyuan; Yin, Lingyu; Sun, Guifen; Goldammer, Johann

2016-08-01

Forest fires are a major concern in China because of the economical and biodiversity looses and because the emission of trace gases into the atmosphere. During 12 years LATUV has been working in the development of forest fires products, especially in North China. A catalogue of products has been generated like: forest fire detection, burnt area mapping, gas emissions, severity and burnt biomass.Forest fires can be detected by different platforms and sensor but the rate of false alarms is high because of industrial activity. The gas emissions are important, because of the forest fires inside China and because the forest fires between China and Russia that have a considerable impact in the atmosphere composition in China.The availability of new sensors on board sentinel 2 and sentinel 3 platforms will increase the product catalogue with new products more accurate and increasing the periodicity information.

Fire safety applications for spacecraft

NASA Technical Reports Server (NTRS)

Friedman, Robert; Olson, Sandra L.

1989-01-01

Fire safety for spacecraft is reviewed by first describing current practices, many of which are adapted directly from aircraft. Then, current analyses and experimental knowledge in low-gravity combustion, with implications for fire safety are discussed. In orbiting spacecraft, the detection and suppression of flames are strongly affected by the large reduction in buoyant flows under low gravity. Generally, combustion intensity is reduced in low gravity. There are some notable exceptions, however, one example being the strong enhancement of flames by low-velocity ventilation flows in space. Finally, the future requirements in fire safety, particularly the needs of long-duration space stations in fire prevention, detection, extinguishment, and atmospheric control are examined. The goal of spacecraft fire-safety investigations is the establishment of trade-offs that promote maximum safety without hampering the useful human and scientific activities in space.

Techniques for fire detection

NASA Technical Reports Server (NTRS)

Bukowski, Richard W.

1987-01-01

An overview is given of the basis for an analysis of combustable materials and potential ignition sources in a spacecraft. First, the burning process is discussed in terms of the production of the fire signatures normally associated with detection devices. These include convected and radiated thermal energy, particulates, and gases. Second, the transport processes associated with the movement of these from the fire to the detector, along with the important phenomena which cause the level of these signatures to be reduced, are described. Third, the operating characteristics of the individual types of detectors which influence their response to signals, are presented. Finally, vulnerability analysis using predictive fire modeling techniques is discussed as a means to establish the necessary response of the detection system to provide the level of protection required in the application.

Burning in Banksia Woodlands: How Does the Fire-Free Period Influence Reptile Communities?

PubMed Central

Valentine, Leonie E.; Reaveley, Alice; Johnson, Brent; Fisher, Rebecca; Wilson, Barbara A.

2012-01-01

Fire is an important management tool for both hazard reduction burning and maintenance of biodiversity. The impact of time since last fire on fauna is an important factor to understand as land managers often aim for prescribed burning regimes with specific fire-free intervals. However, our current understanding of the impact of time since last fire on fauna is largely unknown and likely dependent on vegetation type. We examined the responses of reptiles to fire age in banksia woodlands, and the interspersed melaleuca damplands among them, north of Perth, Western Australia, where the current prescribed burning regime is targeting a fire-free period of 8–12 years. The response of reptiles to fire was dependent on vegetation type. Reptiles were generally more abundant (e.g. Lerista elegans and Ctenophorus adelaidensis) and specious in banksia sites. Several species (e.g. Menetia greyii, Cryptoblepharus buchananii) preferred long unburnt melaleuca sites (>16 years since last fire, YSLF) compared to recently burnt sites (<12 YSLF). Several of the small elapids (e.g. the WA priority listed species Neelaps calonotus) were only detected in older-aged banksia sites (>16 YSLF). The terrestrial dragon C. adelaidensis and the skink Morethia obscura displayed a strong response to fire in banksia woodlands only. Highest abundances of the dragon were detected in the recently burnt (<7 YSLF) and long unburnt (>35 YSLF) banksia woodlands, while the skink was more abundant in older sites. Habitats from a range of fire ages are required to support the reptiles we detected, especially the longer unburnt (>16 YSLF) melaleuca habitat. Current burning prescriptions are reducing the availability of these older habitats. PMID:22496806

Burning in banksia woodlands: how does the fire-free period influence reptile communities?

