Using Landsat 8 imagery in detecting cork oak (Quercus suber L.) woodlands: a case study in Calabria (Italy)
Giuseppe Modica, Francesco Solano, Angelo Merlino and 4 more
Journal of Agricultural Engineering · 2016
doi:10.4081/jae.2016.571 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
In the Mediterranean basin, cork oak (Quercus suber L.) woodlands are characteristic and widespread forestry ecosystems. Though presenting significant economic potential as a renewable resource, they are not adequately valorised, in spite of a growing market demand for cork and cork-based products, which are appreciated, today, for their use in sustainable building. In this respect, cork meets the needs of the building industry in responding to the growing demand for quality products, which are eco- and energy-friendly and hygienically safe. Moreover, European cultural and biodiversity value has been attributed to cork oak woodlands and their most significant examples have been included in the Natura 2000 framework. So far, in some countries like Italy, the territorial distribution and characterisation of cork oak woodlands have not been adequately investigated. This study provides a method for mapping the actual presence of cork oak woodlands and for assessing their potential distribution. Special attention was given to the characterisation of cork oak spectral signature. To this end, Landsat 8 satellite images, digital photointerpretation and in situ surveys were implemented. The work carried out allows assessing the effectiveness of GIS and remote sensing techniques coupled with ancillary data and tools, and their applicability for the development of a comprehensive mapping and monitoring system of cork oak woodlands in Mediterranean ecosystems. Such techniques are vital to develop a detailed management strategy and to assist restoration activities and the economic assessment of semi-natural habitats. A case study, carried out in two different locations in Calabria (Italy), is provided.
Abstract licence: CC BY-NC
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.