A Novel Interpolation Method for Soil Parameters Combining RBF Neural Network and IDW in the Pearl River Delta

• Published in: Agronomy (Basel) Vol. 14; no. 11; p. 2469
• Main Authors: Zhao, Zuoxi, Luo, Shuyuan, Zhao, Xuanxuan, Zhang, Jiaxing, Li, Shanda, Luo, Yangfan, Dai, Jiuxiang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2024
• Subjects: Accuracy; Agricultural management; Agricultural production; Agriculture; China; Climate change; Crop growth; Crop production; Crop yield; Crops; Data points; Environmental monitoring; Geospatial data; IDW; interpolation; Land use; Methods; Natural resources; neural network; Neural networks; Nitrates; Parameters; Precipitation; Radial basis function; RBF; Root-mean-square errors; Soil fertility; Spatial data; China; Pearl River Delta

Soil fertility is a critical factor in agricultural production, directly impacting crop growth, yield, and quality. To achieve precise agricultural management, accurate spatial interpolation of soil parameters is essential. This study developed a new interpolation prediction framework that combines...