Introduction to ArcGIS Pro basics, cartography, spatial analysis, image analysis, 3D modeling, spatial statistical analysis and modeling, python integration, and case application to improve the scientific research ability of the whole process

Table of contents

Chapter 1 Getting Started GIS Theory and ArcGIS Pro Basics

Chapter 2 Basic ArcGIS Data Management and Transformation

Chapter 3 Data Editing and Query, Topology Check

Chapter 4 Mapping Map Symbols and Layout Design

Chapter 5 Spatial Analysis ArcGIS Vector Spatial Analysis and Application

Chapter 6 ArcGIS Grid Spatial Analysis and Application

Chapter 7 Image Remote Sensing Image Processing

Chapter 8 Three-Dimensional Part Three-Dimensional Analysis

Chapter 9 Advanced Spatial Statistical Analysis and Spatial Relationship Modeling Analysis

Chapter 10 GIS-based Geospatial Modeling

Chapter 11 Introduction to Python Scripting in ArcGIS Pro

Special Application Analysis

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GIS is the use of electronic computers and their external equipment to collect, store, analyze and describe the entire or part of the earth's surface and spatial information systems. Simply put, it combines geospatial information and some attribute information related to the geographic information in a certain region to achieve comprehensive management of geographic and attribute information. The research object of GIS is the whole geographic space, and geographic information is related to geographic location, so the development of GIS has been paid attention to worldwide. In recent years, GIS has also received much attention in our country, and has been used in urban and rural planning, disaster monitoring, resource inventory, land survey, environmental management, urban pipe network, combat command, macro decision-making, urban public services, transportation, navigation, e-government and other fields. been widely applied. So how to deeply understand the principles of GIS? How to efficiently process multi-source spatial data? How to establish practical GIS technology application solutions for specific fields? This course will provide a set of methods and cases based on ArcGIS Pro spatial data processing.

Compared with ArcGIS, ArcGIS Pro, as ESRI's GIS product for the new era, inherits the powerful data management, mapping, and spatial analysis capabilities of traditional desktop software (ArcMap) on the original ArcGIS platform, and also has its unique Some special functions, such as 2D and 3D fusion, big data, vector slice production and release, task workflow, super-forced map, space-time cube, etc. At the same time, it integrates ArcMap, ArcSence, and ArcGlobe to realize 3D integration and synchronization.

This tutorial will organize your GIS work into projects using ArcGIS Pro, which you can use to map 2D and 3D data. With ArcGIS Pro, you can create and edit a variety of features, while also integrating data from multiple sources such as text, vector, raster, lidar, multidimensional data into your project. This course will teach you to use ArcGIS Pro to analyze data, manage GIS data, and build tools for automating work or solving complex problems. You can use analysis and geoprocessing features in ArcGIS Pro to answer many spatial questions and perform spatial analysis. With spatial analysis tools such as vector data analysis, raster data analysis, 3D analysis, hydrological analysis, etc., you can solve complex location-oriented problems, explore and understand your data from a geographic perspective, identify relationships, detect and quantify patterns, evaluate trends, and make predictions and decisions. Python can be used to automate geoprocessing tools and provides the ability to create your own geoprocessing tools, either as script tools or as Python toolbox tools. This course will teach you to save time on repetitive tasks, minimize errors, and efficiently iterate on analyzes by creating models or scripts to transform into custom tools.

You will learn to use the above principles and technical methods in specific practical cases to improve the application ability and efficiency of GIS technology.

Chapter 1 Getting Started GIS Theory and ArcGIS Pro Basics

1. Introduction to basic principles of GIS and commonly used software
2. Installation and configuration of ArcGIS Pro
3. Introduction to new features of ArcGIS Pro 3.0
4. The main components of the ArcGIS Pro user interface (functional areas, views, and panes) and their interactions.
5. ArcGIS Pro project creation: including maps, scenes, layouts and other items
6. Browsing and viewing of spatial information
7. Query and output of spatial information
8. Document saving method

Chapter 2 Basic ArcGIS Data Management and Transformation

1. ArcGIS data management
2. Data type and conversion
3. Data structure and conversion
4. Data format and conversion 5.
ArcGIS and external data conversion
6. The theory, method and steps of geospatial data database construction
7. Map projection basis
8 .Common map projection and projection transformation operations in China
9. Transformation of Beijing54, Xian80, WGS84, CGCS2000 different geographic coordinate systems

Chapter 3 Data Editing and Query, Topology Check

1. Introduction to common data sources
2. Spatial data collection methods
3. Introduction to multiple georeferencing methods
4. Spatial data geometric collection
5. Spatial data attribute collection
6. Data inspection and topology processing
7. Data processing: data cutting, data splicing, data extraction

Chapter 4 Mapping Map Symbols and Layout Design

1. Introduction to GIS mapping
2. Symbol setting for spatial data display
3. Making professional map symbols
4. Labeling and annotation
5. Thematic map layout design and finishing
6. Thematic map drawing skills and map output
7. Research area map production

