The use of multispectral sensing techniques to detect ponderosa pine trees under stress from insect or pathogenic organisms Annual progress report

Ground and aerial imaging techniques to detect tree damage caused by bark beetles in forested area

The use of multispectral sensing techniques to detect Ponderosa pine trees under stress from insect or pathogenic organisms

Multispectral sensing techniques for ground and airborne detection of Ponderosa pine trees under stress from insect or pathogenic organism

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Eucalyptus tree stands killed by low temperatures in December 1972 were outlined by image enhancement of two separate dates of ERTS-1 images (January 22, 1973-I.D. 1183-18175 and April 22, 1973-I.D. 1273-18183). Three stands larger than 500 meters in size were detected very accurately. In Colorado, range and grassland communities were analyzed by visual interpretation of color composite scene I.D. 1028-17135. It was found that mixtures of plant litter, amount and kind of bare soil, and plant foliage cover made classification of grasslands very difficult. Changes in forest land use were detected on areas as small as 5 acres when ERTS-1 color composite scene 1264-15445 (April 13, 1973) was compared with 1966 ASCS index mosaics (scale 1:60,000). Verification of the changes were made from RB-57 underflight CIR transparencies (scale 1:120,000)

Inventory of forest and rangeland resources, including forest stress

There are no author-identified significant results in this report

Evaluation of ERTS-1 data for inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Results of photointerpretation indicated that ERTS is a good classifier of forest and nonforest lands (90 to 95 percent accurate). Photointerpreters could make this separation as accurately as signature analysis of the computer compatible tapes. Further breakdowns of cover types at each site could not be accurately classified by interpreters (60 percent) or computer analysts (74 percent). Exceptions were water, wet meadow, and coniferous stands. At no time could the large bark beetle infestations (many over 300 meters in size) be detected on ERTS images. The ERTS wavebands are too broad to distinguish the yellow, yellow-red, and red colors of the dying pine foliage from healthy green-yellow foliage. Forest disturbances could be detected on ERTS color composites about 90 percent of the time when compared with six-year-old photo index mosaics. ERTS enlargements (1:125,000 scale, preferably color prints) would be useful to forest managers of large ownerships over 5,000 hectares (12,500 acres) for broad area planning. Black-and-white enlargements can be used effectively as aerial navigation aids for precision aerial photography where maps are old or not available

The use of multispectral sensing techniques to detect ponderosa pine trees under stress from insect or pathogenic organisms

Application of multispectral sensors to detect insect and disease infestation of ponderosa pine tree