Massively-Parallel Change Detection for Satellite Time Series Data with Missing Values

Fabian Gieseke, Sabina Rosca, Troels Henriksen, Jan Verbesselt, Cosmin E. Oancea

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

1 Citation (Scopus)

Abstract

Large amounts of satellite data are now becoming available, which, in combination with appropriate change detection methods, offer the opportunity to derive accurate information on timing and location of disturbances such as deforestation events across the earth surface. Typical scenarios require the analysis of billions of image patches/pixels. While various change detection techniques have been proposed in the literature, the associated implementations usually do not scale well, which renders the corresponding analyses computationally very expensive or even impossible. In this work, we propose a novel massively-parallel implementation for a state-of-the-art change detection method and demonstrate its potential in the context of monitoring deforestation. The novel implementation can handle large scenarios in a few hours or days using cheap commodity hardware, compared to weeks or even years using the existing publicly available code, and enables researchers, for the first time, to conduct global-scale analyses covering large parts of our Earth using little computational resources. From a technical perspective, we provide a high-level parallel algorithm specification along with several performance-critical optimizations dedicated to efficiently map the specified parallelism to modern parallel devices. While a particular change detection method is addressed in this work, the algorithmic building blocks provided are also of immediate relevance to a wide variety of related approaches in remote sensing and other fields.
Original languageEnglish
Title of host publication2020 IEEE 36th International Conference on Data Engineering (ICDE)
PublisherIEEE
Pages385-396
ISBN (Electronic)9781728129037
ISBN (Print)9781728129044
DOIs
Publication statusPublished - 27 May 2020
Event2020 IEEE 36th International Conference on Data Engineering (ICDE) - Dallas, TX, USA
Duration: 20 Apr 202024 Apr 2020

Conference

Conference2020 IEEE 36th International Conference on Data Engineering (ICDE)
Period20/04/2024/04/20

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