scholarly journals Integrated Satellite System for Fire Detection and Prioritization

2022 ◽  
Vol 14 (2) ◽  
pp. 335
Author(s):  
Giuseppe Mazzeo ◽  
Fortunato De Santis ◽  
Alfredo Falconieri ◽  
Carolina Filizzola ◽  
Teodosio Lacava ◽  
...  
Keyword(s):  
Fire Detection ◽  
Satellite System ◽  
Affected Area ◽  
Satellite Systems ◽  
Usable Information ◽  
Infrared Imager ◽  
Synthetic Indicator ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Several studies have shown the relevance of satellite systems in detecting, monitoring, and characterizing fire events as support to fire management activities. On the other hand, up to now, only a few satellite-based platforms provide immediately and easily usable information about events in progress, in terms of both hotspots, which identify and localize active fires, and the danger conditions of the affected area. However, this kind of information is usually provided through separated layers, without any synthetic indicator which, indeed, could be helpful, if timely provided, for planning the priority of the intervention of firefighting resources in case of concurrent fires. In this study, we try to fill these gaps by presenting an Integrated Satellite System (ISS) for fire detection and prioritization, mainly based on the Robust Satellite Techniques (RST), and the Fire Danger Dynamic Index (FDDI), an original re-structuration of the Índice Combinado de Risco de Incêndio Florestal (ICRIF), for the first time presented here. The system, using Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High Resolution Radiometer (AVHRR), and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data, provides near real-time integrated information about both the fire presence and danger over the affected area. These satellite-based products are generated in common formats, ready to be ingested in Geographic Information System (GIS) technologies. Results shown and discussed here, on the occasion of concurrent winter and summer fires in Italy, in agreement with information from independent sources, demonstrate that the ISS system, operating at a regional/national scale, may provide an important contribution to fire prioritization. This may result in the mitigation of fire impact in populated areas, infrastructures, and the environment.

scholarly journals NASA MODIS Previews NPOESS VIIRS Capabilities

2006 ◽  
Vol 21 (4) ◽  
pp. 649-655 ◽  
Author(s):  
Thomas F. Lee ◽  
Steven D. Miller ◽  
Carl Schueler ◽  
Shawn Miller
Keyword(s):  
Satellite System ◽  
Infrared Imager ◽  
Defense Meteorological Satellite Program ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data ◽  
Color Simulation ◽  
True Color ◽  
Real Time Simulations

Abstract The Visible/Infrared Imager Radiometer Suite (VIIRS), scheduled to fly on the satellites of the National Polar-orbiting Operational Environmental Satellite System, will combine the missions of the Advanced Very High Resolution Radiometer (AVHRR), which flies on current National Oceanic and Atmospheric Administration satellites, and the Operational Linescan System aboard the Defense Meteorological Satellite Program satellites. VIIRS will offer a number of improvements to weather forecasters. First, because of a sophisticated downlink and relay system, VIIRS latencies will be 30 min or less around the globe, improving the timeliness and therefore the operational usefulness of the images. Second, with 22 channels, VIIRS will offer many more products than its predecessors. As an example, a true-color simulation is shown using data from the Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS), an application current geostationary imagers cannot produce because of a missing “green” wavelength channel. Third, VIIRS images will have improved quality. Through a unique pixel aggregation strategy, VIIRS pixels will not expand rapidly toward the edge of a scan like those of MODIS or AVHRR. Data will retain nearly the same resolution at the edge of the swath as at nadir. Graphs and image simulations depict the improvement in output image quality. Last, the NexSat Web site, which provides near-real-time simulations of VIIRS products, is introduced.

