Preprint Article Version 1 This version not peer reviewed

Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin

Version 1 : Received: 4 August 2017 / Approved: 8 August 2017 / Online: 8 August 2017 (08:42:54 CEST)

How to cite: Gengxi, Z.; Su, X.; Singh, V.P.; Ayantobo, O.O. Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin. Preprints 2017, 2017080030 (doi: 10.20944/preprints201708.0030.v1). Gengxi, Z.; Su, X.; Singh, V.P.; Ayantobo, O.O. Modeling NDVI Using Joint Entropy Method considering Hydro-Meteorological Driving Factors in the Middle Reaches of Hei River Basin. Preprints 2017, 2017080030 (doi: 10.20944/preprints201708.0030.v1).

Abstract

Terrestrial vegetation dynamics are closely influenced by a multitude of factors. This study investigated the relationships between vegetation patterns and their main influencing factors. The joint entropy method was employed to evaluate the dependence between normalized difference vegetation index (NDVI) and coupled variables in the middle reaches of Hei River basin. Based on the spatial distribution of mutual information, the whole study area was divided into five sub-regions. In each sub-region, nested statistical models were applied to model the NDVI on the grid and regional scales, respectively. Results showed that the annual average NDVI increased with a rate of 0.005/a in recent 11 years. In the desert regions, the NDVI increased significantly with an increase in precipitation and temperature, and high accuracy of retrieving NDVI model was obtained by coupling precipitation and temperature, especially in sub-region I. In the oasis regions, groundwater was also an important factor driving vegetation growth, and the rise of groundwater level contributed to the growth of vegetation. However, the relationship was weaker in artificial oasis regions (sub-region III and sub-region V) due to the influence of human activities, such as irrigation. The overall correlation coefficient between the observed NDVI and modeled NDVI was observed to be 0.97. Outcomes of this study are suitable for ecosystem monitoring, especially under the realm of climate change. Further studies are necessary and should consider more factors, such as runoff and irrigation.

Subject Areas

Joint entropy; NDVI; temperature; precipitation; groundwater depth; Hei River basin

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