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At least 361 records · Page 20

A Simulated Fire Edge Vis-IR Detection and Tracking Approach for Autonomous sUAS in STEReO

This study presents a fire edge detection and tracking methodology for an autonomous small UAS (sUAS). The sUAS, onboard sensors, and wildfire are simulated to evaluate the methodology. A visible light (Vis) camera and an infrared (IR) camera are simulated onboard the sUAS to identify burnt, burning, and unburnt areas on a static wildfire bitmap. After differentiating between these areas, a form of nonlinear guidance law (NLGL) is used to generate virtual target points (VTP) that guide the sUAS so that the fire edge is kept within the camera FOV. The VTP are passed to the sUAS flight management system (FMS) in the form of waypoints. The approach was tested in simulation and demonstrated tracking curved, sharp, and linear fire edge shapes at different altitudes. Higher altitude tracking proved to demand the least control effort without sacrificing continuous tracking.

Autonomous UAV↗

California Fire Plumes –OVERVIEW – 20 August 2020

At least seven major wildfires were burning across California as early as ~10:30 AM local time on 20 August 2020. They are identified as hot-spots at 4 microns wavelength, highlighted as red dots and superposed on this true-color image from the MODIS instrument aboard the NASA Earth Observing System’s Terra satellite. Wildfires tend to increase in intensity during the day, and fire activity usually peaks in the late afternoon.

wildfires↗

Advancing Wildland Fire Response with NASA’s Second Shift Capabilities

Novel “Second-Shift” capabilities—leveraging Uncrewed Aerial Systems and Optionally Piloted Vehicles—are identified that could extend wildfire aerial logistics support into night or low-visibility conditions. Expert elicitations with subject-matter experts informed the development of these conceptual capabilities and identified key challenges in wildfire logistics operations. Furthermore, the potential of these capabilities could extend beyond aerial logistics support, encompassing aerial suppression, observation, and emergency extraction support for wildland firefighting. An approach to development, implementation and validation of the novel capabilities is described.

Wildfire logistics↗

Advancing Wildland Fire Response with NASA’s Second Shift Capabilities

Novel “Second-Shift” capabilities—leveraging Uncrewed Aerial Systems and Optionally Piloted Vehicles—are identified that could extend wildfire aerial logistics support into night or low-visibility conditions. Expert elicitations with subject-matter experts informed the development of these conceptual capabilities and identified key challenges in wildfire logistics operations. Furthermore, the potential of these capabilities could extend beyond aerial logistics support, encompassing aerial suppression, observation, and emergency extraction support for wildland firefighting. An approach to development, implementation and validation of the novel capabilities is described.

Wildfire logistics↗

Improving Satellite-Based Hotspot Detection Through Deep Learning-Enabled Smoke Recognition

While geostationary satellites, such as the GOES-R series, provide wildland fire hotspot readings at a high temporal resolution, they are prone to false negative readings and decreased confidence. One cause of decreased hotspot confidence is cloud contamination. Smoke produced from wildfire is often misinterpreted as cloud contamination, resulting in inaccurate and unsure sensor readings. To this end, we built a deep learning image segmentation model to identify smoke and cloud in true color satellite images. The model is pre-trained using self-supervised learning on over 10,000 GOES-R images to learn the underlying structure of satellite imagery. Then, the model is fine-tuned on a set of 130 labeled documents using supervised learning. The resulting model performs multi-class image segmentation with 85% accuracy and runs in under a minute on a standard personal computer. When paired alongside hotspot data, the model’s outputs can help increase confidence in wildfire location by identifying cases of cloud contamination that are due to smoke. The resulting model can be deployed in a stand-alone application or bundled in an Open Data Integration for wildland fire management (ODIN) application.

