Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain
The <i>Delottococcus aberiae</i> is a mealybug pest known as <i>Cotonet de les Valls</i> in the province of Castellón (Spain). This tiny insect is causing large economic losses in the Spanish agricultural sector, especially in the citrus industry. The European Copernicus prog...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/23/4362 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850259970841378816 |
|---|---|
| author | Fàtima Della Bellver Belen Franch Gras Italo Moletto-Lobos César José Guerrero Benavent Alberto San Bautista Primo Constanza Rubio Eric Vermote Sebastien Saunier |
| author_facet | Fàtima Della Bellver Belen Franch Gras Italo Moletto-Lobos César José Guerrero Benavent Alberto San Bautista Primo Constanza Rubio Eric Vermote Sebastien Saunier |
| author_sort | Fàtima Della Bellver |
| collection | DOAJ |
| description | The <i>Delottococcus aberiae</i> is a mealybug pest known as <i>Cotonet de les Valls</i> in the province of Castellón (Spain). This tiny insect is causing large economic losses in the Spanish agricultural sector, especially in the citrus industry. The European Copernicus program encourages the progress of Earth observation (EO) in relation to the development of agricultural monitoring tools. In this context, this work is based on the analysis of the temporal evolution of spectral surface reflectance data from Sen2Like, analyzing healthy and fields affected by the mealybug. The study area is focused on the surroundings of Vall d’Uixó (Castellón, Spain), involving an approximate area of 25 ha distributed in a total of 21 fields of citrus trees with different mealybug incidence, classified as healthy or unhealthy, during the 2020–2021 season. The relationship between the mealybug infestation level and the Normalized Difference Vegetation Index (NDVI) and other optical bands (Red, NIR, SWIR, derived from Sen2Like) were analyzed by studying the time-series evolution of each parameter across the time period 2017–2022. In this study, we also demonstrate that evergreen fruit trees such as citrus, show a seasonality across the EO-based time series, which is linked to directional effects caused by the sensor–sun geometry. This can be mitigated by using a Bidirectional Reflectance Distribution Function (BRDF) model such as the High-Resolution Adjusted BRDF Algorithm (HABA). To study the infested fields separately from healthy ones and avoid mixing fields with very different spectral responses caused by field type, separation between rows, or age, we studied the evolution of each parcel separately using monthly linear regressions, considering the 2017–2018 seasons as a reference when the pest had not developed yet. The observations indicate the feasibility of the distinction between affected and healthy plots during a year utilizing specific spectral ranges, with SWIR proving a notably effective channel, enabling separability from mid-summer to the fall. Furthermore, the anomaly inspection demonstrates an increase in the effects of the pest from 2020 to 2022 in all spectral regions and enables a first approximation for identifying healthy and affected fields based on negative anomalies in the red and SWIR channels and positive anomalies in the NIR and NDVI. This work contributes to the development of new monitoring tools for efficient and sustainable action in pest control. |
| format | Article |
| id | doaj-art-bc3012606ffc4668a9826073eaec26f4 |
| institution | OA Journals |
| issn | 2072-4292 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-bc3012606ffc4668a9826073eaec26f42025-08-20T01:55:45ZengMDPI AGRemote Sensing2072-42922024-11-011623436210.3390/rs16234362Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern SpainFàtima Della Bellver0Belen Franch Gras1Italo Moletto-Lobos2César José Guerrero Benavent3Alberto San Bautista Primo4Constanza Rubio5Eric Vermote6Sebastien Saunier7Global Change Unit, Parc Científic, Universitat de València (Paterna), 46980 Paterna, SpainGlobal Change Unit, Parc Científic, Universitat de València (Paterna), 46980 Paterna, SpainGlobal Change Unit, Parc Científic, Universitat de València (Paterna), 46980 Paterna, SpainGlobal Change Unit, Parc Científic, Universitat de València (Paterna), 46980 Paterna, SpainDepartamento de Producción Vegetal, Universitat Politécnica de València (Valencia), 46022 Valencia, SpainCentro de Tecnologías Físicas, Universitat Politécnica de València (Valencia), 46022 