Year: 2026
Type: dataset
Abstract: An Integration Framework for Agricultural AnalyticsVersion 0.1.0Description Assembles agricultural analyses around a single unit of observation, the management unit within a season, and keeps climate, soil and remote-sensing covariates aligned to it.Covariates are aggregated over phenological windows derived from accumulated growing degree days rather than calendar months, following McMaster and Wilhelm (1997) <doi:10.1016/S0168-1923(97)00027-0>.Models are validated with spatial resampling by default, since random cross-validation inflates apparent skill when observations are spatially autocorrelated, as shown by Roberts and others (2017) <doi:10.1111/ecog.02881>.Prediction intervals use split conformal inference after Lei and others (2018) <doi:10.1080/01621459.2017.1307116>.
Author: Muhammad Farooqi
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
OpenAlex ID: W7204253466