Tae-Byeong Chae

Image Fusion-Based Change Detection for Flood Extent Extraction Using Bi-Temporal Very High-Resolution Satellite Images

Change detection based on satellite images acquired from an area at different dates is of widespread interest, according to the increasing number of flood-related disasters. The images help to generate products that support emergency response and flood management at a global scale. In this paper, a novel unsupervised change detection approach based on image fusion is introduced. The approach aims to extract the reliable flood extent from very high-resolution (VHR) bi-temporal images. The method takes an advantage of the spectral distortion that occurs during image fusion process to detect the change areas by flood. To this end, a change candidate image is extracted from the fused image generated with bi-temporal images by considering a local spectral distortion. This can be done by employing a universal image quality index (UIQI), which is a measure for local evaluation of spectral distortion. The decision threshold for the determination of changed pixels is set by applying a probability mixture model to the change candidate image based on expectation maximization (EM) algorithm. We used bi-temporal KOMPSAT-2 satellite images to detect the flooded area in the city of N′djamena in Chad. The performance of the proposed method was visually and quantitatively compared with existing change detection methods. The results showed that the proposed method achieved an overall accuracy (OA = 75.04) close to that of the support vector machine (SVM)-based supervised change detection method. Moreover, the proposed method showed a better performance in differentiating the flooded area and the permanent water body compared to the existing change detection methods.

A study of the feasibility of using KOMPSAT-5 SAR data to map sea ice in the Chukchi Sea in late summer

ABSTRACT In this study, a sea ice mapping model based on Random Forest (RF), a rule-based machine learning approach, has been developed for the Korea Multi-Purpose Satellite-5 (KOMPSAT-5) Synthetic Aperture Radar (SAR) data in Enhanced Wide swath mode obtained from 6 August to 9 September 2015 in the Chukchi Sea. A total of 12 texture features derived from backscattering intensity and the gray-level co-occurrence matrix were used as input variables for sea ice mapping. The RF model produced a sea ice map with a grid spacing of 125 m, demonstrating excellent performance in the classification of sea ice and open water with an overall accuracy of 99.2% and a kappa coefficient of 98.5%. Sea ice concentration (SIC) retrieved from the RF-derived sea ice maps was compared with that from ice charts. The mean and median values of the differences between the SICs derived from the RF model and the ice charts were −8.85% and −8.38%, respectively. Such difference was attributed to both the uncertainty in the ice charts and classification error of the RF model.

Parallel Processing with MPI for Inter-band Registration in Remote Sensing

Inter-band registration is an essential processing method that is used to generate satellite imagery products with raw data obtained from a high-resolution satellite. The processing method requires considerable time owing to its high computational cost as well as the large-scale data to be processed. In this paper, we present a parallel inter-band registration method on windows-based clusters as part of an effort to reduce the total execution time during product generation. We use a blade system as clusters and the MPICH2 library for the parallel programming tool. We logically divide roles of the nodes into one root node, three sub-root nodes, and several compute nodes. We divide the inter-band registration into sequential and parallel processing areas to design the nodes suitable for inter-band registration. The root node and sub-root nodes control the sequential processing area and exchange data with compute nodes in the parallel processing area. In addition, we introduce an object-oriented pseudo code for easy parallelization using a Message Passing Interface (MPI). We apply our system on the KOMPSAT-2 product generation process. The experimental result shows that our system reduces the total execution time from 330 seconds to 79 seconds.

The KOMPSAT-5 Image Reception and Processing Element

KOREAs first synthetic aperture radar (SAR) satellite, KOMPSAT-5, is now ready to launch in the middle of 2011. The KOMPSAT-5 will be delivered to low Earth orbit for all-weather day-night monitoring of the Korean peninsula. The primary mission goal is to provide GOLDEN mission: Geographic information system, Ocean management, Land management, Disaster monitoring, and ENvironment monitoring. In order to fulfill the GOLDEN mission, the KOMPSAT-5 will use COSI (COrea SAR Instrument) payload to provide high-resolution mode SAR images of 1 m resolution, standard mode SAR images of 3 m resolution, and wide-swath mode SAR images of 20 m resolution, all with the viewing condition of a 45-degree incidence angle. The KOMPSAT-5 Ground Segment (KGS) constitutes three central elements—Mission Control Element, Calibration and Verification Element, and Image Reception and Processing Element (IRPE)—for controlling and operating the KOMPSAT-5 satellite; for calibrating its COSI payload; for archiving the SAR data; and for generating and distributing basic products. This paper outlines the KGS layout, describes the IRPE in more detail, and presents the overall operational workflow.