Climate change: vegetation and phenological phase dynamics. Issue 4 (8th July 2020)

• Record Type: Journal Article
• Authors: Li, Yang; Qin, Yaochen; Ma, Liqun; Pan, Ziwu
• Is Part Of: International journal of climate change strategies and management. Volume 12:Issue 4(2020)
• Page Start: 495
• Page End: 509
• Publication Date: 2020-07-08
• Subjects: MODIS-EVI -- S-G filter -- Growing season -- Change trend -- Climatic factors -- Loess Plateau; Climatic changes -- Periodicals; Environmental policy -- Periodicals; 363.73874
• DOI: 10.1108/IJCCSM-06-2019-0037
• Languages: English
• ISSNs: 1756-8692

Abstract

Abstract : Purpose: The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau. Design/methodology/approach: The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described. Findings: The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November. Originality/value: This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.