Mining Satellite Imagery for Offshore Wind Energy

This work mines big data in Sentinel-1 satellite images to unveil geographical patterns in offshore wind energy. We leverage unsupervised machine learning to extract insights from a 44GB open access dataset for decision support in wind farm orientations to guide stakeholders. It has broader impacts of overcoming climate change by enhancing renewable energy.

Authors

Cristian Monsalve
Aparna S. Varde (ORCID: https://orcid.org/0000-0002-3170-2510)

Institutions

Montclair State University (US)

Publication Details

Published: 2024-12-15
DOI: https://doi.org/10.1109/bigdata62323.2024.10825812
Citations: 2
Primary Topic: Remote Sensing and LiDAR Applications
Type: article
Field-Weighted Citation Impact: 0.41

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article

Mining Satellite Imagery for Offshore Wind Energy

Cristian Monsalve, Aparna S. Varde

Dec 15, 2024

2 citations

Remote Sensing and LiDAR Applications

0.41

article

Mining Satellite Imagery for Offshore Wind Energy

Cristian Monsalve, Aparna S. Varde

December 15, 2024article en

2 citations

Abstract

Montclair State University (US)

Affordable and clean energy

Openalex Percentile: Top 39%

Remote Sensing and LiDAR Applications

0.41

DOI Source OpenAlex

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Mining Satellite Imagery for Offshore Wind Energy — Cristian Monsalve, Aparna S. Varde · (2024) | TGRS Research Map | TGRS