A Geometry-Based Approach to Identifying Cloud Shadows in the VIIRS Cloud Mask Algorithm for NPOESS

2009 ◽  
Vol 26 (7) ◽  
pp. 1388-1397 ◽  
Author(s):  
Keith D. Hutchison ◽  
Robert L. Mahoney ◽  
Eric F. Vermote ◽  
Thomas J. Kopp ◽  
John M. Jackson ◽  
...  
Keyword(s):  
Satellite System ◽  
Spectral Signatures ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask ◽  
New Procedures ◽  
Global Datasets ◽  
Operational Time

Abstract A geometry-based approach is presented to identify cloud shadows using an automated cloud classification algorithm developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new procedures exploit both the cloud confidence and cloud phase intermediate products generated by the Visible/Infrared Imager/Radiometer Suite (VIIRS) cloud mask (VCM) algorithm. The procedures have been tested and found to accurately detect cloud shadows in global datasets collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are applied over both land and ocean background conditions. These new procedures represent a marked departure from those used in the heritage MODIS cloud mask algorithm, which utilizes spectral signatures in an attempt to identify cloud shadows. However, they more closely follow those developed to identify cloud shadows in the MODIS Surface Reflectance (MOD09) data product. Significant differences were necessary in the implementation of the MOD09 procedures to meet NPOESS latency requirements in the VCM algorithm. In this paper, the geometry-based approach used to predict cloud shadows is presented, differences are highlighted between the heritage MOD09 algorithm and new VIIRS cloud shadow algorithm, and results are shown for both these algorithms plus cloud shadows generated by the spectral-based approach. The comparisons show that the geometry-based procedures produce cloud shadows far superior to those predicted with the spectral procedures. In addition, the new VCM procedures predict cloud shadows that agree well with those found in the MOD09 product while significantly reducing the execution time as required to meet the operational time constraints of the NPOESS system.

First-Light Imagery from Suomi NPP VIIRS

2013 ◽  
Vol 94 (7) ◽  
pp. 1019-1029 ◽  
Author(s):  
Donald Hillger ◽  
Thomas Kopp ◽  
Thomas Lee ◽  
Daniel Lindsey ◽  
Curtis Seaman ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Fire Detection ◽  
Satellite System ◽  
Defense Meteorological Satellite Program ◽  
Wide Range ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Low Levels ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Meteorological Satellite

The Suomi National Polar-Orbiting Partnership (NPP) satellite was launched on 28 October 2011, heralding the next generation of operational U.S. polar-orbiting satellites. It carries the Visible– Infrared Imaging Radiometer Suite (VIIRS), a 22-band visible/infrared sensor that combines many of the best aspects of the NOAA Advanced Very High Resolution Radiometer (AVHRR), the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. VIIRS has nearly all the capabilities of MODIS, but offers a wider swath width (3,000 versus 2,330 km) and much higher spatial resolution at swath edge. VIIRS also has a day/night band (DNB) that is sensitive to very low levels of visible light at night such as those produced by moonlight reflecting off low clouds, fog, dust, ash plumes, and snow cover. In addition, VIIRS detects light emissions from cities, ships, oil flares, and lightning flashes. NPP crosses the equator at about 0130 and 1330 local time, with VIIRS covering the entire Earth twice daily. Future members of the Joint Polar Satellite System (JPSS) constellation will also carry VIIRS. This paper presents dramatic early examples of multispectral VIIRS imagery capabilities and demonstrates basic applications of that imagery for a wide range of operational users, such as for fire detection, monitoring ice break up in rivers, and visualizing dust plumes over bright surfaces. VIIRS imagery, both single and multiband, as well as the day/night band, is shown to exceed both requirements and expectations.

scholarly journals Differentiating between Clouds and Heavy Aerosols in Sun-Glint Regions

2010 ◽  
Vol 27 (6) ◽  
pp. 1085-1094 ◽  
Author(s):  
Keith D. Hutchison ◽  
Bruce Hauss ◽  
Barbara D. Iisager ◽  
Hiroshi Agravante ◽  
Robert Mahoney ◽  
...  
Keyword(s):  
Satellite System ◽  
Sensor Data ◽  
Infrared Imager ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask ◽  
Data Dropouts ◽  
New Procedures

