首页> 外文期刊>Journal of Environmental Protection and Ecology >MULTIVARIATE STATISTICAL METHODOLOGIES FOR TESTING HYPOTHESIS OF LAND-USE CHANGE AT THE REGIONAL LEVEL. A REVIEW AND EVALUATION
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MULTIVARIATE STATISTICAL METHODOLOGIES FOR TESTING HYPOTHESIS OF LAND-USE CHANGE AT THE REGIONAL LEVEL. A REVIEW AND EVALUATION

机译:用于检验区域水平上土地利用变化假说的多元统计方法。回顾与评估

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摘要

Various models of land-use and land-cover change have been developed for better understanding of existing relationships and interactions between human and natural phenomena. Most of these models concentrate on human behaviour (behavioural models) holding a strong explanatory power of the observed patterns of land-use change though very often lacking spatial explicitness. At the same time, there has been a need to study human activities and land-use conversion and modification, with a stronger spatial component and in more depth going into the basic elements that form the underlying causes of land metamorphosis. Combining techniques and methodologies developed in different disciplines might help to better understand and respond to issues related to the changing patterns of land-use. This paper selectively reviews current statistical methodologies for modelling land-use changes. The methodologies are presented and discussed in terms of their mathematical formula as well as the necessary transformations that the dependent and independent variables require in order to fit the models. Different statistical models hold different capabilities that can further help our understanding in human induced land-use and land-cover changes and subsequently promote better decision-making. These models can be used with a wide range of explanatory variables and address serious issues relevant to the level of analysis.
机译:为了更好地了解人与自然现象之间的现有关系和相互作用,已经开发了各种土地利用和土地覆盖变化模型。这些模型大多数都集中在人类行为(行为模型)上,尽管经常缺乏空间明确性,但它们对观察到的土地利用变化模式具有很强的解释力。同时,有必要研究人类活动以及土地利用的转换和改变,其具有更强的空间成分,并更深入地研究构成土地变态的根本原因的基本要素。结合不同学科开发的技术和方法可能有助于更好地理解和应对与土地利用方式变化有关的问题。本文有选择地回顾了当前用于对土地利用变化进行建模的统计方法。这些方法论以其数学公式以及因变量和自变量为拟合模型所需的必要转换进行了介绍和讨论。不同的统计模型具有不同的功能,可以进一步帮助我们理解人为引起的土地利用和土地覆盖的变化,从而促进更好的决策。这些模型可用于各种解释变量,并解决与分析级别有关的严重问题。

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