Machine Learning and Citizen Science Approaches for Monitoring the Changing Environment

Sulong Zhou

REVIEW

Machine Learning and Citizen Science Approaches for Monitoring the Changing Environment

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2312.07698 v1 pith:66VQ7BYT submitted 2023-12-12 cs.LG

Machine Learning and Citizen Science Approaches for Monitoring the Changing Environment

Sulong Zhou This is my paper

classification cs.LG

keywords answerapproacheschangingcitizenlearningmachinequestionsscience

verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

0 comments

read the original abstract

This dissertation will combine new tools and methodologies to answer pressing questions regarding inundation area and hurricane events in complex, heterogeneous changing environments. In addition to remote sensing approaches, citizen science and machine learning are both emerging fields that harness advancing technology to answer environmental management and disaster response questions.

Machine Learning and Citizen Science Approaches for Monitoring the Changing Environment

discussion (0)