Work

Annual 30 m land cover dataset on the Tibetan Plateau from 1990 to 2023

Year: 2025

Type: data-paper

Abstract: Accurate land cover data was fundamental for formulating sound land planning and sustainable development strategies. This study focused on the Tibetan Plateau (TP), a globally sensitive ecological area, and developed a locally tailored annual 30 m resolution land cover dataset from 1990 to 2023 (TPLCD). Leveraging the Google Earth Engine (GEE) platform for Landsat data processing, LandTrendr was employed to generate robust, high-precision training samples. Subsequently, random forest classification and spatiotemporal smoothing strategies were applied to precisely map the land cover dynamics of the TP. Rigorous validation through visual interpretation, authoritative third-party datasets (Geo-Wiki and GLCVSS), and thematic dataset cross-comparisons, revealed an overall accuracy of 84.8%, and a Kappa coefficient of 0.78, fully affirming the dataset's high reliability. This dataset provided invaluable empirical evidence for understanding the vulnerability and adaptability of the TP's ecosystem.

Source: Scientific Data

DOI: 10.1038/s41597-025-04759-6

Authors: Siya Li, Quansheng Ge, Fubao Sun, Qiulei Ji, Wenbin Liu, Ronggao Liu, Duanyang Xu, Zexing Tao

Institutions: Chinese Academy of Sciences, Institute of Geographic Sciences and Natural Resources Research, University of Chinese Academy of Sciences, Research Center for Eco-Environmental Sciences, State Key Laboratory of Resources and Environmental Information System

Language: English

Topic: Remote-Sensing Image Classification

Subfield: Media Technology

Field: Engineering

Domain: Physical Sciences

SDG: Life on land

Open Access status: gold

Estimated APC paid: $2,490

OpenAlex ID: W4408911512

Cites: 90

Cited by: 10

Related to: 10