摘要
该研究基于谷歌地球引擎(Google Earth Engine,GEE)共享的遥感数据及对地分析,在线访问MOD13 Q1数据,采用一元线性回归法、最大合成法(Maximum Value Composite,MVC)和均值法,分析2000-2018年中国丝绸之路经济带沿线省份的植被覆盖时空变化趋势;并利用地理探测器模型定量分析不同自然因子对植被覆盖变化的影响。结果表明:1)2000-2018年植被覆盖变化时空差异显著,空间变化趋势以改善为主,且改善区域主要在广西、重庆、陕西、宁夏及甘肃南部;2)NDVI年最大值(NDVImax)和NDVI生长季均值(NDVISeaAvg)随时间变化均呈显著的波动增加趋势(P<0.001);3)年均降水量、湿润指数、植被类型和土壤类型是NDVImax空间分布的主要驱动因子,解释力分别为0.776、0.764、0.762和0.505;4)各自然因子存在促进植被生长的最适宜范围或特征,不同自然因子之间的交互作用为双因子增强或非线性增强。研究结果有助于理解自然因子对植被覆盖变化的影响及其驱动机制,为合理利用土地、有效保护生态环境提供科学参考。
Changes of vegetation cover directly determine local climate and ecological balance,particularly on environmental construction and land use.Western China is included in the Silk Road Economic Belt,accounting for more than half of the total land area of China,but its economic development is relatively backward.Much attention has paid to construct a friendly environment while developing economy,in order to achieve the sustainable development of the green economy in western China.It has become one of the urgent issues to clarify the influence of natural factors on vegetation cover,and thereby to take corresponding measures or policies.In this study,five provinces in northwest China and four provinces in southwest China were selected as the study area,where the complex and diverse characteristics of terrain and climate have shaped the unique spatial distribution pattern of vegetation cover.MOD13 Q1 and SRTM was accessed online,based on massive remote sensing data shared by Google Earth Engine(GEE)and powerful ground analysis capabilities.The monthly climate data set was from the China Meteorological Data(http://data.cma.cn/),while,the humidity index,cumulative temperature(≥10℃),soil type,vegetation type,and physiognomy type were all from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences(http://www.resdc.cn/).The linear regression,Maximum Value Composite(MVC)and mean method were used to analyze the spatiotemporal variation of vegetation cover in provinces along the Silk Road Economic Belt in China during 2000-2018.A total of eight factors can be identified on the changes of vegetation cover,using factor detector and ecological detector in the geographical detector to screen out the annual average precipitation,humidity index,vegetation type,soil type,annual average temperature,physiognomy type,slope,and cumulative temperature(≥10℃).Risk detector was used to recognize the optimal range or behaviors of different natural factors,thereby to promote vegetation growth.interaction
作者
胡克宏
张震
郜敏
陆艺杰
Hu Kehong;Zhang Zhen;Gao Min;Lu Yijie(School of Geomatics,Anhui University of Science and Technology,Huainan 232001,China)
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2020年第17期149-157,共9页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家自然科学基金资助项目(41701087)。
关键词
遥感
植被
自然因子
GEE
地理探测器
remote sensing
vegetation
natural factors
GEE
geographical detector
