Spatial Distribution of Grain Yield in the Songnen Plain Agro-Pastoral Zone in Heilongjiang Province: A Study Using Geostatistics and Geographically Weighted Regression

Abstract

This study examines the spatial distribution of grain yield in the Songnen Plain Agro-Pastoral Zone in Heilongjiang Province from 2015, 2017, 2019 and 2021, using Kriging interpolation as the primary method. Ordinary Kriging (exponential kernel/semivariogram, step = 13) achieved optimal accuracy (RMSE = 0.856), outperforming Co-Kriging. Incorporating all covariates lowered precision due to weak spatial autocorrelation in slope and aspect, while limiting covariates to elevation and soil type improved results. Spatial patterns revealed a southwest-to-northeast gradient. Over time, yields increased notably in the southwest and northern areas, with Wudalianchi rising by 259.71%, but declining locally, such as a 12.20% drop in Shuangcheng. Environmental factors like slope and soil showed spatially heterogeneous influences, interacting with policies and socioeconomic variables. The grain yield center shifted slightly northward. Geographically Weighted Regression (GWR) further validated these spatial patterns. These findings provide valuable insights into covariate selection and spatial drivers, supporting more precise agricultural planning and management in the region.