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Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas

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Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas

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dc.contributor.author Morell-Monzó, Sergio es_ES
dc.contributor.author Estornell Cremades, Javier es_ES
dc.contributor.author Sebastiá-Frasquet, M.-T. es_ES
dc.date.accessioned 2021-05-27T03:35:56Z
dc.date.available 2021-05-27T03:35:56Z
dc.date.issued 2020-06 es_ES
dc.identifier.issn 2072-4292 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166852
dc.description.abstract [EN] Agricultural land abandonment is an important environmental issue in Europe. The proper management of agricultural areas has important implications for ecosystem services (food production, biodiversity, climate regulation and the landscape). In the coming years, an increase of abandoned areas is expected due to socio-economic changes. The identification and quantification of abandoned agricultural plots is key for monitoring this process and for applying management measures. The Valencian Region (Spain) is an important fruit and vegetable producing area in Europe, and it has the most important citrus industry. However, this agricultural sector is highly threatened by diverse factors, which have accelerated land abandonment. Landsat and MODIS satellite images have been used to map land abandonment. However, these images do not give good results in areas with high spatial fragmentation and small-sized agricultural plots. Sentinel-2 and airborne imagery shows unexplored potential to overcome this thanks to higher spatial resolutions. In this work, three models were compared for mapping abandoned plots using Sentinel-2 with 10 m bands, Sentinel-2 with 10 m and 20 m bands, and airborne imagery with 1 m visible and near-infrared bands. A pixel-based classification approach was used, applying the Random Forests algorithm. The algorithm was trained with 144 plots and 100 decision trees. The results were validated using the hold-out method with 96 independent plots. The most accurate map was obtained using airborne images, the Enhanced Vegetation Index (EVI) and Thiam's Transformed Vegetation Index (TTVI), with an overall accuracy of 88.5%. The map generated from Sentinel-2 images (10 m bands and the EVI and TTVI spectral indices) had an overall accuracy of 77.1%. Adding 20 m Sentinel-2 bands and the Normalized Difference Moisture Index (NDMI) did not improve the classification accuracy. According to the most accurate map, 4310 abandoned plots were detected in our study area, representing 32.5% of its agricultural surface. The proposed methodology proved to be useful for mapping citrus in highly fragmented areas, and it can be adapted to other crops. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Remote Sensing es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Citrus es_ES
dc.subject Land abandonment es_ES
dc.subject High-resolution imagery es_ES
dc.subject Sentinel-2 es_ES
dc.subject Image classification es_ES
dc.subject Random Forests algorithm es_ES
dc.subject Machine learning algorithms es_ES
dc.subject.classification INGENIERIA CARTOGRAFICA, GEODESIA Y FOTOGRAMETRIA es_ES
dc.subject.classification TECNOLOGIA DEL MEDIO AMBIENTE es_ES
dc.title Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/rs12122062 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Politécnica Superior de Gandia - Escola Politècnica Superior de Gandia es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria es_ES
dc.description.bibliographicCitation Morell-Monzó, S.; Estornell Cremades, J.; Sebastiá-Frasquet, M. (2020). Comparison of Sentinel-2 and High-Resolution Imagery for Mapping Land Abandonment in Fragmented Areas. Remote Sensing. 12(12):1-18. https://doi.org/10.3390/rs12122062 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/rs12122062 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 12 es_ES
dc.relation.pasarela S\414501 es_ES
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