PubMed

Valentine, Leonie E; Reaveley, Alice; Johnson, Brent; Fisher, Rebecca; Wilson, Barbara A

2012-01-01

Fire is an important management tool for both hazard reduction burning and maintenance of biodiversity. The impact of time since last fire on fauna is an important factor to understand as land managers often aim for prescribed burning regimes with specific fire-free intervals. However, our current understanding of the impact of time since last fire on fauna is largely unknown and likely dependent on vegetation type. We examined the responses of reptiles to fire age in banksia woodlands, and the interspersed melaleuca damplands among them, north of Perth, Western Australia, where the current prescribed burning regime is targeting a fire-free period of 8-12 years. The response of reptiles to fire was dependent on vegetation type. Reptiles were generally more abundant (e.g. Lerista elegans and Ctenophorus adelaidensis) and specious in banksia sites. Several species (e.g. Menetia greyii, Cryptoblepharus buchananii) preferred long unburnt melaleuca sites (>16 years since last fire, YSLF) compared to recently burnt sites (<12 YSLF). Several of the small elapids (e.g. the WA priority listed species Neelaps calonotus) were only detected in older-aged banksia sites (>16 YSLF). The terrestrial dragon C. adelaidensis and the skink Morethia obscura displayed a strong response to fire in banksia woodlands only. Highest abundances of the dragon were detected in the recently burnt (<7 YSLF) and long unburnt (>35 YSLF) banksia woodlands, while the skink was more abundant in older sites. Habitats from a range of fire ages are required to support the reptiles we detected, especially the longer unburnt (>16 YSLF) melaleuca habitat. Current burning prescriptions are reducing the availability of these older habitats.

Fire history in interior ponderosa pine communities of the Black Hills, South Dakota, USA

Treesearch

Peter M. Brown; Carolyn Hull Sieg

1996-01-01

Chronologies of fire events were reconstructed from crossdated fire-scarred ponderosa pine trees for four sites in the south-central Black Hills. Compared to other ponderosa pine forests in the southwest US or southern Rocky Mountains, these communities burned less frequently. For all sites combined, and using all fires detected, the mean fire interval (MFI), or number...

Wildland fire in ecosystems: fire and nonnative invasive plants

Treesearch

Kristin Zouhar; Jane Kapler Smith; Steve Sutherland; Matthew L. Brooks

2008-01-01

This state-of-knowledge review of information on relationships between wildland fire and nonnative invasive plants can assist fire managers and other land managers concerned with prevention, detection, and eradication or control of nonnative invasive plants. The 16 chapters in this volume synthesize ecological and botanical principles regarding relationships between...

Alaska and Yukon Fires

Atmospheric Science Data Center

2014-05-15

article title:  Smoke Signals from the Alaska and Yukon Fires   ... the Yukon Territory from mid-June to mid-July, 2004. Thick smoke particles filled the air during these fires, prompting Alaskan officials to issue air quality warnings. Some of the smoke from these fires was detected as far away as New Hampshire. These ...

Is Your School Truly Fire-Safe?

ERIC Educational Resources Information Center

Saunders, Carol Silverman

1995-01-01

Though most people assume that their schools are protected by smoke alarms and sprinkler systems, many are not. Older schools can fall through fire-code loopholes. Some schools have insufficient fire detection systems. Sprinkler systems can be too expensive for schools. Parents should educate themselves and insist on fire safety. (SM)

Stay or Go?

