1990—2020年黄土高原典型县域植被覆盖变化及影响因素

doi:10.13866/j.azr.2024.01.14

Abstract

Abstract:

To explore the dynamic evolution of vegetation and its influencing factors in Ji County during the last 30 years, this study used Landsat images, along with meteorological, land use, and night light data. This study adopted trend, partial correlation, random forest, and residual analysis methods to explore the temporal and spatial variation-related characteristics in vegetation coverage and the influence of the climate and human factors on the vegetation changes in the County. (1) FVC in the study area demonstrated a significant upward trend from 1990 to 2020, with an annual growth rate of 0.49%, and the vegetation quality was distinctly higher. (2) The low and high rates of FVC had an obvious staggered spatial distribution. The proportion of areas with a marked enhancement in FVC was 51%, and a remarkable reduction in FVC was 7%. (3) Temperature and precipitation inhibited vegetation growth in the FVC high-value and built-up areas, but promoted vegetation cover in others. The contribution rates of climate change and human activities to vegetation dynamics were 53.43% and 46.57%, respectively, and were considered global influencing factors. When used as local variables, the relative contribution rates were reduced to 13.07%. Human activity was an essential factor affecting vegetation degradation in certain areas, such as the central and eastern parts of Jixian County, and the vegetation restoration in the west and south. This study can provide a scientific basis for the follow-up work of regional ecological restoration.

Key words: fractional vegetation cover, Google Earth Engine, climate change, human activity, Loess Plateau

ZHAO Yuqi, WEI Tianxing. Changes in vegetation cover and influencing factors in typical counties of the Loess Plateau from 1990 to 2020[J].Arid Zone Research, 2024, 41(1): 147-156.

Figures/Tables 10

Fig. 1

Tab. 1

Tab. 2

Contribution of climate factors and human activities to vegetation coverage"

驱动因素划分			驱动因素贡献率/%		分类结果
Slope_FVCobs	Slope_FVCcc	Slope_FVCres	气候变化	人类活动	分类结果
>0	>0	>0	$S l o p e F V C c c S l o p e F V C o b s$	$S l o p e F V C r e s S l o p e F V C o b s$	气候变化和人类活动
	>0	<0	100	0	气候变化
	<0	>0	0	100	人类活动
<0	<0	<0	$S l o p e F V C c c S l o p e F V C o b s$	$S l o p e F V C r e s S l o p e F V C o b s$	气候变化和人类活动
	<0	>0	100	0	气候变化
	>0	<0	0	100	人类活动

Tab. 2

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Tab. 3

Fig. 6

Fig. 7

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影响因素	名称	年份	数据来源	数据类别	分辨率
自然因素	气温	1990—2020年	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	逐月平均气温数据集	1 km
自然因素	降水	1990—2020年	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	逐月降水量数据集	1 km
人为因素	夜间灯光指数	1990—2020年	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	中国人工夜间灯光数据集	1 km
人为因素	土地利用	2000年，2018年	中国科学院资源环境科学与数据中心（https://www.resdc.cn/）	土地利用数据集	30 m

		气温	降水	土地利用	夜间灯光指数
单一要素重要性		0.76	0.13	0.04	0.07
组合因素贡献力	气温	0.62
	降水	0.71	0.38
	土地利用	0.63	0.55	0.51
	夜间灯光指数	0.66	0.44	0.5	0.07

Changes in vegetation cover and influencing factors in typical counties of the Loess Plateau from 1990 to 2020

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