Evento

Maxent model application for tree pest monitoring

Marzialetti, Pablo ; Giovanni, Laneve ; Santilli, Giancarlo ; Huan, Wenjiang ; Zappacosta, Diego Carlos Icon

Otros responsables

Fecha

2019

Editorial

Institute of Electrical and Electronics Engineers

Revista

Título del libro

Nombre del evento

International Symposium on Geoscience and Remote Sensing

Fecha del evento

2019-07-28

Institución organizadora

Institute of Electrical and Electronics Engineers
The Geoscience and Remote Sensing Society

ISSN

eISSN

ISBN

978-1-5386-9154-0

Idioma

Inglés

Tipo del evento

Simposio

Resumen

Tree pests can cause rapid and widespread damage, reducing the economic value of plants, production, in the case of fruit trees, and their role in mitigating climate change. There are several diseases that affect trees, including, for example, pine tree nematode (PWN), trunk fungal diseases, or Xylella fastidiosa (Xf).Mapping of diseased plants based on visual or automatic analysis of remote sensing data could be a useful support for in situ investigation planning. However, there is a clear need for better modeling methods to elaborate potential critical scenarios in order to early detect diseases (e.g. Xf) in host plants.Maxent (Maximum Entropy) has proved powerful when modeling species with available scarce presence-only occurrence data. The purpose is to predict potential distributions or explore expanding distributions. In this work we applied the Maxent model comparing local modeling results with worldwide cases towards a more comprehensive analysis of potential pest risk zones.

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