The Implications of Fire Management in the Andean Paramo: A Preliminary Assessment Using Satellite Remote Sensing

• Published in: Remote Sensing
• Main Authors: Pasquale Borrelli, Dolors Armenteras, Panos Panagos, Sirio Modugno, Brigitta Schütt
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2015
• Subjects: vegetation monitoring; Landsat; MODIS; FIRMS; image differencing; dNDVI; dNBR; land degradation; logistic regression analysis; Science; Q; Tundra
• Online Access: https://doi.org/10.3390/rs70911061; https://doaj.org/article/dfb7f76b0c794805902360a473eee4db

The upper ranges of the northern Andes are characterized by unique Neotropical, high altitude ecosystems known as paramos. These tundra-like grasslands are widely recognized by the scientific community for their biodiversity and their important ecosystem services for the local human population. Despite their remoteness, limited accessibility for humans and waterlogged soils, paramos are highly flammable ecosystems. They are constantly under the influence of seasonal biomass burning mostly caused by humans. Nevertheless, little is known about the spatial extent of these fires, their regime and the resulting ecological impacts. This paper presents a thorough mapping and analysis of the fires in one of the world’s largest paramo, namely the “Complejo de Páramos” of Cruz Verde-Sumapaz in the Eastern mountain range of the Andes (Colombia). Landsat TM/ETM+ and MODIS imagery from 2001 to 2013 was used to map and analyze the spatial distribution of fires and their intra- and inter-annual variability. Moreover, a logistic regression model analysis was undertaken to test the hypothesis that the dynamics of the paramo fires can be related to human pressures. The resulting map shows that the burned paramo areas account for 57,179.8 hectares, of which 50% (28,604.3 hectares) are located within the Sumapaz National Park. The findings show that the fire season mainly occurs from January to March. The accuracy assessment carried out using a confusion matrix based on 20 reference burned areas shows values of 90.1% (producer accuracy) for the mapped burned areas with a Kappa Index of Agreement (KIA) of 0.746. The results of the logistic regression model suggest a significant predictive relevance of the variables road distance (0.55 ROC (receiver operating characteristic)) and slope gradient (0.53 ROC), indicating that the higher the probability of fire occurrence, the smaller the distance to the road and the higher the probability of more gentle slopes. The paper sheds light on fires in the Colombian paramos and provides a solid ...