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Position: Home > Articles > Spectroscopic detection of forest diseases: a review (1970–2020) Journal of Forestry Research 2021,33 (1)

Spectroscopic detection of forest diseases: a review (1970–2020)

作  者：
Lorenzo Cotrozz
单  位：
Department of Agriculture, Food and Environment, University of Pisa, Pisa, Ital
关键词：
Forest management;Plant disease detection;Reflectance;Remote sensing;Spectral imaging;MYCOSPHAERELLA LEAF DISEASE;PLANTATION CANOPY CONDITION;BAND NEEDLE BLIGHT;BURN SEVERITY;WATER STATUS;IMAGERY;REGRESSION;MORTALITY;EUCALYPTUS;TRAIT
摘  要：
Abstract Sustainable forest management is essential to confront the detrimental impacts of diseases on forest ecosystems. This review highlights the potential of vegetation spectroscopy in improving the feasibility of assessing forest disturbances induced by diseases in a timely and cost-effective manner. The basic concepts of vegetation spectroscopy and its application in phytopathology are first outlined then the literature on the topic is discussed. Using several optical sensors from leaf to landscape-level, a number of forest diseases characterized by variable pathogenic processes have been detected, identified and quantified in many country sites worldwide. Overall, these reviewed studies have pointed out the green and red regions of the visible spectrum, the red-edge and the early near-infrared as the spectral regions most sensitive to the disease development as they are mostly related to chlorophyll changes and symptom development. Late disease conditions particularly affect the shortwave-infrared region, mostly related to water content. This review also highlights some major issues to be addressed such as the need to explore other major forest diseases and geographic areas, to further develop hyperspectral sensors for early detection and discrimination of forest disturbances, to improve devices for remote sensing, to implement long-term monitoring, and to advance algorithms for exploitation of spectral data. Achieving of these goals will enhance the capability of vegetation spectroscopy in early detection of forest stress and in managing forest diseases.

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