1992
DOI: 10.1007/bf02348592
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Assessment of pine forest damage by blight based on Landsat TM data and correlation with environmental factors

Abstract: Landsat TM images were obtained of blight damage to a Japanese red pine forest in the western part of Hiroshima Prefecture, Japan, using a spectral vegetation index; that is, the ratio of the digital number (relative reflectance on the ground surface) of TM Band 4 to Band 3 observed in May 1987, which decreased with the increase in the canopy cover of damaged pine trees measured in the field. The TM images suggested that the areas of damaged forest were concentrated in or near cities, industrial areas and expr… Show more

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Cited by 9 publications
(3 citation statements)
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“…Remote sensing technology has become an important technical means for identifying forest diseases and insect pests [3,4]. The spectral characteristics of infected plants constitute the main basis for identifying forest pests via remote sensing technology [5].…”
Section: Introductionmentioning
confidence: 99%
“…Remote sensing technology has become an important technical means for identifying forest diseases and insect pests [3,4]. The spectral characteristics of infected plants constitute the main basis for identifying forest pests via remote sensing technology [5].…”
Section: Introductionmentioning
confidence: 99%
“…The correlation between the indices and net annual volume change was more than 0.8. Nakane and Kimura (1992) observed that the simple ratio index (NIR/ Red) decreased with increasing pine blight damage on Japanese red pine. In Canada, Hudak et al (1993) used discriminant analysis to separate defoliation classes of balsam fir on the basis of the spectral channels.…”
Section: Introductionmentioning
confidence: 93%
“…Generally, either crop plant pests, fruit tree pests, forest pests or grassland pests that could cause discoloration or deformation of the leaves, or produce residues on the leaf surfaces, could be monitored using remote sensing technologies [4]. There have been many reports about remote sensing monitoring of plant diseases in the world [5], [6], [7], [8], [9], [10], [11], [12], [13], [14]. The reports about remote sensing monitoring of wheat stripe rust caused by Puccinia striiformis f. sp.…”
Section: Introductionmentioning
confidence: 99%