Land serves as a vital production resource, and therefore land planning plays an important role in sustainable land‐use design. Iran includes large areas of the world's drylands, many of which are used as rangelands, and where the population has increased by 60% from 1985 to 2016. Further population increase in Iran would probably require more land resources to be allocated for human needs. However, the pace and patterns of these changes remain unclear. The aim of this study was to map land‐cover change from 1985 to 2016 and predict future land‐cover change in the Zayandehrood ecologic sub‐basins of Central Iran. By using multiseasonal LANDSAT imagery, we mapped land‐cover change with a Random Forest classifier for 1985, 1998, and 2016 with an overall accuracy of 80% for each period. Classification results revealed that from 1985 to 2016 residential areas doubled and industrial areas increased at the expense of rangelands. Our study also revealed cropland expansion at the expense of rangelands, cropland abandonment, and contraction of croplands due to residential and industrial development. Prediction of changes by 2036 with a multilayer perceptron neural network and Markov chain analysis showed further expansion of industries and residencies, particularly near the Ghamashlu Wildlife Refuge. Despite the partial restoration of rangelands in some parts of the world, our study provides evidence of ongoing rangeland degradation in Iran due to conversion to other land uses. Therefore, the study underscores the importance of sustainable land management of already cultivated areas and the development of strategies for the protection of global rangelands.

Land serves as a vital production resource, and therefore, land planning plays an important role in sustainable land-use design.Increasing the global population alters landscapes via land-use and land-cover change across different landscapes, including the drylands. Iran includes large areas of dryland, where the population increased by 60% from 1985 to 2016. Further population increase in Iran would require more land resources to be allocated for human needs. However, the pace and patterns of these changes remain unclear. The aim of this study was to map land-cover change from 1985 to 2016 and predict future land-cover change in the Zayandehrood ecologic sub-basins of Central Iran. By using multiseasonal Landsat imagery, nine thematic classes were mapped with a random forest classifier for 1985, 1998, and 2016 with an overall accuracy of 80% for each period. Classification results revealed that from 1985 to 2016 residential areas doubled and industrial areas increased at the expense of rangelands. Our study also revealed cropland expansion at the expense of rangelands, cropland abandonment and contraction of croplands due to residential and industrial development. Prediction of changes by 2036 with a multi-layer perceptron neural network and Markov chain analysis revealed further expansion of industries and residencies particularly nearby the protected areas such as Ghamashlu Wildlife Refuge. Predicted contraction of some degraded agricultural lands and concomitant agricultural expansion in the agricultural frontier by 2036, underscore the importance of sustainable land management in highly arid areas of Iran and improvement of the strategies for the protection of rangelands.