ISPRS-Annals ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences ISPRS-Annals ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2194-9050 Copernicus Publications Göttingen, Germany 10.5194/isprsannals-I-4-199-2012 DATA ACQUISITION STRATEGIES FOR ASTER GLOBAL DEM GENERATION Urai M. 1 3 Tachikawa T. 2 Fujisada H. 3 Geological Survey of Japan, AIST, 1-1-1 Higashi, Tsukuba, Ibaraki, 305-8567 Japan Japan Space Systems, The Kikai Shinko Kaikan Bldg. 6F, 3-5-8 Shibakoen, Minato-ku, Tokyo 105-0011 Japan Sensor Information Laboratory Corp., 3-14-17 Azuma, Tsukuba, Ibaraki, 305-0031 Japan 20 07 2012 I-4 199 202 Copyright: © 2012 M. Urai et al. 2012 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://isprs-annals.copernicus.org/articles/I-4/199/2012/isprs-annals-I-4-199-2012.html The full text article is available as a PDF file from https://isprs-annals.copernicus.org/articles/I-4/199/2012/isprs-annals-I-4-199-2012.pdf

The ASTER Global DEM (GDEM) version 1, is a global digital elevation model with one arc-second grid, generated using the ASTER stereo image archive 2000 to August 2008, and was released on June 29, 2009. The GDEM-1 had some bad elevation data. The most simple and effective way to reduce bad elevation data in the GDEM-1 is to add new ASTER observation data and re-generate the GDEM. An ASTER Data Acquisition Request was defined, based on the number of good pixels and the number of observations at each observation area, for the GDEM version 2 that was released on October 17, 2011. Using more input data and an improved algorithm, GDEM version 2 reduced the amount of the bad pixel by 4.5% to 7.5% and increased the amount of good tiles by 10.7% to 54.3% over the GDEM-1, except for Antarctica. Another ASTER data set is being collected for GDEM version 3, scheduled for 2013. The ASTER data collection scheme, however, has some constraints. This study sought for techniques to optimize the GDEM data collection balancing the overall ASTER operations and reduction of bad pixels in the GDEM data.