基于地理探测器的区域植被覆盖度的定量影响——以京津风沙源区为例

Quantitative influence of regional fractional vegetation cover based on geodetector model—Take the Beijing-Tianjin sand source region as an example

植被覆盖度(FVC)是衡量生态环境优秀的重要指标.本文基于MODIS NDVI数据,运用像元二分法模型,估算了2000~2018年京津风沙源区FVC,分析了其时空变化特征.在此基础上,基于地理探测器模型,定量分析了自然因素和人类活动因素等12个因子对京津风沙源区FVC空间分布的影响.结果表明,近20a来京津风沙源区FVC整体上呈增加趋势,增加率为8.2%.空间上,研究区73.7%的区域FVC在增加,其中显著增加的区域主要集中在晋北山地丘陵亚区、燕山丘陵山地水源保护亚区、大兴安岭南部亚区和科尔沁沙地亚区的南部.2000~2018年,降水是影响京津风沙源区FVC空间分布的主要自然因子,解释力为63.3%;年末大牲畜头数是影响FVC空间分布的主要人为因子,解释力为34.8%.自然因素和人类活动之间的双因子交互作用以双协同作用和非线性协同作用为主,表明相对于单因子,自然因素和人类活动间的交互作用对FVC的解释力更强.其中,降水与其他11个因子的交互作用对研究区FVC起主导作用,解释力超过60%.

Fractional Vegetation Cover(FVC)is an important index to measure the excellence of ecological environment.In this study,the FVC in Beijing-Tianjin sand source region(BTSSR)was estimated from 2000 to 2018 based on MODIS NDVI data and Dimidiate Pixel model and its spatial-temporal variation characteristics were analyzed.Moreover,the effects of 12 influencing factors,including natural factors and human activities on FVC,were quantitatively analysed by using Geodetector model in the BTSSR.The results showed that,in recent 20 years,the FVC in the BTSSR showed an increasing trend with a rate of 8.2%.FVC increased in 73.7%of the study area,and the regions with the significant upward trends were mainly in the sub-areas of Northern Shanxi’s Mountains,Yanshan Mountains,Southern Great Hinggan Mountains and the southern Horqin Sandy Land.From 2000 to 2018,precipitation and the count of large livestock at the end of the year were the main natural and human factors affecting the spatial distribution of FVC in BTSSR,with explanatory powers of 63.3%and 34.8%,respectively.The two-factor interaction between natural factors and human activities was dominated by double synergy and non-linear synergy,which indicated that the interaction between natural factors and human activities had a stronger impact on FVC than single factors.The interaction between precipitation and other 11factors played a leading role in FVC of the study area with the explanatory power of over 60%.