Variation in NDVI and its response to climate change and human activities in Gansu Province during 2000-2020

doi:10.7522/j.issn.1000-694X.2022.00162

Journal of Desert Research ›› 2023, Vol. 43 ›› Issue (4): 118-127.DOI: 10.7522/j.issn.1000-694X.2022.00162

Variation in NDVI and its response to climate change and human activities in Gansu Province during 2000-2020

Jianbing Lu¹(), Ke Ju², Weibin Liao³()

^1.Surveying and Exploration Institute of Geological and Mineral Exploration and Development Bureau of Gansu Province，Lanzhou 730060，China
^2.School of Public Health and Preventive Medicine，Monash University，Melbourne 3004，Australia
^3.West China School of Public Health / West China Fourth Hospital，Sichuan University，Chengdu 610041，China

Received:2022-09-07 Revised:2022-12-06 Online:2023-07-20 Published:2023-08-14
Contact: Weibin Liao

Abstract

Abstract:

As a vulnerable eco-environmental area， Gansu is the earliest province where the State Council implements the Grain to Green Program. It is of great significance to clarify the spatio-temporal variation characteristics of vegetation cover and its response to climate change and human activities in Gansu， as well as great value for the construction of ecological civilization and the realization of the sustainable development strategy. In this study， the generalized additional two-way fixed effects model was used to quantitatively evaluate the impact of human activities and climate change on vegetation changes， linear trend analysis and partial correlation analysis were also used to analyze the spatio-temporal variation characteristics of vegetation cover. The results showed that：（1） Vegetation NDVI showed an increasing trend in Gansu during 2000-2020， with a rate of 0.004·a^-1. Vegetation NDVI showed a significant upward trend in 81.43% of the area， while vegetation NDVI decreased significantly in 1.08% of the area， and the rest of area was found with no significant change. （2） NDVI of Gansu showed a better correlation with precipitation than with temperature； Temperature generally inhibit vegetation NDVI growth， while a significant and positive non-linear correlation is founded between NDVI and precipitation. （3） The regions where the NDVI increased caused by human activity were mainly located in in Central Gansu Loess Plateau and East Gansu Loess Plateau， with a contribution of 15.4%-48.6%； while the regions where the NDVI decreased caused by human activity were mainly located in Gannan Plateau， Hexi Corridor and Mazong Mountain. The results of this study can provide reference for assessing the vegetation cover change under the background of the Grain to Green Program in Gansu.

Key words: NDVI, Gansu Province, climate change, human activities, Generalized Additive Models, fixed effect

CLC Number:

X171.4

Jianbing Lu, Ke Ju, Weibin Liao. Variation in NDVI and its response to climate change and human activities in Gansu Province during 2000-2020[J]. Journal of Desert Research, 2023, 43(4): 118-127.

Figures/Tables 11

Fig.1 Geographical location and distribution of meteorological stations in Gansu

Table 1 Identification criterion and contribution calculation of the drivers of NDVI change

类型	$s l o p e (N D V I 预测)$	$s l o p e (N D V I 残差)$	气候变化的贡献度	人类活动的贡献度	说明
$s l o p e (N D V I 观测) > 0$	$> 0$	$> 0$	$s l o p e (N D V I 预测) s l o p e (N D V I 观测) × 100$	$s l o p e (N D V I 残差) s l o p e (N D V I 观测) × 100$	气候变化和人类活动各自导致植被覆盖增加的贡献度
	$> 0$	$< 0$	100	0	气候变化导致植被覆盖增加
	$< 0$	$> 0$	0	100	人类活动导致植被覆盖增加
$s l o p e (N D V I 观测) < 0$	$< 0$	$< 0$	$s l o p e (N D V I 预测) s l o p e (N D V I 观测) × 100$	$s l o p e (N D V I 残差) s l o p e (N D V I 观测) × 100$	气候变化和人类活动各自导致植被覆盖减少的贡献度
	$< 0$	$> 0$	100	0	气候变化导致植被覆盖减少
	$> 0$	$< 0$	0	100	人类活动导致植被覆盖减少

