P35: Monitor slow-moving subsidence | |
Maturity score | |
Mean: 2.5 | STD: 0.66 |
Constraints and limitations · In areas with varied topography and dense vegetation cover, analysing subsidence can be challenging due to the influence of terrain on measurements. · Local factors like soil composition, water table fluctuations, and geologic conditions can influence subsidence rates, leading to complexities in interpretation. | |
Relevant user needs UN37: Projection of risk to portfolio assets into the future. | |
R&D gaps · Not cost-effective as needs very detailed height data and an understanding of subsidence risks | |
Potential improvements drivers · Develop automated algorithms and systems for the detection of slow-moving subsidence. These algorithms can process large datasets quickly and provide real-time or near-real-time alerts to users when subsidence is detected, enabling prompt responses. · Provide tools and services for long-term trend analysis, enabling users to assess subsidence patterns over extended periods. | |
Utilisation level review | |
Utilisation score | |
Mean: 2.00 | STD: 0.82 |
No utilisation · Unawareness of the existence of this EO product Low utilisation Medium utilisation · Higher cost of using the best available commercial EO product. High utilisation | |
Critical gaps related to relevant user needs | |
Guideline gap UN37: Projection of risk to portfolio assets into the future. | |
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