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Farmer Perceptions of Land Cover Classification of UAS Imagery of Coffee Agroecosystems in Puerto Rico

Authors :
Gwendolyn Klenke
Shannon Brines
Nayethzi Hernandez
Kevin Li
Riley Glancy
Jose Cabrera
Blake H. Neal
Kevin A. Adkins
Ronny Schroeder
Ivette Perfecto
Source :
Geographies, Vol 4, Iss 2, Pp 321-342 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Highly diverse agroecosystems are increasingly of interest as the realization of farms’ invaluable ecosystem services grows. Simultaneously, there has been an increased use of uncrewed aerial systems (UASs) in remote sensing, as drones offer a finer spatial resolution and faster revisit rate than traditional satellites. With the combined utility of UASs and the attention on agroecosystems, there is an opportunity to assess UAS practicality in highly biodiverse settings. In this study, we utilized UASs to collect fine-resolution 10-band multispectral imagery of coffee agroecosystems in Puerto Rico. We created land cover maps through a pixel-based supervised classification of each farm and assembled accuracy assessments for each classification. The average overall accuracy (53.9%), though relatively low, was expected for such a diverse landscape with fine-resolution data. To bolster our understanding of the classifications, we interviewed farmers to understand their thoughts on how these maps may be best used to support their land management. After sharing imagery and land cover classifications with farmers, we found that while the prints were often a point of pride or curiosity for farmers, integrating the maps into farm management was perceived as impractical. These findings highlight that while researchers and government agencies can increasingly apply remote sensing to estimate land cover classes and ecosystem services in diverse agroecosystems, further work is needed to make these products relevant to diversified smallholder farmers.

Details

Language :
English
ISSN :
26737086
Volume :
4
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Geographies
Publication Type :
Academic Journal
Accession number :
edsdoj.2768278c9cd64146b430066da0d61395
Document Type :
article
Full Text :
https://doi.org/10.3390/geographies4020019