bug-bounty527
xss286
rce147
bragging-post119
google118
account-takeover107
exploit100
open-source95
privilege-escalation92
facebook89
authentication-bypass88
microsoft87
csrf85
stored-xss75
malware71
access-control69
web-security68
cve66
ai-agents64
reflected-xss63
writeup63
ssrf55
input-validation55
phishing50
smart-contract49
defi48
cross-site-scripting48
api-security47
sql-injection47
apple47
information-disclosure47
tool46
ethereum45
privacy44
cloudflare40
browser38
vulnerability-disclosure38
reverse-engineering38
llm37
burp-suite37
web-application37
automation36
opinion36
web335
oauth35
html-injection34
dos34
remote-code-execution34
lfi34
responsible-disclosure33
0
2/10
Meta AI and the World Resources Institute released Canopy Height Maps v2 (CHMv2), an improved open-source forest mapping model using DINOv3 for satellite-based tree canopy height estimation with R² improved from 0.53 to 0.86. The advancement enables governments and researchers to monitor forest health, restoration efforts, and carbon storage at global scale with enhanced accuracy and consistency.
computer-vision
machine-learning
forest-monitoring
satellite-imagery
environmental-research
self-supervised-learning
lidar
climate-action
open-source-model
earth-observation
Meta AI
World Resources Institute
Canopy Height Maps v2
CHMv2
DINOv3
DINOv2
SAT-493M
John Brandt
Forest Research
Forestry Commission
European Commission
Joint Research Centre
Cities for Smart Surfaces
Smart Surfaces Coalition
WRI Ross Center for Sustainable Cities