土壤容重的建模和制图方法:以乌克兰切尔诺夫茨地区为例

IF 0.5 Q3 GEOGRAPHY
V. Cherlinka, Y. Dmytruk, L. Cherlinka, M. Gunchak, V. Sobko
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引用次数: 0

摘要

许多国家的土壤监测项目通常不测量土壤容重这样的指标。同时,土壤覆盖状况评估的现代问题要求将其应用于农业景观的土壤管理。我们在地理空间建模中看到了这个问题的解决方案。我们开发了一种模拟土壤容重的技术,其算法包括五个阶段:建立农用工业土壤类群模型图,建立粘土含量图,构建腐殖质含量图,选择土壤容重对腐殖质和粘土含量的经验依赖关系,评估这些依赖关系的可靠性,并在GRASS GIS中实现,最后对土壤容重的空间连续分布进行制图建模。同时,建立了提高土壤容重建模和制图方法质量的参数。首先,这是增加密度、腐殖质和粘土含量的采样数据集,以提高所选回归公式的可靠性。这也是利用地统计学方法或模型对腐殖质含量空间建模质量的提高。为了改善粘土含量图,需要提高DEM和预测器的分辨率,选择更准确的DEM来源和预测算法。所提出的方法已在乌克兰切尔诺夫茨地区的一部分地区得到应用,并有可能在全国范围内使用。URL: https://www.gcass.science.upjs.sk/
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Methods of modeling and mapping of the soil bulk density: a case study from Chernivtsi region, Ukraine
Soil monitoring programs in many countries often do not measure such an indicator as soil bulk density. At the same time, modern problems of assessing the condition of the soil cover require its use in soil management of agricultural landscapes. We see the solution to this problem in geospatial modeling. We have developed a technique for simulating soil bulk density, the algorithm of which consists of five stages: the creation of model maps of agro-industrial soil groups, modeling of a clay content map, construction of a map of humus content, selection of empirical dependences of soil bulk density on humus and clay content with evaluation reliability of these dependencies and their implementation in GRASS GIS and, finally, cartographic modeling of the spatial continuous distribution of soil bulk density. At the same time, parameters for improving the quality of methods modeling and mapping the soil bulk density were established. First of all, this is an increase in the sampling dataset of density, humus, and clay content to improve the reliability of the selected regression formula. It is also an improvement in the quality of spatial modeling of the humus content using geostatistical methods or modeling. To improve the clay content map, it is necessary to increase the resolution of DEM and predictors, to choose more accurate sources of DEM and prediction algorithms. The application of the presented methodology is shown in a part of Chernivtsi region, Ukraine, with the possibility of use on the scale of the entire country. URL: https://www.gcass.science.upjs.sk/
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
4
期刊介绍: Geographia Cassoviensis is a biannual peer-reviewed journal published by the Pavol Jozef Šafárik University in Košice since 2007. It is available both in print and open-access electronic version. The journal publishes original research articles from Geography and other closely-related research fields. Since 2016 the journal is indexed in SCOPUS and ERIH PLUS - European Reference Index for Humanities and Social Sciences, and since 2017 also in Emerging Sources Citation Index by Clarivate Analytics.
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