Paterna, SpainNASA Goddard Space Flight Center, 8800 Greenbelt Road, Greenbelt, MD 20771, USATelespazio France, Satellite System and Operation, 26 Avenue JF Champollion, BP 52309, CEDEX 1, 31023 Toulouse, FranceThe <i>Delottococcus aberiae</i> is a mealybug pest known as <i>Cotonet de les Valls</i> in the province of Castellón (Spain). This tiny insect is causing large economic losses in the Spanish agricultural sector, especially in the citrus industry. The European Copernicus program encourages the progress of Earth observation (EO) in relation to the development of agricultural monitoring tools. In this context, this work is based on the analysis of the temporal evolution of spectral surface reflectance data from Sen2Like, analyzing healthy and fields affected by the mealybug. The study area is focused on the surroundings of Vall d’Uixó (Castellón, Spain), involving an approximate area of 25 ha distributed in a total of 21 fields of citrus trees with different mealybug incidence, classified as healthy or unhealthy, during the 2020–2021 season. The relationship between the mealybug infestation level and the Normalized Difference Vegetation Index (NDVI) and other optical bands (Red, NIR, SWIR, derived from Sen2Like) were analyzed by studying the time-series evolution of each parameter across the time period 2017–2022. In this study, we also demonstrate that evergreen fruit trees such as citrus, show a seasonality across the EO-based time series, which is linked to directional effects caused by the sensor–sun geometry. This can be mitigated by using a Bidirectional Reflectance Distribution Function (BRDF) model such as the High-Resolution Adjusted BRDF Algorithm (HABA). To study the infested fields separately from healthy ones and avoid mixing fields with very different spectral responses caused by field type, separation between rows, or age, we studied the evolution of each parcel separately using monthly linear regressions, considering the 2017–2018 seasons as a reference when the pest had not developed yet. The observations indicate the feasibility of the distinction between affected and healthy plots during a year utilizing specific spectral ranges, with SWIR proving a notably effective channel, enabling separability from mid-summer to the fall. Furthermore, the anomaly inspection demonstrates an increase in the effects of the pest from 2020 to 2022 in all spectral regions and enables a first approximation for identifying healthy and affected fields based on negative anomalies in the red and SWIR channels and positive anomalies in the NIR and NDVI. This work contributes to the development of new monitoring tools for efficient and sustainable action in pest control.https://www.mdpi.com/2072-4292/16/23/4362pest detectionSen2LikeBRDFNDVI<i>Delottococcus aberiae</i> |
| spellingShingle | Fàtima Della Bellver Belen Franch Gras Italo Moletto-Lobos César José Guerrero Benavent Alberto San Bautista Primo Constanza Rubio Eric Vermote Sebastien Saunier Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain Remote Sensing pest detection Sen2Like BRDF NDVI <i>Delottococcus aberiae</i> |
| title | Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain |
| title_full | Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain |
| title_fullStr | Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain |
| title_full_unstemmed | Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain |
| title_short | Pest Detection in Citrus Orchards Using Sentinel-2: A Case Study on Mealybug (<i>Delottococcus aberiae</i>) in Eastern Spain |
| title_sort | pest detection in citrus orchards using sentinel 2 a case study on mealybug i delottococcus aberiae i in eastern spain |
| topic | pest detection Sen2Like BRDF NDVI <i>Delottococcus aberiae</i> |
| url | https://www.mdpi.com/2072-4292/16/23/4362 |
| work_keys_str_mv | AT fatimadellabellver pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT belenfranchgras pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT italomolettolobos pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT cesarjoseguerrerobenavent pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT albertosanbautistaprimo pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT constanzarubio pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT ericvermote pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain AT sebastiensaunier pestdetectionincitrusorchardsusingsentinel2acasestudyonmealybugidelottococcusaberiaeiineasternspain |