Next Article in Journal
The Impact of Climate and Land Use Change on Greek Centipede Biodiversity and Conservation
Previous Article in Journal
Land Unit Delineation Based on Soil-Forming Factors: A Tool for Soil Survey in Mountainous Protected Areas
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

A Large-Language-Model-Based Dataset of Plant Species for Green Roofs in China

1
College of Computer Science, Beijing University of Technology, Beijing 100124, China
2
Green Intelligence Environmental School, Yangtze Normal University, Chongqing 408100, China
3
Department of Information Science and Technology, Shihezi University, Shihezi 832000, China
*
Authors to whom correspondence should be addressed.
Land 2025, 14(8), 1684; https://doi.org/10.3390/land14081684
Submission received: 23 July 2025 / Revised: 14 August 2025 / Accepted: 19 August 2025 / Published: 20 August 2025

Abstract

As urbanization accelerates, a host of negative ecological impacts have become increasingly prominent. Green roofs, as a sustainable solution, can effectively mitigate the urban heat island effect and reduce carbon footprints. However, the lack of datasets on plant species suitable for green roofs in China has hindered the advancement of relevant research and practical applications. Therefore, this study constructed a diversified dataset of plant species for green roofs in China, using data sources from the China National Knowledge Infrastructure (CNKI) and Web of Science (WoS). Generated by integrating the Kimi large language model (Kimi LLM) API with knowledge graph technology, the dataset contains 2248 plant records. It specifically includes a statistical CSV file with detailed plant information, a CSV file of species combinations, a CSV file linking plant combinations to cities, and original plant data extracted from research papers. Technical experiments have validated the accuracy and efficiency of this dataset in acquiring plant species. Suitable for plant selection in green roof projects, this dataset will provide strong support for in-depth research and wider applications in the field of urban sustainability.
Keywords: green roofs; plant species dataset; Kimi LLM; knowledge graph; urban sustainability green roofs; plant species dataset; Kimi LLM; knowledge graph; urban sustainability

Share and Cite

MDPI and ACS Style

Han, H.; Liu, X.; Lin, S.; Chang, Y.; Ding, S.; Zhang, J. A Large-Language-Model-Based Dataset of Plant Species for Green Roofs in China. Land 2025, 14, 1684. https://doi.org/10.3390/land14081684

AMA Style

Han H, Liu X, Lin S, Chang Y, Ding S, Zhang J. A Large-Language-Model-Based Dataset of Plant Species for Green Roofs in China. Land. 2025; 14(8):1684. https://doi.org/10.3390/land14081684

Chicago/Turabian Style

Han, Haoyu, Xiliang Liu, Shaofu Lin, Yumiao Chang, Shimin Ding, and Jing Zhang. 2025. "A Large-Language-Model-Based Dataset of Plant Species for Green Roofs in China" Land 14, no. 8: 1684. https://doi.org/10.3390/land14081684

APA Style

Han, H., Liu, X., Lin, S., Chang, Y., Ding, S., & Zhang, J. (2025). A Large-Language-Model-Based Dataset of Plant Species for Green Roofs in China. Land, 14(8), 1684. https://doi.org/10.3390/land14081684

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop