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A hypsometric map is a type of map used to represent topographic characteristics by filling different map areas with diverging colors. The setting of appropriate diverging colors is essential for the map to reveal topographic details. When lunar real environmental exploration programs are performed, large-scale hypsometric maps with a high resolution and greater topographic detail are helpful. Compared to the situation on Earth, fewer lunar exploration objects are available, and the topographic waviness is smaller at a large scale, indicating that presenting the topographic details using traditional hypsometric map-making methods may be difficult. To solve this problem, we employed the Chang’E2 (CE2) topographic and imagery data with a resolution of 7 m and developed a new hypsometric map-making method by setting the diverging colors based on information entropy. The resulting map showed that this method is suitable for presenting the topographic details and might be useful for developing a better understanding of the environment of the lunar surface.

Blue jets and blue starters are partially ionized luminous cones of primarily blue light that propagate upward out of the top of thunderstorms at speeds of order 100 km s−1. Blue jets propagate up ∼40 km, but blue starters, which resemble blue jets, terminate abruptly after only a few kilometers of upward travel. Theories on the origin of blue jets have proposed that they are due to either positive or negative streamers or runaway electrons. Quantitative analysis of new multi‐instrument observations of a blue starter from an aircraft during the Energetics of Upper Atmospheric Excitation by Lightning, 1998 (EXL98) campaign of July 1998, shows that the ionization accounts for ∼3% of the observed intensity. Quantitative analysis of a remarkable color photograph of a blue jet taken from Réunion Island in the Indian Ocean shows that the minimum optical energy deposition was ∼0.5 MJ. The same photograph shows details of streamers never before seen.

The Global Marine Environment Datasets (GMED) is a compilation of publicly available climatic, biological and geophysical environmental layers featuring present, past and future environmental conditions. Marine biologists increasingly utilize geo-spatial techniques with modelling algorithms to visualize and predict species biodiversity at a global scale. Marine environmental datasets available for species distribution modelling (SDM) have different spatial resolutions and are frequently provided in assorted file formats. This makes data assembly one of the most time-consuming parts of any study using multiple environmental layers for biogeography visualization or SDM applications. GMED covers the widest available range of environmental layers from a variety of sources and depths from the surface to the deepest part of the ocean. It has a uniform spatial extent, high-resolution land mask (to eliminate land areas in the marine regions), and high spatial resolution (5 arc-minute, c. 9.2 km near equator). The free public online availability of GMED enables rapid map overlay of species of interest (e.g. endangered or invasive) against different environmental conditions of the past, present and the future, and expedites mapping distribution ranges of species using popular SDM algorithms. GMED can be found at http://gmed.auckland.ac.nz/ (DOI: https://10.6084/m9.figshare.5937268).

We introduce a data-reduction package written in Interactive Data Language (IDL) for the Magellan Echellete Spectrograph (MAGE). MAGE is a medium-resolution (R 4100), cross-dispersed, optical spectrograph, with coverage from . The MAGE Spectral Extractor (MASE) incorporates the entire image reduction and calibration process, including bias subtraction, flat fielding, wavelength calibration, sky subtraction, object extraction, and flux calibration of point sources. We include examples of the user interface and reduced spectra. We show that the wavelength calibration is sufficient to achieve 5 km s-1 rms accuracy and relative flux calibrations better than 10%. A lightweight version of the full reduction pipeline has been included for real-time source extraction and signal-to-noise estimation at the telescope. Massachusetts Institute of Technology. School of Science National Science Foundation (AST- 0215989) Carnegie Observatories

Abstract The Internet and the Internet of Things (IoT) connect the world inside and outside the network through online and offline communication, which forms the original single network virtual platform. The integration of IoT, virtual reality and artificial intelligence can provide intelligent WebVR interaction for various application fields. However, we need to solve the problems of data lightweight, real-time data transmission based on the IoT, and visualization of scene data on the Web. This paper uses the IoT and virtual reality technology to propose a virtual reality scene modeling method based on the IoT platform, as well as the database dynamic loading management method and device of the virtual reality system, which includes building the database, storing the involved data structures for various scenes and functions in the virtual reality system. The time–space IoT engine is connected with the integrated service sharing center. The IoT platform collects data through the IoT sensor system and provides support for the application platform through the integrated service sharing center. The proposed method can meet the needs of large-scale data acquisition and modeling, shorten the loading time, improve the efficiency, and save the wasted computing resources and memory.

We made a study of the characteristics of geomagnetic negative sudden impulses (SI−s) identified in the midlatitude geomagnetic SYM indices and the causative structures in the solar wind using data from the Wind and ACE spacecraft. A total of 28 SI−s with an amplitude larger than 20 nT in the H component SYM index were found over the period 1995 through 1999, with 50% of them occurring in conjunction with a positive sudden impulse, SI+ (i.e., SI pair). In the SI pairs the amplitude of SI− was almost always larger than that of the preceding SI+. We attempted for the first time a classification of structures in the solar wind associated with SI−s. It is found that reverse shocks are not responsible for SI−s. Instead, SI−s are associated with varied structures such as tangential discontinuities at high‐low speed stream interfaces, front boundaries of interplanetary magnetic clouds, and trailing edges of heliospheric plasma sheets. There is no preferential association of SI−s in our sample with any particular type of solar wind structure. We investigated statistically the polarization characteristics of SI−s at high latitude. The sense of the polarization in the auroral zone tended to be clockwise in the afternoon and counterclockwise in the morning. The rotational sense reversed in the polar cap. The latitudinal reversal occurred in the range from 65° to 80°. Thus the polarization distribution of SI− is not opposite to but is consistent with that of SI+. We suggest that the contribution from the longitudinal movement of a twin vortex ionospheric current system is dominant to produce the polarization of SC and SI−.

Because ALEXIS is a spinning satellite, it is an ideal platform with which to study the time variability of the EUV cosmos. The main thrusts of this effort are to 1) detect EUV sources at known and unknown locations, 2) provide notification of transients in near real time to enable immediate follow-up from other observatories, and 3) create a time history of observed sources for comparison with previously published catalogs to aid in determining long duration variability from EUV sources.