11:00 AM - 1:00 PM
[MGI35-P02] Development of Mars Web-GIS for understanding the terrain by combining rover and orbiter data
A huge amount of data has been accumulated on Mars due to the increasing number of missions and various kinds of instruments with higher accuracy. It is not easy to process the huge amount of data and to understand the relationship of them visually and intuitively. In recent years, especially, very informative data from rovers on Mars have been added. It is important to integrate the information from multiple probes to understand the surface environment of Mars properly.
Geographic Information System (GIS) is a tool to visualize, integrate, and analyze the data with geographical information. "Red Ace", which was developed in Matsubara et al. (2018), is one of such tools. "Red Ace" mainly displays spectral data that helps us to understand the mineral distribution on Mars.
The best way to understand the topography is to use the 3D display, but currently there are only a few 3D GIS tools for Mars. The rover observation data has a very high spatial resolution while the observation area is extremely narrower than that of the orbiter. Visualization of such multi-scaled observation data on Mars will contribute to the understanding of Mars.
We have developed a new Web-GIS application for Mars named as "Red Ace2" which can handle multiple kinds of observation data at the same time such as the rover image from the Opportunity, Orbiter image from HiRISE, and the DEM (Digital Elevation Model) data. The “Red Ace2” can display Mars rover's observation data, the Mars orbiter's observation 2D/3D images data of high-resolution, the terrain data, and 360° view where machine learning is applied to extrapolate the missing data.
"Red Ace2" is developed based on CesiumJS, an open-source JavaScript library for 2D/3D maps. HiRISE 2D data can be manipulated intuitively by OpenLayers, an open-source JavaScript library, and HiRISE 3D data can be manipulated fundamentally by Three.JS, an open-source JavaScript library. By clicking on HiRISE 3D data with Opportunity's movement path, the rover minute image appears. The Opportunity observation data can be manipulated by OpenLayers. By selecting a specific Mars-day called “sol”, users can view 360° 3D data using a composite image created by combining Opportunity mosaics data and images created by machine learning.
We have adopted JSON format for the data handling in "Red Ace2" following Matsubara et al. (2018), so we can integrate the two Red Aces in future easily.
Geographic Information System (GIS) is a tool to visualize, integrate, and analyze the data with geographical information. "Red Ace", which was developed in Matsubara et al. (2018), is one of such tools. "Red Ace" mainly displays spectral data that helps us to understand the mineral distribution on Mars.
The best way to understand the topography is to use the 3D display, but currently there are only a few 3D GIS tools for Mars. The rover observation data has a very high spatial resolution while the observation area is extremely narrower than that of the orbiter. Visualization of such multi-scaled observation data on Mars will contribute to the understanding of Mars.
We have developed a new Web-GIS application for Mars named as "Red Ace2" which can handle multiple kinds of observation data at the same time such as the rover image from the Opportunity, Orbiter image from HiRISE, and the DEM (Digital Elevation Model) data. The “Red Ace2” can display Mars rover's observation data, the Mars orbiter's observation 2D/3D images data of high-resolution, the terrain data, and 360° view where machine learning is applied to extrapolate the missing data.
"Red Ace2" is developed based on CesiumJS, an open-source JavaScript library for 2D/3D maps. HiRISE 2D data can be manipulated intuitively by OpenLayers, an open-source JavaScript library, and HiRISE 3D data can be manipulated fundamentally by Three.JS, an open-source JavaScript library. By clicking on HiRISE 3D data with Opportunity's movement path, the rover minute image appears. The Opportunity observation data can be manipulated by OpenLayers. By selecting a specific Mars-day called “sol”, users can view 360° 3D data using a composite image created by combining Opportunity mosaics data and images created by machine learning.
We have adopted JSON format for the data handling in "Red Ace2" following Matsubara et al. (2018), so we can integrate the two Red Aces in future easily.