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Detecting Jack Pine Budworm Defoliation Using Spectral Mixture Analysis

Identifieur interne : 002090 ( Main/Exploration ); précédent : 002089; suivant : 002091

Detecting Jack Pine Budworm Defoliation Using Spectral Mixture Analysis

Auteurs : Volker C. Radeloff [États-Unis] ; David J. Mladenoff [États-Unis] ; Mark S. Boyce [États-Unis]

Source :

RBID : ISTEX:7C56FA574BB059A270FD2AC16FF432B5591DC490

Abstract

Insect defoliation is a major disturbance force in forested ecosystems. Monitoring outbreaks, and estimating the areas affected, is therefore important for both forest managers and forest ecologists. The objective of our study was to classify jack pine budworm defoliation levels in Landsat TM imagery recorded previous to and during the 1990–1995 outbreak in our 450,000 ha study area in northwestern Wisconsin (USA). Many previous studies correlated insect defoliation and remotely sensed imagery with moderate to good success, but it often remained unclear if actual defoliation effects or other forest attributes correlated with defoliation were detected. For example, a larger deciduous component in mixed jack pine stands will limit budworm populations and thereby defoliation. The deciduous component in stands is a determining factor for insect defoliation, whereas needle discoloration and tree mortality are their effect. We used pre-outbreak Landsat TM data (1987) to identify determining factors for jack pine budworm population levels and peak-outbreak imagery (1993) for detecting actual defoliation. Our satellite data were atmospherically corrected using a radiative transfer model (5S). Spectral mixture analysis was performed using spectrometer measurements of jack pine needles and bark as representations of surface materials (“endmembers”). The explanatory power of the resulting fraction images was evaluated using jack pine budworm population data collected at 33 sampling points. Near-infrared reflectance (NIR) increased in defoliated stands between 1987 and 1993, but single date NIR in each year was negatively correlated with budworm levels in 1993 (r=−0.69 and −0.47). This was because hardwood trees within jack pine stands caused higher NIR reflectance but limited jack pine budworm populations. The 10% NIR difference between pure and mixed jack pine stands outweighed the 3–5% increase in NIR due to defoliation and necessitated stratification of the satellite data by tree species. Spectral mixture analysis performed on pure jack pine stands resulted in a strong negative correlation between the 1993 green needle fraction and the 1993 budworm population data (r=−0.94). This study was, to our knowledge, the first that applied spectral mixture analysis for forest damage detection, and also the first to use insect population measurements as independent field data. These methods, and the separation of determinants and effects of jack pine budworm defoliation, enabled us to detect actual defoliation with high accuracy.

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DOI: 10.1016/S0034-4257(99)00008-5


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<div type="abstract" xml:lang="en">Insect defoliation is a major disturbance force in forested ecosystems. Monitoring outbreaks, and estimating the areas affected, is therefore important for both forest managers and forest ecologists. The objective of our study was to classify jack pine budworm defoliation levels in Landsat TM imagery recorded previous to and during the 1990–1995 outbreak in our 450,000 ha study area in northwestern Wisconsin (USA). Many previous studies correlated insect defoliation and remotely sensed imagery with moderate to good success, but it often remained unclear if actual defoliation effects or other forest attributes correlated with defoliation were detected. For example, a larger deciduous component in mixed jack pine stands will limit budworm populations and thereby defoliation. The deciduous component in stands is a determining factor for insect defoliation, whereas needle discoloration and tree mortality are their effect. We used pre-outbreak Landsat TM data (1987) to identify determining factors for jack pine budworm population levels and peak-outbreak imagery (1993) for detecting actual defoliation. Our satellite data were atmospherically corrected using a radiative transfer model (5S). Spectral mixture analysis was performed using spectrometer measurements of jack pine needles and bark as representations of surface materials (“endmembers”). The explanatory power of the resulting fraction images was evaluated using jack pine budworm population data collected at 33 sampling points. Near-infrared reflectance (NIR) increased in defoliated stands between 1987 and 1993, but single date NIR in each year was negatively correlated with budworm levels in 1993 (r=−0.69 and −0.47). This was because hardwood trees within jack pine stands caused higher NIR reflectance but limited jack pine budworm populations. The 10% NIR difference between pure and mixed jack pine stands outweighed the 3–5% increase in NIR due to defoliation and necessitated stratification of the satellite data by tree species. Spectral mixture analysis performed on pure jack pine stands resulted in a strong negative correlation between the 1993 green needle fraction and the 1993 budworm population data (r=−0.94). This study was, to our knowledge, the first that applied spectral mixture analysis for forest damage detection, and also the first to use insect population measurements as independent field data. These methods, and the separation of determinants and effects of jack pine budworm defoliation, enabled us to detect actual defoliation with high accuracy.</div>
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