Grenoble2023-11-21T16:43:01+00:00

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CLIMABOROUGH Tender

Tender CHALLENGES / GRENOBLE-ALPES MÉTROPOLE

Grenoble-Alpes Métropole (GAM) is composed of 49 municipalities and 450.000 inhabitants. GAM is carrying out an ambitious development project called GRANDALPE 25 with the cities of Grenoble, Echirolles and Eybens. This project concerns an area with 30.000 inhabitants and 40.000 jobs and aims to make this district an active living space, an innovative economic hub, and a leader in new mobility models.

GRANDALPE 25 is also intended to be a demonstrator of ecological transition and will mobilise all available assets to build a future city that is no longer using fossil fuels.

Envisaged solution

within this meta-project, GAM would like to examine socio-technical systems enabling to model the impact of a construction project on Urban Heat Islands (UHI), Daytime Thermal Comfort (DTC) and CO2 capture data through fertilisation and vegetation. The ultimate goal is to raise the awareness of citizens on the current environmental situation, guide the urban planners acting within public authorities in taking decisions concerning new building, greening or redevelopment projects, and support the private sector in their current and future initiatives. In so doing, the whole community will be facilitated in its pathway towards mitigating the consequences of climate change.

Information on the location of the experimentation

The experimentation should take place in GrandAlpe: a 400-hectare territory in the heart of the metropolitan area, in the Grenoble, Echirolles and/or Eybens districts.

Figure 6: GrandAlpe location in the Grenoble Metropolitan area (more information: https://www.grenoblealpesmetropole.fr/337-grandalpe.htm)

Specific requirements

  • Solutions that promote datasets creation, including data acquisition by IoT sensors and the collection of real time environmental data
  • Solutions that allow relevant data visualisations, both for remote monitoring purposes and to improve decision making
  • Solutions that integrate created datasets and embed visualisation functions in a single tool;
  • Solutions that embed gamification and/or educational aspects, such as general or specific advice on how to improve the greening of a certain area / construction lot, understand data visualisations, etc.
  • Solutions that are promptly available as applications (for smartphones and tablet PCs, on Android and/or IOS operating systems).  

The proposed solutions should also be:

  • technically ergonomic, so that they are at least comprehensible by GAM staff.involving
    • different user profiles
    • easy to adapt to different types of user
  • owned by the GAM, in order to control content distribution and modify certain indicators
  • integrated with GAM services 
  • meeting GAM IT security constraints
  • working with standard projections e.g. Lambert 93 or CC45 or WGS84
  • supported by a rigorous methodology taking into account the complexity of Urban Heat Islands UHI.
  • lightweight and not require too many IT resources (on the users’ laptop as well as financially: avoid 5K euros per installation)
  • Data must be updatable (time step of 1 year if possible)
    • Prefer less exhaustive but regularly updated data (example: not the case with LIDAR data – which is an exhaustive dataset).
    • Possibility: the current state is a simplified version of an exhaustive dataset and it is then updated with less exhaustive data.

Minimum requirements

Data usage

The applicants are encouraged to make a proposition about datasets that could answer the need previously described. For example, LIDAR data sets could be used and enable a high level of details. If there are “better” data sets (easier to manage and providing a good level of information), the supplier should make a suggestion: https://geoservices.ign.fr/lidarhd#telechargement

 Data acquisition

The provider should at least use the following datasets made available by the City : Suppliers must determine the data they need to acquire themselves. The aim is to minimise purchased data as much as possible, and to rely on high-quality open source data and existing data from the Grenoble metropolitan area.

Data availability

The minimum requirement is to make a proposition about datasets that could answer the need previously described. The below data could be used if necessary:

  • Orthophoto: https://tiles.rtge.craig.fr
  • MOS (mode d’occupation du sol) : https://www.aurg.fr/article/303/2205-connaitre-l-occupation-des-sols-avec-le-mos-2020.htm
    Parcel data set: https://cadastre.data.gouv.fr/datasets/plan-cadastral-informatise

Data generation

The solution should at least generate the following datasets:

  • Impermeabilization of the soil studied
  • Vegetation of the soil studied (Trees; Shrub layer; Grass)
  • Daytime thermal comfort
  • Building related data (Vertical surfaces; nature of building materials roughness of buildings)
  • Coverage of the territory’s bodies of water and rivers

Optional

  • Soil fertility (the soil may not be vegetated, but it may be fertile)  
  • Tree species
  • Welcoming fauna on the ground studied: smooth functioning of the urban green and blue network  
  • Soil water retention

Datasets based on modelling:

  • level of de- / impermeabilization (in m2)
  • Canopy coverage achieved (in %)
  • Quantity of CO2 captured
  • impact of the de- / impermeabilization caused by the project on perceived temperature (UHI and DTC)
  • impact of vegetation created by the project on perceived temperature (UHI and DTC)
  • impact of the amount of water (bodies of water / river / etc) brought in by the project on the perceived temperature (UHI and DTC)

Optional

  • Quantity (in m2) of surface returned to living organisms (fertile land)
  • Impact of the amount of water captured by the soil

Impact on Wildlife   

Data Visualization

The proposed solution should be able to display results:

  • On maps
  • In figures (e.g. rate of vegetation on GrandAlpe; rate of soil sealing in a district)
    and to visualise the results at the resolution of one metre.

Socio—technical solution A

The active engagement of citizens should at least be ensured during the 12 months of experimentation. see point 4 above.

Socio—technical solution B

The way active engagement of citizens will contribute to a better performance of the solution should be described in detail.

Socio—technical solution C

A minimum number of 50 citizens should be engaged by the provider during the 12 months of experimentation.

Socio—technical solution D

The solution should at least demonstrate impacts on the following citizen behaviours: becoming aware of the issues surrounding UHI and DTC; a change of public demand in the neighbourhoods in favour of less impermeabilization and more vegetation

Socio—technical solution E

The provider should at least involve the following local stakeholders during the 12 months of experimentation”:

  • GAM services (Canopy, PLUi, Public space development project managers);
  • Development actors (General Contractors, Constructors, Architects);
  • Elected representatives;
  • Citizens

Interoperability

The solution should at least be interoperable with the following existing IT systems”:

  • Metropole’s IT systems (notably the Postgis / postgres SIT),
  • tools used by GAM planners (eg MOS, a tool created by AURG).

Additionally the solution must be capable of being overlaid on the Cadastre of Grenoble Alpes Metropole

Privacy 

Use of the solution should not imply the release of personal data unless for specific and motivated purposes.

Scalability

The aim is to use it for all Grenoble metropolitan areas.

Transferability

The partner should be able to provide us with the methodology used to implement the solution.

To participate to the tender, please read our tender documentation, this page is a simple overview about the Grenoble challenge. To visit the documentation, click on the green button below.

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CLIMABOROUGH is a project,
co-funded by the European Union and CINEA, with the ambition to bridge the gap between design and implementation of urban innovations, particularly in the face of climatic change and its consequential needs for adaptation and mitigation.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the granting authority can be held responsible for them.

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