A Statistical and Spatial Analysis of Portuguese Forest Fires in Summer 2016 Considering Landsat 8 and Sentinel 2A Data

Ana Teodoro,Ana Amaral

doi:10.3390/environments6030036

Abstract

Forest areas in Portugal are often affected by fires. The objective of this work was to analyze the most fire-affected areas in Portugal in the summer of 2016 for two municipalities considering data from Landsat 8 OLI and Sentinel 2A MSI (prefire and postfire data). Different remote sensed data-derived indices, such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR), could be used to identify burnt areas and estimate the burn severity. In this work, NDVI was used to evaluate the area burned, and NBR was used to estimate the burn severity. The results showed that the NDVI decreased considerably after the fire event (2017 images), indicating a substantial decrease in the photosynthesis activity in these areas. The results also indicate that the NDVI differences (dNDVI) assumes the highest values in the burned areas. The results achieved for both sensors regarding the area burned presented differences from the field data no higher than 13.3% (for Sentinel 2A, less than 7.8%). We conclude that the area burned estimated using the Sentinel 2A data is more accurate, which can be justified by the higher spatial resolution of this data.

Highlights

Europe’s Mediterranean forests have, in the last summers (2016–2017), been extremely affected by large and devastating fires [1,2,3]
Results indicate that Normalized Difference Vegetation Index (NDVI) values were significantly lower at the 95% confidence level for burned meadows following the fire date, yet not significantly lower at the 95% confidence level in the unburned meadows
The differenced Normalized Burn Ratio (dNBR) was computed in order to evaluate the burn severity

Summary

Introduction

Europe’s Mediterranean forests have, in the last summers (2016–2017), been extremely affected by large and devastating fires [1,2,3]. The high frequency at which forest fires have occurred in recent years in Portugal increase the need for a better interpretation and mapping of fire-damaged areas. In Portugal, in the summers of 2016 and 2017, several districts were devastated by forest fires, where hundreds of hectares were burnt, destroying goods and taking human lives. The identification of fire-affected areas should be done quickly, accurately, and at low cost in order to be effective. There is terminology associated with fire intensity, fire severity, and burn severity that should be introduced [4]. Fire intensity describes the physical combustion process of energy release from organic matter [5]. Several definitions of fire severity have been proposed in the literature, generally related to the degree of environmental change caused by fire [5,6]

Objectives

Methods

Results

Conclusion