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Use of spatial interpolation methods in a GIS environment for mapping, critical for agricultural production, climatic parameters on the island of Crete

Karanikas Georgios

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Summary

Climate and meteorological phenomena are strongly linked to the social and economic life of a place. One of the main pillars of Crete's economy is the primary economic sector as we see at least 90,000 tones of olive oil produced per year and most of it exported to the rest of the country and the world. The development and maintenance of this sector is inextricably linked to climatic conditions, such as drought phenomena, for example, which leave a strong imprint on the island's olive oil production, while at the same time vineyards and many types of crops are also severely affected. We understand that it is very important to find methods and models to map the climatic data of the region spatio-temporally, as this will allow for more efficient research to be carried out by the sector in question, so that methods for the protection and improvement of agricultural production can be predicted and developed.The aim of this study is the spatio-temporal mapping of the climatic data that are critical for the agricultural production of Crete. The information recorded by meteorological stations, especially on the island of Crete, is rather limited as it is available from stations that are fixed but at the same time very dispersed. A main objective of this thesis is to compare and determine the choice of an appropriate spatial interpolation model for the optimal spatial representation of meteorological variables in GIS environment. The geostatistical methods used in this thesis are ordinary kriging, simple kriging, disjunctive kriging and co-kriging. The atmospheric parameters used are: mean annual temperature, minimum annual temperature, maximum annual temperature, mean annual rainfall and mean annual wind speed. The above climatic data come from a 3-year period, 2017, 2018 and 2019.In addition, a secondary variable, the Digital Elevation Model of Greece (DEM), was used. The results were evaluated using the cross-validation method.Finally, we present maps showing the distribution of land use for the island of Crete, in which we have isolated the areas that may be affected by the extreme values of minimum annual temperature, maximum annual temperature and average rainfall, which can be used as an example and help primary sectors to observe the agricultural areas affected by the phenomenon in question.

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