List : 衛星データ
Automatic extraction of changes in cities and buildings from two satellite images! New Tellus tool “Tellus-DEUCE” is now available.
We will introduce what you can do with the new Tellus tool "Tellus-DEUCE," released on the 25th of February 2021, which can automatically extract the difference between two selected satellite images using AI, showing some actual screenshots and how to use it.
The 4th Tellus Satellite Challenge! Explanation of approaches taken by the winners
"Coastline extraction" was the theme of the 4th Tellus Satellite Challenge. In this article, we will look at the approaches taken by the winners, make comparisons, and summarize their methods so that they can be applied to other (satellite) image data competitions.
Marine litter in the oceans can’t be solved by volunteering. Project IKKAKU’s Vision for an Economic System That Combats Marine Pollution
Project IKKAKU is working to create an economic system that combats marine pollution. We spoke with Yuko Ueno, a representative from Leave a Nest America, about their plans.
Is the Susanoo Shrine built in a location that is resistant to flood damage? We took a look at the enshrined deity and used satellite data to examine the city it is in.
In this article, we will be using the satellite data platform "Tellus" to look into a series of shrines called the Yasaka Shrines, which have both Buddhist and Shinto aspects to them. We will look specifically at their Hikawa sect which enshrines the deity Susanoo. Looking at Shrines From Space! Pretty Cool, Eh?
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?
The Shift to a Five Axelspace GRUS Satellite System. The roadmap to achieving profits of $100 million.
Axelspace released their plans to launch four GRUS small satellites. The company shared its revenue goals at the unveiling of its satellites. Along with a summary of the event, we here at the SORABATAKE editorial department would like to share an estimation of how many satellite images they will need to sell to achieve their goals.
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.
Using SSD to Perform Object Detection on Airplanes
For readers who want to try using machine learning and satellite data to do something interesting, we'd like to suggest trying out object detection. In this article, we attempt to use satellite data in order to perform object detection on airplanes.
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 4th Tellus Satellite Challenge is now underway! The theme is “coastline extraction.”
Here is an overview of the 4th Tellus Satellite Challenge, a competition for segmentation using satellite images, with details of the competition, helpful papers, and material.
Structural Classifications Using SAR Polarimetry (Polarimetric Decomposition)
In today's article, we will be testing out whether or not you can use polarimetric decomposition to differentiate between natural and man-made objects.
Do Smaller Antenna Really Correlate With Higher Resolution? Thorough Examination of One of SAR’s Mysteries Without Using any Formulas!
This time, we are speaking with a broad group of people who are interested in SAR images, including an engineer who processes them, to a business developer, obsessed with the SAR industry, to learn what determines the resolution of SAR images from top to bottom.
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!
NDVI provided by Shikisai (GCOM-C) is available on Tellus!
We will be introducing the summary and directions for using the NDVI (normalized difference vegetation index) data provided by Shikisai (GCOM-C), that was added to Tellus OS on May 28, 2020.
Using Tellus to Determine Land Subsidence via InSAR Analysis [Code Included]
This article will go over coding algorithms for the interferometric analysis of SAR images. Anyone can use this code to create their own InSAR images.
Get super-resolution for satellite images using SRCNN [with code]
In this article, we will try to get super-resolution images of actual satellite data using Tellus.