A shadow- eliminated vegetation index (SEVI) for removal of self and cast shadow effects on vegetation in rugged terrains

The effect of terrain shadow, including the self and cast shadows, is one ofthe main obstacles for accurate retrieval of vegetation parameters byremote sensing in rugged terrains. A shadow- eliminated vegetation index(SEVI) was developed, which was computed from only red and nearinfrared top-of-atmosphere reflectance without other heterogeneous dataand topographic correction. After introduction of the conceptual modeland feature analysis of conventional wavebands, the SEVI was constructedby ratio vegetation index (RVI), shadow vegetation index (SVI) andadjustment factor (f (Δ)). Then three methods were used to validate theSEVI accuracy in elimination of terrain shadow effects, including relativeerror analysis, correlation analysis between the cosine of solar incidenceangle (cosi) and vegetation indices, and comparison analysis between SEVIand conventional vegetation indices with topographic correction. Thevalidation results based on 532 samples showed that the SEVI relativeerrors for self and cast shadows were 4.32% and 1.51% respectively. Thecoefficient of determination between cosi and SEVI was only 0.032 and thecoefficient of variation (std/mean) for SEVI was 12.59%. The results indicatethat the proposed SEVI effectively eliminated the effect of terrain shadowsand achieved similar or better results than conventional vegetation indiceswith topographic correction.

Virtual&augmented reality for biological microscope in experiment education

Background Mixed-reality technologies,including virtual reality(VR)and augmented reality(AR),are considered to be promising potential tools for science teaching and learning processes that could foster positive emotions,motivate autonomous learning,and improve learning outcomes.Methods In this study,a technology-aided biological microscope learning system based on VR/AR is presented.The structure of the microscope is described in a detailed three-dimensional(3D)model,each component being represented with their topological interrelationships and associations among them being established.The interactive behavior of the model was specified,and a standard operating guide was compiled.The motion control of components was simulated based on collision detection.Combined with immersive VR equipment and AR technology,we developed a virtual microscope subsystem and a mobile virtual microscope guidance system.Results The system consisted of a VR subsystem and an AR subsystem.The focus of the VR subsystem was to simulate operating the microscope and associated interactive behaviors that allowed users to observe and operate the components of the 3D microscope model by means of natural interactions in an immersive scenario.The AR subsystem allowed participants to use a mobile terminal that took a picture of a microscope from a textbook and then displayed the structure and functions of the instrument,as well as the relevant operating guidance.This flexibly allowed students to use the system before or after class without time and space constraints.The system allowed users to switch between the VR and AR subsystems.Conclusions The system is useful for helping learners(especially K-12 students)to recognize a microscope's structure and grasp the required operational skills by simulating operations using an interactive process.In the future,such technology-assisted education would be a successful learning platform in an open learning space.