Survivors 2070 Part Four: Signs of Change Below

A New Discovery

Three years into the mission, AI sensors detected a temperature rise over the equator. It was small, less than one degree. But it was the first shift in a frozen world.

Alina ran simulation models.

“If this trend continues, surface thaw begins in twelve years.”

Marcus looked at the hologram. “We cannot survive up here indefinitely.”

Rajan said, “Then Earth is our only future.”

The news spread. People cheered. Some cried. Others became anxious.

New Concerns

The outer panels began to degrade. Micrometeoroid strikes increased. Replicators could not replace certain alloy composites. Engineers predicted structural failure in fifteen years.

Elias brought the issue to the council.

“We need a long-term plan. If Earth recovers, we must be ready. If not, we need alternative habitats.”

Rajan replied, “We return home. That is the only path.”

Later, in private, Marcus admitted to Alina,

“We may not have a choice. Halo Arc is aging faster than expected.”

Preparing for Descent

Teams began mapping possible landing zones. Temperatures were lowest in the northern hemisphere. Some equatorial regions looked survivable. Radiation levels remained high in certain areas but were manageable.

Lila told her students,

“One day you will walk on Earth. Our goal is to keep you ready for that moment.”

A boy asked, “Will it still look like the pictures?”

Lila paused. “Different. But still ours.”

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

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.

MDPI