Publications

Zheng, LL; Li, DH; Xu, JH; Xia, ZL; Hao, HC; Chen, ZS (2022). A twenty-years remote sensing study reveals changes to alpine pastures under asymmetric climate warming. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 190, 69-78.

Abstract
Meteorological records over the past five decades have shown that climate warming has been faster during the nighttime than during the daytime. However, the responses of vegetation development to asymmetric warming are not well understood due to the misinterpretation of phenology that have resulted from the snowmelt effect. We applied normalized difference vegetation index (NDVI) sources from Global Inventory Modeling and Mapping Studies (GIMMS:1982-2015) and Moderate Resolution Imaging Spectroradiometer (MODIS: 2000-2020) to reveal maximum greenness in high-mountain Asia (HMA). The snow-free normalized difference phenology index (NDPI), which is a 3-band vegetation index that designed to best contrast vegetation from soil and snow, was applied for estimating the start of the growing season (SOS). We found that alpine pastures in HMA generally became greener and the SOS was delayed. Preseason daytime temperatures (Tday) and nighttime temperatures (Tnight) had opposite effects on maximum greenness, with Tday being negative and Tnight being positive. The responses of SOS to Tday and Tnight were highly related with the frequency of meteorological drought events during 2000-2020. In regions with lower frequency of drought events, both daytime and nighttime warming could advance SOS. In regions with higher frequency of drought events, daytime warming could delay SOS, but nighttime warming could advance SOS. The results of our study are of great significance to understand the responses of alpine ecosystems to asymmetric climate warming. Such an understanding is quite valuable for pasture management and future vegetation climate projections.

DOI:
10.1016/j.isprsjprs.2022.06.001

ISSN:
1872-8235