Hack4Nature Tree Challenge

1. ITRS
Individual Tree Remote Sensing

2. Problématique
How can cities' tree heritage be inventoried
automatically?

3. Challenges
Acquire more reliable, accurate, regular
information to improve city nature while
reducing the cost of input.
Making it easier to acquire qualitative data
-> Better management of tree heritage
-> Better decision-making

4. Currently
Manual census
 most municipalities still use paper or manual
 Very limited inventory status of municipalities that does not allow
effective management plans to be put in place
 High financial and human cost thus discouraging for the majority
of municipalities

5. State of the
art
LiDAR Detection
 Great performance
 Expensive
 Not very accessible
 https://hal-
lirmm.ccsd.cnrs.fr/lirmm-
01685327/document

6. State of the art
Satellite image recognition
 Well known in scientific
literature
 Individual difficult tree
distinction
 Only possible to obtain contact
information
Kaggle DSTL Competition
https://github.com/robmarkcole/sa
tellite-image-deep-learning
DeepForest
https://github.com/weecology/Dee
pForest

7. State of the art
Infrared and thermal
detection
 Other information (silhouette,
health status) is available

8. Our solution
 Technology assembly (Google-type
360 high-resolution camera - infrared
- GPS)
 Algo tree detection and its features
(deep learning)
 Tracking and Response Dashboard

9. Benefits
Accessible and existing
technologies
Fast implementation
Simplicity of execution for
municipalities
Proven complementarity with
ecoteka