2026-10-06T19:01:36Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34039119 2026-10-01T05:29:20Z category_583 portal_316 item_type_1 month_year_10_2026

Image 2_Remote estimation of plastic distribution in California agriculture using Sentinel-2 imagery: a case study.jpeg Eva Scrivner (25152447) Dexter Hamilton (25152450) Daniel Sousa (3569228) Margot Mattson (23601547) Nicholas E. Williams (25152453) Seeta Sistla (141971) Photogrammetry and Remote Sensing apparent visible wavelength California agriculture plasticulture reflectance spectroscopy remote sensing sentinel-2 <p>Global application of agricultural plastic mulch is increasing. While these films offer benefits for crop production, they also are a large source of plastic waste and pollution in both terrestrial and aquatic systems. The current scale of global mulch application and its deleterious impacts are unclear. Current estimates of agricultural plastic use remain limited by field-specific growing patterns and data limitations. Satellite spectroscopy may offer a means to reduce this uncertainty and model agricultural plastic use on large spatial and temporal scales, though temporally variable crop canopy growth and spectrally diverse plastic targets complicate this approach. To build toward improved plasticulture estimates, this study presents an interpretable, spectral-based classification of bulk plastic use in a California agricultural site using Sentinel-2 imagery. In situ reflectance measurements of soil and white, green, and black plastic mulch endmembers were collected using a Spectra Vista Corporation HR-1024i Spectroradiometer from 350–2500 nm. A combination of field observations and high spatial resolution NearMap imagery (n = 416 spectra) were compiled and divided into 60% training and 40% testing data using a stratified sampling approach. Informed by field reflectance data, mixture analyses, and Sentinel-2 reflectance imagery, an empirical decision tree classification was parameterized to classify dark and bright plastic debris from soil and crop (accuracy = 0.982, kappa coefficient = 0.973, macro-averaged F1-score = 0.967). Modeled agricultural plastic distributions were then retrieved through a time series of Sentinel-2 imagery over Santa Maria, CA, from April 2023 to January 2025, elucidating patterns in plastic application and crop canopy growth without the need for prior knowledge of field growing and management patterns. These results are encouraging for the utility of optical remote sensing in modeling plastic use patterns and identifying contamination hotspots throughout California and, potentially, similarly mulched agroecological systems.</p> 2026-10-01T05:29:20Z Image Figure 10.3389/frsen.2026.1927646.s002 https://figshare.com/articles/figure/Image_2_Remote_estimation_of_plastic_distribution_in_California_agriculture_using_Sentinel-2_imagery_a_case_study_jpeg/34039119 CC BY 4.0