Noninteger Dimension of Seasonal Land Surface Temperature (LST)

During the few last years, climate change, including global warming, which is attributed to human activities, and its long-term adverse effects on planet’s functions have been identified as most challenging discussion topics provoked significant concern effort find possible solutions. Since warmth arising from Earth’s landscapes affects world’s weather patterns, we decided study changes in Land Surface Temperature (LST) patterns different seasons through nonlinear methods. Here, particularly wanted estimate noninteger dimension fractal structure of Temperature. For this study, LST data were obtained during daytime by a Moderate Resolution Imaging Spectroradiometer (MODIS) NASA’s Terra satellite. Depending time year collected, temperatures changed ranges. equatorial regions remain warm, Antarctica Greenland cold, also because altitude temperature, selected Riley County US state Kansas, does not belong any these location types, observed seasonal temperature county. According our analysis, may provide complexity index characterize datasets. The multifractal analysis confirmed that define self-organizing system produces data. Thus, only wide range dimensions, but they are fractal. results present show belongs class processes with dimension. Moreover, self-organized behavior governing an underlying principle might be general outcome activities shape surface temperature. We explicitly acknowledge important role geometry when analyzing tracing settlement urbanization dynamics at various scales toward purposeful planning development patterns.