"R Language + Remote Sensing" Comprehensive Evaluation Method of Water Environment

【目标】：
1、掌握RBasic application of language and analysis methods of water environment data
2、Master the preprocessing method of water environment remote sensing data
3、Master waterline extraction——Mixed method of water body index and threshold value（遥感）
4、Master water depth extraction——Multiple regression analysis method（R语言+遥感）
5、Master the water temperature for extraction——支持向量机方法（R语言+遥感）
6、Master water extraction——Neural network analysis methods（R语言+遥感）
7、Master the visualization mapping method of water environment remote sensing information extraction results（R语言）

【专家】：张博士,Front-line researchers from key universities and research institutes,长期从事机器学习、Remote sensing technology and application research,主持多项国家级科研项目,编写著作3部,The first author publishes a scientific paper20余篇.Multi-platform for remote sensing technology at home and abroad、Status of multi-sensor applications,As well as a deep understanding of the core technologies involved,精通ENVI、R语言、Mathlab和Unscrambler等分析工具,Has rich scientific research and water chlorophyll、悬浮物、Sediment and yellow substance extraction experience.

>>> “R 语 言 + 遥 感” 的 水 环 境 综 合 评 价 方 法 实 践 技 术 应 用

专题一 R语言概述
1.1 R语言特点（R语言）
1.2 安装R（R语言）
1.3 安装RStudio（R语言）
（1）下载地址
（2）安装步骤
（3）软件配置
1.4 第一个程序Hello world（R语言）
（1）Hello world
（2）R语言基础
（3）RLinguistic Numerical Computing
（4）R语言常用函数
（5）RLanguage data entry method

1.5 case formRBasic learning of language grammar（R语言）
（1）Read water environment data sources
（2）设置路径
（3）使用read.csv读取数据
（4）Transform based on data type
（5）Basic analysis of water environment data
（6）Advanced analysis of water environment data
（7）Verify correct data characteristics based on decision tree prediction
（8）Validation of prediction results based on confusion matrix

专题二 Remote sensing data preprocessing 
2.1 Remote Sensing Water Environment Pollution Evaluation Theory（遥感）
（1）Principles of remote sensing of water environment
（2）Water environment remote sensing modeling method
2.2 Remote sensing data acquisition methods（遥感）
2.3 Radiometric Correction Methods for Remote Sensing Data（遥感）
（1）Load and display data
（2）辐射定标
（3）大气校正

2.4 High-definition fusion method of remote sensing data（遥感）
（1）融合的原理
（2）Gram-SchmidtFusion implementation 

专题三 Waterline extraction——Mixed method of water body index and threshold value（遥感）
3.1 水体指数计算
（1）加载数据
（2）Calculate the water body index
3.2 The threshold method determines the waterline
（1）Creation of a region of interest
（2）The background pixels are set to0
（3）阈值的实现
（4）Waterline extraction

3.3 Crop lake data  

专题四 Deep water extraction——Multiple regression analysis method（R语言+遥感）
4.1 Apply model theory for solar radiation bands
4.2 How to obtain water depth data
4.3 加载影像
4.4 Measured water data
4.5 假设条件
4.6 数据整理
4.7 将数据导入R语言
4.8 采用RLanguage correlation test

（1）The principle of correlation test
（2）R语言语法
（3）进行相关性分析
（4）绘制相关性图
（5）建立多元线性回归模型
（6）Multiple linear regression model of water depth
4.9 digital mapping
4.10 精度验证
（1）Open the resulting image
（2）Open the Accuracy Evaluation Template
（3）Check the measured water depth
（4）Analyze extraction accuracy
 

专题五 Water temperature extraction——支持向量机方法（R语言+遥感）
5.1 Principles of water surface temperature inversion
5.2 Landsat8Satellite thermal infrared band
5.3 Heat radiation conduction equation

5.4 The extraction method of surface heat information is realized
（1）打开数据
（2）Image radiometric calibration
（3）地表比辐射率计算
（4）Calculation of black body radiance and surface temperature
（5）Calculated surface temperature
（6）图像裁剪
（7）Color mapping
（8）Production of temperature profiles
（9）Collect temperature values ​​for precise geographic locations
5.5 water temperature forecastR语言实现
（1）技术背景
（2）导入数据
（3）Data preview and inspection
（4）Data classification is done using support vector machines
（5）The water temperature prediction is realized based on the support vector machine training model
5.6 RThe language draws a graph comparing predicted and measured values
（1）绘制基本散点图
（2）Group data based on color and dot shape
（3）Map continuous variables
（4）Handling scatter overlap
（5）添加回归模型拟合线
（6）向散点图添加边际地毯
（7）向散点图添加标签

 

专题六 Water extraction——神经网络分析（R语言+遥感）
6.1 Principles of water composition inversion
6.2 加载影像
6.3 A component content index model was established
6.4 生成12A spectral dataset of parameters
（1）LayerStacking生成数据集
（2）Extract the spectral parameters of the sampling point

6.5 A dataset of measured water surface data and spectral parameters
6.6 RLinguistic prediction of water quality component content
（1）技术背景
（2）导入数据
（3）安装nnet包
（4）Predict chlorophyll、氮、磷、钾含量
（5）Draw chlorophyll、氮、磷、Potassium neural network diagram

专题七 Visual mapping of extraction results of remote sensing information of water environment（R语言）
 7.1 叶绿素、泥沙、Suspended solids diagram
（1）Monochrome display
（2）Gradient filled display
（3）Gradient colors and different shapes fill the display diagram
7.2 Graph of the correlation coefficient between water depth and water temperature
（1）相关热力图
（2）Change graph
7.3 Visualization of water temperature data
（1）散点分布图
（2）Histogram
7.4 Visualization of water quality data
（1）Time series peaks and peaks
（2）量化波形图
（3）日历图

Discuss Q&A
根据科研或生产实际,提供数据,Brainstorm the overall implementation plan of remote sensing technology 提供若干附加材料,包括典型论文、其它软件以及学习材料
实例回顾、训练、巩固
答疑与讨论

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