Non-Integer Dimension of Seasonal Land Surface Temperature (LST)

Abstract

During few last years, climate change including global warming which is attributed to
 human activities and also its long-term adverse effects on the planet’s functions have
 been identified as the most challenging discussion topics which have arisen many
 concerns and efforts to find the possible solutions. Since the warmth arising from
 Earth’s landscapes affects the world’s weather and climate patterns, we decided to study
 the changes in the Land Surface Temperature (LST) patterns in different seasons
 through non-linear methods. Here, we particularly want to estimate the non-integer
 dimension and fractal structure of the land surface temperature. For this study, the
 (LST) data has been obtained during the daytime by the Moderate Resolution Imaging
 Spectroradiometer (MODIS) on NASA’s Terra satellite. Depending on what time of the
 year data has been collected, temperatures change in different ranges. Since equatorial
 regions remain warm, and Antarctica and Greenland remain cold, and also because
 altitude affects temperature, we selected Riley County in the U.S. state of Kansas,
 which does not belong to any of this type locations and we are interested to observe the
 seasonal changes in temperature in this county. The results of the present study show
 that the Land Surface Temperature (LST) belongs to the class of fractal process with
 non-integer dimension.