Building Inventory - gap analysis

P09: Building inventory

Download the product sheet gap analysis 

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.