2026-10-11T03:33:15Z https://www.scidb.cn/oai

10.57760/sciencedb.j00001.01815 2026-07-06T10:52:30Z

2026-07-06 Data and Code Availability Dataset for AI-Based Remote Sensing Research across Four Core Journals doi:10.57760/sciencedb.j00001.01815 en This dataset was compiled from publications indexed in the Web of Science Core Collection focusing on artificial intelligence in remote sensing, released prior to October 2025. All articles from three leading remote sensing journals (Remote Sensing, IEEE JSTARS and IEEE TGARS) with more than 50 relevant outputs were incorporated into the sample set. For comparative analysis, 181 papers sourced from even-numbered volumes (300–315, 2024) of Remote Sensing of Environment were further chosen as the control group, forming a final sample spanning four core journals in the discipline. Each article was manually annotated across dimensions including data and code availability statements (ASDC), open-access status and hyperlink availability. Data availability was graded on a six-tier scale and code availability on a five-tier scale, with respective rankings stretching from fully accessible to no ASDC disclosure. Geographically, the dataset is unrestricted by specific territorial boundaries and encompasses research outputs published over the latest decade. Rigorous quality assurance was implemented through exhaustive manual tagging and stratified sampling balanced by publication volume and temporal distribution. The curated dataset enables quantitative investigations into data and code sharing practices for remote sensing studies and underpins future research advancing academic transparency and experimental reproducibility. Remote Sensing; Artificial Intelligence; Research Data Sharing; Open Source Code; ASDC statement; Academic Transparency 赵斐 赖彦材 张红月 赵龙 李国庆 PUBLIC https://creativecommons.org/publicdomain/zero/1.0/ dataset Science Data Bank