Vegetation coverage change and its influencing factors across the northwest region of China during 2000-2019

doi:10.7522/j.issn.1000-694X.2021.00200

Journal of Desert Research ›› 2022, Vol. 42 ›› Issue (4): 11-21.DOI: 10.7522/j.issn.1000-694X.2021.00200

Vegetation coverage change and its influencing factors across the northwest region of China during 2000-2019

Zhenliang Yin¹(), Qi Feng¹, Lingge Wang², Zexia Chen², Yabin Chang², Rui Zhu²

^1.Key Laboratory of Ecohydrology of Inland River Basin，Northwest Institute of Eco-Environment and Resources，Chinese Academy of Sciences，Lanzhou 730000，China
^2.Faculty of Geomatics / Nationl-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring / Gansu Provincial Engineering Laboratory for National Geographic State Monitoring，Lanzhou Jiaotong University，Lanzhou 730000，China

Received:2021-08-17 Revised:2021-11-21 Online:2022-07-20 Published:2022-08-29

Abstract

Abstract:

The problem of land desertification in northwest region of China is serious and the ecological environment is severe. It is of great significance to clarify the spatio-temporal variation characteristics and driving factors of vegetation cover in this area for ecological environment protection. In this study， MOD13A3 products in this area were used as the data source to obtain the NDVI sequence set from 2000 to 2019 through the maximum value synthesis method. Trend analysis， anomaly analysis， Hurst index， geographic detector， correlation analysis and residue analysis were used to analyze the spatiotemporal variation characteristics and impact factors of vegetation cover in the study area. The results showed that ：（1） In recent 20 years， the vegetation coverage in the study area showed an overall growth trend， with an increase rate of 0.0027·a^-1 and an average NDVI of 0.252. However， the growth rate of the Yellow River basin area （0.0062·a^-1） is higher than that of the semi-arid grassland area （0.0026·a^-1） and inland arid area （0.0018·a^-1）. （2） The vegetation coverage in the study area is on the rise， accounting for 55.77% of the total area， while the degraded area accounts for 3.76% of the total area. The increased land use types were mainly tillage， forest and grassland. The area with sustainable change trend of vegetation cover accounted for 31.87% of the total area， the sustainable improvement （17.04%） was greater than the sustainable degradation （1.27%）， and the growth and sustainable growth of the Yellow River basin area were the best. （3） The main contributing factors that affect the spatial distribution of vegetation cover are precipitation， temperature， sunshine and relative humidity in order of influence， but the influence degree of each sub-region is slightly different. The spatial distribution of arid areas in the Yellow River basin and inland is most affected by precipitation， and the semi-arid grassland is most affected by sunshine. （4） Vegetation cover changes is mainly driven by natural factors and human activities， and natural factors on the growth of vegetation role in promoting are greater than human activity， and natural factors on vegetation cover change in the rate of contribution are higher. The results of this study can provide reference for assessing the ecological environment change under the background of climate change in northwest China.

Key words: northwest region, NDVI, vegetation coverage change, influencing factor, GeoDetector, Hurst index

CLC Number:

X826

Zhenliang Yin, Qi Feng, Lingge Wang, Zexia Chen, Yabin Chang, Rui Zhu. Vegetation coverage change and its influencing factors across the northwest region of China during 2000-2019[J]. Journal of Desert Research, 2022, 42(4): 11-21.

Figures/Tables 16

Fig.1 Study area and land use types

Table 1 The determination criterion of driving factors and calculation method of contribution rate

Slope（实际值）	驱动因素	驱动因素的划分标准		驱动因素的贡献率
Slope（实际值）	驱动因素	Slope（NDVI_NA）	Slope（NDVI_HA）	自然因子	人类活动
>0	HA ＆ NA	>0	>0	$S l o p e (N D V I N A) S l o p e (实际值)$	$S l o p e (N D V I H A) S l o p e (实际值)$
	NA	>0	<0	100	0
	HA	<0	>0	0	100
<0	HA＆NA	<0	<0	$S l o p e (N D V I N A) S l o p e (实际值)$	$S l o p e (N D V I H A) S l o p e (实际值)$
	NA	<0	>0	100	0
	HA	>0	<0	0	100

Table 1 The determination criterion of driving factors and calculation method of contribution rate

Slope（实际值）	驱动因素	驱动因素的划分标准		驱动因素的贡献率
Slope（实际值）	驱动因素	Slope（NDVI_NA）	Slope（NDVI_HA）	自然因子	人类活动
>0	HA ＆ NA	>0	>0	$S l o p e (N D V I N A) S l o p e (实际值)$	$S l o p e (N D V I H A) S l o p e (实际值)$
	NA	>0	<0	100	0
	HA	<0	>0	0	100
<0	HA＆NA	<0	<0	$S l o p e (N D V I N A) S l o p e (实际值)$	$S l o p e (N D V I H A) S l o p e (实际值)$
	NA	<0	>0	100	0
	HA	>0	<0	0	100

Fig.2 Spatial distribution of mean NDVI during 2000-2019

Table 2 Statistical results of NDVI values of different land cover types in each subregion

