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
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.
