01989nam a2200217 a 4500 00025016 20425s2011 xxu eng d 3845406186 (paperback) 9783845406183 (paperback) 50 22 Tesfamariam, Ermias Beyene. Distributed processing of large remote sensing images using mapreduce : a case of edge detection methods / Ermias Beyene Tesfamariam. [S.l.] : LAP LAMBERT Academic Publishing, 2011. 84 p. ; 22 cm. Advances in remote sensing technology and their ever increasing repositories of the collected data are revolutionizing the mechanisms these data are collected, stored and processed. This exponential growth of data archives and the increasing users’ demand for real-and near-real time remote sensing data products has challenged the data providers to deliver the required services. The remote sensing community has recognized the challenge in processing large and complex satellite datasets to derive customized products and several efforts have been made in the past few years towards incorporation of high-performance computing models. This study analyzes the recent advancements in distributed computing technologies, the MapReduce programming model, extends it for use in the area of remote sensing image processing. Performance tests for processing of large archives of Landsat images were performed with the Hadoop framework. The findings demonstrate that MapReduce has a potential for scaling large-scale remotely sensed images processing and perform more complex geospatial problems. 00025016 Earth sciences Remote sensing. Remote-sensing images. Ayesha Abed Library General shelf. 12095 12095 0 0 ddc 0 550_TES 0 20072 BRACUL BRACUL GEN 2012-04-25 karim International 5500.00 2 6 550 TES 3010025016 2022-09-03 2022-08-30 1 2012-04-25 BK