Global trends in the development of low-orbit space systems for optoelectronic Earth observation
Bibliographic record
Abstract
The aim of this work is to identify the global trends in the use of low-orbit spacecraft constellations, which have a number of substantial advantages in Earth remote sensing (ERS). Much attention is given to the construction of large constellations of single- and different-type spacecraft by foreign companies and operators, such as Digital Globe, Planet Labs, Black Sky, Satellogic S.A. etc., and to the plans of deployment of constellations of this type in the USA, China, Japan, Canada, Europe, and other countries. The characteristics of the various, mainly commercial, low-orbit constellations of optoelectronic Earth observation spacecraft put into orbit over the past five years are considered. It is shown that low-orbit spacecraft constellations can be used to good advantage in the solution of numerous socio-economic problems, such as geodesy and cartography, urban development, transport infrastructure, crop estimate, environmental monitoring, health monitoring, etc., and new problems aimed at prompt continuous monitoring of various objects. The paper presents a comparative analysis of the technical implementations and ways of achievement of the main target spacecraft characteristics, such as information performance, capture range, revisit time, geodetic connection accuracy, imaging immediacy, and the possibility of stereo and video imaging by satellite constellations. It is shown that the construction of large low-orbit constellations is a new trend in the world astronautics, which requires systematic methods for their design and control. The results obtained allows one to make recommendations on the design of low-orbit constellations of home ERS spacecraft, in particular on the development of orbit determination models and algorithms and spacecraft dynamics models.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".