SWCalibrateR: Interactive, Web – Based Calibration of Soil Moisture Sensors

Q1 Social Sciences Journal of Open Research Software Pub Date : 2019-06-20 DOI:10.5334/JORS.254
J. Brenner, G. Genova, G. Bertoldi, G. Niedrist, S. Chiesa
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Abstract

SWCalibrateR is a user-friendly web application. We designed SWCalibrateR to interactively estimate linear regression relationships of any couple of field data series. We specifically developed this toolbox to calibrate soil moisture sensors based on gravimetric soil moisture samples. The application has been implemented using R-shiny ( https://shiny.rstudio.com/ ). As a user you can upload your own dataset and dynamically filter it by categories like soil type, land use, soil depth and others. With SWCalibrateR you can visualise the filtered data scatter and the estimated linear model. You can diagnose your model estimate and thus easily remove outliers influencing your model estimate. SWCalibrateR handles robust estimates of linear models besides ordinary least square estimation. Additional features are an interactive data table view and mapping of the data points. Funding statement: This work was supported by the farming consulting centre for fruticulture and viticulture “Sudtiroler Beratungsring” and the research grant “MONALISA” of the Provincia Autonoma di Bolzano, Alto Adige, Ripartizione Diritto allo studio, Universita e ricerca scientifica.
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SWCalibrateR:交互式的,基于网络的土壤湿度传感器校准
SWCalibrateR是一个用户友好的web应用程序。我们设计了SWCalibrateR来交互式地估计任何一对现场数据序列的线性回归关系。我们专门开发了这个工具箱来校准基于重力土壤水分样品的土壤水分传感器。该应用程序已使用R-shiny (https://shiny.rstudio.com/)实现。作为用户,你可以上传你自己的数据集,并根据土壤类型、土地利用、土壤深度等类别进行动态过滤。使用SWCalibrateR,您可以可视化过滤后的数据散点和估计的线性模型。您可以诊断模型估计,从而轻松地删除影响模型估计的异常值。SWCalibrateR处理线性模型的稳健估计,除了普通的最小二乘估计。其他功能包括交互式数据表视图和数据点的映射。资助说明:这项工作得到了水果栽培和葡萄栽培农业咨询中心“sudtiroller beratungspring”和Bolzano自治省、Alto Adige、Ripartizione Diritto allo studio、ricerca科学大学的研究补助金“MONALISA”的支持。
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来源期刊
Journal of Open Research Software
Journal of Open Research Software Social Sciences-Library and Information Sciences
CiteScore
6.50
自引率
0.00%
发文量
7
审稿时长
21 weeks
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