Earth observation↗

A Field Campaign to Study Lightning that Ignites the Bush

The impact of recent wildland fires in the United States and Australia have received much attention in the past several years. As a result, NASA has developed a new Earth Science program to better understand, predict, and manage this phenomenon, as well as a future suborbital mission to studying pyro-cumulonimbus clouds and their effects on the Earth system. In Australia, government and philanthropic stakeholders are supporting a series of field campaigns over the next few years to inform science requirements and advance technology for a future satellite mission to monitor Bushfires. Lightning flashes are a major source of wildland fires, but uncertainties remain about the physical characteristics of lightning and their parent thunderstorms responsible for igniting wildfires. It was long believed that most lightning-ignited wildfires are largely caused by positive flashes to the ground (CGs) and multi-stroke CGs, but a recent study looking at 26-years of NLDN data indicate otherwise. Perhaps this finding is due to statistical chance—there are more negative CGs that occur globally—or perhaps there is some unknown electrical property of the thundercloud from which the igniting flashes emanate. Regardless, new observing strategies are needed. Additionally, long continuing current CGs, which are more likely to ignite a fire, can elude detection by operational ground-based lightning location systems, making it difficult to efficiently identify potential wildland fires and manage them before they have adverse impacts. To address these science and operational gaps, NASA’s Lightning Mapping Array along with electric and magnetic field change meters will be deployed for the Australian Bushfire campaign to document the electrical structure and properties of thunderstorms and lightning that occur in a wildland fire susceptible region. Another aspect of the campaign will be the use of NASA’s airborne lightning observatory, which includes a spectrometer and high-speed imager, to document the radiometric attributes of these flashes coincident with the ground-based RF observations. These observations will be used to better understand the properties of lightning that ignite wildland fires as well as inform design of a lightning detection system for the future Bushfire Monitoring satellite mission.

lightning↗

Mobile satellite communications in the Forest Service

There are usually some places within a forest that do not have adequate communication coverage due to line-of-sight or other reasons. These areas are generally known by the foresters and radio technicians and allowances are made for that when working or traveling in those areas. However, when wildfire or other emergencies occur, communications are vital because wildfires can require hundreds of firefighters and cover thousands of acres. During these emergency operations, the existing communications are not adequate and complete radio systems are moved into the area for the conduct of fire communications. Incident command posts (ICPs) and fire camps are set up in remote locations and there is constant need for communications in the fire area and to agency headquarters and dispatch offices. Mobile satellite communications would be an ideal supplement to the Forest Service's current communications system in aiding forest fire control activities.

Warren, John R.↗

Atmospheric chemistry in the Arctic and subarctic - Influence of natural fires, industrial emissions, and stratospheric inputs

Layers with enhanced concentrations of trace gases intercepted by the NASA Electra aircraft over Alaska during the Arctic Boundary Layer Expedition (ABLE 3A) in July-August 1988 are discussed. Haze layers apparently associated with boreal fires were enriched in hydrocarbons and NO(y), with emission factors corresponding closely to laboratory data for smoldering combustion. It is argued that atmospheric composition was strongly modified by wildfires during several periods of the ABLE 3A mission. The associated enhancement of NO(y) was smaller than observed for most other combustion processes but was nonetheless significant in the context of very low background concentrations. Ozone production in fire plumes was negligible. Ambient O3 was supplied by the stratosphere, with little direct input from midlatitude source during summer. It is argued that NO(y) was supplied about equally by the stratosphere and by wildfires. Hydrocarbons and CO appear to derive from biomass fires and from human activities.

Wofsy, S. C.↗

Estimating Canopy Water Content of Chaparral Shrubs Using Optical Methods

California chaparral ecosystems are exceptionally fire adapted and typically are subject to wildfire at decadal to century frequencies. The hot dry Mediterranean climate summers and the chaparral communities of the Santa Monica Mountains make wildfire one of the most serious economic and life-threatening natural disasters faced by the region. Additionally, the steep fire-burned hillsides are subject to erosion, slumpage, and mud slides during the winter rains. The Santa Monica Mountain Zone (SMMZ) is a 104,000 ha eastwest trending range with 607 m of vertical relief and located in the center of the greater Los Angeles region. A series of fires in the fall of 1993 burned from Simi Valley to Santa Monica within a few hours. Developing techniques to monitor fire hazard and predict the spread of fire is of major concern to the region. One key factor in the susceptibility to fire is the water content of the vegetation canopy. The development of imaging spectrometry and remote sensing techniques may constitute a tool to provide this information.

