Decadal to centennial land use and land cover change has been consistently singled out as a key element and an important driver of global environmental change, playing an essential role in balancing energy use. Understanding long-term human-environment interactions requires historical reconstruction of past land use and land cover changes. Most of the existing historical reconstructions have insufficient spatial and thematic detail and do not consider various land change types. In this context, this paper explored the possibility of using a cellular automata-Markov model in 90 m × 90 m spatial resolution to reconstruct historical land use in the 1930s in Zhenlai County, China. Then the three-map comparison methodology was employed to assess the predictive accuracy of the transition modeling. The model could produce backward projections by analyzing land use changes in recent decades, assuming that the present land use pattern is dynamically dependent on the historical one. The reconstruction results indicated that in the 1930s most of the study area was occupied by grasslands, followed by wetlands and arable land, while other land categories occupied relatively small areas. Analysis of the three-map comparison illustrated that the major differences among the three maps have less to do with the simulation model and more to do with the inconsistencies among the land categories during the study period. Different information provided by topographic maps and remote sensing images must be recognized.