Seigne Pauline, Guignard Yann AGORAH, agence d'urbanisme

Seigne Pauline, Guignard Yann AGORAH, agence d'urbanisme

by Seigne Pauline, Guignard Yann

Applied Sciences & Engineering Urban Planning & Mobility RPRegional and area planningRPCUrban and municipal planning and policy
🎙 Seigne Pauline, Guignard Yann 👥 12K 📅 October 3, 2025 ⏱ 18 min 👁 82 📄 expert opinion 🧭 2026-08-16
Available in: English (current) Français

Keywords

LIDAR HDCOSIAbiomassvegetation volumeurban planning

Summary

This presentation by Pauline Seigne and Yann Guignard from AGORAH, an urban planning agency in La Réunion, demonstrates the use of two new geospatial datasets: COSIA (land cover from AI) and LIDAR HD (high-density LiDAR). They aim to detect and estimate vegetation volume to support public policies and planning. The first example estimates biomass in private gardens using COSIA to identify vegetated areas and LIDAR-derived height models to calculate volume, visualized in 3D. The second example applies similar methods to ravines to guide waste collection after cyclones. The speakers highlight the data’s high resolution and open access but note the large file sizes and the need for manual downloading. They also discuss limitations, such as the data being a snapshot in time and potential inaccuracies in dense forests. The presentation concludes with a call for collaboration and emphasizes the value of these datasets for various applications.

146 words

Critical Evaluation

Value of the Information & Strength of the Argument

The presentation provides valuable insights into the practical application of COSIA and LIDAR HD data for biomass estimation, a topic of growing importance for environmental management. The methodology is clearly explained, with step-by-step examples that illustrate the process from data selection to 3D visualization. The argumentation is solid, based on real-world case studies and acknowledging limitations, which enhances credibility. However, the presentation is more of a demonstration than a rigorous scientific analysis, lacking quantitative validation or comparison with ground truth data.

Scientific Rigor, Source Quality, Title Accuracy

The presentation is scientifically rigorous in its use of official datasets (IGN’s COSIA and LIDAR HD) and follows a logical methodology. However, it does not cite external sources or references, relying solely on the presenters’ expertise. The title is somewhat vague but the description clarifies the content. The adequacy between title and content is good, as the presentation indeed focuses on the use of these datasets for vegetation volume estimation.

166 words

Title / Content Match

The title is a bit generic but accurately reflects the authors and their affiliation, while the description clarifies the content.

Quality & Reliability

7/10

The presentation is based on practical experience with geospatial data (COSIA, LIDAR HD) and demonstrates a clear methodology. However, it lacks formal citations and peer-reviewed validation, and the speakers acknowledge limitations in accuracy for dense forests.

Key Moments

Markers derived by PSI from the transcript: the creator did not define chapters.

Cited Sources

Concurring Sources

  • IGN - LIDAR HD — The dataset is officially provided by IGN and is used in the presentation.
  • IGN - COSIA — The dataset is officially provided by IGN and is used in the presentation.

Contribution & Novelties

The presentation showcases an innovative application of open geospatial data (COSIA and LIDAR HD) for estimating vegetation volume, which is useful for urban planning and disaster management. It provides a replicable methodology that can be adapted to other territories. The 3D visualization of biomass in private gardens and ravines offers a novel perspective for stakeholders.

Pour aller plus loin :

  • LIDAR HD - IGN — Official page for LIDAR HD data, providing technical details and access.
  • COSIA - IGN — Official page for COSIA land cover data.
  • Remote sensing of vegetation — Overview of remote sensing techniques for vegetation analysis.
  • Biomass estimation methods — General methods for biomass estimation.

109 words

Radar Profile

The radar profile shows balanced scores across all dimensions, with slightly higher scores in information quantity and quality, indicating a well-rounded presentation. The lower technical level score suggests it is accessible to a general audience, while still providing substantial content.

Reliability 7/10

💬 Sur les 0 commentaires analysés, aucune tendance n'est disponible.