Exploring the relationship between vegetation and dust-storm intensity (DSI) in China

doi:10.1007/s11442-016-1275-2

Abstract

Abstract:

It is difficult to estimate the effects of vegetation on dust-storm intensity (DSI) since land surface data are often recorded aerially while DSI is recorded as point data by weather stations. Based on combining both types of data, this paper analyzed the relationship between vegetation and DSI, using a panel data-analysis method that examined six years of data from 186 observation stations in China. The multiple regression results showed that the relationship between changes in vegetation and variance in DSI became weaker from the sub-humid temperate zone (SHTZ) to dry temperate zone (DTZ), as the average normalized difference vegetation index decreased in the four zones in the study area. In the SHTZ and DTZ zones, the regression model could account for approximately 24.9% and 8.6% of the DSI variance, respectively. Lastly, this study provides some policy implications for combating dust storms.

Key words: relationship, dust-storm intensity, land surface feature, northern China

Minghong TAN. Exploring the relationship between vegetation and dust-storm intensity (DSI) in China[J].Journal of Geographical Sciences, 2016, 26(4): 387-396.

Figures/Tables 8

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	SDSI	Spr_10	Sum_10	Spr_20	Sum_20	Spr_30	Sum_30	Spr_40	Sum_40	Spr_50	Sum_50
SDSI	1	-0.168	-0.272	-0.172	-0.273	-0.166	-0.273	-0.163	-0.271	-0.158	-0.263
Spr_10		1	0.666	0.968	0.674	0.945	0.658	0.928	0.647	0.895	0.621
Sum_10			1	0.648	0.967	0.628	0.932	0.624	0.909	0.602	0.853
Spr_20				1	0.702	0.987	0.695	0.974	0.687	0.943	0.660
Sum_20					1	0.690	0.977	0.691	0.959	0.671	0.904
Spr_30						1	0.710	0.995	0.708	0.979	0.697
Sum_30							1	0.718	0.993	0.718	0.969
Spr_40								1	0.724	0.990	0.717
Sum_40									1	0.727	0.982
Spr_50										1	0.741
Sum_50											1

Model		Non-standardized coefficients		Standardized coefficients	t	Sig.	Collinearity statistics
Model		B	Std. Error	Beta	t	Sig.	Tolerance	VIF
SHTZ	(Constant)	408.026	208.969		1.953	0.052
	LnSum_20	-58.358	24.968	-0.145	-2.337	0.020	0.936	1.068
	LnSpr_20	-15.210	27.548	-0.050	-0.552	0.581	0.430	2.326
	Sum_20STD	-0.008	0.266	-0.002	-0.029	0.977	0.852	1.174
	Spr_20STD	0.057	0.521	0.010	0.110	0.912	0.407	2.457
	Wind	1.867	1.016	0.126	1.838	0.068	0.759	1.318
	V_1983	133.383	19.339	0.427	6.897	0.000	0.936	1.068
SDTZ	(Constant)	2179.793	375.277		5.808	0.000
	LnSum_20	-245.668	56.350	-0.288	-4.360	0.000	0.626	1.598
	Lnspr_20	-112.639	83.428	-0.108	-1.350	0.178	0.427	2.341
	Sum_20STD	-1.764	0.733	-0.157	-2.406	0.017	0.639	1.566
	Spr_20STD	1.891	1.329	0.112	1.423	0.156	0.444	2.253
	Wind	0.002	0.009	0.009	0.167	0.868	0.993	1.007
	V_1983	113.965	48.431	0.126	2.353	0.019	0.952	1.050
DTZ	(Constant)	119.356	217.082		0.550	0.583
	LnSum_20	-113.267	62.578	-0.250	-1.810	0.071	0.141	7.094
	Lnspr_20	104.619	87.193	0.152	1.200	0.231	0.167	5.984
	Sum_20STD	0.852	0.695	0.143	1.225	0.221	0.198	5.053
	Spr_20STD	-2.589	1.327	-0.193	-1.951	0.052	0.274	3.644
	Wind	4.344	1.878	0.164	2.313	0.021	0.537	1.863
	V_1983	85.220	46.245	0.100	1.843	0.066	0.912	1.096
QTZ	(Constant)	1331.376	275.143		4.839	0
	LnSum_20	-245.585	70.107	-0.458	-3.503	0.001	0.19	5.251
	Lnspr_20	36.739	109.948	0.044	0.334	0.739	0.184	5.421
	Sum_20STD	0.93	1.166	0.072	0.798	0.426	0.396	2.524
	Spr_20STD	2.247	2.338	0.092	0.961	0.338	0.354	2.822
	Wind	-8.675	3.019	-0.184	-2.873	0.004	0.79	1.266
	V_1983	118.291	70.748	0.102	1.672	0.096	0.87	1.15

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