2001~2021年中国NDVI时空格局变化及对气候的响应

孙瑞, 张方敏, 翁升恒, 刘倩

中国环境科学 ›› 2023, Vol. 43 ›› Issue (10) : 5519-5528.

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中国环境科学 ›› 2023, Vol. 43 ›› Issue (10) : 5519-5528.
环境生态

2001~2021年中国NDVI时空格局变化及对气候的响应

  • 孙瑞1, 张方敏1, 翁升恒2, 刘倩1
作者信息 +

Spatio-temporal changes of NDVI and its response to climate in China from 2001 to 2021

  • SUN Rui1, ZHANG Fang-min1, WENG Sheng-heng2, LIU Qian1
Author information +
文章历史 +

摘要

基于MODIS MOD13A3数据集和气候资料数据,通过线性回归、Theil-Sen趋势与Mann-Kendall显著性检验等统计方法分析了2001~2021年中国九大流域NDVI时空变化特征,采用地理探测器探究了中国九大流域NDVI对降水、气温、太阳总辐射和饱和水气压差的响应.结果表明, 2001~2021年中国及九大流域NDVI整体呈现显著上升趋势(P<0.05),其中长江流域、珠江流域、东南诸河流域及淮河流域冬季的NDVI变化率最大,海河流域春季最大,西南诸河流域秋季最大,其他流域夏季最大;NDVI变化率在不同土地利用变化类型上表现为非城市化地区(0.0026/a)>未发生土地利用类型变化地区(0.0021/a)>城市化地区(0.0013/a),其中东南诸河流域和西南诸河流域的城市化地区NDVI整体表现为退化.空间上,NDVI变化率呈现出由东向西、由南向北递减的分布.植被生长稳定区域占26.43%,主要集中在内陆河流域以及西南诸河西北部区域;植被改善面积占70.31%,主要分布在九大流域内的非城市化区域;植被退化面积占3.25%,集中在内陆河流域北部地区、西南诸河流域的东部、长江流域的西部及东部沿海流域.地理探测器分析表明,降水在全国尺度上是控制NDVI空间分布的主要决定因子,其次是气温、饱和水气压差、太阳总辐射;在九大流域内,降水仍是大部分流域的主要决定因子,但在长江流域、珠江流域和淮河流域,饱和水气压差是主要决定因子.2001~2021年,长江流域、松辽河流域、黄河流域和西南诸河流域的气候因子对NDVI的影响作用大部分在增加,而其他流域的气候影响作用基本在下降.

Abstract

Based on the MODIS MOD13A3 dataset and climate data to analyze the spatio-temporal variations of NDVI in the nine major basins in China from 2001 to 2021 by statistical methods of linear regression, Theil-Sen trend and Mann-Kendall significance test. Further, the responses of NDVI to precipitation, air temperature, solar radiation and saturated water pressure difference in the nine major basins in China were investigated by using Geodetector analysis. The results showed that NDVI showed a significant upward trend (P<0.05) both in China and the nine major river basins from 2001 to 2021. The change rate of NDVI in the Yangtze River Basin, the Pearl River Basin, the Southeast River Basin and the Huaihe River Basin was the largest in winter, the Haihe River Basin in spring, the Southwest River Basin in autumn, and the other river basins in summer. From the perspective of land use change types, the NDVI change rate was ranking in the order of non-urbanized area (0.0026/a) > non-type change area (0.0021/a) > urbanized area (0.0013/a). Moreover, the NDVI of the urbanization areas was degraded in the Southeast River Basin and the Southwest River Basin. Spatially, the change rate of NDVI decreased from east to west and from south to north. The areas with stable vegetation growth accounted for 26.43% of the total area of China, mainly concentrated in the Inland River Basin and the northwest of the Southwest River Basin. The areas with vegetation improvement accounted for 70.31%, mainly distributed in the non-urbanized area of the nine major river basins. The area with vegetation degradation accounted for 3.25%, which was concentrated in the north of the Inland River Basin, the east of the Southwest River Basin, the west of Yangtze River Basin and the coastal basins in the east China. The factor detection results showed precipitation was the main factor controlling the spatial distribution of NDVI across China, followed by air temperature, saturated water pressure difference and solar radiation. In most of the nine river basins, precipitation was still the main determinant, but the saturated water pressure difference was the main determinant in the Yangtze River Basin, the Pearl River Basin and the Huaihe River Basin. In the past 21years, the influence of climatic factors on NDVI in the Yangtze River Basin, the Songliao River Basin, the Yellow River Basin and the Southwest River Basin has mostly increased, while the influence of climatic factors in other river basins has basically decreased.

关键词

NDVI / 地理探测器 / 九大流域 / 气候因素 / 时空变化

Key words

climatic factors / Geodetector / NDVI / nine major basins / spatial-temporal variations

引用本文

导出引用
孙瑞, 张方敏, 翁升恒, 刘倩. 2001~2021年中国NDVI时空格局变化及对气候的响应[J]. 中国环境科学. 2023, 43(10): 5519-5528
SUN Rui, ZHANG Fang-min, WENG Sheng-heng, LIU Qian. Spatio-temporal changes of NDVI and its response to climate in China from 2001 to 2021[J]. China Environmental Science. 2023, 43(10): 5519-5528
中图分类号: X171.1   

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基金

江苏省碳达峰碳中和科技创新专项资金资助项目(BK20220017);中国气象局创新发展专项资助项目(CXFZ2023J073);江苏省研究生科研创新计划资助项目(KYCX23_1338)

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