Salinization is a common problem for agriculture in dryland environments and it has greatly affected land productivity and even caused cropland abandonment in Central and Southern Iraq. Hence it is of pressing importance to quantify the spatial distribution of salinity and its changing trend in space and time and ascertain the driving forces thereof. This study aims at such a diachronic salinity mapping and analysis using multitemporal remote sensing taking a pilot site, the Dujaila area in Central Iraq, as an example. For this purpose, field survey and soil sampling were conducted in the 2011–2012 period, and a multitemporal remote sensing dataset consisting of satellite imagery dated 1988–1993, 1998–2002, and 2009–2012 was prepared. An innovative processing approach, the multiyear maxima-based modeling approach, was proposed to develop remote sensing salinity models. After evaluation of their suitability, the relevant models were applied to the images for multitemporal salinity mapping, quantification, and change tracking in space and time. The driving causes of salinization in the study area were evaluated. The results reveal that the developed salinity models can reliably predict salinity with an accuracy of 82.57%, indicating that our mapping methodology is relevant and extendable to other similar environments. In addition, salinity has experienced significant changes in the past 30 years in Dujaila, especially, very strongly salinized land got continuously expanded, and all these changes are related to land use practices and management of farmers, which are closely associated with the macroscopic socioeconomic environment of the country.