 Hello, I'm Ali Lopez and I'm talking about the work from work to assist welfare global vulnerability in Colombian ecosystems. A background about this topic is the historical frequency for the Wi-Fi, the alerts in this country. And it's important because we lost three cover, about that 6.7%. And this is very important because the impact for the emission to CO2 are very important, but the ecosystem and the ecological biodiversity. In Colombia, you have in this map the frequency for the Wi-Fi and as you look the principal urban areas, we are very questioned about what is the impact for the Wi-Fi near to the urban areas. And we've selected two areas with this criteria and Kundinamarca and Magdalena were the selection for this analysis. You can see that for example, Kundinamarca, it's the region with elevation for the sea level and Magdalena, it's located near to the sea. The ecosystem that you can be in Colombia, in the Kundinamarca, it's this, in Sandinian forest on Paramo. You look at the vegetation is very different with the Magdalena, the tropical dry forest is a vegetation that allows leaves in the dry seasons. And this is very important because the organic matter is different in the combustion capacity. We analyzed the rigs, but in this presentation only focused to the vulnerability and response capacity. But to analyze this in Grayson's file with the FWU and exposure for the Wi-Fi. For the framework, this is for analysis in the line cover type. We use the MODIS image and calculate the NDVI and NDWI for the vegetation and this is go to the line cover and they use the meteorological neural network for the estimate the FWU for the probability to Wi-Fi and use to the probability of Wi-Fi occurrence in function on the line cover and use this prediction for reduction the scale and in this moment we calculate with the vulnerability. Okay, this is the category but the equivalence for the categories in the NWU and NDWI. For the vulnerability analysis, we review the international, regional, national and local information about that base source and integrate this data about the global vulnerability index. It's adapted to Colombia about that criteria, that multi-criteria matrix. This is the six criteria that we use. The occupation in the WUE is the Wayland-Urban interface and the neighborhood 2G line cover about that you confuse to capacity. Use the response capacity that this is an index national for disaster rigs and use for the vulnerability ecology. Others data, for example, the Corinland cover distribution category that use the adaptation to fire combustion used to the consistent red list of Colombia and calculate the Wayland-Urban interface base it to Miranda. This is the final index with the six criteria and in this criteria we calculate for the Magdalena and Cundinamarca and finally we have this MAPE. This MAPE can you see about the global vulnerability in the two regions and finally use the result to neural network that FW for calculate the rigs in this area. We think that is the vulnerability framework is being adapted for Latin American country. Colombia has in this moment database that is used for the wildfire rigs assessment and the predict for the wildfire vulnerability can be used to increase the response capacity and the results have been used to adapt adaptation plan by temperature increase in the country. Thanks. Thank you. Any questions for Alli?