Abstract An approach is presented to distinguish between clouds and heavy aerosols in sun-glint regions with automated cloud classification algorithms developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. The approach extends the applicability of an algorithm that has already been applied successfully in areas outside the geometric and wind-induced sun-glint areas of the earth over both land and water surfaces. The successful application of this approach to include sun-glint regions requires an accurate cloud phase analysis, which can be degraded, especially in regions of sun glint, because of poorly calibrated radiances of the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Consequently, procedures have been developed to replace bad MODIS level 1B (L1B) data, which may result from saturation, dead/noisy detectors, or data dropouts, with radiometrically reliable values to create the Visible Infrared Imager Radiometer Suite (VIIRS) proxy sensor data records (SDRs). Cloud phase analyses produced by the NPOESS VIIRS cloud mask (VCM) algorithm using these modified VIIRS proxy SDRs show excellent agreement with features observed in color composites of MODIS imagery. In addition, the improved logic in the VCM algorithm provides a new capability to differentiate between clouds and heavy aerosols within the sun-glint cone. This ability to differentiate between clouds and heavy aerosols in strong sun-glint regions is demonstrated using MODIS data collected during the recent fires that burned extensive areas in southern Australia. Comparisons between heavy aerosols identified by the VCM algorithm with imagery and heritage data products show the effectiveness of the new procedures using the modified VIIRS proxy SDRs. It is concluded that it is feasible to accurately detect clouds, identify cloud phase, and distinguish between clouds and heavy aerosol using a single cloud mask algorithm, even in extensive sun-glint regions.

scholarly journals Inter-calibration of polar imager solar channels using SEVIRI

2013 ◽  
Vol 6 (2) ◽  
pp. 3215-3247 ◽  
Author(s):  
J. F. Meirink ◽  
R. A. Roebeling ◽  
P. Stammes
Keyword(s):  
High Resolution ◽  
Spectral Response ◽  
Calibration Method ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aqua Satellite ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Direct Inter ◽  
Very High

Abstract. Accurate calibration of satellite imagers is a prerequisite for using their measurements in climate applications. Here we present a method for the inter-calibration of geostationary and polar-orbiting imager solar channels based on regressions of collocated near-nadir radiances. Specific attention is paid to correcting for differences in spectral response between instruments. The method is used to calibrate the solar channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the geostationary Meteosat satellite with corresponding channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the polar-orbiting Aqua satellite. The SEVIRI operational calibration is found to be stable during the years 2004 to 2009 but off by −8, −6, and +3.5% for channels 1 (0.6 μm), 2 (0.8 μm), and 3 (1.6 μm), respectively. These results are robust for a range of choices that can be made regarding data collocation and selection, as long as the viewing and illumination geometries of the two instruments are matched. Uncertainties in the inter-calibration method are estimated to be 1% for channel 1 and 1.5% for channels 2 and 3. A specific application of the method is the inter-calibration of polar imagers using SEVIRI as a transfer instrument. This offers an alternative to direct inter-calibration, which in general has to rely on high-latitude collocations. Using this method we have tied MODIS-Terra and Advanced Very High Resolution Radiometer (AVHRR) instruments on National Oceanic and Atmospheric Administration (NOAA) satellites 17 and 18 to MODIS-Aqua for the years 2007 to 2009. While reflectances of the two MODIS instruments differ less than 2% for all channels considered, deviations of an existing AVHRR calibration from MODIS-Aqua reach −3.5 and +2.5% for the 0.8 and 1.6 μm channels, respectively.

scholarly journals The identification and tracking of volcanic ash using the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infra-Red Imager (SEVIRI)

2013 ◽  
Vol 6 (3) ◽  
pp. 5577-5619 ◽  
Author(s):  
A. R. Naeger ◽  
S. A. Christopher
Keyword(s):  
Volcanic Ash ◽  
Atmospheric Dispersion ◽  
Atmospheric Measurements ◽  
Distribution Maps ◽  
Infrared Imager ◽  
Atmospheric Dispersion Models ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Aircraft Data