	土地利用类型	NDVI均值	面积占比 /%	NDVI分级
	土地利用类型	NDVI均值	面积占比 /%	<0.2	0.2—0.4	0.4—0.6	0.6—0.8	>0.8
黄河流域片区	耕地	0.5197	21.56	0.98	19.63	48.86	28.95	1.57
	林地	0.7092	11.35	0.64	6.92	15.33	40.38	36.73
	草地	0.4959	53.45	6.13	32.25	26.16	27.92	7.54
	水域	0.3779	1.68	23.72	29.89	28.91	16.36	1.13
	建设用地	0.4575	2.78	6.17	32.23	39.36	21.94	0.30
	未利用地	0.2974	9.19	37.40	40.46	11.55	9.00	1.60
半干旱草原片区	耕地	0.4747	7.11	0.14	24.90	62.69	12.27	0.01
	林地	0.6020	1.54	1.82	11.42	29.39	49.21	8.16
	草地	0.3460	76.29	18.89	45.11	30.91	4.94	0.15
	水域	0.2908	1.05	37.46	36.92	22.75	2.84	0.03
	建设用地	0.4080	1.22	6.30	38.17	50.08	5.45	0.00
	未利用地	0.2604	12.78	49.46	29.55	15.37	5.54	0.09
内陆干旱片区	耕地	0.5106	4.49	4.48	19.69	43.53	30.89	1.42
	林地	0.4812	1.74	19.00	18.85	20.00	37.95	4.19
	草地	0.2731	27.69	50.09	26.07	13.18	9.06	1.60
	水域	0.1081	2.07	83.90	9.08	4.58	2.34	0.10
	建设用地	0.3638	0.47	31.07	22.62	28.73	17.17	0.42
	未利用地	0.0974	63.55	93.95	4.45	1.20	0.40	0.01

Fig.3 Annual variation trend of NDVI

Fig. 4 NDVI variation trend during 2000-2019

Table 3 The statistics results for Slope trend

等级	黄河流域片区		半干旱草原片区		内陆干旱片区		总体
等级	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%
11	2 446	0.38	236	0.08	2 545	0.11	5 227	0.16
12	5 064	0.80	1 199	0.40	10 242	0.43	16 505	0.49
13	19 806	3.11	16 212	5.40	67 968	2.82	103 986	3.11
14	62 099	9.75	64 994	21.64	1 225 958	50.93	1 353 051	40.46
15	220 899	34.69	152 987	50.94	846 164	35.16	1 220 050	36.48
16	173 282	27.21	54 022	17.99	167 009	6.94	394 313	11.79
17	153 234	24.06	10 655	3.55	87 044	3.62	250 933	7.50

Fig.5 Distribution for the persistence of NDVI variation trend

Table 4 Regional statistical results based on trend and persistence

等级	黄河流域片区		半干旱草原片区		内陆干旱片区		总体
等级	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%	面积/km²	比例/%
11	1 569	0.25	102	0.03	1 386	0.06	3 057	0.09
12	2 612	0.41	290	0.10	4 438	0.18	7 340	0.22
13	6 632	1.04	2 721	0.91	22 807	0.95	32 160	0.96
14	15 739	2.47	9 669	3.22	428 196	17.79	453 604	13.56
15	59 626	9.36	22 247	7.41	269 161	11.18	351 034	10.50
16	55 584	8.73	9 849	3.28	50 245	2.09	115 678	3.46
17	58 936	9.26	2 924	0.97	41 094	1.71	102 954	3.08
21	436 132	68.49	252 503	84.08	1 589 601	66.04	2 278 236	68.13

Table 5 The impact of natural factors on NDVI spatial distribution

区域	海拔	坡度	坡向	年均降水量	年均气温	年均日照时间	年均相对湿度	距离水域的距离
总体	0.0692	0.0886	0.0028	0.5728	0.1136	0.4063	0.4881	0.2027
黄河流域片区	0.2520	0.1816	0.0056	0.5264	0.4175	0.4677	0.4112	0.1487
半干旱草原片区	0.0712	0.1189	0.0103	0.6394	0.3836	0.6847	0.6051	0.2953
干旱内陆河片区	0.0973	0.0857	0.0013	0.3006	0.1104	0.1501	0.3072	0.1807

Fig.6 Spatial distribution of correlation between each factor and NDVI

Table 6 The area of significant correlation between NDVI and factors in different regions

区域	面积 /km²	降水/%		气温/%		日照/%		相对湿度/%
区域	面积 /km²	显著正相关	显著负相关	显著正相关	显著负相关	显著正相关	显著负相关	显著正相关	显著负相关
半干旱草原片区	300 305	74.51	0.02	0.04	4.52	1.71	2.85	4.00	0.57
黄河流域片区	636 830	60.23	0.15	2.78	0.58	0.54	2.82	2.90	0.85
内陆干旱片区	2 406 930	26.40	0.20	4.36	6.74	2.51	8.59	7.84	5.38
全区	3 344 065	37.16	0.18	3.67	5.37	2.06	6.98	6.56	4.08

Fig.7 Spatial distribution and main area percentage of the impacts of natural factors and human activities on vegetation cover change in study area during 2000-2019

Fig.8 Spatial distribution and main area percentage of driving factors of vegetation change in the study area during 2000-2019

Table 7 Statistics of contribution rate of natural factors and human activities in different regions

区域	植被变化面积/km²	贡献率
		0—20%		20%—40%		40%—60%		60%—80%		80%—100%
		人类活动	自然因子	人类活动	自然因子	人类活动	自然因子	人类活动	自然因子	人类活动	自然因子
半干旱草原片区	236 728	65.19	6.94	16.64	2.88	8.39	8.47	2.86	16.72	6.92	64.99
黄河流域片区	576 189	25.80	4.38	33.66	8.15	28.16	28.36	8.06	33.58	4.33	25.54
内陆干旱片区	1 186 471	22.45	8.46	31.67	11.69	25.90	26.06	11.60	31.57	8.38	22.22
全区	1 999 388	28.47	7.11	30.47	9.63	24.48	24.64	9.54	30.39	7.04	28.24

Fig.9 Spatial distribution of the contributions of natural factors and human activities on vegetation cover change in study area during 2000-2019

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Vegetation coverage change and its influencing factors across the northwest region of China during 2000-2019

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