Climate-Driven Forecasting of Agricultural Land Cover Change in North Dakota’s Red River Valley Using Remote Sensing and Machine Learning

Abstract The Red River Valley (RRV) of North Dakota, a major agricultural hub in North America, has experienced notable shifts in crop patterns over recent decades. However, few studies have quantitatively examined how long-term climatic trends influence spatial changes in crop patterns or how these climate variables can be used to predict future agricultural land cover in this region. This study evaluates climate–agriculture dynamics from 1997 to 2023 and forecasts land cover changes for 2033 u