The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetatio...The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.展开更多
针对传统多尺度模型对模型点云比较方法(Multiscale Model to Model Cloud Comparison,M3C2)计算法向量与形变量时易受离群点影响的缺点,提出一种基于离群点探测准则的改进算法。首先,在估计关键点法向量时,依据改进离群点探测准则迭代...针对传统多尺度模型对模型点云比较方法(Multiscale Model to Model Cloud Comparison,M3C2)计算法向量与形变量时易受离群点影响的缺点,提出一种基于离群点探测准则的改进算法。首先,在估计关键点法向量时,依据改进离群点探测准则迭代剔除离群点,提高法向量估计的准确性,然后,通过离群点探测剔除圆柱内离群点,最后,结合正态分布加权计算形变量。实验结果表明,相较于M3C2原始算法,改进算法将法向量均方差精度指标提升50%以上,在形变量较大区域可将形变量估值均方差精度指标提高200%以上。改进算法具有更好的适用性和可靠性。展开更多
基金supported by the National Natural Science Foundation of China (42377472, 42174055)the Jiangxi Provincial Social Science "Fourteenth Five-Year Plan" (2024) Fund Project (24GL45)+1 种基金the Research Center of Resource and Environment Economics (20RGL01)the Provincial Finance Project of Jiangxi Academy of Sciences-Young Talent Cultivation Program (2023YSBG50010)
文摘The Three-River Source Region(TRSR)in China holds a vital position and exhibits an irreplaceable strategic importance in ecological preservation at the national level.On the basis of an in-depth study of the vegetation evolution in the TRSR from 2000 to 2022,we conducted a detailed analysis of the feedback mechanism of vegetation growth to climate change and human activity for different vegetation types.During the growing season,the spatiotemporal variations of normalized difference vegetation index(NDVI)for different vegetation types in the TRSR were analyzed using the Moderate Resolution Imaging Spectroradiometer(MODIS)-NDVI data and meteorological data from 2000 to 2022.In addition,the response characteristics of vegetation to temperature,precipitation,and human activity were assessed using trend analysis,partial correlation analysis,and residual analysis.Results indicated that,after in-depth research,from 2000 to 2022,the TRSR's average NDVI during the growing season was 0.3482.The preliminary ranking of the average NDVI for different vegetation types was as follows:shrubland(0.5762)>forest(0.5443)>meadow(0.4219)>highland vegetation(0.2223)>steppe(0.2159).The NDVI during the growing season exhibited a fluctuating growth trend,with an average growth rate of 0.0018/10a(P<0.01).Notably,forests displayed a significant development trend throughout the growing season,possessing the fastest rate of change in NDVI(0.0028/10a).Moreover,the upward trends in NDVI for forests and steppes exhibited extensive spatial distributions,with significant increases accounting for 95.23%and 93.80%,respectively.The sensitivity to precipitation was significantly enhanced in other vegetation types other than highland vegetation.By contrast,steppes,meadows,and highland vegetation demonstrated relatively high vulnerability to temperature fluctuations.A further detailed analysis revealed that climate change had a significant positive impact on the TRSR from 2000 to 2022,particularly in its northwestern areas,accounting for 85.05%of the total area.Meanwhile,human activity played a notable positive role in the southwestern and southeastern areas of the TRSR,covering 62.65%of the total area.Therefore,climate change had a significantly higher impact on NDVI during the growing season in the TRSR than human activity.
文摘针对传统多尺度模型对模型点云比较方法(Multiscale Model to Model Cloud Comparison,M3C2)计算法向量与形变量时易受离群点影响的缺点,提出一种基于离群点探测准则的改进算法。首先,在估计关键点法向量时,依据改进离群点探测准则迭代剔除离群点,提高法向量估计的准确性,然后,通过离群点探测剔除圆柱内离群点,最后,结合正态分布加权计算形变量。实验结果表明,相较于M3C2原始算法,改进算法将法向量均方差精度指标提升50%以上,在形变量较大区域可将形变量估值均方差精度指标提高200%以上。改进算法具有更好的适用性和可靠性。
