Geoinformation Science Research Team

MUltiband Satellite Imagery for object Classification (MUSIC) for HotArea dataset

We created MUltiband Satellite Imagery for object Classification (MUSIC) for HotArea (HA) dataset. The HA is a system to automatically detect hotspots (e.g., fires and volcanoes) in the world in mid-resolution satellite data and displays the results on a web-based GIS system. Currently Hotarea utilizes Landsat 8 and Sentinel-2 data in global scale and in some selected regions, respectively.

MUltiband Satellite Imagery for object Classification (MUSIC) to detect Golf Course

We have created MUltiband Satellite Imagery for object Classification (MUSIC) to detect Golf Course (GC). There are more than 30,000 golf courses all over the world. They are good targets for research of automatic object detection due to their specific shape, world-wide distribution and common size. MUSIC for GC is the dataset to support the global survey of golf courses based on satellite imagery.

We have created Hyper Spectral Salient Object Detection Dataset (HS-SOD)

Automated Attitude Determination for Pushbroom Sensors Based on Robust Image Matching

Ryu Sugimoto, Toru Kouyama, Atsunori Kanemura, Soushi Kato, Nevrez Imamoglu, Ryosuke Nakamura

<Abstract>

Accurate attitude information from a satellite image sensor is essential for accurate map projection and reducing computational cost for post-processing of image registration, which enhance image usability, such as change detection. We propose a robust attitude-determination method for pushbroom sensors onboard spacecraft by matching land features in well registered base-map images and in observed images, which extends the current method that derives satellite attitude using an image taken with 2-D image sensors. Unlike 2-D image sensors, a pushbroom sensor observes the ground by changing its position and attitude according to the trajectory of a satellite. To address pushbroom-sensor observation, the proposed method can trace the temporal variation in the sensor attitude by combining the robust matching technique for a 2-D image sensor and a non-linear least squares approach, which can express gradual time evolution of the sensor attitude. Experimental results using images taken from a visible and near infrared pushbroom sensor of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard Terra as test image and Landsat-8/OLI images as a base map show that the proposed method can determine satellite attitude with an accuracy of 0.003° (corresponding to the 2-pixel scale of ASTER) in roll and pitch angles even for a scene in which there are many cloud patches, whereas the determination accuracy remains 0.05° in the yaw angle that does not affect accuracy of image registration compared with the other two axes. In addition to the achieved attitude accuracy that was better than that using star trackers (0.01°) regarding roll and pitch angles, the proposed method does not require any attitude information from onboard sensors. Therefore, the proposed method may contribute to validating and calibrating attitude sensors in space, at the same time better accuracy will contribute to reducing computational cost in post-processing for image registration.

Animal Detection Using Thermal Images and Its Required Observation Conditions

Yu Oishi, Hiroyuki Oguma, Ayako Tamura, Ryosuke Nakamura and Tsuneo Matsunaga　

<Abstract>
Information about changes in the population sizes of wild animals is extremely important for conservation and management. Wild animal populations have been estimated using statistical methods, but it is difficult to apply such methods to large areas. To address this problem, we have developed several support systems for the automated detection of wild animals in remote sensing images. In this study, we applied one of the developed algorithms, the computer-aided detection of moving wild animals (DWA) algorithm, to thermal remote sensing images. We also performed several analyses to confirm that the DWA algorithm is useful for thermal images and to clarify the optimal conditions for obtaining thermal images (during predawn hours and on overcast days). We developed a method based on the algorithm to extract moving wild animals from thermal remote sensing images. Then, accuracy was evaluated by applying the method to airborne thermal images in a wide area. We found that the producer's accuracy of the method was approximately 77.3% and the user's accuracy of the method was approximately 29.3%. This means that the proposed method can reduce the person-hours required to survey moving wild animals from large numbers of thermal remote sensing images. Furthermore, we confirmed the extracted sika deer candidates in a pair of images and found 24 moving objects that were not identified by visual inspection by an expert. Therefore, the proposed method can also reduce oversight when identifying moving wild animals. The detection accuracy is expected to increase by setting suitable observation conditions for surveying moving wild animals. Accordingly, we also discuss the required observation conditions. The discussions about the required observation conditions would be extremely useful for people monitoring animal population changes using thermal remote sensing images.

Extremely strong polarization of an active asteroid (3200) Phaethon

Takashi Ito, Masateru Ishiguro, Tomoko Arai, Masataka Imai, Tomohiko Sekiguchi, Yoonsoo P. Bach, Yuna G. Kwon, Masanori Kobayashi, Ryo Ishimaru, Hiroyuki Naito, Makoto Watanabe & Kiyoshi Kuramoto

<Abstract>
The near-Earth asteroid (3200) Phaethon is the parent body of the Geminid meteor stream. Phaethon is also an active asteroid with a very blue spectrum. We conducted polarimetric observations of this asteroid over a wide range of solar phase angles α during its close approach to the Earth in autumn 2016. Our observation revealed that Phaethon exhibits extremely large linear polarization: P = 50.0 ± 1.1% at α = 106.5°, and its maximum is even larger. The strong polarization implies that Phaethon's geometric albedo is lower than the current estimate obtained through radiometric observation. This possibility stems from the potential uncertainty in Phaethon's absolute magnitude. An alternative possibility is that relatively large grains (~300 μm in diameter, presumably due to extensive heating near its perihelion) dominate this asteroid's surface. In addition, the asteroid's surface porosity, if it is substantially large, can also be an effective cause of this polarization.