Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and...Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.展开更多
本文以陇中黄土高原的祖厉河流域为研究区,基于Landsat系列遥感影像,利用主成分变换方法,与地面温度和植被指数相结合,进行土地利用/土地覆盖提取研究,在此基础上,探讨祖厉河流域土地利用/土地覆盖变化(LUCC)及其驱动因素。利用基于TM...本文以陇中黄土高原的祖厉河流域为研究区,基于Landsat系列遥感影像,利用主成分变换方法,与地面温度和植被指数相结合,进行土地利用/土地覆盖提取研究,在此基础上,探讨祖厉河流域土地利用/土地覆盖变化(LUCC)及其驱动因素。利用基于TM影像的SEBAL(Surface Energy Balance Algorithm for Land)模型,从祖厉河流域三期影像提取了区域蒸散发通量。首先进行了NDVI、比辐射率和地面温度等地表参数的计算,然后反演了地表的净辐射、土壤热通量和感热通量,根据能量守恒最终获得日蒸散发量。结合气象观测数据反演作物系数,最后计算月蒸散发量。对同期的土地利用/土地覆盖数据和陆面蒸散发量进行对比分析,探讨了土地利用类型的变化对流域内能量和水分时空分异的影响。展开更多
基金funded by the National Natural Science Foundation of China(U21A2011).
文摘Climate warming and humidification trends have significantly influenced vegetation growth patterns in Chinese semi-arid areas.Exploring vegetation dynamics is crucial for understanding regional ecosystem structure and improving the efforts of ecosystem restoration.However,the applicability of various vegetation indices(VIs)in these arid areas remains uncertain.Evaluating the applicability of multiple VIs for vegetation monitoring can elucidate the variability of VIs performance at regional scale.Therefore,this study selected the Zuli River Basin(ZLRB),a typical loess hilly watershed in the semi-arid areas of China.Using Landsat data,we calculated the Normalized Difference Vegetation Index(NDVI),Enhanced Vegetation Index(EVI),and kernel NDVI(kNDVI)for the ZLRB from 1990 to 2020.We analyzed the spatiotemporal variations of these VIs using trend analysis and the Mann-Kendall test,and quantified the contributions of climate change(considering time-lag effects)and human activities to VIs changes through wavelet and residual analyses.Results indicated that VIs generally exhibited an upward trend in the ZLRB,with significant improvements observed in 54.91% of the area for NDVI,31.69% for EVI,and 33.71% for kNDVI.Among them,NDVI outperformed EVI and kNDVI in capturing vegetation changes in the semi-arid area.VIs responded to precipitation with 1-month time lag and no time lag to temperature during growing season.Moreover,precipitation had a stronger positive correlation with VIs than temperature.Climate change was identified as the dominant driver of vegetation dynamics in the ZLRB,accounting for 93.12% of NDVI variation,while human activities contributed only 6.88%.Comparative analysis of VIs suggests that NDVI was more suitable for describing vegetation changes in the typical arid area of the ZLRB.Our findings underscore the importance of selecting appropriate VIs for targeted ecological restoration and sustainable land management.
文摘本文以陇中黄土高原的祖厉河流域为研究区,基于Landsat系列遥感影像,利用主成分变换方法,与地面温度和植被指数相结合,进行土地利用/土地覆盖提取研究,在此基础上,探讨祖厉河流域土地利用/土地覆盖变化(LUCC)及其驱动因素。利用基于TM影像的SEBAL(Surface Energy Balance Algorithm for Land)模型,从祖厉河流域三期影像提取了区域蒸散发通量。首先进行了NDVI、比辐射率和地面温度等地表参数的计算,然后反演了地表的净辐射、土壤热通量和感热通量,根据能量守恒最终获得日蒸散发量。结合气象观测数据反演作物系数,最后计算月蒸散发量。对同期的土地利用/土地覆盖数据和陆面蒸散发量进行对比分析,探讨了土地利用类型的变化对流域内能量和水分时空分异的影响。
