Investigating the capability of LST, GPM, and TVDI data in climatic classification by De martonne method in Iran

Subject Areas : Geospatial systems development

asiyeh tayebi ¹ , mohammad hossein mokhtari ²

1 - Master of Remote Sensing and GIS, School of Humanities, University of Yazd, Iran
2 - Associate Professor, Faculty of Natural Resources and Desert Studies/Department of Arid and Desert Management/ Yazd University,

Received: 2022-06-24 Accepted : 2022-08-06 Published : 2024-09-29

Keywords: Climate, Modis, precipitation, De Martonne.,

Abstract :

Knowing the natural characteristics of each region, especially identifying the climate classification, plays an important role in planning and optimal use of resources. In determining the climate, data such as temperature and precipitation can be used for the zoning of climates; However, due to the fact that some areas do not have terrestrial synoptic stations, satellite data is used, which will be received at any time, place and without cost. The purpose of this research is to investigate the climate classification of Iran with satellite data, which was checked in accordance with the climate of De martonne and during the years 2016 to 2019, and in it, the MODIS sensor satellite products, LST indices, NDVI and GPM images from TRMM satellite were used. The TVDI index was calculated from the combination of the two mentioned indices. The parameters used in the De martonne climate map include the average temperature and annual precipitation, which were used as the inputs of the satellite De martonne due to the close relationship they showed with the satellite data used. In the Pearson correlation analysis between average parameters, precipitation with GPM and TVDI were in correlation of 0.52 and 0.56, respectively, and meteorological temperature and LST were in correlation of 0.90. The results of these data stated that between the De martonne method of weather station data and the De martonne relationship obtained from satellite data, the minimum correlation was rp=0.55 and the maximum rp=0.89 and the resulting zoning map From the maximum correlation, it showed Kappa=0.90; The highest climate level in both classifications belongs to the dry climate at about 70% and the lowest level is the Mediterranean climate with less than 5%