Table 1 Identification criterion and contribution calculation of the drivers of NDVI change

类型	$s l o p e (N D V I 预测)$	$s l o p e (N D V I 残差)$	气候变化的贡献度	人类活动的贡献度	说明
$s l o p e (N D V I 观测) > 0$	$> 0$	$> 0$	$s l o p e (N D V I 预测) s l o p e (N D V I 观测) × 100$	$s l o p e (N D V I 残差) s l o p e (N D V I 观测) × 100$	气候变化和人类活动各自导致植被覆盖增加的贡献度
	$> 0$	$< 0$	100	0	气候变化导致植被覆盖增加
	$< 0$	$> 0$	0	100	人类活动导致植被覆盖增加
$s l o p e (N D V I 观测) < 0$	$< 0$	$< 0$	$s l o p e (N D V I 预测) s l o p e (N D V I 观测) × 100$	$s l o p e (N D V I 残差) s l o p e (N D V I 观测) × 100$	气候变化和人类活动各自导致植被覆盖减少的贡献度
	$< 0$	$> 0$	100	0	气候变化导致植被覆盖减少
	$> 0$	$< 0$	0	100	人类活动导致植被覆盖减少

Fig.2 Annual change of maximal NDVI in Gansu Province during 2000-2020

Fig.3 Spatial distribution of maximal NDVI （A） in Gansu Province and its changing trend （B） during 2000-2020

Table 2 Areas and proportion of vegetation NDVI change in Gansu Province

分类标准	变化类型	面积占比/%
$s l o p e (N D V I) < 0 ? 且 ? P < 0.01$	极显著退化	0.59
$s l o p e (N D V I) < 0 ? 且 ? P < 0.05$	显著退化	0.49
$P > 0.05$	无显著变化	17.49
$s l o p e (N D V I) > 0 ? 且 ? P < 0.05$	显著改善	8.82
$s l o p e (N D V I) > 0 ? 且 ? P < 0.01$	极显著改善	72.61

Table 2 Areas and proportion of vegetation NDVI change in Gansu Province

分类标准	变化类型	面积占比/%
$s l o p e (N D V I) < 0 ? 且 ? P < 0.01$	极显著退化	0.59
$s l o p e (N D V I) < 0 ? 且 ? P < 0.05$	显著退化	0.49
$P > 0.05$	无显著变化	17.49
$s l o p e (N D V I) > 0 ? 且 ? P < 0.05$	显著改善	8.82
$s l o p e (N D V I) > 0 ? 且 ? P < 0.01$	极显著改善	72.61

Fig.4 Partial correlation coefficients of NDVI and climate factors in Gansu Province

Table 3 Goodness of fit of linear and non-linear models

模型	AIC	GCV	R²
线性	-2 030.514	0.008 79	0.961
非线性	-2 035.646	0.008 71	0.966

Table 4 Result of non-linear climate factors modeling

气象因子	EDF	P
气温	1	0.174
降水	3.081	<0.001

Table 5 Result of GAM model in different settings

变量	模型1	P	变量	模型2	P	变量	模型3	P
气温	-0.007	0.17	气温	-0.009 3	0.04	气温	-0.006 8	0.116 3
时间	0.044 1	0.001	时间	0.055 1	0.001	时间	0.053 4	0.001
截距	0.141	0.001	截距	0.15	0.001	截距	0.1397	0.001
R²	0.966		R²	0.984		R²	0.987

Fig. 5 The cumulative effects of precipitation on NDVI in Gansu Province under different settings

Fig.6 Contributions of climatic change and human activities to NDVI change under different settings in Gansu Province

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Variation in NDVI and its response to climate change and human activities in Gansu Province during 2000-2020

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