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地域研究与开发 >

2023 , Vol. 42 >Issue 2: 155 - 160

DOI: https://doi.org/10.3969/j.issn.1003-2363.2023.02.025

生态环境

淮河流域NDVI时空变化特征及其气候响应 

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  • 1.信阳师范学院 地理科学学院，河南 信阳 464000；2.河南省淮河流域遥感大数据与智能分析工程研究中心，河南 信阳 464000；3.河南省水土环境污染协同防治重点实验室，河南 信阳 464000； 4.湖南师范大学 地理科学学院，长沙 410081
牛继强（1977-），男，山东郯城县人，教授，博士，博士生导师，主要从事地理计算、空间分析与时空数据挖掘等研究，（E-mail）niujiqiang@xynu.edu.cn。

网络出版日期: 2024-06-25

基金资助

国家自然科学基金项目（41771438）；河南省自然科学基金项目（222300420277）；河南省高等学校科技创新团队支持计划项目（221RTSTHN010）

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Spatio-temporal Variation of NDVI and Its Climatic Response in the Huaihe River Basin

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  • 1.School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China; 2.Henan Engineering Research Center for Big Data of Remote Sensing and Intelligent Analysis in Huaihe River Basin, Xinyang 464000, China; 3.Henan Key Laboratory for Synergistic Prevention of Water and Soil Environmental Pollution, Xinyang 464000, China; 4.School of Geographical Sciences, Hunan Normal University, Changsha 410081, China

Online published: 2024-06-25

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摘要

植被和气象因子间的相关性分析对认识生态系统整体性有重要意义。使用GIMMS NDVI3g遥感数据，结合气温、降水数据，运用趋势分析、相关分析方法，探究1982—2015年淮河流域归一化植被指数（NDVI）与气温、降水的时空变化及其相关性。结果表明：（1）在时间尺度上，1982—2015年淮河流域植被覆盖整体呈上升趋势，NDVI的增速为0.000 678/年，气温、降水也呈增长趋势。（2）在像元尺度的空间分布上，约3/4像元的NDVI呈增长趋势，三者关系显示淮河流域气温、降水条件有利于植被生长，植被覆盖稳定且持续恢复，生态环境健康发展。（3）像元尺度的变化趋势以及NDVI与气温、降水的相关性对比分析发现，淮河流域气温升高对NDVI的促进作用相较于降水更为明显。

关键词： NDVI；时空变化；气温与降水；淮河流域

本文引用格式

牛继强, 张倩, 杨晨曦, 陈飞燕 . 淮河流域NDVI时空变化特征及其气候响应 [J]. 地域研究与开发, 2023 , 42(2) : 155 -160 . DOI: 10.3969/j.issn.1003-2363.2023.02.025

Abstract

The correlation analysis between vegetation and meteorological factors is significant to understanding ecosystem integrity. Using GIMMS NDVI3g remote sensing data and temperature and precipitation data, trend analysis and correlation analysis methods were used to explore the spatiotemporal variation and correlation between normalized vegetation index and temperature and precipitation in the Huaihe River Basin during 1982—2015. The results showed that: (1) In terms of time scale, the Huaihe River Basin vegetation cover showed an increasing trend during 1982—2015, and the growth rate of NDVI was 0.000 678/year. The temperature and precipitation also showed an increasing trend. (2) In the spatial distribution of pixel scale, NDVI of about 3/4 pixels showed an increasing trend. The relationship between the three elements showed that the temperature and precipitation conditions in the Huaihe River Basin were conducive to vegetation growth, the stable and continuous recovery of vegetation cover, and the healthy development of the ecological environment. (3) The changing trend of pixel scale and the correlation analysis of NDVI with air temperature and precipitation showed that increased air temperature in the Huaihe River Basin promoted NDVI more obviously than precipitation.

Key words： NDVI; spatiotemporal variation; temperature and precipitation; Huaihe River Basin

