Impact of Solar Farm Expansion on Forest Cover in Massachusetts
An Analysis Using Artificial Intelligence and Remote Sensing
Bibliographic Data
| ID | 21373513 |
|---|---|
| Authors | Natasha Farina (Salem State University), Stephen Young (0000-0002-3472-3093, Salem State University, corresponding author), Stephen S Young (Salem State University), Fatema Nafa (0000-0001-9798-1279, Salem State University), George Waddington (Salem State University) |
| Year | 2025 |
| Volume | 77 |
| Issue | 3 |
| Pages | 257-268 |
| Publication date | 2025-05-04 |
| Open Access | No |
| Type | ARTICLE |
| Venue | The Professional Geographer (JOURNAL) |
| Journal identifiers | ISSN: 0033-0124 • E-ISSN: 1467-9272 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/00330124.2025.2499477 |
| OpenAlex | W4410398273 |
| Language | EN |
| Citations received | 1 |
| References cited | 38 |
To decarbonize the electric grid, the U.S. state of Massachusetts has been investing in solar farms. This research aims to understand how the development of solar farms in Massachusetts has influenced deforestation between 2000 and 2021. Worcester County, in central Massachusetts, was used as a case study because it encompasses both urban areas and forests and has a land cover typical of the state. The research used Global Forest Watch Landsat imagery to analyze overall deforestation at the state level, and then high-resolution imagery (15 cm) and machine learning to identify all solar farms in Worcester County followed by the use of Goggle Earth imagery to determine the land-cover types prior to the construction of solar farms. Machine learning on high-resolution aerial imagery was able to identify all solar farms in Worcester County. The study found that a majority (51 percent) of solar farms had the entire forest cover cleared to make way for solar panels and 11 percent of the solar farms were in regions that had some tree cover prior to construction. State-level policies drive the construction of solar farms, and these results indicate that unintended deforestation can occur when trying to decarbonize the grid
Biology · Cover (algebra) · Forest cover · Geography · Remote sensing · Agriculture Sustainability and Environmental Impact · Ecology · Engineering · Environmental Science · Forestry · Photovoltaic Systems and Sustainability · Solar Radiation and Photovoltaics
Getting the message right on nature‐based solutions to climate change
Machine learning and deep learning
U-Net
World Scientists’ Warning of a Climate Emergency
Forests and Climate Change
The role of renewable energy in the global energy transformation
Role of renewable energy sources in environmental protection
High-Resolution Global Maps of 21st-Century Forest Cover Change
Climate change and forced migrations
How the environment became global
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |