Driving Forces of Forest Expansion Dynamics across the Iberian Peninsula (1987–2017): A Spatio-Temporal Transect

Abstract

This study analyzes the spatio-temporal dynamics of the drivers of forest expansion in the Iberian Peninsula for the periods 1987–2002–2017 through a 185 km-wide north–south Landsat scene transect. The analysis has considered a variety of biogeographical regions [0–3500 m.a.s.l, annual rainfalls 150–2200 mm] and 30 explanatory variables. A rigorous map production at 30 m resolution, including detailed filtering methods and uncertainty management at pixel scale, provided high-quality land cover maps. The main forest expansion trajectories were related to explanatory variables using boosted regression trees. Proximity to previous forests was a key common factor for forest encroachment in all forest types, with other factors being distance to the hydrographic network, temperature and precipitation for broadleaf deciduous forests (BDF), precipitation, temperature and solar radiation for broadleaf evergreen forests (BEF) and precipitation, distance to province capitals, and solar radiation for needleleaf evergreen forests (NEFs). Results also showed contrasting forest expansion trajectories and drivers per biogeographic region, with a high dynamism of grasslands towards new forest in the Eurosiberian and the mountainous Mediterranean regions, a high importance of croplands as land cover origin of new forest in the Mesomediterranean, and increasing importance over time of socioeconomic drivers (such as those employed in the industry sector and the utilized agricultural area) in the Supramediterranean region but the opposite pattern in the Southern Mesomediterranean. Lower precipitation rates favored new NEFs from shrublands in the Thermomediterraean region which, together with the Northern Mesomediterranean, exhibited the highest relative rates of new forests. These findings provide reliable insights to develop policies considering the ecological and social impacts of land abandonment and subsequent forest expansion.

Abandoned Agricultural Areas: From Quantification to Qualification by Integration of GIS and Remote Sensing

“…In the following steps of the study, further biophysical variables will be included and, above all, they will be related to planning and infrastructural variables such as the distance from roads and inhabited centres. This qualitative analysis, although preliminary, gives us an indication of a very important aspect, namely that in this study area the abandonment (from a topographical point of view) was not concentrated at the highest altitudes and steepest slopes, which are those considered at greater risk [23,24]. Obviously the analysis is much simplified but the fact that it can be replicated in series within QGIS for all the layers and the possibility of replicating the scripts of RStudio directly within the same software, provide a speed of operations that do not create computational problems by increasing the number of variables to be considered.…”

Actas del XIX Congreso de Tecnologías de la Información Geográfica. TIG al servicio de los ODS Zaragoza, 12 a 14 de septiembre de 2022

“…Además, dicha estimación de las bandas del IRoc, apoyada en las imágenes multiespectrales de gran detalle en cubiertas específicas, podría revertir en la mejora de la corrección radiométrica de las imágenes de Sentinel-2 (y de otras plataformas como Landsat) para diferentes cubiertas, a falta de datos objetivos en la mayoría de los casos. De esta manera, podría mejorarse la elaboración de mapas de cubiertas del suelo (Alonso et al, 2021;González-Guerrero y Pons, 2020;Padial-Iglesias et al, 2022;Pucher et al, 2022) Las hipótesis de este trabajo es que, ante la falta de datos en los rangos espectrales del IRoc en las imágenes multiespectrales adquiridas desde UAS, la alternativa es la obtención de bandas sintéticas del IRoc a partir de algunas, o todas, las otras regiones captadas, y que la estimación de los valores puede realizarse con un razonable nivel de exactitud a partir de la correlación lineal múltiple con las bandas del visible y del IRc tomadas desde el mismo sensor en el mismo instante.…”