Work

Analysis archive for: Integrating Earth observation, crop models, and knowledge- and physics-guided AI for crop yield forecasting

Year: 2026

Type: dataset

Abstract: Record ledger, search strings, screening and bibliometric code, canonical journal dictionary, Layer C comparison sheet, T/F coding, figure-generation scripts, protocol v9, and denominator-sensitivity tables. Manuscript-writing and table-generation code are not included. Official Web of Science and Scopus full-record exports are not included.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22181420

Author: Hasan, Umut

Institutions: Yili Normal University, East China Normal University

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDG: Zero hunger

Open Access status: green

OpenAlex ID: W7204734271

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