Abstract. In this paper, we develop an algorithm based on combining spectral, spatial, and temporal thresholds from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) daytime measurements to identify and track different aerosol types, primarily volcanic ash. Contemporary methods typically do not use temporal information to identify ash. We focus not only on the identification and tracking of volcanic ash during the Eyjafjallajökull volcanic eruption period beginning 14 April 2010 to May but a pixel level classification method for separating various classes in the SEVIRI images. Three case studies on 19 April, 16 May, and 17 May are analyzed in extensive detail with other satellite data including the Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Facility for Airborne Atmospheric Measurements (FAAM) BAe146 aircraft data to verify the aerosol spatial distribution maps generated by the SEVIRI algorithm. Our results indicate that the SEVIRI algorithm is able to track volcanic ash even at these high latitudes. Furthermore, the BAe146 aircraft data shows that the SEVIRI algorithm detects nearly all ash regions when AOD > 0.2. However, the algorithm has higher uncertainties when AOD is < 0.1 over water and AOD < 0.2 over land. The ash spatial distributions provided by this algorithm can be used as a critical input and validation for atmospheric dispersion models simulated by Volcanic Ash Advisory Centers (VAACs). Identifying volcanic ash is an important first step before quantitative retrievals of ash concentration can be made.

scholarly journals Aerosol Optical Depth from MODIS satellite data above the Pierre Auger Observatory

2019 ◽  
Vol 197 ◽  
pp. 02011
Author(s):  
Nataliia Borodai
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite System ◽  
Horizontal Resolution ◽  
Pierre Auger Observatory ◽  
Fluorescence Detector ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol optical depth can be retrieved from measurements performed by Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument. The MODIS satellite system includes two polar satellites, Terra and Aqua. Each of them flies over the Pierre Auger Observatory once a day, providing two measurements of aerosols per day and covering the whole area of the Observatory. MODIS aerosol data products have been generated by three dedicated algorithms over bright and dark land and over ocean surface. We choose the Deep Blue algorithm data to investigate the distribution of aerosols over the Observatory, as this algorithm is the most appropriate one for semi-arid land of the Pierre Auger Observatory. This data algorithm allows us to obtain aerosol optical depth values for the investigated region, and to build cloud-free aerosol maps with a horizontal resolution 0.1°×0.1°. Since a suffcient number of measurements was obtained only for Loma Amarilla and Coihueco fluorescence detector (FD) sites of the Pierre Auger Observatory, a more detailed analysis of aerosol distributions is provided for these sites. Aerosols over these FD sites are generally distributed in a similar way each year, but some anomalies are also observed. These anomalies in aerosol distributions appear mainly due to some transient events, such as volcanic ash clouds, fires etc. We conclude that the Deep Blue MODIS algorithm provides more realistic aerosol optical depth values than other available algorithms.

scholarly journals Distinguishing Aerosols from Clouds in Global, Multispectral Satellite Data with Automated Cloud Classification Algorithms

2008 ◽  
Vol 25 (4) ◽  
pp. 501-518 ◽  
Author(s):  
Keith D. Hutchison ◽  
Barbara D. Iisager ◽  
Thomas J. Kopp ◽  
John M. Jackson
Keyword(s):  
Satellite System ◽  
Classification Algorithms ◽  
Cloud Classification ◽  
Infrared Imager ◽  
Other Information ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Mask ◽  
New Procedures

Abstract A new approach is presented to distinguish between clouds and heavy aerosols with automated cloud classification algorithms developed for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new procedures exploit differences in both spectral and textural signatures between clouds and aerosols to isolate pixels originally classified as cloudy by the Visible/Infrared Imager/Radiometer Suite (VIIRS) cloud mask algorithm that in reality contains heavy aerosols. The procedures have been tested and found to accurately distinguish clouds from dust, smoke, volcanic ash, and industrial pollution over both land and ocean backgrounds in global datasets collected by NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. This new methodology relies strongly upon data collected in the 0.412-μm bandpass, where smoke has a maximum reflectance in the VIIRS bands while dust simultaneously has a minimum reflectance. The procedures benefit from the VIIRS design, which is dual gain in this band, to avoid saturation in cloudy conditions. These new procedures also exploit other information available from the VIIRS cloud mask algorithm in addition to cloud confidence, including the phase of each cloudy pixel, which is critical to identify water clouds and restrict the use of spectral tests that would misclassify ice clouds as heavy aerosols. Comparisons between results from these new procedures, automated cloud analyses from VIIRS heritage algorithms, manually generated analyses, and MODIS imagery show the effectiveness of the new procedures and suggest that it is feasible to identify and distinguish between clouds and heavy aerosols in a single cloud mask algorithm.

