MAPS: A new model using data fusion to enhance the accuracy of high-resolution mapping for livestock production systems

• DOI: 10.1016/j.oneear.2023.08.012
• Publication Date: 2023-09-15T14:33:11Z
• Authors: Mingjin Cheng; Xin Liu; Hu Sheng; Zengwei Yuan

To meet growing demand for animal-based foods, livestock production has intensified to maximize output with limited resources and space. This increased the spatial heterogeneity of distribution, which in turn caused severe nutrient loss risk antimicrobial resistance, zoonotic disease, human exposure disease pollution. There is an urgent need spatially explicit impact assessments, but current methods lack resolution needed accurately map fine-scale distribution. Here we developed a mapping agricultural systems (MAPS) model by fusing enterprise registration information (ERI), can directly represent activities, other currently available data generate high-resolution mapping. Using example pig China, global leading producer, show that MAPS improves accuracy location/size estimates 12%–84%, illustrating 44% underestimation numbers dense farming areas (>1,000 pigs/km2) existing methods. also reveals transfer from rural peri-urban areas, implying more decoupled pig-crop China. enables assessments support sustainable planning intensive alleviate health risks.