Disturbance Regimes and Trends in Continental Spain (1985- 2023) Using Dense Landsat Time Series

Abstract

Forest disturbance regimes across biomes are changing differently due to contrasting effects of global change. Detailed quantitative data on historical disturbance events are necessary to establish baselines to assess change and to develop management alternatives to increase forest resilience. However, accurate data on forest disturbance over large spatial and temporal scales are scarce and difficult to obtain. Remote sensing is a powerful tool to fill this data gap, but it has historically faced challenges in detecting certain types of disturbances such as degradation which occurs with relatively low alterations of the forest cover. Recent advances enabled by the availability of Landsat analysis-ready imagery, the development of cloud computing platforms such as Google Earth Engine, and the implementation of time series analysis techniques have made it possible to overcome some of these challenges and improve degradation detection. However, the implementation of such methods in temperate Mediterranean transition regions remains scarce. In this study, we used dense Landsat time series and a novel forest monitoring algorithm, Continuous Change Detection and Classification - Spectral Mixture Analysis specifically designed to detect degradation, to monitor forest disturbances in continental Spain from 1985 to 2023. The algorithm was adapted separately for the temperate and the Mediterranean biomes. We characterised disturbance regimes and trends (patch size, severity, and frequency) at the national scale by biomes and forest type (broadleaf, needleleaf and mixed forests), and observed that disturbances are larger but less frequent and less severe in the Mediterranean than in the temperate biome. We also observed that disturbances are significantly larger and more severe in needleleaf forests than in mixed and broadleaf forests, despite the similar frequency for all forest types. Lastly, trends in size and severity are decreasing in Spain and in all biomes and forest types (except in broadleaf forests), while the frequency is increasing.

Keywords: Forest disturbance, degradation, global change, time-series analysis, CCDC-SMA, Mediterranean.