From statistics to grids: A two-level model to simulate crop pattern dynamics

Crop planting patterns are an important component of agricultural land systems. These have been significantly changed due to the combined impacts climatic changes and socioeconomic developments. However, extent these their possible on environment, terrestrial landscapes rural livelihoods largely unknown lack spatially explicit datasets including crop patterns. To fill this gap, study proposes a new method for spatializing statistical data generate multitemporal pattern datasets. This features two-level model that combines land-use simulation simulation. The output first level is spatial distribution cropland, which then used as input second level, allocates censuses individual gridded cells according certain rules. was tested using from 2000 2019 Heilongjiang Province, China, validated remote sensing images. results show has high accuracy area spatialization. Spatial over given time period can be supplementary information thus support wide range application in