Earth Observation Technologies: Low-End-Market Disruptive Innovation

Abstract

After decades of traditional space businesses, the space paradigm is changing. New approaches to more efficient missions in terms of costs, design, and manufacturing processes are fostered. For instance, placing big constellations of micro-and nano-satellites in Low Earth Orbit and Very Low Earth Orbit (LEO and VLEO) enables the space community to obtain a huge amount of data in near real-time with an unprecedented temporal resolution. Beyond technology innovations, other drivers promote innovation in the space sector like the increasing demand for Earth Observation (EO) data by the commercial sector. Perez et al. stated that the EO industry is the second market in terms of operative satellites (661 units), micro-and nano-satellites being the higher share of them (61%). Technological and market drivers encourage the emergence of new start-ups in the space environment like Skybox, OneWeb, Telesat, Planet, and OpenCosmos, among others, with novel business models that change the accessibility, affordability, ownership, and commercialization of space products and services. This chapter shows some results of the H2020 DISCOVERER (DISruptive teChnOlogies for VERy low Earth oRbit platforms) Project and focuses on understanding how micro-and nano-satellites have been disrupting the EO market in front of traditional platforms. Satellites Missions and Technologies for Geosciences 2 Figure 1. Micro-and nano-satellites launched between 1997 and 2017, classified by sectors (own elaboration).

Guidance, navigation and attitude control of mini-satellites in a low earth orbit constellation for areal survey

“…Lifetime up to 10 years, fast spatial TMs with effective damping the SC structure oscillations as well as reasonable mass, size and energy characteristics have the motivated development of AOCSs equipped with gyro moment clusters (GMCs) based on gyrodines (GDs) -single-gimbal control moment gyroscopes. Many studies have been carried out on the orbital structures of information satellites [Ballard, 1980;Walker, 1984;Mozhaev, 1989;Lang, 2003;Chernov and Chernyavsky, 2004;Ulybyshev, 2016;Razoumny, 2016;Ulybyshev and Lysenko, 2019], including constellations of Earth-observing mini-satellites [Rodriguez-Donaire and et al, 2020;Lappas and Kostopoulos, 2020].…”

On Circuit-Based Hybrid Quantum Neural Networks for Remote Sensing Imagery Classification

“…, the probabilities of measuring |0 and |1 are 1 3 and 2 3 , respectively. Moreover, the measurement process does irreversibly modify the qubit, so that after the measurement the qubit can be |ψ = |0 with probability α 2 , and |ψ = |1 with probability β 2 .…”

“…E ARTH Observation (EO) has consistently leveraged technological and computational advances helping in develop novel techniques to characterize and model the human environment [1], [2], [3]. Given that many remote sensing missions are currently operative, carrying on board multispectral, hyperspectral, and radar sensors, and the improved capabilities in transmitting and saving a continuously increasing number of images, nowadays estimated in over 150 terabytes per day [4], the amount of data from EO applications has reached impressive volumes so that it is referred to as Big Data.…”

Strategic similarities between earth observation small satellite constellations in very low earth orbit and low-cost carriers by means of strategy canvas

“…The low-cost development approach in manufacturing and assembly techniques will not only reduce the cost of developing and operating a constellation but also open new market opportunities. This driver will make constellations in (V)LEO commercially successful since the private sector is interested in increasing modularity and standardisation to reduce the operational costs of their smallsats and accelerate the time-to-flight [51].…”