Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between ...Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction;however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water-Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions;2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance;and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier’s performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.展开更多
ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目...ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目前利用ALI数据的全色波段以及多光谱波段进行高精度图像融合的研究较少,本文进行的实验是分别利用HSV变换、主成分分析(PCA)、Brovey变换、Gram-Schmidt变换等融合方法对ALI数据进行图像融合,通过图像融合结果的质量评价指标得出较好融合方法是HSV变换。展开更多
Fasting is a popular dietary strategy because it grants numerous advantages,and redox regulation is one mecha-nism involved.However,the precise redox changes with respect to the redox species,organelles and tissues re...Fasting is a popular dietary strategy because it grants numerous advantages,and redox regulation is one mecha-nism involved.However,the precise redox changes with respect to the redox species,organelles and tissues remain unclear,which hinders the understanding of the metabolic mechanism,and exploring the precision redox map under various dietary statuses is of great significance.Twelve redox-sensitive C.elegans strains stably expressing genetically encoded redox fluorescent probes(Hyperion sensing H_(2)O_(2) and Grx1-roGFP2 sensing GSH/GSSG)in three organelles(cytoplasm,mitochondria and endoplasmic reticulum(ER))were constructed in two tissues(body wall muscle and neurons)and were confirmed to respond to redox challenge.The H_(2)O_(2) and GSSG/GSH redox changes in two tissues and three organelles were obtained by confocal microscopy during fasting,refeeding,and satiation.We found that under fasting condition,H_(2)O_(2) decreased in most compartments,except for an increase in mitochondria,while GSSG/GSH increased in the cytoplasm of body muscle and the ER of neurons.After refeeding,the redox changes in H_(2)O_(2) and GSSG/GSH caused by fasting were reversed in most organelles of the body wall muscle and neurons.In the sati-ated state,H_(2)O_(2) increased markedly in the cytoplasm,mitochondria and ER of muscle and the ER of neurons,while GSSG/GSH exhibited no change in most organelles of the two tissues except for an increase in the ER of muscle.Our study systematically and precisely presents the redox characteristics under different dietary states in living animals and provides a basis for further investigating the redox mechanism in metabolism and optimizing dietary guidance.展开更多
基金the National Natural Science Foundation of China (Grant Nos. 41401489 and 41376178)Shanghai Foundation for University Youth Scholars (Project No. ZZHY13033)the Innovation Programme of the Shanghai Municipal Education Commission (Project No. 15ZZ082).
文摘Many megacities (such as Shanghai) are located in coastal areas, therefore, coastline monitoring is critical for urban security and urban development sustainability. A shoreline is defined as the intersection between coastal land and a water surface and features seawater edge movements as tides rise and fall. Remote sensing techniques have increasingly been used for coastline extraction;however, traditional hard classification methods are performed only at the pixel-level and extracting subpixel accuracy using soft classification methods is both challenging and time consuming due to the complex features in coastal regions. This paper presents an automatic sub-pixel coastline extraction method (ASPCE) from high-spectral satellite imaging that performs coastline extraction based on spectral mixture analysis and, thus, achieves higher accuracy. The ASPCE method consists of three main components: 1) A Water-Vegetation-Impervious-Soil (W-V-I-S) model is first presented to detect mixed W-V-I-S pixels and determine the endmember spectra in coastal regions;2) The linear spectral mixture unmixing technique based on Fully Constrained Least Squares (FCLS) is applied to the mixed W-V-I-S pixels to estimate seawater abundance;and 3) The spatial attraction model is used to extract the coastline. We tested this new method using EO-1 images from three coastal regions in China: the South China Sea, the East China Sea, and the Bohai Sea. The results showed that the method is accurate and robust. Root mean square error (RMSE) was utilized to evaluate the accuracy by calculating the distance differences between the extracted coastline and the digitized coastline. The classifier’s performance was compared with that of the Multiple Endmember Spectral Mixture Analysis (MESMA), Mixture Tuned Matched Filtering (MTMF), Sequential Maximum Angle Convex Cone (SMACC), Constrained Energy Minimization (CEM), and one classical Normalized Difference Water Index (NDWI). The results from the three test sites indicated that the proposed ASPCE method extracted coastlines more efficiently than did the compared methods, and its coastline extraction accuracy corresponded closely to the digitized coastline, with 0.39 pixels, 0.40 pixels, and 0.35 pixels in the three test regions, showing that the ASPCE method achieves an accuracy below 12.0 m (0.40 pixels). Moreover, in the quantitative accuracy assessment for the three test sites, the ASPCE method shows the best performance in coastline extraction, achieving a 0.35 pixel-level at the Bohai Sea, China test site. Therefore, the proposed ASPCE method can extract coastline more accurately than can the hard classification methods or other spectral unmixing methods.
文摘ALI(The Advanced Land Imager)数据是通过地球观测卫星-1(EO-1)搭载的高级陆地成像仪所获取的,数据的分辨率可满足遥感影像应用的多个领域,因此对ALI数据应用研究具有重要的意义。随着图像融合技术的迅速发展,融合方法种类较多,由于目前利用ALI数据的全色波段以及多光谱波段进行高精度图像融合的研究较少,本文进行的实验是分别利用HSV变换、主成分分析(PCA)、Brovey变换、Gram-Schmidt变换等融合方法对ALI数据进行图像融合,通过图像融合结果的质量评价指标得出较好融合方法是HSV变换。
基金supported by the National Key R&D Program(2022YFA1303000 and 2017YFA0504000)the National Natural Science Foundation of China(91849203,31900893)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB39000000).
文摘Fasting is a popular dietary strategy because it grants numerous advantages,and redox regulation is one mecha-nism involved.However,the precise redox changes with respect to the redox species,organelles and tissues remain unclear,which hinders the understanding of the metabolic mechanism,and exploring the precision redox map under various dietary statuses is of great significance.Twelve redox-sensitive C.elegans strains stably expressing genetically encoded redox fluorescent probes(Hyperion sensing H_(2)O_(2) and Grx1-roGFP2 sensing GSH/GSSG)in three organelles(cytoplasm,mitochondria and endoplasmic reticulum(ER))were constructed in two tissues(body wall muscle and neurons)and were confirmed to respond to redox challenge.The H_(2)O_(2) and GSSG/GSH redox changes in two tissues and three organelles were obtained by confocal microscopy during fasting,refeeding,and satiation.We found that under fasting condition,H_(2)O_(2) decreased in most compartments,except for an increase in mitochondria,while GSSG/GSH increased in the cytoplasm of body muscle and the ER of neurons.After refeeding,the redox changes in H_(2)O_(2) and GSSG/GSH caused by fasting were reversed in most organelles of the body wall muscle and neurons.In the sati-ated state,H_(2)O_(2) increased markedly in the cytoplasm,mitochondria and ER of muscle and the ER of neurons,while GSSG/GSH exhibited no change in most organelles of the two tissues except for an increase in the ER of muscle.Our study systematically and precisely presents the redox characteristics under different dietary states in living animals and provides a basis for further investigating the redox mechanism in metabolism and optimizing dietary guidance.
