1. Agricultural plastic waste spatial estimation by Landsat 8 satellite images
- Author
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Rosa Viviana Loisi, Fortunato De Santis, Gabriele Nolè, Giuliano Vox, Antonio Lanorte, Evelia Schettini, Ileana Blanco, Lanorte, A., De Santis, F., Nole, G., Blanco, I., Loisi, R. V., Schettini, E., and Vox, G.
- Subjects
010504 meteorology & atmospheric sciences ,Plastic materials ,Land use map ,Horticulture ,01 natural sciences ,Pixel-based approach ,Waste production ,Waste mapping ,0105 earth and related environmental sciences ,Remote sensing ,Support Vector Machines classification ,Contextual image classification ,business.industry ,Forestry ,Plastic covering detection ,04 agricultural and veterinary sciences ,Computer Science Applications ,Support vector machine ,Spatial estimation ,Agriculture ,040103 agronomy & agriculture ,0401 agriculture, forestry, and fisheries ,Environmental science ,Plastic waste ,Satellite ,business ,Agronomy and Crop Science - Abstract
The use of plastic materials in agriculture involves several benefits but it results in huge quantities of agricultural plastic waste to be disposed of. Input and output data on the use of plastics in agriculture are often difficult to obtain and poor waste management schemes have been developed. The present research aims to estimate and map agricultural plastic waste by using satellite images. Waste was evaluated by means of the indexes relating waste production to crop type and plastic application as defined by the land use map realized by classifying the Landsat 8 image. The image classification was carried out using Support Vector Machines (SVMs), and the accuracy assessment showed that the overall accuracy was 94.54% and the kappa coefficient equal to 0.934. Data on the plastic waste obtained by the satellite land use map were compared with the data obtained by using the institutional land use map; a difference of 1.74% was identified on the overall quantity of waste.
- Published
- 2017
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