黄河流域植被覆盖度变化及驱动因素  

Change and driving factors of vegetation coverage in the Yellow River Basin

作　　者：王晓蕾[1,2] 石守海 陈江朝霞 WANG Xiao-lei;SHI Shou-hai;CHEN jiang-zhao-xia(School of Geoscience and Technology,Zhengzhou University,Zhengzhou 450000,China;Joint Laboratory of Eco-Meteorology,Zhengzhou University,Chinese Academy of Meteorological Sciences,Zhengzhou University,Zhengzhou 450000,China)

机构地区：[1]郑州大学地球科学与技术学院,河南郑州450000 [2]郑州大学,中国气象科学研究院郑州大学生态气象联合实验室,河南郑州450000

出　　处：《中国环境科学》2022年第11期5358-5368,共11页China Environmental Science

基　　金：河南省高等学校重点科研项目(21A420006);河南省自然科学基金资助项目(212300410292);河南省科技攻关项目(212102210137)

摘　　要：利用Google Earth Engine(GEE)遥感云计算平台通过像元二分模型反演出1999~2019年植被覆盖度,采用一元线性回归和变异系数法来研究FVC的变化趋势特征及其稳定性,通过地理探测器进行植被变化的驱动分析.结果表明:黄河流域FVC总体上西北低东南高;中高和高被覆盖区分别占研究区总面积的21.74%和17.87%;近20a年黄河流域FVC已有较好改善,流域中部植被改善最明显,改善区域占流域总面积的48.52%;FVC的稳定性以较平稳为主.降水、日照时间及相对湿度三个驱动因子对黄河流域FVC影响力最强.各驱动因子对FVC影响存在交互作用,以双因子增强或者非线性增强为主,双因子交互作用增强了单因子的影响;本研究也揭示了促进植被生长的各因子最适宜范围,有助于更好地理解自然和社会因素对植被覆盖变化的影响及其驱动机制.The pixel binary model was used to inverse the fractional vegetation cover(FVC)from 1999 to 2019 based on the Google Earth Engine platform,and the unary linear regression analysis and the coefficient of variance method were used to study the changes in the FVC trend characteristics and stability.The geographic detector was used to analyze the driving force of vegetation change.The results showed that:(1)The FVC of the Yellow River Basin was generally low in the northwest and high in the Southeast;the medium-high and high-covered areas accounted for 21.74%and 17.87%of the study area,respectively;the FVC of the Yellow River Basin had improved well in the past two decades.The improvement of vegetation in the middle reaches of the basin was the most obvious,and the improvement area accounted for 48.52%of the total area in our study area;the stability of FVC was mainly stable.(2)The three driving factors of precipitation,sunshine duration,and relative humidity had the strongest influence on FVC in the Yellow River Basin.(3)Each driving factor had an interaction effect on the FVC.The two-factor enhancement or nonlinear enhancement was the main factor.The two-factor interaction enhanced the impact of the single factor.This study also revealed the most suitable range of factors that promoted vegetation growth.These results help to better understand the impact of natural and social factors on vegetation cover changes and their driving mechanisms.

关 键 词：植被覆盖度 时空变化 驱动分析 地理探测器 黄河流域 

分 类 号：X87[环境科学与工程—环境工程]