Underreporting of wildland fires in the US Fire Reporting System NFIRS: California

2017 ◽  
Vol 26 (8) ◽  
pp. 732 ◽  
Author(s):  
David T. Butry ◽  
Douglas S. Thomas
Keyword(s):  
Reporting System ◽  
Fire Detection ◽  
Resource Assessment ◽  
Wildland Fires ◽  
Fire Incident ◽  
The Us ◽  
Moderate Resolution ◽  
Large Fires ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

The absence of a comprehensive and accurate database on fire occurrence means that some proportion of wildfires is not reported. This paper examines wildfires reported in the National Fire Incident Reporting System (NFIRS) database and compares it with the satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) fire detection data and the CAL FIRE Fire and Resource Assessment Program (FRAP) geodatabase to understand underreporting of wildland fires in the NFIRS system. The paper discusses a series of large wildland fires and uses a Generalised Linear Model to identify the conditions where large wildfires go unreported. This paper shows that the NFIRS database, which is the primary fire database in the US, significantly underreports wildland fires. Evidence from California suggests that 32% of fires within local jurisdictions detected via MODIS satellite were identified in the NFIRS database; thus, there could be a significant number of fires going unreported nationwide. Examining eight large fires in California, only 16% of the structures damaged or destroyed, as reported in CAL FIRE, were reported in NFIRS. Areas with underreporting tend to have a higher level of poverty, higher population density, higher level of people without vehicles, lower income and a higher level of single parents with children under 18, as well as a higher level of people under the age of 18.

scholarly journals Inter-calibration of polar imager solar channels using SEVIRI

2013 ◽  
Vol 6 (9) ◽  
pp. 2495-2508 ◽  
Author(s):  
J. F. Meirink ◽  
R. A. Roebeling ◽  
P. Stammes
Keyword(s):  
High Resolution ◽  
Spectral Response ◽  
Calibration Method ◽  
Infrared Imager ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Aqua Satellite ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Direct Inter ◽  
Very High

Abstract. Accurate calibration of satellite imagers is a prerequisite for using their measurements in climate applications. Here we present a method for the inter-calibration of geostationary and polar-orbiting imager solar channels based on regressions of collocated near-nadir reflectances. Specific attention is paid to correcting for differences in spectral response between instruments. The method is used to calibrate the solar channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the geostationary Meteosat satellite with corresponding channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the polar-orbiting Aqua satellite. The SEVIRI operational calibration is found to be stable during the years 2004 to 2009, but offset by −8, −6, and +3.5 % for channels 1 (0.6 μm), 2 (0.8 μm), and 3 (1.6 μm), respectively. These results are robust for a range of choices that can be made regarding data collocation and selection, as long as the viewing and illumination geometries of the two instruments are matched. Uncertainties in the inter-calibration method are estimated to be 1 % for channel 1 and 1.5 % for channels 2 and 3. A specific application of our method is the inter-calibration of polar imagers using SEVIRI as a transfer instrument. This offers an alternative to direct inter-calibration, which in general has to rely on high-latitude collocations. Using this method we have tied MODIS-Terra and Advanced Very High Resolution Radiometer (AVHRR) instruments on National Oceanic and Atmospheric Administration (NOAA) satellites 17 and 18 to MODIS-Aqua for the years 2007 to 2009. While reflectances of the two MODIS instruments differ less than 2 % for all channels considered, deviations of an existing AVHRR calibration from MODIS-Aqua reach −3.5 and +2.5 % for the 0.8 and 1.6 μm channels, respectively.

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