ERIC Educational Resources Information Center

Kroll, Karen

2003-01-01

Discusses whether U.S. schools equipped with fire sprinklers and fire detection and intercom systems should be able to use a delayed evacuation policy when it comes to fire drills or actual fires. A controversial project in Minnesota is examining that question. The paper discusses concerns about delayed evacuation, the impact of delayed evacuation…

49 CFR 176.69 - General stowage requirements for hazardous materials.

Code of Federal Regulations, 2010 CFR

2010-10-01

... equipped with a fixed fire extinguishing and fire detection system, the freight containers or barges need... by paragraph (a) of this section if fire fighting equipment capable of reaching and piercing the..., their removal from a potentially dangerous situation, and the removal of packages in case of fire. (b...

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2016-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

Forecasting wildland fire behavior using high-resolution large-eddy simulations

NASA Astrophysics Data System (ADS)

Munoz-Esparza, D.; Kosovic, B.; Jimenez, P. A.; Anderson, A.; DeCastro, A.; Brown, B.

2017-12-01

Wildland fires are responsible for large socio-economic impacts. Fires affect the environment, damage structures, threaten lives, cause health issues, and involve large suppression costs. These impacts can be mitigated via accurate fire spread forecast to inform the incident management team. To this end, the state of Colorado is funding the development of the Colorado Fire Prediction System (CO-FPS). The system is based on the Weather Research and Forecasting (WRF) model enhanced with a fire behavior module (WRF-Fire). Realistic representation of wildland fire behavior requires explicit representation of small scale weather phenomena to properly account for coupled atmosphere-wildfire interactions. Moreover, transport and dispersion of biomass burning emissions from wildfires is controlled by turbulent processes in the atmospheric boundary layer, which are difficult to parameterize and typically lead to large errors when simplified source estimation and injection height methods are used. Therefore, we utilize turbulence-resolving large-eddy simulations at a resolution of 111 m to forecast fire spread and smoke distribution using a coupled atmosphere-wildfire model. This presentation will describe our improvements to the level-set based fire-spread algorithm in WRF-Fire and an evaluation of the operational system using 12 wildfire events that occurred in Colorado in 2016, as well as other historical fires. In addition, the benefits of explicit representation of turbulence for smoke transport and dispersion will be demonstrated.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Obtaining a Pragmatic Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Earth Observation Data

NASA Astrophysics Data System (ADS)

Kantzas, Euripides; Quegan, Shaun

2015-04-01

Fire constitutes a violent and unpredictable pathway of carbon from the terrestrial biosphere into the atmosphere. Despite fire emissions being in many biomes of similar magnitude to that of Net Ecosystem Exchange, even the most complex Dynamic Vegetation Models (DVMs) embedded in IPCC General Circulation Models poorly represent fire behavior and dynamics, a fact which still remains understated. As DVMs operate on a deterministic, grid cell-by-grid cell basis they are unable to describe a host of important fire characteristics such as its propagation, magnitude of area burned and stochastic nature. Here we address these issues by describing a model-independent methodology which assimilates Earth Observation (EO) data by employing image analysis techniques and algorithms to offer a realistic fire disturbance regime in a DVM. This novel approach, with minimum model restructuring, manages to retain the Fire Return Interval produced by the model whilst assigning pragmatic characteristics to its fire outputs thus allowing realistic simulations of fire-related processes such as carbon injection into the atmosphere and permafrost degradation. We focus our simulations in the Arctic and specifically Canada and Russia and we offer a snippet of how this approach permits models to engage in post-fire dynamics hitherto absent from any other model regardless of complexity.

An evaluation of image based techniques for wildfire detection and fuel mapping

NASA Astrophysics Data System (ADS)

Gabbert, Dustin W.

