Table of contents
Chapter 1 Getting Started GIS Theory and ArcGIS Pro Basics
Chapter 2 Basics ArcGIS Data Management and Conversion
Chapter 3 Data Editing and Query, Topology Check
Chapter 4 Cartography 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
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 course organizes 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. ArcGIS Pro installation and configuration
3. Introduction of new features of ArcGIS Pro 3.0
4. The main components of the ArcGIS Pro user interface (ribbon, 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. Inquiry and output of spatial information
8. How to save the document
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. Conversion between ArcGIS and external data
6. Theories, methods and steps of geospatial data database construction
7. Map projection basics
8. Common map projection and projection transformation operations in my country
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 method
3. Introduction to multiple georeferencing methods
4. Geometry acquisition of spatial data
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 settings for spatial data display
3. Make 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 making
Chapter 5 Spatial Analysis ArcGIS Vector Spatial Analysis and Application
1. Introduction to ArcGIS Pro geoprocessing tools
Run tools in the Geoprocessing pane
Run tools in ModelBuilder
Run the tool 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; application, tool, model, and model process environment settings
3. Basic processing of raster data (stitching, cropping, resampling, NoData processing, data conversion, etc.) and cases
4. Distance Mapping
5. Density Mapping
6. Raster interpolation
7. Statistical analysis
8. Reclassify
9. Raster Computing
10. Calculation and application of raster data model
Chapter 7 Image Remote Sensing Image Processing
1. UAV data processing
Data loading Puncture point Correction Accuracy evaluation Product generation
2. Mosaic dataset
Create mosaic dataset Add raster to mosaic dataset
Remove black edges Image color uniformity
Synchronization of mosaic datasets Mosaic dataset restoration
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 source
2D and 3D data BIM data Tilt photogrammetry data
3. Three-dimensional data analysis
DEM 3D production 3D format conversion 3D symbol design
Quickly create 3D models Polyhedron editing Visual analysis
4. Digital surface model and its application
Create raster surfaces
Basic analysis method based on grid DEM Slope and aspect calculation
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
How to set the spatial range Set the number of rows and columns
Rotation angle Output feature class
2. Spatial Autocorrelation Analysis "Analyze Mode" Tool
Average Nearest Neighbor
High/Low Clustering: The 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 Count events within the aggregation plane
Capture nearby events to create weighted points Analyze scope
Hot Spot Analysis: Gi* statistical results will be automatically corrected for multiple testing and spatial dependence using the False Discovery Rate (FDR) correction method.
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 the dataset using the Fill Missing Values tool
Three types of regression models: continuous (Gaussian), binary (logistic), and count (Poisson)
Selection of neighborhood (bandwidth) Local weighting scheme Prediction
Coefficient grid Interpret messages and diagnostics Output graphs
Multiple scale geographically weighted regression (MGWR)
Chapter 10 GIS-Based Geospatial Modeling
1. Geospatial modeling ideas
2. GIS-based geospatial modeling
Analysis of model connotation
GIS-based model realization
Using Modelbuilder to build calculation models
3. Modelbuilder modeling environment introduction
Build and save the model in Model Builder
Set model parameters
Set model tool properties
Documentation tool
4. NC data batch processing modeling training
5. Implement the Suitability Modeling Workflow
6. Create a suitability model:
Determine and prepare conditional data
Convert the value of each condition into a generic 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. Introduction to Python and environment configuration and installation;
2.Python basics
3. Introduction to ArcPy import and function
Chart module (arcpy.charts)
Data access module (arcpy.da)
Geocoding module (arcpy.geocoding)
Image analysis module (arcpy.ia)
Drawing 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. Element geometry object operation
6. Raster data operation
7. Cartography
8. Tool creation in the Python toolbox
Special Application Analysis
Hydrological analysis
suitability evaluation
spatio-temporal analysis
