Near Real-Time Browsable Landsat-8 Imagery
AbstractThe successful launch and operation of Landsat-8 extends the remarkable 40-year acquisition of space-based land remote-sensing data. To respond quickly to emergency needs, real-time data are directly downlinked to 17 ground stations across the world on a routine basis. With a size of approximately 1 Gb per scene, however, the standard level-1 product provided by these stations is not able to serve the general public. Users would like to browse the most up-to-date and historical images of their regions of interest (ROI) at full-resolution from all kinds of devices without the need for tedious data downloading, decompressing, and processing. This paper reports on the Landsat-8 automatic image processing system (L-8 AIPS) that incorporates the function of mask developed by United States Geological Survey (USGS), the pan-sharpening technique of spectral summation intensity modulation, the adaptive contrast enhancement technique, as well as the Openlayers and Google Maps/Earth compatible superoverlay technique. Operation of L-8 AIPS enables the most up-to-date Landsat-8 images of Taiwan to be browsed with a clear contrast enhancement regardless of the cloud condition, and in only one hour’s time after receiving the raw data from the USGS Level 1 Product Generation System (LPGS). For any ROI in Taiwan, all historical Landsat-8 images can also be quickly viewed in time series at full resolution (15 m). The debris flow triggered by Typhoon Soudelor (8 August 2015), as well as the barrier lake formed and the large-scale destruction of vegetation after Typhoon Nepartak (7 July 2016), are given as three examples of successful applications to demonstrate that the gap between the user’s needs and the existing Level-1 product from LPGS can be bridged by providing browsable images in near real-time. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Liu, C.-C.; Nakamura, R.; Ko, M.-H.; Matsuo, T.; Kato, S.; Yin, H.-Y.; Huang, C.-S. Near Real-Time Browsable Landsat-8 Imagery. Remote Sens. 2017, 9, 79.
Liu C-C, Nakamura R, Ko M-H, Matsuo T, Kato S, Yin H-Y, Huang C-S. Near Real-Time Browsable Landsat-8 Imagery. Remote Sensing. 2017; 9(1):79.Chicago/Turabian Style
Liu, Cheng-Chien; Nakamura, Ryosuke; Ko, Ming-Hsun; Matsuo, Tomoya; Kato, Soushi; Yin, Hsiao-Yuan; Huang, Chung-Shiou. 2017. "Near Real-Time Browsable Landsat-8 Imagery." Remote Sens. 9, no. 1: 79.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.