Evaluate the Effect of Relative Humidity in the Atmosphere of Baghdad City urban expansion Using Remote Sensing Data

Abstract

The effects of land use/cover change are recognized as one of the challenges facing humans in the twenty-first century. In contrast to less developed regions, its characteristics are characterized by a variety of climatic conditions. The changes result in “Urban Heat Island”, in which the temperature in cities is higher than the temperature in the rest of the country. By monitoring the city of Baghdad for a short period, Baghdad's urbanization progressed quickly, which negatively affected the region’s climate through the decreasing of agricultural lands surrounding the area. Understanding the extent of effects on the environment is critical for long-term development. Climate change and environmental cleanup include making the right decisions and taking actions to reduce the detrimental impact of urbanization on both the urban population and ecosystems. As a result, we investigated the relationship between urbanization and relative humidity in Baghdad city, using remote sensing images and data downloaded from the European Center for Forecasting (ECMWF) for Baghdad city. By calculating several factors, such as relative humidity (RH), temperature (Ta), and evaporation, and confirming the changes observed in urban areas Landsat 5 and Landsat 8 images were processed and analyzed in the (ArcGIS 10.8) program for the years 2010 to 2020. The study proves that there is a clear association between growing urbanization and the relative humidity rate and how increase in building areas and the rate of increase in temperature rise in them. The purpose of this study is to assess the impact of relative humidity level on the microclimate of Baghdad city from 2010 to 2020, the built-up increased from 19.60% to 27.44%. While, NDVI calculation healthy vegetation has almost disappeared with its percentage going down from 0.05% to 0.00. This study compares the microclimates of two study areas: ancient and modern, both of which differ in terms of vegetation cover and urban distribution and is based on remote sensing data.