#### Overview The need to monitor, understand and navigate our changing planet is stronger than ever. [[Earth Observation]] (EO) using satellites and remote sensing technologies gives us unique data through "eyes in the sky". Today, there are ca. 1k eyes in the sky, with 4x that by 2030 along with ca. 100k of other satellites from just 5k today. There is also a strong, growing demand for "Earth Intelligence", reflected by the ca. $9.2 billion invested with a 15% CAGR. ^[https://www.strategyand.pwc.com/uk/en/reports/expanding-frontiers-down-to-earth-guide-to-investing-in-space.pdf]. The increasing satellite capacity and demand for downstream intelligence, leads to an explosion of complexity, the handling of which is highly coupled to unlocking value. > Value Thesis: Quantum Technologies could help in the midstream spacecraft operations and management (resilient ground segment mission planning systems) as well as in the downstream application elements (enhanced earth intelligence) ---- #### Quantitative Indicators - **Space for Earth matters. **Space is the hidden utility powering our lives, valued at ca. $470 billion, growing at 11% leading to a $ 1 trillion market by 2030. Space for Earth makes a difference with Earth Observation companies offering services underpinning £106 bn of the UK economy. - **Earth Observation is growing.** The market specifically is set to grow at 15% with an est. value of ca. $6.4 billion by 2030. ^[https://www.globenewswire.com/en/news-release/2022/06/28/2470861/0/en/At-CAGR-15-2-Growing-Number-of-Earth-Observation-Projects-Remote-Sensing-Services-Market-Size-to-Reach-USD-64-375-Million-by-2030-Report-by-Acumen-Research-and-Consulting.html] - ** Decreasing Launch Costs & Increasing Capacity.** Since 1981, the cost of launch satellites has been driven down by 30x. In the past 60 years, we have launched 11k satellites, by 2030, we will have launched ca. 6x to 10x that. As launch capacity comes online, a new wave of launches is expected. With decreasing launch cost per kg, satellite buses are expected to grow in size - **Earth Observation is critical for Climate Mitigation.** Greater than 50% of the world's climate variables are only measurable from space ^[ https://www3.weforum.org/docs/WEF_Space_and_Net_Zero_2021.pdf ]. E.g. GHGSat uses EO satellites to detect industrial methane leaks and helped remove 2.3 megatons of methane in one year, equivalent to taking 500k cars off the road. ^[https://www.asc-csa.gc.ca/eng/blog/2022/10/07/satellites-serving-a-greener-planet.asp]. Weather satellites provide vital data for predicting and monitoring weather patterns, offering early warnings for natural disasters. It aids in agricultural planning, assessing crop health, managing water resources, and monitoring environmental shifts. - **Improving Operational Utility across the Satellite Lifecycle is paramount. ** Assuming an operator acquires a $100 million system designed for 10 years and would like to amortize the investment in 2 years, then revenues per day needed is $55k per day. If $30k per day revenue is only possible then that would be ammortized over ca. 9 years. ^[http://web.mit.edu/aeroastro/www/people/dnewman/pdfs/2_26%20copy.pdf] ![[Pasted image 20240112151727.png]] #### EO Directional Arrows of Progress In the Earth Observation (EO) sector, we're witnessing a paradigm shift, akin to moving from the cumbersome mainframe computers to sleek, powerful smartphones. This is the arrow of inevitability & impossibility: 1. **From Clunky Giants to Agile Swarms**: The field is transitioning from a reliance on a few bulky, expensive satellites to deploying swarms of small, cost-effective satellites. This change is like replacing a few old-school telescopes with a network of high-tech binoculars, each one offering a unique view of our planet. 2. **Quality and Quantity in Harmony**: There's a strategic pivot happening. We're not just focusing on getting crisper images; we're after a bigger picture. It's about enhancing coverage and reducing revisit times. Imagine a world where we get updates about Earth's changes almost as they happen - that's the goal. 3. **Democratization of Data**: The surge in data production is turning EO from a niche field for a select few into a universally accessible resource. It's like opening up an exclusive library to the public. With more players entering the scene, we're looking at more affordable, widespread access to Earth data. 4. **Smart Data, Smarter Business**: EO providers are evolving their business models. It's no longer just about selling raw data, like images of parking lots. The future is in selling insights, like traffic flow analytics. It’s like moving from selling paint to selling masterpieces. 