A Classification of Climate by Principal Component Analysis and Its Relationship To Tree Species Distribution
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This article is published in Forest Science.The article was published on 1968-09-01 and is currently open access. It has received 21 citations till now. The article focuses on the topics: Principal component analysis.read more
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Predicting the spatial-distribution of climate - temperature in great-britain
Jack J. Lennon,John Turner +1 more
TL;DR: Four categories of model, simple interpolation, thin plate splines, multiple linear regression and mixed spline-regression, were tested for their ability to predict the spatial distribution of temperature on the British mainland.
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Spatial prediction of climatic state factor regions in Alaska
Tim Hammond,John Yarie +1 more
TL;DR: In this article, temperature and precipitation data from weather stations in Alaska and western Canada were analyzed via universal kriging to estimate mean annual and mean growing season temperature and mean annual growing season precipitation values on a 10 km grid.
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Some Vegetation-Environment Relationships in the Upland Forests of Oklahoma
TL;DR: Results of these studies indicate that factors affecting the supply of available moisture usually have the greatest influence on the vegetation of an area.
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The history, status and future of climatic classification
TL;DR: The use of more than one variable has been a long-standing feature in the classification of weather data as discussed by the authors, with Koppen's method proving to be the most durable.
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The relationship of climatic indices and variables to corn (maize) yields: a principal components analysis
TL;DR: In this article, a multivariate statistical technique of principal components analysis was used to evaluate the relationship of climatic indices and variables to corn yields in the Great Plains and Midwest of the United States.