Analysis of spatiotemporal variation of sparse vegetation net primary productivity and meteorological factors

doi:10.13474/j.cnki.11-2246.2022.0067

Abstract

Abstract: Based on the improved CASA model,this paper uses methods containing spatial analysis,correlation analysis,and geographical detector model to explore the spatiotemporal pattern of the vegetation net primary production (NPP) in the Gurbantunggut desert from 2001 to 2018,and reveals the climate forcing factors of NPP and their impacts in the study area.The results of this paper show that:①In the past 18 years,the change of vegetation NPP in the Gurbantunggut desert showes a fluctuating increasing trend,with the growth rate of 0.56 gC· a^-1,and the average NPP is 46.90 gC· m^-2· a^-1.②From 2001 to 2018,the average annual NPP showes a spatial distribution pattern of increasing from northwest to southeast,and it is stable in the hinterland of the desert and more active around.③NPP in the Gurbantunggut desert is mainly affected by precipitation and is positively correlated with precipitation and temperature.In terms of the forcing analysis of each factor,precipitation (0.614 4) is the dominant factor restricting the growth of desert vegetation.

Key words: net primary productivity;remote sensing;CASA model;precipitation;temperature

CLC Number:

P237

YAN Linan, WANG Xinjun, CHEN Bei, CHANG Mengdi, LI Na. Analysis of spatiotemporal variation of sparse vegetation net primary productivity and meteorological factors[J]. Bulletin of Surveying and Mapping, 2022, 0(3): 1-6.

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