Few events can cause the catastrophic impact to ecology, infrastructure, and human safety of a wildland fire along the wildland urban interface. The suppression of natural wildland fires over the past decade has caused a buildup of dry, dead surface fuels: a condition that, coupled with the right weather conditions, can cause large destructive wildfires that are capable of threatening both ancient tree stands and manmade infrastructure. Firefighters use fire danger models to determine staffing needs on high fire risk days; however models are only as effective as the spatial and temporal density of their observations. OKFIRE, an Oklahoma initiative created by a partnership between Oklahoma State University and the University of Oklahoma, has proven that fire danger assessments close to the fire - both geographically and temporally - can give firefighters a significant increase in their situational awareness while fighting a wildland fire. This paper investigates several possible solutions for a small Unmanned Aerial System (UAS) which could gather information useful for detecting ground fires and constructing fire danger maps. Multiple fire detection and fuel mapping programs utilize satellites, manned aircraft, and large UAS equipped with hyperspectral sensors to gather useful information. Their success provides convincing proof of the utility that could be gained from low-altitude UAS gathering information at the exact time and place firefighters and land managers are interested in. Close proximity, both geographically and operationally, to the end can reduce latency times below what could ever be possible with satellite observation. This paper expands on recent advances in computer vision, photogrammetry, and infrared and color imagery to develop a framework for a next-generation UAS which can assess fire danger and aid firefighters in real time as they observe, contain, or extinguish wildland fires. It also investigates the impact information gained by this system could have on pre-fire risk assessments through the development of very high resolution fuel maps.

An Evaluation of Image Based Techniques for Early Wildfire Detection and Fuel Mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gabbert, Dustin W.

Few events can cause the catastrophic impact to ecology, infrastructure, and human safety of a wildland fire along the wildland urban interface. The suppression of natural wildland fires over the past decade has caused a buildup of dry, dead surface fuels: a condition that, coupled with the right weather conditions, can cause large destructive wildfires that are capable of threatening both ancient tree stands and manmade infrastructure. Firefighters use fire danger models to determine staffing needs on high fire risk days; however models are only as effective as the spatial and temporal density of their observations. OKFIRE, an Oklahoma initiativemore » created by a partnership between Oklahoma State University and the University of Oklahoma, has proven that fire danger assessments close to the fire – both geographically and temporally – can give firefighters a significant increase in their situational awareness while fighting a wildland fire. This paper investigates several possible solutions for a small Unmanned Aerial System (UAS) which could gather information useful for detecting ground fires and constructing fire danger maps. Multiple fire detection and fuel mapping programs utilize satellites, manned aircraft, and large UAS equipped with hyperspectral sensors to gather useful information. Their success provides convincing proof of the utility that could be gained from low-altitude UAS gathering information at the exact time and place firefighters and land managers are interested in. Close proximity, both geographically and operationally, to the end can reduce latency times below what could ever be possible with satellite observation. This paper expands on recent advances in computer vision, photogrammetry, and infrared and color imagery to develop a framework for a next-generation UAS which can assess fire danger and aid firefighters in real time as they observe, contain, or extinguish wildland fires. It also investigates the impact information gained by this system could have on pre-fire risk assessments through the development of very high resolution fuel maps.« less

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2010 CFR

2010-10-01

... systems will be considered to consist of normal and emergency power supplies, a fire detecting control... subpart, manual fire alarm systems will be considered to consist of normal and emergency power supplies, a...

46 CFR 161.002-2 - Types of fire-protective systems.

Code of Federal Regulations, 2011 CFR

2011-10-01

... systems will be considered to consist of normal and emergency power supplies, a fire detecting control... subpart, manual fire alarm systems will be considered to consist of normal and emergency power supplies, a...

Smoke Detection: Critical Element of a University Residential Fire Safety Program.

ERIC Educational Resources Information Center

Robinson, Donald A.

1979-01-01

A program at the University of Massachusetts/Amherst to assess the fire protection needs of its residential system is described. The study culminated in a multiphase fire safety improvement plan. (JMF)

Exact event-driven implementation for recurrent networks of stochastic perfect integrate-and-fire neurons.

