Mapping Chestnut Stands Using Bi-Temporal VHR Data
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Marchetti, Francesca; Waske, Björn; Arbelo, Manuel; Moreno Ruiz, José Andrés; Alonso Benito, AlfonsoFecha
2019-10-31Resumen
This study analyzes the potential of very high resolution (VHR) remote sensing images and extended morphological profiles for mapping Chestnut stands on Tenerife Island (Canary Islands, Spain). Regarding their relevance for ecosystem services in the region (cultural and provisioning services) the public sector demand up-to-date information on chestnut and a simple straight-forward approach is presented in this study. We used two VHR WorldView images (March and May 2015) to cover different phenological phases. Moreover, we included spatial information in the classification process by extended morphological profiles (EMPs). Random forest is used for the classification process and we analyzed the impact of the bi-temporal information as well as of the spatial information on the classification accuracies. The detailed accuracy assessment clearly reveals the benefit of bi-temporal VHR WorldView images and spatial information, derived by EMPs, in terms of the mapping accuracy. The bi-tempora...
Palabra/s clave
WorldView
bi-temporal image
extended morphological profiles
random forest
Canary Islands