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Measurement of out-of-plane deformation of curved objects with digital speckle pattern interferometry 被引量:1
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作者 Pengfei Li Ping Cai +2 位作者 Jun Long Chiyue Liu Hao Yan 《Chinese Optics Letters》 SCIE EI CAS CSCD 2018年第11期40-46,共7页
Digital speckle pattern interferometry (DSPI) is a high-precision deformation t technique for planar objects. However, for curved objects, the three-dimensional (3D) shape information is needed in order to obtain ... Digital speckle pattern interferometry (DSPI) is a high-precision deformation t technique for planar objects. However, for curved objects, the three-dimensional (3D) shape information is needed in order to obtain correct deformation measurement in DSPI. Thus, combined shape and deformation measurement techniques of DSPI have been proposed. However, the current techniques are either complex in setup or complicated in operation. Furthermore, the operations of some techniques are too slow for real-time measurement. In this work, we propose a DSPI technique for both 3D shape and out-of-plane deformation measurement. Compared with current techniques, the proposed technique is simple in both setup and operation and is capable of fast deformation measurement. Theoretical analysis and experiments are performed. For a cylinder surface with an arch height of 9 mm, the error of out-of-plane deformation measurement is less than 0.15 μm. The effectiveness of the proposed scheme is verified. 展开更多
关键词 Measurement of out-of-plane deformation of curved objects with digital speckle pattern interferometry
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Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe 被引量:7
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作者 JIAO Cuicui YU Guirui +3 位作者 HE Nianpeng MA Anna GE Jianping HU Zhongmin 《Journal of Geographical Sciences》 SCIE CSCD 2017年第1期3-22,共20页
Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spat... Vegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwideplaying an important role in global carbon cycling. Thereforestudying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppean important part of global grasslandsis the largest and relatively well preserved grassland in the world. In this studywe analyzed the spatial pattern of aboveground biomass(AGB)and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources(literatureglobal NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center(ORNL)some data provided by other researchers). Our results demonstrated that:(1) as for the Eurasian steppe overallthe spatial variation in AGB exhibited significant horizontal and vertical zonality. In detailAGB showed an inverted parabola curve with the latitude and with the elevationwhile a parabola curve with the longitude. In additionthe spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregionwhile horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion.(2) Of the examined environmental variablesthe spatial variation of AGB was related to mean annual precipitation(MAP)mean annual temperature(MAT)mean annual solar radiation(MAR)soil Gravel contentsoil p H and soil organic content(SOC) at the depth of 0–30 cm. NeverthelessMAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions.(3) A Gaussian function was found between AGB and MAP in the Eurasian steppe overallwhich was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion(elevation 〈 3000 m)the Mongolian Plateau steppe subregion(elevation 〈 3000 m) and the surface(elevation ≥ 4800 m) of the Tibetan Plateau. Neverthelessthe spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins(elevation 〈 4800 m) of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grasslandthe Tibetan Plateau alpine grasslandetc. 展开更多
关键词 the Eurasian steppe aboveground biomass spatial pattern parabola curve Gaussian function
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