Temporal-spatial monitoring of population growth with RS-GIS technology at Wasit province of Iraq

Abstract

In this study, the growth rate of the population in a spatial-temporal manner has been modeled and explored by relying on the data from remote sensing and using the analytical functions of the geographic information system in Wasit province of Iraq during the period from 2000 to 2020. WorldPop layers were used to prepare population maps and forecast it in 2025 with the help of artificial neural networks. The predictive model was highly accurate (R 2 = 0.98). The next step was to measure the relationship between the rate of population growth and the changes in water areas and the primary production of vegetation with the help of time series of satellite data, which showed the distribution of the population. It is denser in the central, northwestern and southeastern areas of Wasit province. Low density populations have higher frequency. While from 2015 onwards, the frequency of some population classes with higher density increased compared to lower densities. In general, the trend of changes in the average population in the study area has been completely linear. But the maximum annual population density changes were upward and nonlinear. Changes in the area of ​​deciles representing denser areas have increased and the area of ​​deciles representing less densely populated areas has faced a decrease. The results and findings of this study showed that NPP changes were less predictable compared to population density changes because it is a complex function of climatic and human factors. In the estimated population density map in 2025, dense population cores have been formed in the northeastern areas of Wasit province in the vicinity of the border areas with Iran.