Ustin, Susan L.↗

Demonstrating Acquisition of Real-Time Thermal Data over Fires Utilizing UAVs

NASA-Ames Research Center, in collaboration with General Atomics Aeronautical Systems, Inc. has been developing real-time data acquisition and information delivery systems employing uninhabited aerial vehicle (UAV) technology for disaster mitigation and assessment demonstrations. Working in conjunction with the US Forest Service, a disaster community agency responsible for wildfire management and mitigation, we developed a large-scale wildfire demonstration called the First Response Experiment (FIRE). During that experiment in late summer 2001, the participants demonstrated the melding of innovative technologies such as UAV platforms, real-time data processing, and data telemetry for quick analysis of a disaster event. The General Atomics ALTUS UAV, the Airborne Infrared Disaster Assessment System (AIRDAS) and Over-The-Horizon (OTH) satellite data telemetry equipment were employed over a controlled burn to test the feasibility of a disaster monitoring and mitigation platform for hazardous duty. The ALTUS UAV was employed to demonstrate the long duration, altitude, and payload capability of unmanned platforms for acquiring disaster related data. The ALTUS has an operational altitude to 45,000 feet (13,700 in), with a flight duration of twenty-four hours and a payload capacity of over 300 lbs. (148.5 kg). This allows the platform to operate under the conditions that would be necessary for monitoring and mitigating disaster events throughout the Unites States. The four channel AIRDAS data (calibrated thermal infrared digital imagery of the fire event) was sent from the ALTUS UAV via a satellite communications system (NERA transponder and INMARSAT satellite) to a data archive server and an image processing work station at NASA-Ames Research Center, 400 miles away.

Wegener, Steven S.↗

Harnessing Systems Engineering Methodology in Using Earth Science Research Data for Real Applications

For the last three decades, Earth science remote sensing technologies have been providing an enormous amount of useful data and information serving to broaden our understanding of the home planet as a system. NASA's Earth science program has deployed about 18 complex satellites and is in the process of defining and launching multiple observing systems in this decade. At the same time, the European Community and many other countries such as Russia, France, India, Japan, and China have also significantly contributed to Earth science research. To date, the majority of such efforts have concentrated on expanding our scientific understanding of the multiple nonlinear and chaotic processes of Earth's behavior. In recent years, legislators and stakeholders have put serious pressure on the science community to devote more attention to making use of scientific results for societal benefit. For instance, there are a number of areas such as energy forecasting, aviation safety, agricultural efficiency, disaster management, air quality and public health that can directly take advantage of Earth science results to analyze and predict large scale problems and conditions. This is becoming even more important now that we live in a global economy interconnected via the internet and transportation systems; regional environmental conditions can have far reaching impact across continental boundaries. These factors dictate requirements for global data that can help us assess and control the devastating problems of famine, water resources, wildfires, human health and more. To do this requires a serious, organized, and systematic approach that transfers fundamental research products to the applied sciences domain. This paper presents a systems engineering and management process that can effectively make such transfer of data to the user community. Examples are presented on how the above decision making framework can help in solving critical problems such as the spread of vector borne diseases, forecasts of harmful algal blooms as well as forest fires and wildfires, and the intercontinental transport of dust storms and pollution.

Habib, Shahid↗

Applications of Principled Search Methods in Climate Influences and Mechanisms

Forest and grass fires cause economic losses in the billions of dollars in the U.S. alone. In addition, boreal forests constitute a large carbon store; it has been estimated that, were no burning to occur, an additional 7 gigatons of carbon would be sequestered in boreal soils each century. Effective wildfire suppression requires anticipation of locales and times for which wildfire is most probable, preferably with a two to four week forecast, so that limited resources can be efficiently deployed. The United States Forest Service (USFS), and other experts and agencies have developed several measures of fire risk combining physical principles and expert judgment, and have used them in automated procedures for forecasting fire risk. Forecasting accuracies for some fire risk indices in combination with climate and other variables have been estimated for specific locations, with the value of fire risk index variables assessed by their statistical significance in regressions. In other cases, the MAPSS forecasts [23, 241 for example, forecasting accuracy has been estimated only by simulated data. We describe alternative forecasting methods that predict fire probability by locale and time using statistical or machine learning procedures trained on historical data, and we give comparative assessments of their forecasting accuracy for one fire season year, April- October, 2003, for all U.S. Forest Service lands. Aside from providing an accuracy baseline for other forecasting methods, the results illustrate the interdependence between the statistical significance of prediction variables and the forecasting method used.

