Spatial distribution of climatic variables in Tocantins State, Brazil

Q4 Agricultural and Biological Sciences
L. F. Ávila, F. Cassalho, M. Viola, S. Beskow, G. Coelho, Kleudson Da Silva Nardes
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引用次数: 0

Abstract

The recognition of spatial distribution of climatic variables is essential for planning land use and occupation. This is especially relevant in regions where the agricultural frontier is expanding, as it is the case of Tocantins State, Brazil. One of the tools widely used for spatialization of environmental variables is geostatistics, which allows the identification of the spatial dependence of these variables. In this context, this study evaluates the performance of geostatistical interpolators ordinary kriging (OK) and cokriging (CK) by adjusting different semivariogram models, and the sub­sequent spatialization of the variables mean air temperature, insolation, air relative humidity, and potential evapotranspiration for Tocantins State. The main results and conclusions were: i) variogram analysis is essential to improve the mapping results of each variable; ii) cross-validation showed acceptable errors, indicating reliability of results; (iii) the OK outperformed CK, which can be explained by the good spatial dependence structure presented by the primary variable; and iv) the maps produced can corroborate the management of natural resources and land use planning in Tocantins State.
巴西托坎廷斯州气候变量的空间分布
认识气候变量的空间分布对规划土地利用和占用至关重要。这在农业疆界不断扩大的地区尤其重要,例如巴西的托坎廷斯州。广泛用于环境变量空间化的工具之一是地质统计学,它允许识别这些变量的空间依赖性。在此背景下,本研究通过调整不同的半变异函数模型,评估了普通克里格(OK)和共同克里格(CK)地统计插值器的性能,并对Tocantins州的平均气温、日照、空气相对湿度和潜在蒸散量进行了空间化。主要结果和结论是:1)方差分析对于改善各变量的作图结果至关重要;Ii)交叉验证误差可接受,表明结果的可靠性;(3) OK表现优于CK,主要表现为主变量表现出良好的空间依赖结构;制作的地图可以证实Tocantins州的自然资源管理和土地使用规划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cientifica
Cientifica Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
0.50
自引率
0.00%
发文量
4
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