SAS-SSE: Final Presentation S. Sintini, G. Laneve Centro di Ricerca Progetto San Marco Sapienza Università di Roma SAS-MSFRD Tuesday 10 November 2009 ESA/ESRIN

CRPSM Profile The Centro di Ricerca Progetto San Marco, funded in 1993 as a research centre of the University of Rome “La Sapienza”, represents the prosecution of the San Marco Project born in 1962 from a collaboration among Italy (University of Rome "La Sapienza“) and USA (NASA). The aerospace activity has been started both in Rome and in Kenya where the University established a site named San Marco Equatorial Range (SMER) devoted to launch and support space missions. The Kenyan site has been re-named after the Prof. Broglio departure as “Luigi Broglio Space Centre" (BSC), in The San Marco Project has been the first Italian Space Program and the only one that has afforded globally the paramount problems of the space sector:  Personal training;  Satellite construction and launch (the first satellite San Marco 1 launched in 15 th December 1964  The set up of a launch range and ground stations devoted at the Tracking, Telemetry and Remote Sensing;  The development of scientific researches.

CRPSM Profile The Base Camp in 2003 The Base Camp when San Marco Project started (1965) 2 m antenna L-band of the RSC station. 10-m antenna operating in S,X,L bands of the TT&C station. 6m antenna in X band of the RSC station.

CRPSM Profile Training Sun-photometer Field campaign Remote sensing applications  Coastal erosion  Oil spill detection  Atmosphere Monitoring  Sea color and sea/land temperature  Desertification  Water quality (pollution) monitoring  NRT hot spot detection and monitoring  Population monitoring  Prompt estimate of damages  Indices for border monitoring  Automatic detection of objects/infrastructures

MSFRD System: Service description  MSFRD is an automated processing system, developed by CRPSM, capable to merge and compare the outputs provided by SEVIRI/MSG based fire detection systems: SFIDE (CRPSM), MDIFRM (ESA) and third party.  The processing is continuous and automated over predefined areas (Italy, Senegal), meaning quasi real-time availability of processing outputs stored in an online area.  The system provides the possibility to perform analysis and comparison on user-defined areas and time interval.  The system offers the possibility to validate the detected hot spots on the base of the reports provided by the agencies devoted to the fires fighting.

A description of the functionalities offered by the system, is given hereinafter: validation of the fires detection modules by using the ground based observations, when available; the statistical analysis of the information retrievable by the hot spots detected by algorithms applied to the SEVIRI images; comparison of the data obtained by two o more fires detection algorithms; testing of user-provided hot spots detection algorithms. MSFRD System: Service functionalities

MSFRD System: Validation The validation is based on the availability of ground based data provided as report by the agencies involved in the activity of fire fighting or obtained during opportunely planned field campaigns. Ground information will be uploaded in the database by service provider or authorized users. When required, for example at the end of the uploading process, the validation procedure can be launched. The validation covers the following aspects:  False alarms (commission errors),  Missed fires (omission errors),  Detection promptness.

MSFRD System: Statistical analysis The statistical analysis based on the study of the hot spots detected on a user defined AOI and time-interval by a selected algorithm regards the following aspects:  Diurnal distribution of the fires for an assigned area and time span;  Daily distribution of the fires for an assigned area and time span;  Promptness of the detection for a given time period and AOI, in this case the promptness is referred to the ground observation (only for confirmed fires);  Distribution of the retrieved temperatures and sizes of the fires (histogram);  Distribution of FRP (Fire Radiative Power) (histogram) or FRP versus time.

MSFRD System: Comparison The comparison module provides a software platform on which SFIDE, MDIFRM and third party S/W outputs can be compared. If more than one algorithm is selected by the user, in other words he is interested in comparing different algorithms, he can select, apart from the statistical analysis above recalled (also adapt to evaluate the performances of the single algorithm), further options : o Promptness of the detection for a given time period and AOI among algorithms; o Differences on the retrieved temperatures and sizes of the fires as function of the time of the day and/or period of the year; o Differences on the estimate of FRP (Fire Radiative Power) (histogram) or FRPs versus time; o diurnal and daily variation of the fires detected by all the algorithms of interest.

