Human thermal sensation over a mountainous area, revealed by the application of ANNs: the case of Ainos Mt., Kefalonia I
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ORIGINAL PAPER
Human thermal sensation over a mountainous area, revealed by the application of ANNs: the case of Ainos Mt., Kefalonia Island, Greece Stelios Maniatis 1 & Panagiotis T. Nastos 2
&
Kostas Moustris 3 & Iliana D. Polychroni 2 & Athanasios Kamoutsis 1
Received: 7 March 2020 / Revised: 14 July 2020 / Accepted: 11 August 2020 # ISB 2020
Abstract Mt. Ainos in Kefalonia Island, Greece, hosts a large variety of plant species, some of them endemic to the region. Because of its rich biodiversity, a large portion of the mountain area is designated as National Park and is protected from human activities such as hunting or logging. Therefore, the area presents a lot of opportunities for ecotourist activities, such as trekking, birdwatching, and mountain climbing. In order to estimate its touristic activities potential, it is essential to assess the mountain’s biometeorological conditions. To achieve that, the human thermal index PET (physiologically equivalent temperature) was used, which is based on a human energy balance model. However, it is difficult to get the specific meteorological data over mountainous areas (air temperature, humidity, wind speed, and global solar radiation), appropriate as input variables for PET modeling. In order to overcome this limitation, artificial neural networks (ANNs) were developed for the estimation of PET index in ten sites within the Ainos National Park. In the process, the spatiotemporal distributions of the PET thermal index were illustrated, taking into consideration the ANN modeling. The findings of the performed analysis shed light that Mt. Ainos offers the greatest touristic opportunities from May to September, when thermal comfort conditions appear. The study also proves that the highest frequency of thermal comfort appears within the aforementioned time period over the highest altitudes, while on the contrary, slightly warm class appears as the altitude decreases on both sides of the mountain. Keywords Ainos Mt. . Kefalonia Island . Greece . Human thermal comfort . Physiologically equivalent temperature . Tourism . Artificial neural networks
Introduction Mountain areas are characterized by their large variety of plant and animal species, as well as for comprising different types of landscapes, because of their topography and intense relief. Distinct ecologic niches inside a mountain environment are compressed into small horizontal distances (Price and Neville * Panagiotis T. Nastos [email protected] 1
Faculty of Crop Science, Laboratory General & Agricultural Meteorology, Agricultural University of Athens, 75 Iera Odos, 11855 Athens, Greece
2
Laboratory of Climatology and Atmospheric Environment, National and Kapodistrian University of Athens, University Campus, 15784 Athens, Greece
3
Department of Mechanical Engineering, University of West Attica, Campus 2, 250 Thivon & P. Ralli, 12244 Aigaleo, Greece
2003). Meteorological parameters such as temperature, radiation, and relative humidity change according to height, plant cover, and topographic characteris
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