Chapter 5 Spatial Analysis ArcGIS Vector Spatial Analysis and Application

1. Introduction to ArcGIS Pro geoprocessing tools
 Running tools in the "Geoprocessing" pane
 Running tools in the model builder
 Running tools in the Python window
2. GIS spatial analysis and functions
3. Vector processing tools and cases
4. Basic processing of vector data (stitching, cropping, fusion, etc.) and cases
5. Vector space overlay analysis and application
6. Proximity analysis and application

Chapter 6 ArcGIS Grid Spatial Analysis and Application

1. Introduction to spatial analysis of raster data
2. Geoprocessing environment settings; environment settings for applications, tools, models, and model processes
3. Basic processing of raster data (stitching, clipping, resampling, NoData processing, data conversion, etc.) and Case
4. Distance mapping
5. Density mapping
6. Raster interpolation
7. Statistical analysis
8. Reclassification
9. Raster calculation
10. Raster data model calculation and application

Chapter 7 Image Remote Sensing Image Processing

1. UAV data processing
 Data loading  Prick point  Correction  Accuracy evaluation  Product generation
2. Mosaic dataset
 Create mosaic dataset
 Add raster to mosaic dataset
 Remove black edges
 Image uniform color
 Synchronous mosaic Dataset
 Mosaic dataset repair
 NDVI calculation
3. Remote sensing image preprocessing and information extraction
 Image viewing  Image enhancement  Band combination  Orthorectification  Image fusion  Vegetation index extraction  Using raster function chain
4. Remote sensing image classification
 Create classification samples
 Image segmentation
 Training sample management
 Select classifier
 Output classification results
 Merge classes
 Reclassify
 Accuracy evaluation

Chapter 8 Three-Dimensional Part Three-Dimensional Analysis

1. 3D production and animation demonstration
2. 3D data sources
 2D and 3D data  BIM data  tilted photogrammetry data
3. 3D data analysis
 DEM 3D production  3D format conversion  3D symbol design
 Rapid creation of 3D models  Polyhedron editing Visual analysis
4. Digital surface model and its application
 Create grid surface
 Basic analysis method based on grid DEM
 Calculation of slope and aspect
 Create curvature surface
 Hydrological analysis
 Visibility calculation
 Hillshade calculation
5. Use of Lidar data
 Create LAS dataset
 Generate DEM, DSM
 Extract trees

Chapter 9 Advanced Spatial Statistical Analysis and Spatial Relationship Modeling Analysis

1. Fishnet analysis
 Method of setting spatial extent
 Setting number of rows and columns
 Rotation angle
 Output feature class

2. Spatial Autocorrelation Analysis "Analyze Mode" tool
 Average Nearest Neighbor
 High/Low Clustering: Getis-Ord General G statistic measures the degree of clustering of high or low values
 Global Moran's I statistic measures spatial autocorrelation

Hot spot analysis

 Optimized Hotspot Analysis
 Initial Data Evaluation
 Event Aggregation
 Counting Events within Aggregate Surfaces  Capture
Nearby Events to Create Weighted Points Test and spatial dependencies are automatically corrected. Output result: The output features will reflect the aggregated weighted features (fishnet polygon or hexagonal polygon cells or the aggregated polygons or weighted points provided for the Incident Point Aggregate Polygon parameter). Each feature has a z-score, p-value, and Gi Bin result, as well as the number of neighbors each feature included in the calculation.

3. Spatial relationship modeling
 Ordinary least squares (OLS)

 Geographically Weighted Regression (GWR)
 Complete datasets using the Fill Missing Values tool
 Three types of regression models: Continuous (Gaussian), Binary (Logistic) and Count (Poisson)
 Select Neighborhood (Bandwidth)
 Local weighting schemes
 Forecasting
 Raster of coefficients
 Interpreting messages and diagnostics
 Output graphs
 Multi-scale geographically weighted regression (MGWR)

Chapter 10 GIS-based Geospatial Modeling

1. Geospatial modeling ideas

2. GIS-based geospatial modeling
 Model connotation analysis
 GIS-based model realization
 Using Modelbuilder to construct calculation models

3. Modelbuilder modeling environment introduction

 Build and save the model in Model Builder
 Set model parameters
 Set model tool properties
 Document tools

4. NC data batch modeling training
5. Implement suitability modeling workflow

6. Create a suitability model
 Identify and prepare condition data
 Convert the value of each condition into a general suitability scale
 Weight conditions relative to each other and combine them to create a suitability map
 Find siting areas or protected areas
 Share and run in server

Chapter 11 Introduction to Python Scripting in ArcGIS Pro

1.Python introduction and environment configuration and installation;
2.Python basics
3.ArcPy import and function introduction
Chart module (arcpy.charts)
Data access module (arcpy.da)
Geocoding module (arcpy.geocoding)
Image analysis Modules (arcpy.ia)
Cartography module (arcpy.mp)
Metadata module (arcpy.metadata)
Network Analyst module (arcpy.nax and arcpy.na)
Sharing module (arcpy.sharing)
Spatial Analyst module (arcpy .sa)
Workflow Manager (Classic) module (arcpy.wmx)

4. Access and manage spatial data
5. Feature geometry object manipulation
6. Raster data manipulation
7. Cartography
8. Tool creation in the Python toolbox