Asia Air Survey

On the 15th of October we visited Asia Air Survey in Osaka, a geospatial information consulting company specializing in aerial surveying. The company was established after world war two to support the reconstruction of post-war Japan. And has since then developed multiple new earth observation techniques. Their scope of business consists mainly of the following three subjects: Surveying, Consulting and Mapping & GIS.

During the first presentation on LiDAR the company showed which applications they had developed throughout the years and how those applications can be used. They showed us how they could identify ground elevation as well as tree top elevations at the same time by using different frequencies. However, when scanning an area with extensive vegetation it would become hard to allow enough laser pulses to reach the ground and thus, the efficiency of determining ground elevations would decline. Therefore it is important to consider the season in which to conduct an analysis of the area. This should in most cases be done during Autumn, when the trees drop there leaves and thus allow more laser pulses to reach the ground.

They have also been able to conduct single tree identification, in which they could identify individual trees and determine its variables such as position, night, diameter at breast height and volume. Through those variables they are able to determine the specie to which the tree belongs. This information can, for example, be useful for forestry and environmental (change) analysis.

With the same method they used for forests it is possible to determine the geography of lakes, rivers and other water bodies. They could determine the water level as well as the elevation of the river bed.

The topic of the second presentation was “Sediment Movement caused by 2016 Kumamoto Earthquake and Subsequent Rainfalls in Aso Caldera”. During this Earthquake several landslides occurred in Aso Caldera, Asia Air Survey spoke about how they used LiDAR in order to analyze sediment movement within this area.

The third presentation focused on a monitoring system for a large rockslide. After eruptions of mount Unzen in 1990 and 1995 there was a fear for large rockslides which might threaten Urban areas at the foot of the mountain. Therefore a monitoring system was implemented. Several monitoring instruments were installed on the mountain to measure the displacement of rocks on the slopes. With those results it was possible to estimate the days before collapse based on the rate of displacement. Several follow up issues have been mentioned such as deciding on definitely action on prevent damage of the area at the foot of the mountain.

The second part of the visit at Asia Air Survey was dedicated to two lectures about the services carried out by Asia Air Survey (AAS). The first lecture was about the usage of mobile mapping for railway maintenance, the second lecture about the use of hyper- and multispectral data.

Japan has, just as the Netherlands, a very extensive and heavily used rail network. Therefore, proper maintenance is of great importance for the reliability of their network. Asia Air Survey has developed a mapping system using laser pulses. This creates a 3D point map of the surroundings which can be used to evaluate the entire network and its surroundings. This strongly differences from the common method of scanning the rails, as with this method much more information is gathered during the inspection ride.

Their client and partner Japan Rail West uses this data to manage their maintenance. As mentioned by others before, Japan is suffering from a decreasing work force. Therefore, this new mapping method is considered to be a solution to the lack of skilled observers because less people are required to carry out the inspections.

The system is built upon a SUV where all the sensors are mounted to. The same vehicle is also used to monitor roads. This SUV is then placed on a wagon using a specialized ladder which on its own already costs $10.000. It was mentioned that this mapping method is still very costly and efforts are taken to reduce the costs of equipment and installation.

The gathered data is used to assess the platforms, signals and wires, crossings, distance posts, bridges, slopes and cross sections. This can all be done from their office, reducing the on-site time necessary to conduct these inspections. Through the use of algorithms AAS can inspect entire rail traces in a very short time, sometimes without the need of human efforts at all. For example, the point cloud can be used to check the rail clearance and automatically detect whether objects are allowed (overhead wire poles) or not (overhanging trees etc.). This can then be passed on to JR West. Another usage is the slope of platforms. The platform should slightly skew from the tracks, such that persons in wheelchairs or baby carriages will not roll onto the rails.

The mobile mapping system is still under development, but during the presentation it became clear that the possibilities for railway and other infrastructure maintenance seems almost limitless.

The last presentation of the AAS visit was about the development of remote sensing with hyperspectral and multispectral data. Current development includes installing a hyperspectral sensor on the International Space Station in 2020 which will give a whole new range of surveying possibilities.

For now, both methods have only been used on planes, but with successful results. Through hyperspectral data AAS successfully estimated the bathymetry of coastal zones with a 10 m grid resolution. This data is a necessity for studying the effects and developments in coastal zones for civil engineers. But AAS not only provides data to relevant partners, they also carry out research themselves. For example, the bathymetry data was used to estimate flood hazard areas for tsunamis.

When the new hyperspectral sensor is successfully installed on the ISS the bathymetry of the Japanese coastal zone can be estimated and monitored for a longer period, providing civil engineers with a new source of large scale data.

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