Drought has turned into a major problem in the world in the recent two decades, especially in arid and semi-arid regions and therefore, its detection and analysis has become more important. Remote sensing drought indices have been widely used to monitor drought. In this thesis, Iran, as a case study, was selected and classified into 6 different climates using De Martonne aridity index. Then, three remote sensing indicators called Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) were obtained through the Google Earth Engine platform from satellite imagery acquired from 2010 to 2021, and separately applied over each climate. A combined indicator called Scaled Drought Condition Index (SDCI) has been also defined by combining those three indices. Results have shown that the country has experienced drought many times during the defined time interval as well a severe drought which has started in January 2020. Results have also shown that different climates have different behavior against precipitation deficit: humid and semi-arid climates are not hardly affected by loss of precipitation compared to other climates. This study has also explored the European Drought Observatory (EDO) and Global Drought Observatory (GDO) of Copernicus Emergency Management Service (CEMS). GDO detects the risk of impact for agriculture for each country by considering vulnerability, exposure and hazard. The advantage of the methodology applied in this thesis is the possibility to directly detect the drought and its severity for a region.
La siccità ha rappresentato un grave problema nel mondo negli ultimi due decenni, soprattutto nelle regioni aride e semi-aride e, pertanto, è importante conoscerla e analizzarla. Gli indici di siccità ottenuti con tecniche di telerilevamento sono ampiamente utilizzati per monitorare questo fenomeno. In questa tesi, l'Iran, che è stato considerato come caso di studio, è stato classificato in 6 diversi tipi di clima utilizzando l'indice di aridità di De Martonne. Tre indicatori, Precipitation Condition Index (PCI), Vegetation Condition Index (VCI) e Temperature Condition Index (TCI) sono stati ottenuti tramite la piattaforma Google Earth Engine da immagini satellitari acquisite dal 2010 al 2021 e applicati separatamente a ciascuna zona climatica. Combinando questi tre indici è stato anche definito un indicatore combinato chiamato Scaled Drought Condition Index (SDCI). I risultati hanno mostrato che il paese ha sperimentato più volte la siccità durante l'intervallo di tempo considerato e una grave siccità è iniziata a gennaio 2020. I risultati hanno anche mostrato che climi diversi hanno comportamenti diversi rispetto al deficit di precipitazioni: i climi umidi e semi-aridi difficilmente risentono di precipitazioni scarse rispetto ad altri climi. In questo studio sono stati anche presi in considerazione l'Osservatorio europeo sulla siccità (EDO) e l'Osservatorio globale sulla siccità (GDO) di Copernicus Emergency Management Service (CEMS). GDO rileva il rischio di siccità per l'agricoltura per ogni Paese considerando vulnerabilità, esposizione e pericolosità. Il vantaggio della metodologia applicata in questa tesi è la possibilità di rilevare direttamente la siccità e la sua gravità per una determinata regione.
Spatiotemporal drought analysis with De Martonne Climate Classification through Google Earth Engine Platform : a case study in Iran
Taheri Qazvini, Adel
2020/2021
Abstract
Drought has turned into a major problem in the world in the recent two decades, especially in arid and semi-arid regions and therefore, its detection and analysis has become more important. Remote sensing drought indices have been widely used to monitor drought. In this thesis, Iran, as a case study, was selected and classified into 6 different climates using De Martonne aridity index. Then, three remote sensing indicators called Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI) were obtained through the Google Earth Engine platform from satellite imagery acquired from 2010 to 2021, and separately applied over each climate. A combined indicator called Scaled Drought Condition Index (SDCI) has been also defined by combining those three indices. Results have shown that the country has experienced drought many times during the defined time interval as well a severe drought which has started in January 2020. Results have also shown that different climates have different behavior against precipitation deficit: humid and semi-arid climates are not hardly affected by loss of precipitation compared to other climates. This study has also explored the European Drought Observatory (EDO) and Global Drought Observatory (GDO) of Copernicus Emergency Management Service (CEMS). GDO detects the risk of impact for agriculture for each country by considering vulnerability, exposure and hazard. The advantage of the methodology applied in this thesis is the possibility to directly detect the drought and its severity for a region.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/188454