Using VIIRS Direct Readout Capabilities for the Improvement of Mexico's Wild Fire Alert System
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1 Using VIIRS Direct Readout Capabilities for the Improvement of Mexico's Wild Fire Alert System Juan M. Escamilla Mólgora 1 National Commission for Knowledge and Use of Biodiversity CONABIO - Mexico 1 CSPP/IMAPP USERS GROUP MEETING May, 21 th, 2013 CIMSS/SSEC, University of Wisconsin- Madison
2 CONABIO National Commission for Knowledge and Use of Biodiversity. Established since employees Mission: Promote, coordinate and support activities related to the knowledge of biologic diversity, its conservation and sustainable use. Main functions: Operation and development of the National System of Biodiversity Information. Coordination of national and international exchange of knowledge related to biodiversity. - Real time alert systems for decition makers.
![Wild Fire Alert System [ Milestones ]](/docs-images/77/76081119/images/3-0.jpg "1999 Begining of the Wild Fire Alert")
3 Wild Fire Alert System [ Milestones ] 1999 Begining of the Wild Fire Alert program. Data from DMSP Upgrade: AVHRR receiving antennae Use Fire Detection Algorithm (Flasse- Ceccato,1996 ) Upgrade: MODIS receiver system mounted. Automated operational products. Use of MOD14 products (Giglio et.al., 2003)
![Wild Fire Alert System [ Milestones ] 2004 Service](/docs-images/77/76081119/images/4-1.jpg "extension to Central America.")
4 Wild Fire Alert System [ Milestones ] 2004 Service extension to Central America Deployment of the current webpage: Development of the new version. VIIRS receiving and processing capabilities
![(Fire mask) Swath reprojected QL and composites [ MODIS swath2grid] Hotspot characterization Anomalies on vegetation index](/docs-images/77/76081119/images/5-6.jpg "Shapefiles and KML Web page publication Email alert W*S Services Oceans Monitoring program Moisture content on fuel Burned area")
5 Current operational processes (MODIS) Raw data acquisition an processing Level1 Products (Seadas 6 & standalone software ) Higher level products End-user products L0 (Terascan RT- STPS) MOD03 (GEO) MOD07 (Atmosphere) MOD09 (Reflectances) MOD13 (NDVI) MOD14 (Fire mask) Swath reprojected QL and composites [ MODIS swath2grid] Hotspot characterization Anomalies on vegetation index Shapefiles and KML Web page publication alert W*S Services Oceans Monitoring program Moisture content on fuel Burned area afection *
6 Current operational processes (VIIRS) Raw data acquisition an processing Level1 Products ( CSPP 3.1. SDR_1_3 EDR_1_0 ) Higher level products End-user products GDNBO s Npp.points (homemade) Shapefiles and KML L0 (Terascan RT-STPS [patched ] ) Day Night Band SVI s Hotspot characterization Web page publication alert RNSCA-RVIRS SVM s AVAFO GEOTIFs W*S Services IICMO Burned area afection *
7 Current Viirs and legacy Modis operational processes
8 Restfull services (Representational State Transfer)
9 e.g. Pass inserter Satellite : npp Telemetry : nppdb Date : Time : Passnumber : 52 Number of lines : 7502 Pass duration : 00:15:30 Sun azimuth : 67 Satellite elevation : 55
10 &mes=04&dia=25&hora=18&min=28&seg=10&sat=npp&n _l=6070&n_p=60&satelev=14&sunelev=84&satazim=99&s unazim=99&n_orb=7738&satzenith=0&sunzenith=25&dur= 00:12:30 Notifications of amount of space left.
11 Operational products
12
13 Viirs and Modis Active Fires
14 VIIRS EDR AVAFO
15 MODIS MOD14 V.
16 Active fires on 1Km grid
17 Featurized hotspots
18 Export to various formats
19 Fixed with: False positives with no data strips
20
21 WMS services: Anomalies on NDVI
22 Percentage on moisture in dead fuel
23 Version 2.0 features Spatially enabled database Object Mapper API Objectified wild fire Web services (JSON,XML) Advanced statistical and numerical modules
24 Postgres POSTGIS 2.0 SQLAlchemy Django Scipy, Numpy, GNU-R
25 Supported by Free and Open Source Software BeautifulSoup Debian
26 Wishlist for CSPP EDR Include Fire Propagation Rate field (as MOD14). white-noise bluring on DNBs Aggregate granules on IICMO products. Is it possible to reproject IICMO files with polar2grid Parallel processing? E.g. per granule. Perhaps with CGI.
27 References S. P. Flasse, P. Ceccato. A contextual Algorithm for AVHRR fire detection. International Jornal of Remote Sensing Vol 17., Iss. 2 (1996). L. Giglio, J.Descloitres, C. Justice, J. Kaufman. An Enhanced Contextual Fire Detection Algorithm for MODIS. Remote Sensing of the Environment Volumen 87, Issue 2-3 (2003). Chuvieco, E. Aguado, I. Dimitrakopoulus, A. Conversion of fuel moisture content values to ignition potential for integrated fire danger assessment, Canadian Journal of Forest Research, 2004, vol. 34 (11), pp
28 References Nieto, H., Aguado, I. Chuvieco, E and Sandholt, I. Dead fuel moisture estimation with MSG SEVIRI data. Retrieval of meteorological data for the calculation of the equilibrium moisture content. Agricultural and Forest Meteorology, Volume 150 (2010) G. J. Roerink, M. Menenti, W. Verhoef "Reconstructing Cloudfree NDVI composites using Fourier analysis of time series." International Journal of Remote Sensing. Vol. 21, Iss. 9, (2000)
29 Thank you for lisening
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