Author(s):
Barbosa, Bruno ; Rocha, Jorge ; Costa, Hugo ; Caetano, Mário
Date: 2022
Persistent ID: http://hdl.handle.net/10362/133574
Origin: Repositório Institucional da UNL
Project/scholarship:
info:eu-repo/grantAgreement/FCT/3599-PPCDT/PCIF%2FSSI%2F0102%2F2017/PT;
Subject(s): Sentinel 2; Forest fires; NDVI; Vegetation changet; Fuel management; Materials Science(all); Instrumentation; Engineering(all); Process Chemistry and Technology; Computer Science Applications; Fluid Flow and Transfer Processes; SDG 15 - Life on Land
Description
Barbosa, B., Rocha, J., Costa, H., & Caetano, M. (2022). Uncovering Vegetation Changes in the Urban–Rural Interface through Semi-Automatic Methods. Applied Sciences, 12(5), 1-14. [2294]. https://doi.org/10.3390/app12052294 -----------Funding: This research was funded by Portuguese Foundation for Science and Technology, I.P. (FCT), under the framework of the Project “FORESTER—Data fusion of sensor networks and fire spread modelling for decision support in forest fire suppression” [name of funder] grant number PCIF/SSI/0102/2017. The APC was funded by the Research Unit UIDB/00295/2020 and UIDP/00295/2020.
Forest fires are considered by Portuguese civil protection as one of the most serious natural disasters due to their frequency and extent. To address the problem, the Fire Forest Defense System establishes the implementation of fuel management bands to aid firefighting. The aim of this study was to develop a model capable of identifying vegetation removal in the urban–rural interface defined by law for fuel management actions. The model uses normalised difference vegetation index (NDVI) of Sentinel-2 images time series and is based on the Welch t-test to find statistically significant differences between (i) the value of the NDVI in the pixel; (ii) the mean of the NDVI in the pixels of the same land cover type in a radius of 500 m; and (iii) their difference. The model identifies a change when the t-test points for a significant difference of the NDVI value in the ‘pixel’ as comparted to the ‘difference’ but not the ‘mean’. We use a moving window limited to 60 days before and after the analysed date to reduce the phenological variations of vegetation. The model was applied in five municipalities of Portugal and the results are promising to identify the places where the management of fuel bands was not carried out. This indicates which model could be used to assist in the verification of the annual management of the fuel bands defined in the law.
