Vol. 79 No. 5-6 (2024)
Articles

Monitoring Insect Infestations in Urban Areas Using PlanetScope Time Series

PDF (Italiano)
  • Francesco Parisi,
  • Valentina Falanga,
  • Saverio Francini,
  • Giovanni D'Amico,
  • Gherardo Chirici,
  • Bruno Lasserre,
  • Marco Marchetti
Francesco Parisi
Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, C. da Fonte Lappone, 86090 Pesche (IS), Italy.
Valentina Falanga
Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, C. da Fonte Lappone, 86090 Pesche (IS), Italy.
Saverio Francini
Dipartimento di Scienze e Tecnologie Agro-alimentari (DISTAL), Università di Bologna, 40126 Bologna, Italy.
Giovanni D'Amico
geoLAB - Laboratorio di Geomatica Forestale, Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura 13, 50145 Firenze, Italy.
Gherardo Chirici
NBFC, National Biodiversity Future Center, Palermo 90133, Italy. geoLAB - Laboratorio di Geomatica Forestale, Dipartimento di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali, Università degli Studi di Firenze, Via San Bonaventura 13, 50145 Firenze, Italy. Fondazione per il Futuro delle Città, Firenze, Italy.
Bruno Lasserre
Dipartimento di Bioscienze e Territorio, Università degli Studi del Molise, C. da Fonte Lappone, 86090 Pesche (IS), Italy.
Marco Marchetti
Sapienza Università di Roma, Dipartimento di Architettura e Progetto, Via Flaminia, 359, 00196 Roma, Italy.
DOI: https://doi.org/10.36253/ifm-1150

Published 2025-02-07

Keywords

  • pine tortoise scale; city of Rome; green areas; Renormalized Difference Vegetation Index; infested trees

How to Cite

Parisi, F., Falanga, V., Francini, S., D’Amico, G., Chirici, G., Lasserre, B., & Marchetti, M. (2025). Monitoring Insect Infestations in Urban Areas Using PlanetScope Time Series. L’Italia Forestale E Montana, 79(5-6), 203–215. https://doi.org/10.36253/ifm-1150

Copyright (c) 2025 Francesco Parisi, Valentina Falanga, Saverio Francini, Giovanni D'Amico, Gherardo Chirici, Bruno Lasserre, Marco Marchetti

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Abstract

The present study aims to evaluate the effectiveness of remote sensing in monitoring the invasion of the pine tortoise scale (Toumeyella parvicornis Cockerell) affecting the stone pine (Pinus pinea L.) in the city of Rome, using PlanetScope images, which are ideal for detecting infestation outbreaks in urban and peri-urban areas.

To conduct the research, a reference dataset was created containing 238 healthy trees in Tuscany and 2023 damaged trees in green areas of Rome. Over 30,000 PlanetScope images were analyzed, testing the effectiveness of the RDVI (Renormalized Difference Vegetation Index) in detecting this specific forest disturbance. Various thresholds were examined to identify the best discrimination between healthy and damaged trees.

The results show a significant decrease in the RDVI during the summer in infested areas, while healthy trees remained stable. The identified threshold provided an accuracy of 99% in detecting infested trees. However, it is acknowledged that the dataset of healthy trees came from natural forest areas, where higher photosynthetic activity is expected compared to urban green areas. From the results obtained, we can conclude that monitoring urban forests through satellite images is essential for managing and preventing pest infestations.

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