Objectives of the service
The proposed service aims to provide reliable and up-to-date flood insights at the property-level for companies and organizations in the wider real estate sector, such as real estate investment banks, property valuation companies, and ESG rating agencies. With the recent introduction of EU Taxonomy regulations, investors and companies are required to disclose the sustainability of their economic activities. Flood data plays a crucial role in assessing the environmental sustainability of a property (“E” part of ESG). However, currently available flood data is limited in geographical coverage, has low temporal resolution, and is not available on the property level. This makes it difficult for investors, banks, and private persons in the real estate domain to make informed decisions about investments and transactions.
To solve this problem, the service leverages the potential of Earth Observation data by using archived and current satellite images, such as Copernicus Sentinel, to produce dynamic flood hazard maps that are capable of keeping up with fast-paced climate change-induced variations of local flood patterns. This service fills the data gaps, reduces data inconsistencies, and saves effort, time, and money for the clients, by providing them with actionable flood information at the property-level through an intuitive web-interface and API.
Users and their needs
Targeted key market segments for the service are:
-
Banks
-
Property valuation companies
-
ESG rating agencies
Service/ system concept
The consortium provides a web-based service that gives up-to-date, comprehensive and reliable flood insights at the property-level.
The following information is provided
-
official flood hazard zone
-
observed flood event count (since 2015)
-
flood occurrence trend (e.g., the difference between the number of observed flood events in the recent year and the usual number of flood events per year expressed in %)
-
uncertainty estimate (values corresponding to the uncertainty estimates of the applied machine learning models).
Clients get access to property-level flood insights through a Web-Interface or API.
A block diagram of the service is provided below
"Data pre-processing" is the process of cleaning, formatting, and organizing the data to prepare it for analysis.
“Ancillary data” includes external data sources such as government and historic flood data, which is used with the main data to improve accuracy
"Data Processing" includes processing satellite images and time series data to identify patterns and trends. The results are then stored in a "Flood insights database".
"Service API/UI" allows users to access the Flood insights database. Users specify a location of interest, and the service provides flood information such as the flood zone and historical flood count for that location.
Space Added Value
The service integrates the Copernicus Sentinel-1 Synthetic Aperture Radar (SAR) imaging mission and the Sentinel-2 multi-spectral optical imagery as space assets to provide a snapshot of flood hazards at the property-level by analysing past and recent floods. Compared to the existing flood hazard data which are typically derived from groundwater and hydrological models, the service additionally incorporates observational data from Sentinel 1 and 2 satellite imagery to provide insights about dynamic flood pattern changes. Through the integration of existing flood hazard data and satellite image time series the PROFEO service is providing unprecedented flood insights at the individual property level.
Current Status
Held numerous customer interviews with potential users in the real estate domain to collect user requirements.
User requirements report finished.
Initial version of Product-Market-Fit Canvas finished.
Work currently in progress:
-
Assessment of existing (developed by ubicube and SentinelHub) flood mapping methods
-
Development of a data fusion method (SAR+optical)
-
Flood maps accuracy assessment
Prime Contractor(s)
Subcontractor(s)
