Annual vegetation maps in the Qinghai–Tibet  Plateau (QTP) from 2000 to 2022 based  on MODIS series satellite imagery

Zhou, Guangsheng; Ren, Hongrui; Zhang, Lei; Lv, Xiaomin; Zhou, Mengzi

doi:https://doi.org/10.5194/essd-17-773-2025

Articles | Volume 17, issue 2

https://doi.org/10.5194/essd-17-773-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-17-773-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 17, issue 2

Data description paper

|

28 Feb 2025

Data description paper |

| 28 Feb 2025

Annual vegetation maps in the Qinghai–Tibet Plateau (QTP) from 2000 to 2022 based on MODIS series satellite imagery

Guangsheng Zhou, Hongrui Ren, Lei Zhang, Xiaomin Lv, and Mengzi Zhou

Data sets

500 m annual vegetation maps of Qinghai Tibet Plateau (2000-2022) Guangsheng Zhou et al. https://doi.org/10.11888/Terre.tpdc.301205

MODIS/Terra Surface Reflectance 8-Day L3 Global 500 m SIN Grid V061 E. Vermote https://doi.org/10.5067/MODIS/MOD09A1.061

MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid V061 M. Friedl and D. Sulla-Menashe https://doi.org/10.5067/MODIS/MCD12Q1.061

A Dataset of Global Land Cover Validation Samples L. Liu et al. https://doi.org/10.5281/zenodo.3551995

The 30 m annual land cover datasets and its dynamics in China from 1985 to 2022 J. Yang and X. Huang https://doi.org/10.5281/zenodo.8176941

GLC_FCS30D: the first global 30-m land-cover dynamic monitoring product with fine classification system from 1985 to 2022 L. Liu et al. https://doi.org/10.5281/zenodo.8239305

Short summary

This study developed a new approach to long-time continuous annual vegetation mapping from remote sensing imagery, and mapped the vegetation of the Qinghai–Tibet Plateau (QTP) from 2000 to 2022 using the MOD09A1 product. The overall accuracy of continuous annual QTP vegetation mapping reached 83.3%, with the reference annual 2020 data reaching an accuracy of 83.3% and a kappa coefficient of 0.82. The study supports the use of remote sensing data to mapping long-time continuous annual vegetation.