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Identifying spatially correlated patterns between surface water and frost risk using EO data and geospatial indices

Louka Panagiota, Papanikolaou Ioannis, Petropoulos Georgios, Kalogeropoulos Kleomenis, Stathopoulos Nikolaos

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/7E9F9C03-B4D9-4757-9060-E3068F083FE2
Έτος 2020
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά P. Louka, I. Papanikolaou, G. P. Petropoulos, K. Kalogeropoulos, and N. Stathopoulos, “Identifying spatially correlated patterns between surface water and frost risk using EO data and geospatial indices,” Water, vol. 12, no. 3, Mar. 2020. doi: 10.3390/w12030700 https://doi.org/10.3390/w12030700
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Περίληψη

Frost is one the most significant hazards affecting various aspects of human lives including infrastructure, agriculture, economy and biodiversity. Water bodies are one of the key factors controlling temperature fluctuations and frost. This study introduces a contemporary method for identifying and spatially analyzing frost risk and also explores its spatial correlation with water bodies. The proposed technique is based on coupling freely distributed geospatial data with a time series of land surface temperature (LST) data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. A region located in NW Greece, which annually suffers from very low temperatures and frost conditions and hosts important infrastructure and other human activities, was selected as a case study. In total, 5944 images were processed covering a 14-year long period. A frost frequency map of the study area was compiled along with two geospatial indices associated to distance from rivers/lakes (Hydro Distance Index—HDI) and from the seashore (Sea Distance Index—SDI). Their combined statistical and spatial correlation analysis indicated a protective buffer zone from frost at distances up to 20 km from sea and up to 5 km from lakes and rivers respectively, suggesting that the protective buffer zone depends on the water volume. Statistically, frost frequency was found to be positively correlated with both SDI (rs = 0.527) and HDI (rs = 0.145). Also, the effect of topography was examined in our analysis. Results showed that altitude and slope were moderately correlated to frost frequency; yet, the significance of the correlation was reported to be lower to SDI. Furthermore, the spatial autocorrelation analysis revealed a correspondence in the clustering of frost frequency maps with the HDI and SDI. Our findings demonstrate that water bodies are a major controlling factor for frost occurrence, by lowering frost frequency in water surrounding areas. Furthermore, it highlights the promising potential of our proposed methodology in quantifying frost effects, which can form a potentially useful tool assisting effective planning of protection measures and frost hazard mitigation in general.

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