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The uniform angle index (UAI) is used to characterize the spatial distribution of a forest community or of individual tree species within that community. This study presents an empirical assessment of the performance of a new statistical test used in conjunction with the UAI. In this study, the UAI is applied to observed and simulated communities. The effect of plot size and density are examined and the results are compared with the criteria of the aggregation index R of Clark and Evan (CE-R) and Ripley's L function (RL). The results suggest that the UAI performs well in determining a particular class of spatial pattern and that, in contrast to the CE-R index, it is unaffected by population density because the standard deviation can be estimated when the density is known using a new empirical relationship presented in this paper. The results of this study represent an improvement in the development of the UAI, verifying its performance and confirming its overall utility. Our comparative analysis positions the UAI among its historical competitors, the CE-R and RL criteria. The UAI index, which does not require expensive mapping of tree positions, can produce results that are equivalent to those obtained by RL and more robust and reliable than those obtained by CE-R. Key words: forest, spatial patterns of trees, uniform angle index, significance test, method. L'indice d'angle uniforme (UAI) est utilise pour caracteriser la distribution spatiale d'une communaute ou d'une espece particuliere dans cette communaute. Cette etude presente une evaluation empirique de la performance d'un nouveau test statistique utilise avec l'UAI. Dans cette etude l'UAI est applique a des communautes reelles et simulees. L'effet de la dimension et de la densite des places echantillons ainsi que les resultats sont compares aux fonctions R de Clark et Evans (CE-R) et L de Ripley (RL). Les resultats indiquent que l'UAI a une bonne performance pour determiner une classe particuliere de configuration spatiale et que, contrairement a la fonction CE-R, il n'est pas influence par la densite de la population parce que l'ecart-type peut etre estime lorsque la densite est connue, en utilisant une nouvelle relation empirique presentee dans cet article. Les resultats de cette etude constituent une amelioration dans le developpement de l'UAI car ils corroborent sa performance et confirment sont utilite generale. Notre analyse comparative place l'UAI au meme rang que ses competiteurs historiques: les fonctions CE-R et RL. L'UAI, qui ne requiert pas une cartographie couteuse de la position des arbres, peut produire des resultats qui sont equivalents a ceux obtenus avec la fonction RL et plus robustes et plus fiables que ceux obtenus avec la fonction CE-R. [Traduit par la Redaction] Mots-cles: foret, configurations spatiales des arbres, indice d'angle uniforme, test d'hypothese, methode., 1. Introduction The tree distribution in horizontal space reflects very specific relationships among the individuals in a particular forest community and among individuals within a given species in that community. [...]

Comprehensive evaluation of forest state is the precondition and critical step for forest management. To solve the problem that the radar plot and unit circle only focus on the value of each the evaluation index, this paper proposes a novel method for comprehensively and simultaneously evaluating the functionality and inhomogeneity of forest state based on the modified unit circle method. We evaluated the forest state of the Quercus aliena BL. var. acuteserrata Maxim. ex Wenz. broad-leaved mixed forest in the Xiaolong Mountains Forest Area of Gansu Province and the Pinus koraiensis Sieb. et Zucc. broad-leaved mixed forest in Jilin Province in China. According to the principle of comprehensive, scientific and operability, 10 evaluation indices on forest structure and vitality were selected to construct the evaluation indicator system. Each index was normalized based on the assignment method and ensured to be strictly positive based on reciprocal transformation method. The areas and arc length of the closed graph, formed by connecting every two adjacent indicators, in the radar plot and unit circle were extracted. Based on the isoperimetric theorem (isoperimetric inequality), a comprehensive evaluation model was constructed. Compared with radar chart and unit circle method, each index in the newly proposed unit circle method is represented by an independent sector region, reflecting the contribution of the index to the overall evaluation result. Each index has the same relative importance weight, contributing to the estimation the relative sizes of each aspect of forest state. The unique area and arc length of the closed graph help summarize the overall performance with a global score. The expression effect of improved unit circle has been enhanced, and as an English proverb put it, "A picture is worth a thousand words." The new proposed method simultaneously evaluates the functionality and inhomogeneity of the forest state and it is a powerful tool for the diagnosis of forest state problems and the decision-making of forest management. [ABSTRACT FROM AUTHOR]