Glymour, Clark↗

Ozone Production from the 2004 North American Boreal Fires

We examine the ozone production from boreal forest fires based on a case study of wildfires in Alaska and Canada in summer 2004. The model simulations were performed with the chemistry transport model, MOZART-4, and were evaluated by comparison with a comprehensive set of aircraft measurements. In the analysis we use measurements and model simulations of carbon monoxide (CO) and ozone (O3) at the PICO-NARE station located in the Azores within the pathway of North American outflow. The modeled mixing ratios were used to test the robustness of the enhancement ratio deltaO3/deltaCO (defined as the excess O3 mixing ratio normalized by the increase in CO) and the feasibility for using this ratio in estimating the O3 production from the wildfires. Modeled and observed enhancement ratios are about 0.25 ppbv/ppbv which is in the range of values found in the literature, and results in a global net O3 production of 12.9 2 Tg O3 during summer 2004. This matches the net O3 production calculated in the model for a region extending from Alaska to the East Atlantic (9-11 Tg O3) indicating that observations at PICO-NARE representing photochemically well-aged plumes provide a good measure of the O3 production of North American boreal fires. However, net chemical loss of fire related O3 dominates in regions far downwind from the fires (e.g. Europe and Asia) resulting in a global net O3 production of 6 Tg O3 during the same time period. On average, the fires increased the O3 burden (surface-300 mbar) over Alaska and Canada during summer 2004 by about 7-9%, and over Europe by about 2-3%.

Pfister, G. G.↗

Large Unmanned Aircraft System Operations in the National Airspace System - the NASA 2007 Western States Fire Missions

The National Aeronautics and Space Administration (NASA) Dryden Flight Research Center (DFRC) Ikhana (ee-kah-nah) project executed the 2007 Western States Fire Missions over several of the western United States using an MQ-9 unmanned aircraft system (UAS) in partnership with the NASA Ames Research Center, the United States Forest Service, and the National Interagency Fire Center. The missions were intended to supply infrared imagery of wildfires to firefighters on the ground within 10 minutes of data acquisition. For each of the eight missions, the NASA DFRC notified the Federal Aviation Administration (FAA) of specific flight plans within three or fewer days of the flight. The FAA Certificate of Waiver or Authorization (commonly referred to as a COA ) process was used to obtain access to the United States National Airspace System. Significant time and resources were necessary to develop the COA application, perform mission planning, and define and approve emergency landing sites. Unique aspects of flying unmanned aircraft created challenges to mission operations. Close coordination with FAA headquarters and air traffic control resulted in safe and successful missions that assisted firefighters by providing near-real-time imagery of selected wildfires.

Buoni, Gregory P.↗

A VARI-Based Relative Greenness from MODIS Data for Computing the Fire Potential Index

The Fire Potential Index (FPI) relies on relative greenness (RG) estimates from remote sensing data. The Normalized Difference Vegetation index (NDVI), derived from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery is currently used to calculate RG operationally. Here we evaluated an alternate measure of RG using the Visible Atmospheric Resistant Index (VARI) derived from Moderate Resolution Imaging Spectrometer (MODIS) data. VARI was chosen because it has previously been shown to have the strongest relationship with Live Fuel Moisture (LFM) out of a wide selection of MODIS-derived indices in southern California shrublands. To compare MODIS-based NDVI-FPI and VARI-FPI, RG was calculated from a 6-year time series of MODIS composites and validated against in-situ observations of LFM as a surrogate for vegetation greenness. RG from both indices was then compared in terms of its performance for computing the FPI using historical wildfire data. Computed RG values were regressed against ground-sampled LFM at 14 sites within Los Angeles County. The results indicate the VARI-based RG consistently shows a stronger relationship with observed LFM than NDVI-based RG. With an average R2 of 0.727 compared to a value of only 0.622 for NDVI-RG, VARI-RG showed stronger relationships at 13 out of 14 sites. Based on these results, daily FPI maps were computed for the years 2001 through 2005 using both NDVI-RG and VARI-RG. These were then validated against 12,490 fire detections from the MODIS active fire product using logistic regression. Deviance of the logistic regression model was 408.8 for NDVI-FPI and 176.2 for VARI-FPI. The c-index was found to be 0.69 and 0.78, respectively. The results show that VARI-FP outperforms NDVI-FPI in distinguishing between fire and no-fire events for historical wildfire data in southern California for the given time period.

