生态环境学报 ›› 2022, Vol. 31 ›› Issue (10): 1939-1950.DOI: 10.16258/j.cnki.1674-5906.2022.10.002
收稿日期:
2022-05-03
出版日期:
2022-10-18
发布日期:
2022-12-09
通讯作者:
*作者简介:
余玉洋(1993年生),男,讲师,博士,研究方向为生态系统服务与植被遥感。E-mail: yuyuyangg@qq.com
基金资助:
YU Yuyang*(), SONG Fengyi, ZHANG Shijie
Received:
2022-05-03
Online:
2022-10-18
Published:
2022-12-09
摘要:
植被是陆地生态系统的重要组成部分,对陆地碳循环、能量交换、水平衡以及气候变化有着重大影响。归一化植被指数(NDVI)可反映区域植被的生长状况,通常利用NDVI变化评估区域或全球生态环境质量。人类活动和气候变化影响区域植被的生长环境,定量解析NDVI变化的影响因素极其重要。鉴于此,利用长期(2000—2020年)NDVI数据集分析NDVI的时空变化格局,并利用残差分析法解析人类活动和气候变化对NDVI变化的影响和贡献率。结果如下,(1)时间序列上,河南省月平均NDVI变化明显,7—9月处于高值区,而11月至次年1月处于低值区;在空间上,豫西阔叶林NDVI均值高于豫东栽培植被的NDVI均值。(2)在低海拔地区,NDVI均值随着海拔升高而升高,半阴坡和半阳坡的NDVI均值高于阴坡和阳坡的NDVI均值。(3)NDVI年均值与降水的偏相关系数略高于气温与NDVI的偏相关系数,表明年均NDVI受降水的影响比受气温的影响显著。(4)在人类活动和气候变化共同驱动下,河南省NDVI在长时间序列中得到改善的区域面积比例为82.5%,其中人类活动和气候变化的平均贡献率分别为72.26%和27.74%。对河南省NDVI的时空变化和驱动因素的定量分析可为河南省社会-生态可持续发展和生态文明建设提供科学参考。
中图分类号:
余玉洋, 宋丰艺, 张世杰. 2000—2020年河南省NDVI时空变化及其驱动因素定量分析[J]. 生态环境学报, 2022, 31(10): 1939-1950.
YU Yuyang, SONG Fengyi, ZHANG Shijie. Quantitative Analysis of Temporal and Spatial Changes of NDVI and Its Driving Factors in Henan Province from 2000 to 2020[J]. Ecology and Environment, 2022, 31(10): 1939-1950.
数据类型 Type of data | 数据描述 Data description | 数据来源 Data sources |
---|---|---|
基础地理信息数据 Basic geographic information data | 行政区划、河流、道路等 | http://www.ngcc.cn/ngcc/ |
高程数据 Elevation data | 来源于地理空间数据云,空间分辨率为30 m | http://www.gscloud.cn/ |
植被数据 Vegetation data | 来源于中国科学院资源环境科学与数据中心,空间分辨率为250 m | https://www.resdc.cn/DataSearch.aspx |
气象数据 Meteorological data | 2000-2020年逐日数据,指标包括降水、最高气温、最低气温数据 | http://data.cma.cn/ |
表1 数据来源
Table 1 Data sources
数据类型 Type of data | 数据描述 Data description | 数据来源 Data sources |
---|---|---|
基础地理信息数据 Basic geographic information data | 行政区划、河流、道路等 | http://www.ngcc.cn/ngcc/ |
高程数据 Elevation data | 来源于地理空间数据云,空间分辨率为30 m | http://www.gscloud.cn/ |
植被数据 Vegetation data | 来源于中国科学院资源环境科学与数据中心,空间分辨率为250 m | https://www.resdc.cn/DataSearch.aspx |
气象数据 Meteorological data | 2000-2020年逐日数据,指标包括降水、最高气温、最低气温数据 | http://data.cma.cn/ |
S(NDVIobs) | 驱动要素 Driving factor | 划分标准 Criteria for the classification | 贡献率 Contribution rate/% | |||
---|---|---|---|---|---|---|
S(NDVICC) | S(NDVIHA) | 气候变化 Climate change | 人类活动 Human activity | |||
>0 (积极作用 Positive effects) | 气候变化和人类活动 | >0 | >0 | S(NDVICC)/S(NDVIobs) | S(NDVIHA)/S(NDVIobs) | |
气候变化 | >0 | <0 | 100 | 0 | ||
人类活动 | <0 | >0 | 0 | 100 | ||
<0 (消极作用 Negative effects) | 气候变化和人类活动 | <0 | <0 | S(NDVICC)/S(NDVIobs) | S(NDVICC)/S(NDVIobs) | |
气候变化 | <0 | >0 | 100 | 0 | ||
人类活动 | >0 | <0 | 0 | 100 |
表2 NDVI变化的驱动因素判定标准及贡献率计算方法
Table 2 Criteria for determining the drivers of NDVI changes in vegetation and the calculation of their contribution
S(NDVIobs) | 驱动要素 Driving factor | 划分标准 Criteria for the classification | 贡献率 Contribution rate/% | |||
---|---|---|---|---|---|---|
S(NDVICC) | S(NDVIHA) | 气候变化 Climate change | 人类活动 Human activity | |||
>0 (积极作用 Positive effects) | 气候变化和人类活动 | >0 | >0 | S(NDVICC)/S(NDVIobs) | S(NDVIHA)/S(NDVIobs) | |
气候变化 | >0 | <0 | 100 | 0 | ||
人类活动 | <0 | >0 | 0 | 100 | ||
<0 (消极作用 Negative effects) | 气候变化和人类活动 | <0 | <0 | S(NDVICC)/S(NDVIobs) | S(NDVICC)/S(NDVIobs) | |
气候变化 | <0 | >0 | 100 | 0 | ||
人类活动 | >0 | <0 | 0 | 100 |
图11 2000—2020年气候变化和人类活动对河南省植被生长起积极作用(a,b)和消极作用(c,d)的贡献率空间分布
Figure 11 Spatial distribution of positive (a, b) and negative (c, d) contributions of human activities and climate change to vegetation growth in Henan Province from 2000 to 2020
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