Socio-economic dataset at 1 km grid cell for fire prediction in 1980s and 2000s Madrid (Spain)

<p><span>This data gathers socioeconomic drivers at 1km2 grid cell spatial resolution to predict forest fires in a region in Spain (Madrid) for two periods of time (1980 and 2000s. The response variable was exact located fires by grid cell. <span>The resulting work was published at </span></span>Vilar, L., G&oacute;mez, I., Mart&iacute;nez-Vega, J., Echavarr&iacute;a, P., Ria&ntilde;o, D., &amp; Mart&iacute;n, M. P. (2016). Multitemporal modelling of socio-economic wildfire drivers in central Spain between the 1980s and the 2000s: comparing generalized linear models to machine learning algorithms. <em>PLoS One</em>, <em>11</em>(8), e0161344.</p> <p><span>.-Description of the data and file structure</span></p> <p><span>The data set is an excel file with columns for these variables:</span></p> <table> <tbody> <tr> <td>VARIABLES</td> <td>DESCRIPTION</td> </tr> <tr> <td>CellCode</td> <td>ID of the 1*1km cell</td> </tr> <tr> <td>X</td> <td>X cell coordinate</td> </tr> <tr> <td>Y</td> <td>Y cell coordinate</td> </tr> <tr> <td>POP</td> <td>population density</td> </tr> <tr> <td>AGRI</td> <td>agriculture workforce density</td> </tr> <tr> <td>SERV</td> <td>services workforce density</td> </tr> <tr> <td>FAI</td> <td>200 m Forest Agriculture Interface buffer<span>&nbsp;</span></td> </tr> <tr> <td>WUI</td> <td>12.5m Wildland Urban Interface buffer<span>&nbsp;</span></td> </tr> <tr> <td>FGI</td> <td>200 m Forest Grassland Interface buffer<span>&nbsp;</span></td> </tr> <tr> <td>RAILWAYS</td> <td>70 and 100 m railway buffers<span>&nbsp;</span></td> </tr> <tr> <td>ROADS</td> <td>15, 25 and 50 m road buffers<span>&nbsp;</span></td> </tr> <tr> <td>TRACKS</td> <td>300 m tracks buffer<span>&nbsp;&nbsp;</span></td> </tr> <tr> <td>NPA</td> <td>Natural Protected Area</td> </tr> <tr> <td>FIRE_PRESENCE</td> <td>Response variable. Fire presence/absence</td> </tr> </tbody> </table>