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Results for “Southern Journal of Applied Forestry”

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2 recordsLinked to original sources
USGS1990

Establishment of bottomland oak plantations on the Yazoo National Wildlife Refuge complex

Stocking, height and diameter growth, and invasion of both herbaceous and woody plant species are reported for 5 direct seeded and 5 planted seedling stands of bottomland oaks, all of which were between 4 and 8 years old. Stocking was generally higher in the planted seedling stands. Both height and diameter growth were substantially higher in the planted seedling stands. Low stocking and poor growth, especially for the direct seeded stands, was associated with medium-textured soils and a heavy cover of Johnson grass ( Sorghum halepense ) and goldenrod ( Solidago altissima ). Invasion of woody species was heavily dominated by light-seeded species, and was highest in stands close to mature trees.

Mississippi↗
USGS2015

Remote sensing change detection methods to track deforestation and growth in threatened rainforests in Madre de Dios, Peru

Two forestry-change detection methods are described, compared, and contrasted for estimating deforestation and growth in threatened forests in southern Peru from 2000 to 2010. The methods used in this study rely on freely available data, including atmospherically corrected Landsat 5 Thematic Mapper and Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF). The two methods include a conventional supervised signature extraction method and a unique self-calibrating method called MODIS VCF guided forest/nonforest (FNF) masking. The process chain for each of these methods includes a threshold classification of MODIS VCF, training data or signature extraction, signature evaluation, k-nearest neighbor classification, analyst-guided reclassification, and postclassification image differencing to generate forest change maps. Comparisons of all methods were based on an accuracy assessment using 500 validation pixels. Results of this accuracy assessment indicate that FNF masking had a 5% higher overall accuracy and was superior to conventional supervised classification when estimating forest change. Both methods succeeded in classifying persistently forested and nonforested areas, and both had limitations when classifying forest change.

Madre de Dios↗