Next Article in Journal
A Highly Efficient Compressive Sensing Algorithm Based on Root-Sparse Bayesian Learning for RFPA Radar
Next Article in Special Issue
Mapping Vegetation Changes in Mongolian Grasslands (1990–2024) Using Landsat Data and Advanced Machine Learning Algorithm
Previous Article in Journal
Enhanced Prototypical Network with Customized Region-Aware Convolution for Few-Shot SAR ATR
Previous Article in Special Issue
Evolution and Spatiotemporal Response of Ecological Environment Quality to Human Activities and Climate: Case Study of Hunan Province, China
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing

1
Qinghai Institute of Technology, Xining 810016, China
2
Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
3
Key Laboratory of Ecohydrology of Inland River Basin/Gansu Qilian Mountains Ecology Research Center, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
4
Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
5
Key Laboratory of Western China’s Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, China
6
School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(19), 3565; https://doi.org/10.3390/rs16193565
Submission received: 11 August 2024 / Revised: 18 September 2024 / Accepted: 20 September 2024 / Published: 25 September 2024

Abstract

Frost events during the growing season can significantly impact vegetation function and structure. Solar-induced chlorophyll fluorescence (SIF) and the normalized difference vegetation index (NDVI) are two widely used proxies for measuring vegetation growth. However, the extent to which NDVI and SIF respond to frost events and how the responses vary under different temperature, precipitation, and shortwave radiation conditions are still unclear. In this study, spatially gridded meteorological data were employed to identify frost events during the growing season in the Third Pole. Subsequently, vegetation responses to the frost events were examined using remotely sensed SIF and NDVI data in different seasons in the Third Pole. During the growing season, the number of frost events declined faster from 2001 to 2009 than from 2010 to 2018. From 2001 to 2009, most alpine vegetation areas in the Third Pole exhibited greening trends. SIF exhibited a strong correlation with environmental factors and showed higher sensitivity to environmental factors compared to the NDVI. Over the past two decades, the impact of temperature and frost days on alpine vegetation has decreased while the impact of precipitation and radiation has increased. This suggests that the control mechanisms governing alpine vegetation are gradually shifting in response to ongoing climate change in the Third Pole. This study enhances our comprehension of frost changes in alpine regions during the growing season and enriches our understanding of how alpine vegetation responds to climate change.
Keywords: frost days; Alpine vegetation; GOSIF; NDVI; Third Pole frost days; Alpine vegetation; GOSIF; NDVI; Third Pole

Share and Cite

MDPI and ACS Style

Dong, C.; Wang, X.; Li, Z.; Xiao, J.; Zhu, G.; Li, X. Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing. Remote Sens. 2024, 16, 3565. https://doi.org/10.3390/rs16193565

AMA Style

Dong C, Wang X, Li Z, Xiao J, Zhu G, Li X. Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing. Remote Sensing. 2024; 16(19):3565. https://doi.org/10.3390/rs16193565

Chicago/Turabian Style

Dong, Caixia, Xufeng Wang, Zongxing Li, Jingfeng Xiao, Gaofeng Zhu, and Xing Li. 2024. "Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing" Remote Sensing 16, no. 19: 3565. https://doi.org/10.3390/rs16193565

APA Style

Dong, C., Wang, X., Li, Z., Xiao, J., Zhu, G., & Li, X. (2024). Spatial-Temporal Analysis of the Effects of Frost and Temperature on Vegetation in the Third Pole Based on Remote Sensing. Remote Sensing, 16(19), 3565. https://doi.org/10.3390/rs16193565

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