Soares, C., Príncipe, A., Köbel, M., Nunes, A., Branquinho, C. & Pinho, P. (2018) Tracking tree canopy cover changes in space and time in High Nature Value Farmland to prioritize reforestation efforts.International Journal of Remote Sensing, 39(14), 4714-4726. DOI:10.1080/01431161.2018.1475777 (IF2017 1,782; Q2 Imaging Science & Photographic Technology)
In High Nature Value Farmland areas such as the woodlands locally known as ‘montado’, increasing tree cover is a nature-based solution to mitigate land degradation which leads to loss of productivity and increase susceptibility to climate change. In the Mediterranean dryland areas, native tree species such as Holm-oak provide important ecosystem services. Tree cover provides shadow and food for animals, contributes to soil organic matter and protects soil from erosion, increasing water infiltration and biodiversity, thus increasing woodlands’ resilience. However, Holm-oak trees are facing high mortality rates and low natural regeneration due to both environmental and anthropogenic factors, which call for reforestation actions. Yet, because of its high costs, reforestation must focus on the most degraded areas. Tracking tree canopy cover over space and time using remote-sensing techniques could allow land managers to understand which factors promote or hinder mortality, growth and regeneration at large spatial scales, and help to prioritize areas for restoration. Most studies evaluating tree cover use a space-for-time substitution, are rarely done over time, and address small areas, thus disregarding climate effects; those performing large-scale analysis (i.e. over space) of satellite images seldom provide ground-validated information. To overcome these limitations, this study uses satellite imagery to quantify spatial and temporal changes in tree cover. This was done relating normalized difference vegetation index (NDVI) to aerial photography photointerpretation, over a precipitation gradient in a Mediterranean dryland area. Dry-season NDVI was positively related with tree canopy cover changes, both over space and time. The spatial–temporal models developed here were then validated with independent data and applied over a large area to create regional maps of changes in Holm-oak canopy cover over space and time. Thus, NDVI based-data can be used in large-scale assessments of Holm-oak canopy cover. Our findings provide an important tool to improve forest management strategies, e.g. by enabling to map and quantify tree cover decline, and to prioritize areas for reforestation, thus improving ecosystem services delivery in Holm-oak woodlands, such as improving farmland productivity and resilience to climate change.