A 250&thinsp;m annual alpine grassland AGB dataset over the Qinghai–Tibet Plateau (2000–2019) in China based on in situ measurements, UAV photos, and MODIS data

Zhang, Huifang; Tang, Zhonggang; Wang, Binyao; Kan, Hongcheng; Sun, Yi; Qin, Yu; Meng, Baoping; Li, Meng; Chen, Jianjun; Lv, Yanyan; Zhang, Jianguo; Niu, Shuli; Yi, Shuhua

doi:https://doi.org/10.5194/essd-15-821-2023

Articles | Volume 15, issue 2

https://doi.org/10.5194/essd-15-821-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue:

Extreme environment datasets for the three poles

https://doi.org/10.5194/essd-15-821-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 15, issue 2

Data description paper

|

14 Feb 2023

Data description paper |

| 14 Feb 2023

A 250 m annual alpine grassland AGB dataset over the Qinghai–Tibet Plateau (2000–2019) in China based on in situ measurements, UAV photos, and MODIS data

Huifang Zhang, Zhonggang Tang, Binyao Wang, Hongcheng Kan, Yi Sun, Yu Qin, Baoping Meng, Meng Li, Jianjun Chen, Yanyan Lv, Jianguo Zhang, Shuli Niu, and Shuhua Yi

Data sets

A 250 m annual alpine grassland AGB dataset over the Qinghai-Tibetan Plateau (2000-2019) based on in-situ measurements, UAV images, and MODIS Data H. Zhang, Y. Sun, Y. Qin, B. Meng, M. Li, J. Chen, Y. Lv, S. Niu, and S. Yi https://doi.org/10.11888/Terre.tpdc.272587

Short summary

The accuracy of regional grassland aboveground biomass (AGB) is always limited by insufficient ground measurements and large spatial gaps with satellite pixels. This paper used more than 37 000 UAV images as bridges to successfully obtain AGB values matching MODIS pixels. The new AGB estimation model had good robustness, with an average R² of 0.83 and RMSE of 34.13 g m². Our new dataset provides important input parameters for understanding the Qinghai–Tibet Plateau during global climate change.