P09: Building inventory | |
Maturity score | |
Mean: 2.6 | STD: 0.64 |
Constraints and limitations · Cloud presence · Urban areas across the world can have different building styles, densities, and layouts, which can make creating universally applicable methods challenging. · Tall buildings or structures can cast shadows making it challenging to accurately identify their characteristics, and occlusion might hinder the detection of buildings behind vegetation or other structures. | |
Relevant user needs UN47: Need up-to-date geospatial data on residential and industrial infrastructures locations | |
R&D gaps · Cost of VHR satellite imagery which is essential for the product. · Generality of the models used in one region to another. · Using satellite imagery for building inventory might raise legal and privacy concerns, especially when dealing with sensitive areas or personal property. | |
Potential improvements drivers · Provide more training data for different regions of the world with different building characteristics. · Price models for commercial EO data. | |
Utilisation level review | |
Utilisation score | |
Mean: 2.14 | STD: 0.64 |
No utilisation: · Unavailability of freely available sources of the EO product. · Not aware of any product from which this could be extracted directly. Low utilisation · Higher cost of using the commercial EO product. · The current method (manually counting for a sample area and multiplying up to estimate the whole area) is considered good enough in terms of accuracy, reliability, and price. · Ground truth data is not sufficient for counting individual trees. Medium utilisation The product already satisfies the technical and usability requirements. High utilisation | |
Critical gaps related to relevant user needs | |
Utilisation gap UN47: Need up-to-date geospatial data on residential and industrial infrastructures locations. |
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