Mapping of the post-forest fire scar to estimate potential losses in the paper pulp production area, Municipalities of Yumbo, La Cumbre and Dagua (Valle del Cauca), year 2014
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This study aims to determine the affected area or post-forest fire scar on the paper pulp production crops in the municipalities of Yumbo, La Cumbre and Dagua from Landsat 8 images. The methodology starts from choosing Landsat satellite images 8 with minimal cloud cover, to which radiometric corrections are made by converting digital levels (ND) to radiance and reflectance values, as well as atmospheric and topographic corrections. Subsequently, the normalized vegetation index (NDVI), the normalized moisture difference index (NDMI), as well as the adjusted to the soil (NMDISoil) and finally the normalized fire radius (NBR) are estimated, which were used for the estimation of the vegetation cover before the drought season, the detection of possible sources of fire and finally for the mapping of the post-fire scar, additionally the product brightness temperature was estimated that served to validate the results obtained with the indices before mentioned. By having different capture dates, several phases were obtained, between January and April the vegetation cover was estimated and the areas prone to forest fires for the drought season were determined through the relationship between the NDVI and the brightness temperature, in In the second phase that includes captures between June and August, the detection of forest fires was carried out through the NDMI and NDMISoil indices, giving a positive focus for the image captured on June 1, 2014, additionally for this same date it was shown The calculated temperature result, which reached temperatures higher than 50º Celsius in areas close to the detected focus, this product was also obtained for the images corresponding to August 20 and September 5, showing temperatures higher than 30º Celsius, which corresponds to dates after forest fires, in the third phase corresponding to the month of September the NBR was calculated, allowing the m felling of the post-fire scar, the sequence of the three phases ended with the estimation of affected production areas, where it was found that the crops were affected by almost 38%, which could mean a loss of almost 50% in the pulp production.
Ariza, A. (2013). Descripcion y correcion de productos Landsat 8. Bogota: Grupo Interno de Trabajo en Percepción Remota y Aplicaciones Geográficas.
Quintano, C., Fernandez, A., Fernández, O., & Shimabukuro, E. (2006). Mapping burned areas in Mediterranean countries using spectral mixture analysis from a uni-temporal perspective. International Journal of Remote Sensing, 27 (4), 645-662. https://doi.org/10.1080/01431160500212195
El Tiempo. (18 de Agosto de 2014). Infierno en las montañas de Yumbo por incendio forestal. El Tiempo. https://www.eltiempo.com/archivo/documento/CMS-14398976
Quintan, C., Fernandéz, A., Stein, A & Bijker, W. (2011). Estimation of area burned by forest fires in Mediterranean countries: A remote sensing data mining perspective. Forest Ecology and Management, 266 (8), 1597-1607. 10.1016/j.foreco.2011.07.010
CVC. (2014). 56 Incendios forestales se han registrado en el municipio de dagua en los meses de junio y julio. https://bit.ly/3rOsbqb
Krishna, P. H., & Reddy, C. S. (2012). Assessment of increasing threat of forest fires in Rajasthan, India using multi-temporal remote sensing data (2005–2010). Current Science, 102 (9), 1288-1297.
Lingli Wang, J. J., Qu, J & Xianjun, H .(2008). Forest fire detection using the normalized multi-band drought index (NMDI) with satellite measurements. ScienceDirect, 148 (11) 1767 – 1776. https://doi.org/10.1016/j.agrformet.2008.06.005
Nicholas R. Goodwin, L. J., & Collett, L. (2014). Development of an automatedmethod formapping fire history captured in Landsat TM and ETM+ time series across Queensland, Australia. Remote Sensing of Environment, 148 (4) 206–221. 10.1016/j.rse.2014.03.021
Schroeder, T., Wulder, M., Healey, S., & Moisen, G. (2012). Detecting post-fire salvage logging from Landsat change maps and national fire survey data. Remote Sensing of Environment, 122, 166-174. 10.1016/j.rse.2011.10.031
Vanhellemont, Q., & Ruddick, K. (2014). Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sensing of Environment, 145, 105-115. https://doi.org/10.1016/j.rse.2014.01.009
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