Does drone-facilitated revegetation work? A case study from Taiwan

Unmanned aerial vehicle (UAV) or drone technology has gained significant traction in ecological restoration projects, particularly in revegetation efforts aimed at stabilizing degraded landscapes. Despite this growing interest, empirical data on the effectiveness of drone-based reseeding remain scarce. This study addresses this gap by investigating a core question—“Does drone-facilitated revegetation work?”—using a case study of three landslide-affected sites in Taiwan that underwent UAV seeding, alongside a fourth, untreated control site. We employed a dual remote-sensing approach using Google Earth Engine (GEE), leveraging both the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) to quantify vegetation health before and after drone interventions. Results indicate that two of the three treatment sites showed notable improvements in NDVI and EVI, suggesting successful vegetation establishment, whereas the third site exhibited a less favorable response, highlighting the importance of site-specific conditions. The control site underwent only minimal natural recovery by comparison. These findings underscore the potential advantages of UAV-assisted seeding in challenging terrains and offer insights into how future drone-based revegetation projects might be refined for greater efficacy.

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Publication Details

Journal
Academia Environmental Sciences and Sustainability
Published
2025-04-07
DOI
https://doi.org/10.20935/acadenvsci7624
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.80
Controls
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article

Does drone-facilitated revegetation work? A case study from Taiwan

Samantha Farquhar, Maria Gomez Saldarriaga, Lee M
1 citations
Academia Environmental Sciences and Sustainability
Remote Sensing and LiDAR Applications
0.80
article

Does drone-facilitated revegetation work? A case study from Taiwan

Samantha Farquhar, Maria Gomez Saldarriaga, Lee M
article en
1 citations

Abstract

Unmanned aerial vehicle (UAV) or drone technology has gained significant traction in ecological restoration projects, particularly in revegetation efforts aimed at stabilizing degraded landscapes. Despite this growing interest, empirical data on the effectiveness of drone-based reseeding remain scarce. This study addresses this gap by investigating a core question—“Does drone-facilitated revegetation work?”—using a case study of three landslide-affected sites in Taiwan that underwent UAV seeding, alongside a fourth, untreated control site. We employed a dual remote-sensing approach using Google Earth Engine (GEE), leveraging both the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) to quantify vegetation health before and after drone interventions. Results indicate that two of the three treatment sites showed notable improvements in NDVI and EVI, suggesting successful vegetation establishment, whereas the third site exhibited a less favorable response, highlighting the importance of site-specific conditions. The control site underwent only minimal natural recovery by comparison. These findings underscore the potential advantages of UAV-assisted seeding in challenging terrains and offer insights into how future drone-based revegetation projects might be refined for greater efficacy.

Academia Environmental Sciences and SustainabilityVol. 2(2)
Yale University (US)
Openalex Percentile: Top 31%
Remote Sensing and LiDAR Applications
0.80
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