Explainable artificial intelligence framework for urban global digital elevation model correction based on the SHapley additive explanation-random forest algorithm considering spatial heterogeneity and factor optimization

MLA

Chuanfa Chen, et al. “Explainable Artificial Intelligence Framework for Urban Global Digital Elevation Model Correction Based on the SHapley Additive Explanation-Random Forest Algorithm Considering Spatial Heterogeneity and Factor Optimization.” International Journal of Applied Earth Observations and Geoinformation, vol. 129, no. 103843-, May 2024. EBSCOhost, https://doi.org/10.1016/j.jag.2024.103843.

APA

Chuanfa Chen, Yan Liu, Yanyan Li, & Dongxing Chen. (2024). Explainable artificial intelligence framework for urban global digital elevation model correction based on the SHapley additive explanation-random forest algorithm considering spatial heterogeneity and factor optimization. International Journal of Applied Earth Observations and Geoinformation, 129(103843-). https://doi.org/10.1016/j.jag.2024.103843

Chicago

Chuanfa Chen, Yan Liu, Yanyan Li, and Dongxing Chen. 2024. “Explainable Artificial Intelligence Framework for Urban Global Digital Elevation Model Correction Based on the SHapley Additive Explanation-Random Forest Algorithm Considering Spatial Heterogeneity and Factor Optimization.” International Journal of Applied Earth Observations and Geoinformation 129 (103843-). doi:10.1016/j.jag.2024.103843.