The openEO API–Harmonising the Use of Earth Observation Cloud Services Using Virtual Data Cube Functionalities

Matthias Schramm,Luca Foresta,Wolfgang Wagner,Johannes Reiche,Stefaan Lippens,Pieter Kempeneers,Tomasz Miksa,Edzer Pebesma,Miha Kadunc,Milutin Milenković,Bernhard Gößwein,Jan Verbesselt,Claudio Navacchi,Alexander Jacob,Jeroen Dries,Markus Neteler,Matthias Mohr

doi:10.3390/rs13061125

Abstract

At present, accessing and processing Earth Observation (EO) data on different cloud platforms requires users to exercise distinct communication strategies as each backend platform is designed differently. The openEO API (Application Programming Interface) standardises EO-related contracts between local clients (R, Python, and JavaScript) and cloud service providers regarding data access and processing, simplifying their direct comparability. Independent of the providers’ data storage system, the API mimics the functionalities of a virtual EO raster data cube. This article introduces the communication strategy and aspects of the data cube model applied by the openEO API. Two test cases show the potential and current limitations of processing similar workflows on different cloud platforms and a comparison of the result of a locally running workflow and its openEO-dependent cloud equivalent. The outcomes demonstrate the flexibility of the openEO API in enabling complex scientific analysis of EO data collections on cloud platforms in a homogenised way.

Highlights

IntroductionWith the free-of-charge release of high temporal resolution Moderate Resolution
The openEO API aims to standardise the interface between frontend users and backend platforms to process big Earth Observation (EO) data
The use case of a disturbance mapping in the Brazilian Amazon forest shown here was conducted on a local computer and on a cloud platform, where the latter bases on predefined processes of the openEO standard

Summary

Introduction

With the free-of-charge release of high temporal resolution Moderate Resolution. Imaging Spectroradiometer (MODIS) imagery by the U.S Geological Survey (USGS) in. 2008/2009 [1,2] further boosted the use of remote sensing data, allowing for large-scale land-use studies at low costs [3]. The European Commission adopted an open data policy for its Copernicus program with its Sentinel satellites [4] and high-capacity ground segment. This took the distribution of microwave and optical EO data with high

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Results

Discussion

Conclusion