PubMed

Taillefumier, Thibaud; Touboul, Jonathan; Magnasco, Marcelo

2012-12-01

In vivo cortical recording reveals that indirectly driven neural assemblies can produce reliable and temporally precise spiking patterns in response to stereotyped stimulation. This suggests that despite being fundamentally noisy, the collective activity of neurons conveys information through temporal coding. Stochastic integrate-and-fire models delineate a natural theoretical framework to study the interplay of intrinsic neural noise and spike timing precision. However, there are inherent difficulties in simulating their networks' dynamics in silico with standard numerical discretization schemes. Indeed, the well-posedness of the evolution of such networks requires temporally ordering every neuronal interaction, whereas the order of interactions is highly sensitive to the random variability of spiking times. Here, we answer these issues for perfect stochastic integrate-and-fire neurons by designing an exact event-driven algorithm for the simulation of recurrent networks, with delayed Dirac-like interactions. In addition to being exact from the mathematical standpoint, our proposed method is highly efficient numerically. We envision that our algorithm is especially indicated for studying the emergence of polychronized motifs in networks evolving under spike-timing-dependent plasticity with intrinsic noise.

G-Guidance Interface Design for Small Body Mission Simulation

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Carson, John; Phan, Linh

2008-01-01

The G-Guidance software implements a guidance and control (G and C) algorithm for small-body, autonomous proximity operations, developed under the Small Body GN and C task at JPL. The software is written in Matlab and interfaces with G-OPT, a JPL-developed optimization package written in C that provides G-Guidance with guaranteed convergence to a solution in a finite computation time with a prescribed accuracy. The resulting program is computationally efficient and is a prototype of an onboard, real-time algorithm for autonomous guidance and control. Two thruster firing schemes are available in G-Guidance, allowing tailoring of the software for specific mission maneuvers. For example, descent, landing, or rendezvous benefit from a thruster firing at the maneuver termination to mitigate velocity errors. Conversely, ascent or separation maneuvers benefit from an immediate firing to avoid potential drift toward a second body. The guidance portion of this software explicitly enforces user-defined control constraints and thruster silence times while minimizing total fuel usage. This program is currently specialized to small-body proximity operations, but the underlying method can be generalized to other applications.

The infrared video image pseudocolor processing system

NASA Astrophysics Data System (ADS)

Zhu, Yong; Zhang, JiangLing

2003-11-01

The infrared video image pseudo-color processing system, emphasizing on the algorithm and its implementation for measured object"s 2D temperature distribution using pseudo-color technology, is introduced in the paper. The data of measured object"s thermal image is the objective presentation of its surface temperature distribution, but the color has a close relationship with people"s subjective cognition. The so-called pseudo-color technology cross the bridge between subjectivity and objectivity, and represents the measured object"s temperature distribution in reason and at first hand. The algorithm of pseudo-color is based on the distance of IHS space. Thereby the definition of pseudo-color visual resolution is put forward. Both the software (which realize the map from the sample data to the color space) and the hardware (which carry out the conversion from the color space to palette by HDL) co-operate. Therefore the two levels map which is logic map and physical map respectively is presented. The system has been used abroad in failure diagnose of electric power devices, fire protection for lifesaving and even SARS detection in CHINA lately.

46 CFR 91.20-15 - Scope of inspection.

Code of Federal Regulations, 2010 CFR

2010-10-01

... appliances, fire-detecting and extinguishing equipment, pilot boarding equipment, pollution prevention... accordance with approved plans, and determine that the vessel is in possession of a valid certificate issued... applicable regulations in subchapter H (Passenger Vessels) of this chapter. For example, fire-detecting...

46 CFR 91.20-15 - Scope of inspection.

Code of Federal Regulations, 2014 CFR

2014-10-01

... appliances, fire-detecting and extinguishing equipment, pilot boarding equipment, pollution prevention... accordance with approved plans, and determine that the vessel is in possession of a valid certificate issued... applicable regulations in subchapter H (Passenger Vessels) of this chapter. For example, fire-detecting...

