Classifying Soil Type Using Radar Satellite Images
The growth of the crop is dependent on soil type, apart from atmospheric and geo-location characteristics. As of now, there is no direct and costfree method to measure soil property or to classify soil type. In this work, we proposed a machine learning model to classify soil type using Sentinel-1 sa...
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| Outros Autores: | , , , , , |
| Formato: | article |
| Idioma: | por |
| Publicado em: |
2022
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10174/31998 |
| País: | Portugal |
| Oai: | oai:dspace.uevora.pt:10174/31998 |
| Resumo: | The growth of the crop is dependent on soil type, apart from atmospheric and geo-location characteristics. As of now, there is no direct and costfree method to measure soil property or to classify soil type. In this work, we proposed a machine learning model to classify soil type using Sentinel-1 satellite radar images. Further, the developed classifier achieved 72.17% F1-score classifying sandy, free and clayish on a set of 65003 data points collected over one year (from Oct 2018 to Sep 2019) over 14 corn parcels near Ourique, Portugal. |
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