MSFRD System: Case study Validation of MDIFRM v.1.0 hotspots The timerange is: from ' :00:00' to ' :45:00' The area of interest is defined as follows (Sardinia): lower left corner (38.602, 7.59) - upper right corner (41.643, ) Main findings: N. of recorded Fire Events in this timerange and AOI: 150 N. of Fire Events with corresponding hotspots: 19 N. of Fire Events without corresponding hotspots: 131 N. of hotspots detected by satellite before Ground Intervention: 4 Total n. of hotspots detected within a Fire Event in this timerange and AOI: 258

MSFRD System: Case study Validation of MDIFRM v.1.0 hotspots Fire events with corresponding hotspots Ignition point coordinates Fire begun at (GMT) Fire ended at (GMT) Estimated burned area (ha) Main type of burned vegetation N. of corresponding hotspots ΔMinutes between satellite and ground observation Lat: Lon: :30: :00:00 129Pasture1+45 Lat: Lon: :39: :02:00 42 Mediterranean Scrub 21-9 Lat: Lon: :20: :56:00 20Woodland5+25 Lat: Lon: :00: :05:00 7Other2+45 Lat: Lon: :45: :25:00 9Woodland1+15 Lat: Lon: :32: :00:00 9Pasture6+43 Lat: Lon: :00: :00:00 153Pasture290 Lat: Lon: :21: :00:00 54Woodland5+24 Lat: Lon: :28: :00:00 25Pasture2+2 Lat: Lon: :02: :00:00 16Woodland6-2 Lat: Lon: :50: :00:00 150Woodland5+10 Lat: Lon: :47: :15:00 12Woodland1+43 Lat: Lon: :50: :35:00 36 Mediterranean Scrub 2+85 Lat: Lon: :49: :00:00 120Woodland74-19 Lat: Lon: :30: :00:00 46Crops48+30 Lat: Lon: :20: :00:00 5Pasture23-35 Lat: Lon: :03: :00:00 18 Mediterranean Scrub Lat: Lon: :14: :00:00 8Other14+1 Lat: Lon: :45: :10:00 8 Mediterranean Scrub 1+90 Total n. of fire events with corresponding hotspots19 Table:

MSFRD System: Case study Validation of MDIFRM v.1.0 hotspots Graph:

MSFRD System: Case study Validation of MDIFRM v.1.0 hotspots Graph: Analysis of the distribution of the size of the fire events burned areas. As provided by ground observations. Such distribution confirms that the undetected fires are mostly those of small sizes.

MSFRD System: Case study Validation of MDIFRM v.1.0 hotspots Graph: Analysis of the distribution of the fire events in terms of the characteristics of the vegetation of the burned areas. As provided by ground observations. Such distribution confirms that the undetected fires are mostly those characterized by not-wooded vegetation.

MSFRD System: Case study Comparison: MDIFRM vs SFIDE Algorithms Comparison This module of the MSFRD service provides a platform for comparing the performances of two or more hotspot detection algorithms. The number of hotspots detected simultaneously by all the selected algorithms is estimated and reported along with the comparison of the following parameters: o Comparison of the distribution of hotspot Fire Radiative Power values o Comparison of the distribution of hotspot Estimated Burning Area values o Comparison of the distribution of hotspot Fire Temperature values o Comparison of the distribution of hotspot MIR Temperature values

MSFRD System: Case study Comparison of the distribution of hot spot Fire Radiative Power values

MSFRD System: Case study Statistical Analysis: SFIDE This module of the MSFRD service provides a platform for analyzing the performances of each hotspot detection algorithm. The following analyses may be carried out: Diurnal distribution of detected hotspots Distribution of hotspot Fire Radiative Power values Distribution of hotspot Estimated Burning Area values Distribution of hotspot Fire Temperature values Distribution of hotspot MIR Temperature values Daily distribution of detected hotspots

MSFRD System: Case study Statistical Analysis: SFIDE Diurnal distribution of detected hotspots Description: This analysis shows the diurnal distribution of detected hot spots on a 24 hours scale. Order information: The algorithms selected for analysis is: SFIDE v.1.1 The time-range is: from ' :00:00' to ' :45:00' The area of interest is defined as follows (Sardinia): lower left corner (38.602, 7.59) - upper right corner (41.643, )

MSFRD System: Service evaluation  An evaluation of our services usage is untimely as consequence of its recent acceptance review;  We are planning to evaluate the usage and the quality of the service:  by implementing a system for counting occurrences of interruption, failure, anomalies, etc.  by comparing, periodically, the outputs with results provided by other sources,  by implementing a feedback system by which the users can confirm the quality of the results (i.e. hot spot presence).  By means of the SSE platform we expect to reach a wide number of users.

SSE System: Suggestions  Although the SSE-Portal is rich in content and services, it appears that the academic and scientific community is scarcely aware of its potentialities. An awareness and visibility campaign, fostering the discovery and use of the Portal would surely end up in a better tuning up of the interfaces and services provided to the end user.  The Web Map Viewer, appears to be somewhat limited in the display of information which is not strictly connected to a unique geographical entity. It would be useful to have instruments allowing to provide statistical analyses and ancillary data related to a specific order without having to rely on external web and application servers (i.e. providing space and resources for the elaboration of such data and integrating the output in the WMV itself).  In some cases, it would be useful to add the possibility to animate a series of temporal layers in order to picture the evolution and trend of certain phenomena.

MSFRD Processing System