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The 39th IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019), held 28 July–2 August 2019 at the Pacifico Yokohama Convention Center, Japan, welcomed more than 2,500 participants from 56 countries and areas. The local organizing com-mittee (LOC) received positive feedback from many participants, who described the venue and conference as being very convenient, well organized, and most enjoyable. The general chair attributes these positive evaluations to strong LOC teamwork. The goal of pro-viding the “best experience for all participants,” which IEEE Geoscience and Remote Sensing Society (GRSS) President Paolo Gamba and I confirmed at the GRSS administrative committee meetings, was shared by all of the LOC members.One of the highlights of the symposium was the opening ceremony, which was held in a solemn but warm atmosphere on 29 July with Their Majesties the Emperor and Empress of Japan in attendance. In his address, His Majesty the Emperor referred to the importance of detailed and accurate data acqui-sition and analysis, which greatly encouraged the participants working in the geoscience and remote sensing field.In this column, the LOC cochairs, who supervised the harmonious teamwork, revisit the events and re-view the activities, statistics, and logistics, which will be helpful for future IGARSS events. Following each of the following sections, the chairs’ names are provided so that readers can contact them. The “Conference Re-port” column “IGARSS in Yokohama, Japan: Impres-sions From the First Days” in the September 2010 issue of IEEE Geoscience and Remote Sensing Magazine [1] i s also informative.

形態: カラー図版あり, Physical characteristics: Original contains color illustrations, Accepted: 2019-09-27, 資料番号: PA2010006000

SAR Tomography (TomoSAR) regards multi-baseline observation data as array observation data and realizes three-dimensional imaging by applying direction of arrival (DOA) estimation processing. To improve angular resolution of the TomoSAR with suppressing ambiguity, many repeat-pass data are required. However, it is often difficult to increase the number of data because of the cost. In this paper, we propose to apply the Khatri-Rao (KR) product virtual array processing to the multi-baseline observation data. We show that the KR processing improves angular resolution of the TomoSAR and suppression of ambiguity by using the experimental data obtained by the Pi-SAR2-X.

Recently, microwave remote sensing has been used for observation of the global environment extensively. There are many techniques in the microwave remote sensing. Among them, SAR (Synthetic Aperture Radar) Tomography is one of the emerging technique that can realize three dimensional imaging, by using multiple flight paths. The data pixels in each SAR image obtained at the slightly different paths may be regarded as the observed data with an array antenna. Thus, it is applying the Direction of Arrival (DOA) estimation technique to the array data, we estimate angle of dominant scatterers, or height of the targets. In this report, we provide preliminary results of the multi-baseline SAR Tomography observed by the PiSAR2-X, airborne X-band SAR of NICT, Japan.

The Great East Japan Earthquake occurred at March 11, 2011 and caused massive tidal wave. The tsunami swept away a large quantity of rubble and vessels to the sea and they become so-called marine debris. To assess damage situation and protect marine environment, it is essentially required to investigate the status of those marine debris. The technique based on spaceborne synthetic aperture radar (SAR) can be a strong candidate to achieve this ultimate goal, because of its wide observation area and higher resolution with flexible operability: regardless of the day and night and regardless of the weather. We have monitored marine debris on huge amount of spaceborne SAR imagery right after the great disaster and investigated an effective observation of marine debris to predict future direction. In this paper, we firstly define three types of debris as large debris, small debris, and cluster by considering how marine debris looks like on the SAR imagery. Then, an automatic but accurate detection and classification of a large amount of debris on SAR imagery is proposed. Based on those results, resolution and swath width for efficient marine debris monitoring are obtained. Velocity of marine debris is additionally estimated from multi-temporal SAR images to derive optimum swath width.