46 CFR 91.20-15 - Scope of inspection.

Code of Federal Regulations, 2012 CFR

2012-10-01

... appliances, fire-detecting and extinguishing equipment, pilot boarding equipment, pollution prevention... accordance with approved plans, and determine that the vessel is in possession of a valid certificate issued... applicable regulations in subchapter H (Passenger Vessels) of this chapter. For example, fire-detecting...

46 CFR 91.20-15 - Scope of inspection.

Code of Federal Regulations, 2013 CFR

2013-10-01

... appliances, fire-detecting and extinguishing equipment, pilot boarding equipment, pollution prevention... accordance with approved plans, and determine that the vessel is in possession of a valid certificate issued... applicable regulations in subchapter H (Passenger Vessels) of this chapter. For example, fire-detecting...

46 CFR 91.20-15 - Scope of inspection.

Code of Federal Regulations, 2011 CFR

2011-10-01

... appliances, fire-detecting and extinguishing equipment, pilot boarding equipment, pollution prevention... accordance with approved plans, and determine that the vessel is in possession of a valid certificate issued... applicable regulations in subchapter H (Passenger Vessels) of this chapter. For example, fire-detecting...

Reducing The Risk Of Fires In Conveyor Transport

NASA Astrophysics Data System (ADS)

Cheremushkina, M. S.; Poddubniy, D. A.

2017-01-01

The paper deals with the actual problem of increasing the safety of operation of belt conveyors in mines. Was developed the control algorithm that meets the technical requirements of the mine belt conveyors, reduces the risk of fires of conveyors belt, and enables energy and resource savings taking into account random sort of traffic. The most effective method of decision such tasks is the construction of control systems with the use of variable speed drives for asynchronous motors. Was designed the mathematical model of the system "variable speed multiengine drive - conveyor - control system of conveyors", that takes into account the dynamic processes occurring in the elements of the transport system, provides an assessment of the energy efficiency of application the developed algorithms, which allows to reduce the dynamic overload in the belt to (15-20)%.

Hypersonic, nonequilibrium flow over the FIRE 2 forebody at 1634 sec

NASA Technical Reports Server (NTRS)

Chambers, Lin Hartung

1994-01-01

The numerical simulation of hypersonic flow in thermochemical nonequilibrium over the forebody of the FIRE 2 vehicle at 1634 sec in its trajectory is described. The simulation was executed on a Cray C90 with the program Langley Aerodynamic Upwind Relaxation Algorithm (LAURA) 4.0.2. Code setup procedures and sample results, including grid refinement studies, are discussed. This simulation relates to a study of radiative heating predictions on aerobrake type vehicles.

Downwelled longwave surface irradiance data from five sites for the FIRE/SRB Wisconsin Experiment from October 12 through November 2, 1986

NASA Technical Reports Server (NTRS)

Whitlock, Charles H.; Cox, Stephen K.; Lecroy, Stuart R.

1990-01-01

Tables are presented which show data from five sites in the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE)/Surface Radiation Budget (SRB) Wisconsin experiment regional from October 12 through November 2, 1986. A discussion of intercomparison results is also included. The field experiment was conducted for the purposes of both intensive cirrus-cloud measurements and SRB algorithm validation activities.

Spacecraft Fire Safety: A Human Space Flight Program Perspective

NASA Technical Reports Server (NTRS)

Pedley, Michael D.

2003-01-01

This paper presents viewgraphs on the International Space Station's fire safety program from a human space flight perspective. The topics include: 1) Typical Manned Spacecraft Materials; 2) Typical Flammable Hardware Protection; 3) Materials Flammability; 4) Fire Retardants; 5) Nonflammable Foam Cushion Material; 6) Electrical Wire and Cable; 7) Russian Solid-Fuel Oxygen Generator (SFOG); 8) GOX Ignition Mechanisms; 9) Fire Detection; and 10) Fire Suppression.