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

Maria Gomez Saldarriaga,

Lee M, Samantha Farquhar

et al.

Published: April 7, 2025

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

Language: Английский

Vegetation coverage patterns in the “mountain–basin” system of arid regions: Driving force contribution, non-stationarity, and threshold effects DOI Creative Commons
Rou Ma, Zhengyong Zhang,

Lin Liu

et al.

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103084 - 103084

Published: Feb. 1, 2025

Language: Английский

Citations

0
Does drone-facilitated revegetation work? A case study from Taiwan DOI Creative Commons

Maria Gomez Saldarriaga,

Lee M, Samantha Farquhar

et al.

Published: April 7, 2025

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

Language: Английский

Citations

0