Understanding of the relationship between greenness change and physical geographic factors based on Geographical detector
Pang Jing1 Du Ziqiang2 Zhang Xiaoyu1
(1 College of Environmental Resource Science, Shanxi University, Taiyuan, 030006, China;
2 Institue of Loess Plateau, Shanxi University, Taiyuan 030006,China)
Abstract: An accurate quantitative assessment of the relationship between terrestrial vegetation and physical geographic factors is helpful to understand the driving mechanisms of greenness change inarid and semi-arid ecosystems. Previous studies were inadequate to quantify therelationship between physical geographic factors and greenness change, and only considered the independent role of single , therefore, limits exist in the interaction between the various factors. To address these issues, this study quantitatively analyses the interactive influence of physical geographical factors to vegetation change combining the Geographical Detector model based on spatial variance analysiswith geographical information system techniquesinXinJiang region,China.First,nine relevant parametersincluding mean annual precipitation, mean annual temperature, sunshine duration, mean annual wind velocity, DEM, slope and aspect, soil type and vegetation type data are selected as potential physical geographic factors of greenness change; Then, GIMMS NDVI3g data which are get from the Advanced Very High Resolution Radiometer during 1982 to 2011 were served as an indicator of vegetation activity; Last,the relationship between nine factors and greenness change is derived byrunning the Geographical Detector model. Results demonstrated that 1)precipitation, soil and vegetation types were identified as the leading factors, followed by temperature, duration of sunshine and DEM. 2) DEM enhanced the effect of soil type on NDVI, and both duration of sunshine and DEM enhanced the effect of temperature on NDVI, so duration of sunshine and DEM were auxiliary indicator. Our results brought new insights on greenness dynamics and could provide a basic reference for the local inhabitants and policy-makers to restore degraded aridand semi-arid ecosystems.
Key words: GIMMS NDVI3g data; Geographic Detector model; physical geographic factors; spatial consistence.