5. **Technological Renaissance on the Horizon**: We're at the cusp of a tech explosion in EO. New sensors, space-borne video capabilities, and adaptable in-orbit technologies are on the horizon. It's not just about watching the Earth; it's about understanding and interacting with it in ways we haven't imagined yet. The direction is clear: more agility, wider access, deeper insights, and cutting-edge tech. Earth Observation isn't just changing; it's evolving, growing smarter, more interconnected, and significantly more impactful. #### The Opportunity - **Resilient Mission Planning Systems for Earth Observation ground segments** - Complexity is driven by the no. and nature of requests, conflicting priorities, concentration of satellites to requests, leading to a large & dynamically changing search space ca. 10^1700 that needs to navigated through efficiently. - Optimality matters most here though there is also a time sensitive nature to the problem since the mission plans are acquired by the satellites when they connect with the ground station only. - There is also a limited number of feasible good solutions possible, because one has to factor in the manoeuvres (guidance & relaying) possible that ensure good chain-ability (minimising perturbance and tranquillisation time) - Potential Beneficiaries are EO Data, Application and Service Providers with Proprietary Satellites to operate such as [Planet Labs](https://www.planet.com/?utm_campaign=evr&utm_source=google&utm_medium=paid-search&utm_content=pros-leads-brdresponsivesearch-0923&gclid=Cj0KCQiA67CrBhC1ARIsACKAa8SrYhp00ZkH4gbWvL89_1NGN64QVa79zgCyAbu1ZSSEDESvI1C4qlEaAmfYEALw_wcB), [ICEYE](https://www.iceye.com/), [Constellr](https://www.constellr.com/), [Capella Space](https://www.capellaspace.com/), [GHG Sat](https://www.ghgsat.com/en/), [Pixxel](https://www.pixxel.space/), [Array Labs](https://www.arraylabs.io/), [Satellogic](https://satellogic.com/), [BlackSky](https://www.blacksky.com/) and [Tomorrow](https://www.tomorrow.io/space/) - Potential Partners are: - Ground Station Networks such as [Leaf Space](https://leaf.space/), [Goonhilly Earth Station](https://www.goonhilly.org/), [Serco](https://www.serco.com/eu/sector-expertise/space), [Contec](http://contec.kr/) and [Atlas Operations](https://atlasspace.com/federated-network/?gad_source=1&gclid=Cj0KCQiA67CrBhC1ARIsACKAa8S1MFKvvnGbKXlB_LRTl6sO7P3TckF3yuv7n3gR6coxzWlIhVcBP2MaAigbEALw_wcB) - Mission Control and Logistics players such as [Epsilon3](https://www.epsilon3.io/), [Piestat](https://www.piesat.cn/website/en-us/src/home.html)and [Bright Ascension](https://brightascension.com/) - Relevant work: - Hybrid Quantum Algorithms applied to Satellite Mission Planning: [Talk](https://www.youtube.com/watch?v=V2CslzlCmoY&ab_channel=QCWare) and [Scientific Paper in IEEE special addition on Applied Earth Observation & Remote Sensing](https://ieeexplore.ieee.org/document/10155128?denied=) - [Maximizing EO Satellite Scheduling with quantum-based algorithms](https://www.researchgate.net/publication/366808397_White_Paper_Maximizing_Earth_Observation_Satellites_EOS_Utilization_with_Quantum-Based_Scheduling) - [Optimising EO Image Acquisition using Quantum Computing](https://arxiv.org/abs/2307.14419) - **Enhanced Earth Intelligence to reveal patterns, detect objects and extract geospatial insights at scale.** - Many of the challenges here stem from the need to do more with less from a pattern detection, classification and time-series prediction perspective. - Relevant work: - [Quantum Machine Learning for Remote Sensing](https://arxiv.org/pdf/2311.07626.pdf) - [Hybrid Quantum Neural Networks for Remote Sensing Image Classification](https://arxiv.org/pdf/2109.09484.pdf) - [ESA's Quantum Computing for Earth Observation](https://indico.cern.ch/event/1288979/contributions/5677697/attachments/2757215/4800831/QTML%20ESA%20at%20Industry%20Panel.pdf) - [Cloud Detection in Multi-spectral images](https://arxiv.org/pdf/2306.14515.pdf) ----- #### Sources [Group on Earth Observations - GEO](https://new.earthobservations.org/) | [Quantum Technologies in Space](chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://arxiv.org/pdf/2107.01387.pdf) | [[Earth Observation Ecosystem]] | [[Earth Observation Applications]] | [[Types of Earth Observation Imagery]] | [[Earth Observation Satellites]] | [[Quantum Use Cases MoC]] Tags: #value1pager Links: [[Value One Pagers]]