地理空间分析方法在土地管理和地籍中的应用

T. Myslyva, Bronislava Sheluto, Olesya Kutsaeva, Svetlana Naskova
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引用次数: 3

摘要

本文讨论了利用地理空间分析方法实现土地监测数据可视化和主要农化土壤指标空间分布建模的可能性。研究是在RUP“Uchkhoz BGSHA”(白俄罗斯共和国,莫吉廖夫地区,戈列茨基地区)的土地使用范围内进行的。调查领土总面积为3187.0公顷。利用ArcGIS软件的Geostatistical Analyst模块对土壤腐殖质、流动磷、流动钾和pHKCl的空间分布进行了地理空间分析。采用半变异函数作为研究农化指标空间分布结构的主要工具。确定指数函数为最佳变异函数模型,圆的类型为标准,扇区的类型和数量为4,位移为450,滞后为200 m。插值精度由平均误差(ME)、均方误差(RMSE)和标准误差(RMSS)确定。采用通用克里格法对农化指标的空间分布进行预测和可视化。使用栅格计算器工具、主成分分析和最大似然分类的功能进行多变量分析。通过GIS环境下的多因素分析,寻找和确定具有最优农化指标的站点区域。使用实用程序“区域统计”计算工作包范围内每个电路的面积。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Use of Geospatial Analysis Methods in Land Management and Cadastre
The possibilities of using the geospatial analysis methods for visualizing land monitoring data and modelling the spatial distribution of the main agrochemical soil indicators are discussed in the article. The research was conducted within the limits of land use of RUP “Uchkhoz BGSHA” (Republic of Belarus, Mogilev region, Goretsky district). The total area of the surveyed territory was 3187.0 hectares. The geospatial analysis of the spatial distribution of humus, mobile phosphorus, mobile potassium and pHKCl was carried out using the Geostatistical Analyst module of the ArcGIS software. Semivariograms were used as the main tool for studying the structure of the spatial distribution of agrochemical indicators. The exponential function was identified as the best variogram model, the type of the circle was standard, the type and the number of sectors was 4 with a displacement of 450, and the lag was 200 meters. The interpolation accuracy was determined from the mean error (ME), mean square error (RMSE) and standard error (RMSS). The universal kriging method was used to perform the forecast and visualize the spatial distribution of agrochemical indicators. The multivariate analysis was performed using the functionality of the Raster Calculator tool, Principal Component analysis and Maximum Likelihood Classification. The search and determination of areas of sites with the most optimal agrochemical indicators were carried out by the multifactor analysis in the GIS environment. Calculation of the area of each circuit within the limits of working parcels was carried out using the utility "Zone Statistics".
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