Schneider, P.↗

Resilience of Alaska's Boreal Forest to Climatic Change

This paper assesses the resilience of Alaska s boreal forest system to rapid climatic change. Recent warming is associated with reduced growth of dominant tree species, plant disease and insect outbreaks, warming and thawing of permafrost, drying of lakes, increased wildfire extent, increased postfire recruitment of deciduous trees, and reduced safety of hunters traveling on river ice. These changes have modified key structural features, feedbacks, and interactions in the boreal forest, including reduced effects of upland permafrost on regional hydrology, expansion of boreal forest into tundra, and amplification of climate warming because of reduced albedo (shorter winter season) and carbon release from wildfires. Other temperature-sensitive processes for which no trends have been detected include composition of plant and microbial communities, long-term landscape-scale change in carbon stocks, stream discharge, mammalian population dynamics, and river access and subsistence opportunities for rural indigenous communities. Projections of continued warming suggest that Alaska s boreal forest will undergo significant functional and structural changes within the next few decades that are unprecedented in the last 6000 years. The impact of these social ecological changes will depend in part on the extent of landscape reorganization between uplands and lowlands and on policies regulating subsistence opportunities for rural communities.

Chapin, F. S., III↗

Transport of Cs-137 from Boreal Biomass Burning in Summer of 2010

The summer of 2010 was a severe fire season in western Russia. Wildfires were detected in the Bryansk region, raising concerns that radionuclide contamination from the Chernobyl accident could be resuspended in the atmosphere. We simulate the transport of passive and particulate tracers of biomass burning from this region using the GEOS5 GOCART model driven by assimilated meteorology. Biomass burning emissions are based on MODIS fire detections. We validate the model against aerosol optical depth from MODIS. Using a range of estimates for Cs-137 emissions during wildfires, we estimate the downwind concentration and deposition of Cs-137 based on the emission ratios of Cs-137 to the simulated tracers. We discuss the sensitivity of our results to the location of the fires and the fraction of Cs-137 resuspended.

Strode, Sarah↗

Fire Return Interval Within the Northern Boundary of the Larch Forest

Larch (Larix spp.) dominant forests compose a large proportion of the forests of Russia (i.e., about 40% of forested areas). These forests range from the Yenisei ridge on the west to the Pacific Ocean on the east, and from Lake Baikal on the south to the 73rd parallel in the north. Larch stands comprise the world s northern most forest at Ary-Mas (72 deg 28' N, 102 deg 15' E). Larch dominated forests occupy about 70% of the permafrost areas in Siberia. Larch forms high closure stands as well as open forests, and is found mainly over permafrost, where other tree species barely survive. Wildfires are typical for this territory with the majority occurring as ground fires due to low crown closure. Due to the thin active layer in permafrost soils and a dense lichen-moss cover, ground fires may cause stand mortality. The vast areas of larch-dominant forests is generally considered as a "carbon sink"; however, positive long-term temperature trends at higher latitudes are expected to result in an increase of fire frequency, and thus may convert this area to a source for greenhouse gases. There are recent observations regarding the increase of fire frequency within non-protected territories. Surprisingly, there are few publications on fire chronoseqences for the huge forested territory between the Ural Mountains and the Pacific Ocean. Also there is a general understanding that bimodal (late spring -- early summer and late summer-beginning of fall) fire seasonal distribution in the south becomes uni-modal (late spring -- early summer) in the north. The purpose of this study is to investigate the wildfire history at the northern edge of the zone of larch dominance.

Kharuk, V. I.↗