Spatio-Temporal Dynamics, Spatial Clustering and Forecasting of Selected Crop Production in Jharkhand, India

Abstract Agricultural production in Jharkhand exhibits substantial spatial and temporal heterogeneity, making district-level analysis important for crop planning and resource allocation. The present study examined the spatio-temporal dynamics and forecasted production of Arhar/Tur, Gram, Rapeseed & Mustard, and Wheat across 24 districts of Jharkhand using district-level Area, Production and Yield data for 2002-03 to 2022-23 obtained from the India Data Portal. The analysis integrated compound annual growth rate (CAGR), Mann-Kendall trend analysis, Sen’s slope estimation, ARIMA forecasting, Global Moran’s I, Local Indicators of Spatial Association (LISA), and Getis-Ord Gi* hotspot analysis. CAGR results revealed positive long-term growth in all districts for Gram, Rapeseed & Mustard, and Wheat, while Arhar/Tur recorded growth in 22 districts and decline in two districts. Rapeseed & Mustard recorded the highest mean CAGR (37.78%), whereas Wheat showed the lowest (10.14%). Mann-Kendall analysis indicated significant increasing trends in 58.3% of districts for Arhar/Tur, 87.5% for Gram, 100% for Rapeseed & Mustard, and 87.5% for Wheat. Wheat recorded the highest mean Sen’s slope (616.53), followed by Rapeseed & Mustard (500.32), Gram (434.19), and Arhar/Tur (324.91). Global Moran’s I indicated significant positive spatial autocorrelation only for Arhar/Tur. LISA and Gi* analysis identified crop-specific local clusters and hotspots, with the strongest spatial concentration observed for Arhar/Tur. ARIMA forecasting projected increasing production for Gram, Rapeseed & Mustard, and Wheat during 2023-24 to 2027-28, while Arhar/Tur remained approximately stable under the selected model. The findings demonstrate that temporal growth does not necessarily correspond with spatial concentration and highlight the importance of crop- and district-specific agricultural planning in Jharkhand.