List : 衛星ビジネス
Time has come for 37 space companies to say goodbye to 2020 and welcome in the New Year, 2021!
In this article, we ask each of the 37 Japanese space companies about their highlights in 2020 and their resolutions for 2021. What kind of year was 2020 for the Japanese space industry?
Space as a “means” used in business: summary of market size and operators of microsatellites
Compared to large satellites, small satellites can be developed at a lower cost and in less time. An increasing number of companies are developing small satellites, especially microsatellites. This article explains what companies are working on, in what fields, and also how to make a small satellite.
Using Amedas Data to Visualize Temperature Forecasts and Rainfall in Real Time.
For this article, we used the Amedas minute-by-minute data available on Tellus for our analysis. We looked specifically at the minute-by-minute Amedas data in northern Kyushu for rainfall that occurred between 5th and 6th of July 2017.
No Image Pair required! Converting To and From Optical and SAR Images With Unsupervised Learning
In this article we use a yet-to-be released data set to convert SAR images into optical images, and vise-versa by using unsupervised learning that doesn't require image pairs.
Via using a Learned Model, we create a Machine Learning Model to Easily Detect Golf Courses [Code/Data Included]
Creating a machine learning model with transition learning by using a trained model makes it easier to perform image identification prediction. We will go into detail on images both with and without golf courses, and the coding behind them.
Automatic Detection of Parking-Lot Space With Satellite Data Challenges and Points of Improvement for the Joint Project by Sakura Internet, akippa, and Ridge-i
During a talk session on August 4, it was announced that Sakura Internet, akippa, and Ridge-i are working together to develop an algorithm that uses satellite data to find space that can be rented out for parking cars, so we decided to talk with them about the challenges they face whilst developing this service, and the success they have made using Sharp's super-resolution technology.
The “Extracting Difference Between Two Points of Satellite Data” Challenge — A Look at ABEJA’s Difference Extracting Algorithm
We went behind the scenes to ask ABEJA about the applications and future of their difference extracting algorithm!
Super-Resolution Processing of Satellite Images Using Sharp’s Deep Learning Model
Super-resolution is a technique to artificially raise the resolution of an image. Super-resolution is one of the hot topics in the field of machine learning, but what happens when you combine it with satellite imagery? We went to the Sharp Corporation Research and Development HQ, and asked the manager of the 3rd Research Team for Communication & Image Technology Laboratories, Tomohiro Ikai, and researcher, Eiichi Sasaki about the future of this technology.
Sensing disasters and environmental changes in house! The future of risk management with small SAR satellites
We interviewed Mr. Ichiki, COO of iQPS Inc., which successfully launched its first small SAR satellite "IZANAGI" in December 2019, about his motivation to become a manager and the potential of the satellite business.
Imaging PALSAR-2 L1.1 using Tellus [with code]
This article describes how to extract and visualize complex images (images with phase and reflection intensity information of radio waves) from PALSAR-2 L1.1 data released on Tellus in accordance with the format called the CEOS format.