Background:Accurate mapping of tree species is highly desired in the management and research of plantation forests,whose ecosystem services are currently under threats.Time-series multispectral satellite images,e.g.,f...Background:Accurate mapping of tree species is highly desired in the management and research of plantation forests,whose ecosystem services are currently under threats.Time-series multispectral satellite images,e.g.,from Landsat-8(L8)and Sentinel-2(S2),have been proven useful in mapping general forest types,yet we do not know quantitatively how their spectral features(e.g.,red-edge)and temporal frequency of data acquisitions(e.g.,16-day vs.5-day)contribute to plantation forest mapping to the species level.Moreover,it is unclear to what extent the fusion of L8 and S2 will result in improvements in tree species mapping of northern plantation forests in China.Methods:We designed three sets of classification experiments(i.e.,single-date,multi-date,and spectral-temporal)to evaluate the performances of L8 and S2 data for mapping keystone timber tree species in northern China.We first used seven pairs of L8 and S2 images to evaluate the performances of L8 and S2 key spectral features for separating these tree species across key growing stages.Then we extracted the spectral-temporal features from all available images of different temporal frequency of data acquisition(i.e.,L8 time series,S2 time series,and fusion of L8 and S2)to assess the contribution of image temporal frequency on the accuracy of tree species mapping in the study area.Results:1)S2 outperformed L8 images in all classification experiments,with or without the red edge bands(0.4%–3.4%and 0.2%–4.4%higher for overall accuracy and macro-F1,respectively);2)NDTI(the ratio of SWIR1 minus SWIR2 to SWIR1 plus SWIR2)and Tasseled Cap coefficients were most important features in all the classifications,and for time-series experiments,the spectral-temporal features of red band-related vegetation indices were most useful;3)increasing the temporal frequency of data acquisition can improve overall accuracy of tree species mapping for up to 3.2%(from 90.1%using single-date imagery to 93.3%using S2 time-series),yet similar overall accuracies were achieved using S2 time-series(93.3%)and the fusion of S2 and L8(93.2%).Conclusions:This study quantifies the contributions of L8 and S2 spectral and temporal features in mapping keystone tree species of northern plantation forests in China and suggests that for mapping tree species in China's northern plantation forests,the effects of increasing the temporal frequency of data acquisition could saturate quickly after using only two images from key phenological stages.展开更多
【目的】分析185份陆地棉品种(系)的开花期株高(PH-ST_(1))和吐絮期株高(PH-ST_(2))关联度,发掘动态株高的优异等位变异,为进一步棉花高产分子辅助育种提供参考。【方法】利用185份陆地棉品种(系)的基因型,将137对简单重复序列(simple s...【目的】分析185份陆地棉品种(系)的开花期株高(PH-ST_(1))和吐絮期株高(PH-ST_(2))关联度,发掘动态株高的优异等位变异,为进一步棉花高产分子辅助育种提供参考。【方法】利用185份陆地棉品种(系)的基因型,将137对简单重复序列(simple sequence repeat,SSR)多态性引物开发出的355个多态性位点,并结合5个环境下两个时期的株高表型数据,采用一般线性模型(general linear model,GLM)和混合线性模型(mixed linear model,MLM)进行关联分析。【结果】使用GLM模型和MLM模型,分别检测到54、12个与PH-ST_(1)显著相关的位点和62、12个与PH-ST_(2)显著相关的位点;其中,31个位点在3个或3个以上的环境都与株高显著相关。【结论】挖掘了多个可重复检测到的与陆地棉株高相关联的分子标记位点。定位到与株高性状相关的位点有24个。展开更多
基金supported by National Natural Science Foundation of China(Grant No.41901382)Open Fund of State Key Laboratory of Remote Sensing Science(Grant No.OFSLRSS201917)the HZAU research startup fund(No.11041810340,No.11041810341).
文摘Background:Accurate mapping of tree species is highly desired in the management and research of plantation forests,whose ecosystem services are currently under threats.Time-series multispectral satellite images,e.g.,from Landsat-8(L8)and Sentinel-2(S2),have been proven useful in mapping general forest types,yet we do not know quantitatively how their spectral features(e.g.,red-edge)and temporal frequency of data acquisitions(e.g.,16-day vs.5-day)contribute to plantation forest mapping to the species level.Moreover,it is unclear to what extent the fusion of L8 and S2 will result in improvements in tree species mapping of northern plantation forests in China.Methods:We designed three sets of classification experiments(i.e.,single-date,multi-date,and spectral-temporal)to evaluate the performances of L8 and S2 data for mapping keystone timber tree species in northern China.We first used seven pairs of L8 and S2 images to evaluate the performances of L8 and S2 key spectral features for separating these tree species across key growing stages.Then we extracted the spectral-temporal features from all available images of different temporal frequency of data acquisition(i.e.,L8 time series,S2 time series,and fusion of L8 and S2)to assess the contribution of image temporal frequency on the accuracy of tree species mapping in the study area.Results:1)S2 outperformed L8 images in all classification experiments,with or without the red edge bands(0.4%–3.4%and 0.2%–4.4%higher for overall accuracy and macro-F1,respectively);2)NDTI(the ratio of SWIR1 minus SWIR2 to SWIR1 plus SWIR2)and Tasseled Cap coefficients were most important features in all the classifications,and for time-series experiments,the spectral-temporal features of red band-related vegetation indices were most useful;3)increasing the temporal frequency of data acquisition can improve overall accuracy of tree species mapping for up to 3.2%(from 90.1%using single-date imagery to 93.3%using S2 time-series),yet similar overall accuracies were achieved using S2 time-series(93.3%)and the fusion of S2 and L8(93.2%).Conclusions:This study quantifies the contributions of L8 and S2 spectral and temporal features in mapping keystone tree species of northern plantation forests in China and suggests that for mapping tree species in China's northern plantation forests,the effects of increasing the temporal frequency of data acquisition could saturate quickly after using only two images from key phenological stages.
文摘【目的】分析185份陆地棉品种(系)的开花期株高(PH-ST_(1))和吐絮期株高(PH-ST_(2))关联度,发掘动态株高的优异等位变异,为进一步棉花高产分子辅助育种提供参考。【方法】利用185份陆地棉品种(系)的基因型,将137对简单重复序列(simple sequence repeat,SSR)多态性引物开发出的355个多态性位点,并结合5个环境下两个时期的株高表型数据,采用一般线性模型(general linear model,GLM)和混合线性模型(mixed linear model,MLM)进行关联分析。【结果】使用GLM模型和MLM模型,分别检测到54、12个与PH-ST_(1)显著相关的位点和62、12个与PH-ST_(2)显著相关的位点;其中,31个位点在3个或3个以上的环境都与株高显著相关。【结论】挖掘了多个可重复检测到的与陆地棉株高相关联的分子标记位点。定位到与株高性状相关的位点有24个。