参考文献

［1］金凯,王飞,韩剑桥,等.1982—2015年中国气候变化和人类活动对植被NDVI变化的影响［J］.地理学报,2020,75(5):961-974.
［2］XU B,QI B,JI K,et al.Emerging Hot Spot Analysis and the Spatial-temporal Trends of NDVI in the Jing River Basin of China［J/OL］.Environmental Earth Sciences,2022,81(2):55［2022-10-06］.https://link.springer.com/article/10.1007/s12665-022-10175-5.
［3］邓晨晖,白红英,高山,等.秦岭植被覆盖时空变化及其对气候变化与人类活动的双重响应［J］.自然资源学报,2018,33(3):425-438.
［4］LAN S,DONG Z.Incorporating Vegetation Type Transformation with NDVI Time-series to Study the Vegetation Dynamics in Xinjiang［J］.Sustainability,2022,14(1):1-15.
［5］陈文裕,夏丽华,徐国良,等.2000—2020年珠江流域NDVI动态变化及影响因素研究［J］.生态环境学报,2022,31(7):1306-1316.
［6］王欣平,邵凤娈,毛志红,等.基于MODIS数据的济南市年最大植被覆盖度动态监测［J］.地域研究与开发,2016,35(1):150-155.
［7］XU Y,YANG Y,CHEN X,et al.Bibliometric Analysis of Global NDVI Research Trends from 1985 to 2021［J/OL］.Remote Sensing,2022,14(16):3967［2022-10-06］.https://doi.org/10.3390/rs14163967.
［8］朴世龙,方精云,贺金生,等.中国草地植被生物量及其空间分布格局［J］.植物生态学报,2004,28(4):491-498.
［9］ZHU X,LIU D.Improving Forest Aboveground Biomass Estimation Using Seasonal Landsat NDVI Time-series［J］.ISPRS Journal of Photogrammetry and Remote Sensing,2015,102(4):222-231.
［10］方精云,郭兆迪,朴世龙,等.1981—2000年中国陆地植被碳汇的估算［J］.中国科学(D辑:地球科学),2007(6):804-812.
［11］刘宪锋,潘耀忠,朱秀芳,等.2000—2014年秦巴山区植被覆盖时空变化特征及其归因［J］.地理学报,2015,70(5):705-716.
［12］王祺,蒙吉军,齐杨,等.基于承载力动态变化的生态系统适应性管理：以鄂尔多斯乌审旗为例［J］.地域研究与开发,2015,34(4):154-159.
［13］张华,安慧敏.基于GEE的1987—2019年民勤绿洲NDVI变化特征及趋势分析［J］.中国沙漠,2021,41(1):28-36.
［14］HUANG S,TANG L,HUPY J P,et al.A Commentary Review on the Use of Normalized Difference Vegetation Index (NDVI) in the Era of Popular Remote Sensing［J］.Journal of Forestry Research,2021,32(1):1-6.
［15］李婷婷,郭增长,马超.中国第二、三级阶梯地形过渡带山前植被物候时空变化探析［J］.地理研究,2022,41(11):3000-3020.
［16］赵耀华,彭小清,金浩东,等.基于多源遥感数据的青藏高原植被变化特征评价［J］.冰川冻土,2022,44(4):1216-1230.
［17］张家政,李崇贵,王涛.黄土高原植被覆盖时空变化及原因［J］.水土保持研究,2022,29(1):224-230.
［18］彭文甫,张冬梅,罗艳玫,等.自然因子对四川植被NDVI变化的地理探测［J］.地理学报,2019,74(9):1758-1776.
［19］李旭谱,张福平,魏永芬.黑河流域植被覆盖程度变化研究［J］.地域研究与开发,2013,32(3):108-114.
［20］王情,刘雪华,吕宝磊.基于SPOT-VGT数据的流域植被覆盖动态变化及空间格局特征:以淮河流域为例［J］.地理科学进展,2013,32(2):270-277.
［21］于法稳,李群,沙涛,等.中国生态治理发展报告（2020—2021年）［M］.北京:社会科学文献出版社,2021.
［22］VERHOEVEN V B,DEDOUSSI I C.Annual Satellite-based NDVI-derived Land Cover of Europe for 2001—2019［J/OL］.Journal of Environmental Management,2022,302:113917［2022-10-06］.https://doi.org/10.1016/j.jenvman.2021.113917.
［23］MOTTL O,FLANTUA S G A,BHATTA K P,et al.Global Acceleration in Rates of Vegetation Change over the Past 18,000 Years［J］.Science,2021,372:860-864.
［24］金君良,何健,贺瑞敏,等.气候变化对淮河流域水资源及极端洪水事件的影响［J］.地理科学,2017,37(8):1226-1233.
［25］孙朋,渠玮娟,朱玺,等.1959—2018年淮河流域水热格局差异研究［J］.长江流域资源与环境,2021,30(6):1366-1377.
［26］JIN H,CHEN X,ZHONG R,et al.Spatiotemporal Distribution Analysis of Extreme Precipitation in the Huaihe River Basin Based on Continuity［J］.Natural Hazards,2022,114(3):3627-3656.
［27］刘传明,范观宇,王呈祥,等.淮河生态经济带城镇化与粮食生产耦合协调性时空特征［J］.地域研究与开发,2022,41(1):38-44.
［28］国家大气研究中心.1/12度AVHRR GIMMS 均一化全球指数(1981—2015年)［DB/OL］.(2021-04-19)［2022-10-06］.http://data.tpdc.ac.cn.
［29］彭守璋.中国1km分辨率逐月降水量数据集（1901—2021年）［DB/OL］.(2020-06-08）［2022-10-06］.http://data.tpdc.ac.cn.
［30］HE Q,WANG M,LIU K,et al.Gprchinatemp1km:1 km Monthly Minimum Air Temperature for China from January 1951 to December 2020［J］.Earth System Science Data,2021,14:3273-3292.
［31］徐建华.现代地理学中的数学方法［M］.北京:高等教育出版社,2002.
［32］刘海,黄跃飞,郑粮.气候与人类活动对丹江口水源区植被覆盖变化的影响［J］.农业工程学报,2020,36(6):97-105.
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