Remote sensing of pine scale infestations in a pine forest: support material
Abstract
This dataset contains remote sensing data and supporting materials used to develop and evaluate methods for the detection of pine scale infestations in a pine forest. Pine scale insects represent an important threat to forest health, and early detection through remote sensing can support more effective monitoring and management strategies. The dataset includes imagery and derived data prepared for machine learning and remote sensing analyses, enabling the identification of spectral and spatial patterns associated with pine scale presence. It is intended to support research on automated pest detection using high-resolution remote sensing data. The associated GitHub repository provides code and workflows for data preprocessing, dataset preparation, and experimental analysis, allowing users to reproduce and extend the methods developed in the related research. This dataset may be useful for studies in forest health monitoring, ecological remote sensing, and machine learning applications for environmental analysis. The dataset retrieval and research has been funded by Comando Unità Forestali, Ambientali e Agroalimentari, Carabinieri (grant CREA PRJ4994m 2.99.99.92.00) “Smart Forest Monitoring”.
Fields of Study & Subjects
Forest Insect Ecology and Management
Remote-Sensing Image Classification
Remote Sensing in Agriculture
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 6 March 2026
- Language
- EN
- Document type
- Dataset