2001—2023年新疆NDVI时空格局与驱动力分析

doi:10.13866/j.azr.2025.05.14

Abstract

Abstract:

Based on the Normalized Difference Vegetation Index (NDVI) from 2001 to 2023, the temporal and spatial variation trend of NDVI in Xinjiang, China was explored, and the NDVI driving factors were explored by using the optimal parameter geodetector. The results showed that: (1) From 2001 to 2023, the annual average NDVI in Xinjiang was relatively low, ranging from 0.087 to 0.106. The overall trend showed a fluctuating upward trend, and the vegetation coverage improved. The area with slightly significant or above increased accounted for 52.12%. (2) In terms of spatial distribution, NDVI has obvious heterogeneity, which is characterized by ‘high in northwest and low in southeast’. NDVI is relatively stable as a whole, and the weak variation area accounts for 60.64%, mainly distributed in the basin area. In the future trend of vegetation change, the area from improvement to degradation accounted for 58.24%, indicating that the overall vegetation cover in Xinjiang may show a negative trend in the future. (3) NDVI is mainly affected by vegetation type, land use type and soil type which are the main driving factors of vegetation change in Xinjiang. Under the two-factor interaction, the q value was the highest after the interaction of vegetation type and soil type, while the Palmer Drought Severity Index (PDSI) and radiation had the least impact on NDVI.

Key words: NDVI, optimal parameter, geographic detector, driving factors, Xinjiang

CHEN Zhen, CAI Zhaozhao, MA Nan, DAI Shuo, WANG Zhenlu. Spatial-temporal pattern and driving force analysis of NDVI in Xinjiang from 2001 to 2023[J].Arid Zone Research, 2025, 42(5): 922-932.

Figures/Tables 13

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数据	数据来源	数据说明
MODIS MOD13Q1（NDVI）	美国国家航空航天局（https://www.nasa.gov/）	分辨率为250 m，时间序列为2001—2023年
PDSI	TerraClimate（https://www.climatologylab.org/）	分辨率为0.04°，时间序列为2001—2023年
土壤湿度	TerraClimate（https://www.climatologylab.org/）	分辨率为0.04°，时间序列为2001—2023年
辐射	TerraClimate（https://www.climatologylab.org/）	分辨率为0.04°，时间序列为2001—2023年
VPD	TerraClimate（https://www.climatologylab.org/）	分辨率为0.04°，时间序列为2001—2023年
风速	TerraClimate（https://www.climatologylab.org/）	分辨率为0.04°，时间序列为2001—2023年
降水	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	1 km栅格数据，时间序列为2001—2023年
气温	国家青藏高原科学数据中心（https://data.tpdc.ac.cn/）	1 km栅格数据，时间序列为2001—2023年
高程	中国科学院资源环境科学数据平台（https://www.resdc.cn/）发布的全国DEM1 km、500 m和250 m数据	1 km栅格数据，V4.1版本
土壤类型	中国科学院资源环境科学数据平台（https://www.resdc.cn/）发布的中国土壤类型空间分布数据	1 km栅格数据，分为22个大类
植被类型	中国科学院资源环境科学数据平台（https://www.resdc.cn/）发布的中国100万植被类型空间分布数据	1 km栅格数据，分为9个大类
地貌类型	中国科学院资源环境科学数据平台（https://www.resdc.cn/）发布的中国100万地貌类型空间分布数据	1 km栅格数据，分为7个大类
土地利用类型	中国科学院资源环境科学数据平台（https://www.resdc.cn/）发布的中国多时期土地利用遥感监测数据集	1 km栅格数据，分为6个大类，时间为2020年

C_v	稳定性	说明
C_v<0.1	弱变异	数据波动较小，表明变量稳定，变化幅度小
0.1≤C_v<1	中等变异	数据具有一定波动性，但整体仍较稳定，常用于描述生态或环境变量的正常变异范围
C_v≥1	强变异	数据波动剧烈，表明变量受外界因素影响较大，变化不稳定

Hurst	Slope	未来趋势
>0.5	>0	持续改善
>0.5	<0	持续退化
=0.5	-	无法预测
<0.5	>0	改善到退化
<0.5	<0	退化到改善

驱动因子	空间尺度
驱动因子	0.05°	0.1°	0.15°	0.2°
X1（PDSI）	0.1405	0.1427	0.1489	0.1368
X2（土壤湿度）	0.1908	0.1878	0.1873	0.1947
X3（辐射）	0.1546	0.1562	0.1600	0.1512
X4（VPD）	0.1232	0.1217	0.1204	0.1314
X5（风速）	0.0855	0.0859	0.0830	0.0882
X6（降水）	0.2893	0.2974	0.2892	0.2887
X7（气温）	0.1927	0.1896	0.1932	0.1977
X8（高程）	0.1693	0.1643	0.1741	0.1669
X9（土壤类型）	0.4303	0.4353	0.4389	0.4274
X10（植被类型）	0.4894	0.4891	0.4950	0.4887
X11（地貌类型）	0.1340	0.1355	0.1322	0.1351
X12（土地利用类型）	0.4576	0.4553	0.4583	0.4306
q值的90%分位数	0.4799	0.4789	0.4840	0.4713

符号	连续性因子	分级方法	分级层数
X1	PDSI	几何间隔中断	9
X6	降水	几何间隔中断	9
X2	土壤湿度	自然间隔中断	9
X7	气温	自然间隔中断	8
X3	辐射	分位数间隔中断	8
X5	风速	分位数间隔中断	9
X4	VPD	标准差间隔中断	9
X8	高程	相等间隔中断	8

Spatial-temporal pattern and driving force analysis of NDVI in Xinjiang from 2001 to 2023

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