Research Library

open-access-imgOpen AccessRemote Monitoring of Forest Insect Defoliation -A Review-
Author(s)
CD Rullán-Silva,
Adriana E. Olthoff,
J. A. Delgado de la Mata,
J.A. Pajares-Alonso
Publication year2013
Publication title
forest systems
Resource typeJournals
PublisherNational Institute for Agricultural and Food Research and Technology

Aim of study: This paper reviews the global research during the last 6 years (2007-2012) on the state, trends and potential of remote sensing for detecting, mapping and monitoring forest defoliation caused by insects. Area of study: The review covers research carried out within different countries in Europe and America. Main results: A nation or region wide monitoring system should be scaled in two levels, one using time-series with moderate to coarse resolutions, and the other with fine or high resolution. Thus, MODIS data is increasingly used for early warning detection, whereas Landsat data is predominant in defoliation damage research. Furthermore, ALS data currently stands as the more promising option for operative detection of defoliation. Vegetation indices based on infrared-medium/near-infrared ratios and on moisture content indicators are of great potential for mapping insect pest defoliation, although NDVI is the most widely used and tested. Research highlights: Among most promising methods for insect defoliation monitoring are Spectral Mixture Analysis, best suited for detection due to its sub-pixel recognition enhancing multispectral data, and use of logistic models as function of vegetation index change between two dates, recommended for predicting defoliation. Key words: vegetation damage; pest outbreak; spectral change detection.

Subject(s)agronomy , biology , botany , change detection , climate change , computer science , ecology , environmental science , geography , insect pest , medicine , multispectral image , normalized difference vegetation index , pathology , pest analysis , remote sensing , telecommunications , vegetation (pathology) , vegetation index , warning system
Language(s)English
SCImago Journal Rank0.455
H-Index25
eISSN2171-9845
pISSN2171-5068
DOI10.5424/fs/2013223-04417

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