Abstract
Abstract. Chestnut (Castanea sativa Mill.) managed forests in Galicia (Northwestern Spain) have important cultural, economic and ecosystem values. However, due to rural exodus chestnut stands are being degraded. In order to take restoration and conservation measures knowledge of these forests' location, expanse and stage is needed. The available Spanish official cartography is based on photointerpretation which is inaccurate in terms of chestnut forest location and classification. However, remote sensing has recently been proven to be an effective tool for this purpose. Sentinel 2 multi-temporal classification is recently acquiring importance as a method to classify tree species. This project intends to detect chestnut forests using LiDAR and Sentinel 2 multi-temporal data and to compare these results with those obtained using the official cartography. It also intends to assess how the use of different phenological stages could improve classification results. The results obtained provide an overall accuracy of 76% when a three-month combination is used: (March, July and September) leaf-off stage, flowering and leaf-on stage. Overlapping of the current map and the official cartography lead to an accuracy and precision increase; highlighting the utility of the presented methodology to acquire knowledge about chestnut forests location.
Highlights
Information about forest resource distribution remains essential for policy makers and land management
This study aims to classify areas covered by chestnut forests and to analyze the potential of using multi-temporal information for this purpose
Cross-validation of the results acquired by random forest modelling reveals differences between the results obtained when using different months as predictive variables
Summary
Information about forest resource distribution remains essential for policy makers and land management. Rural abandonment has led to stand degradation and to a loss of knowledge of their distribution These stands still have the potential to become an important source of income for rural areas and to keep providing ecosystem, recreational and cultural services (Roces-Díaz et al, 2018). The current official source of forest location, distribution, expanse and classification in Spain is the Spanish Forest Map (MFE). The Spanish cartographic official source (MFE) is elaborated through photointerpretation and field work on a 1:25000 scale (Miteco, 2014) It consists of a set of polygons where the type of forest, along with its principal and secondary species composition are indicated. When mapping chestnut forest stands, the method and resolution used can become a problem leading to surface overestimation or underestimation This compromises decision making when it comes to chestnut production or conservation measures
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