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所在平台: Udemy |
课程主页: https://www.udemy.com/course/rainfall-indices-for-mcdm-models-in-arcgis-how-and-why/
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**课程名称：** ArcGIS 中用于 MCDM 模型的降雨指数：如何与为何？ (Rainfall Indices for MCDM models in ArcGIS: how and Why?) **课程概述：** 本课程将提供一个完整的流程，指导您如何下载、处理降雨数据，并将日降雨量转换为月降雨量。您将逐步学习 10 种重要的降雨指数的计算方法，并掌握如何在 ArcGIS 中生成 14 种相关的地图，包括： * 长期平均年降雨量（高分辨率 0.04 x 0.04） * 降雨强度指数 (by MFI) * 降雨侵蚀力因子 (R) * 降雨偏差指数 (RDI) * 降水集中指数 (PCI) * 降雨季节性指数 (RSI) * 降雨异常指数 (RAI) * 降雨变率指数 (RVI) * 降雨变异系数 (CVR) * 正常降水量百分比指数 (PNPI) 课程还将涉及如何使用 Excel 进行数据处理，并利用 ArcGIS 制作用于多准则决策分析 (MCDM) 模型的地图。 **课程内容重点：** * **降雨强度：** 强调其对洪水、山洪、荒漠化、河岸侵蚀、沟蚀、土地退化、泥沙输移、土壤侵蚀等方面的重要影响。 * **降雨侵蚀力因子 (R)：** 基于 Wischmeier 和 Smith (1978) 的研究，由 Arnoldus (1980) 修改，根据降雨量、强度和持续时间计算，可用于单场或系列降雨。 * **降水集中指数 (PCI)：** 由 Oliver (1980) 开发，用于量化降雨的周期性变化、集中程度和侵蚀力。 * **降雨季节性指数 (RSI)：** 由 Walsh 和 Lawler (1981) 开发，衡量一年中月降雨量的变率，侧重于季节性差异而非绝对干湿。 * **降雨异常指数 (RAI)：** 由 van Rooy (1965) 开发，用于描述区域干旱和湿润的时段。 * **降雨变率指数 (RVI)：** 为降雨异常值与长期降雨数据标准差的比值。 * **变异系数 (CV)：** 衡量数据离散程度的统计指标。 * **正常降水量百分比指数 (PNPI)：** 最直接的衡量降雨量偏离长期平均值的指标，通常将长期平均降雨量设为“正常”值。 **学习成果：** 完成本课程后，您将能够熟练地使用 Excel 和 ArcMap 为 MCDM 模型准备上述各种降雨参数。
In this course, I have shown a complete process about how to download rainfall data, process data, convert daily to monthly rainfall data, step by step guide of 10 important rainfall indices and 14 maps such as long term average annual rainfall (High resolution 0.04 X 0.04), Rainfall Intensity Index (by MFI), Rainfall erosivity factor (R), Rainfall deviation Index ( RDI), Precipitation concentration Index (PCI), Rainfall seasonality Index (RSI), Rainfall Anomaly Index (RAI), Rainfall variability index (RVI), Co-efficient of the variability of Rainfall (CVR), Percent of normal precipitation index (PNPI) in excel and produced map for MCDM models using ArcGIS.The Rainfall intensity is one of the main factors due to its significant impact on the flood magnitude, flash flood, desertification, Bank erosion, Gully Erosion, land degradation, sediment flux, soil erosion, etc.The rainfall erosivity factor (R) is developed by Wischmeier and Smith (1978) and modified by Arnoldus (1980). It is determined as a function of the volume, intensity and duration of the rainfall and can be computed from a single storm, or a series of storms to include cumulative erosivity from any time periodThe Precipitation Concentration Index (PCI) was developed by Oliver (1980) to quantify the periodic variation of the rainfall, concentration of rainfall and rainfall erosivity.Rainfall seasonality Index (RSI) developed by Walsh and Lawler (1981), refers to the degree of variability in monthly rainfall through the year; it assesses seasonal contrasts in rainfall amounts rather than whether months are ‘dry' or ‘wet' in an absolute sense.Rainfall Anomaly Index (RAI) developed by van Rooy (1965) is used in depicting periods of dryness and wetness in the area.The rainfall variability index (RVI) is the ratio between anomalies over the standard deviation of the long period of rainfall data.The coefficient of variation (CV) is a statistical measure of the dispersion of data points in a data series around the mean.The Percent of normal precipitation index (PNPI) is one of the most straightforward measures of rainfall deviation from its long-term mean. ‘Normal' may be and is usually set to a long-term mean precipitation value at a location.After completing this course, you will be efficiently able to prepare these parameters for MCDM models using Excel and ArcMap.
