Satellite Remote Sensing of Forest Degradation using NDFI and the BFAST Algorithm

Abstract

In this paper, results related with the assessment of the capabilityto detect forest degradation by analyzing NDFI time series through the BFAST algorithm are presented. Recent studies have shown the potential of the BFAST algorithm applied to a time-series of satellite-derived spectral indices such as NDVI or EVI to detect unambiguous and subtle perturbations of the forest cover canopy both positive (e.g. regeneration) and negative (e.g. deforestation). Similarly, these results suggest the feasibility to distinguish between several types of forest degradation and their causal agents such as selective logging and forest fire. In this context, the results derived from this research show that using NDFI as a data source in the BFAST algorithm improves the detection of forest degradation, and additionally provides information to understand both temporal and spatial approaches related with the dynamics of perturbations of the forest canopy.

Más información

Título según WOS: Satellite Remote Sensing of Forest Degradation using NDFI and the BFAST Algorithm
Título según SCOPUS: Satellite Remote Sensing of Forest Degradation using NDFI and the BFAST Algorithm
Título de la Revista: IEEE Latin America Transactions
Volumen: 18
Número: 7
Editorial: IEEE Computer Society
Fecha de publicación: 2020
Página final: 1295
Idioma: Spanish
DOI:

10.1109/TLA.2020.9099771

Notas: ISI, SCOPUS