cuggisrs / arc2qgis

This Manual is migrating to https://arc2qgis.github.io

For each ArcGIS Dekstop tool there is a replacement

Community Documentation of tools in QGIS, GRASS, GDAL, GEOS, Python and any other Open Source tools to replace ArcGIS tools.

No Set Rules as of yet, please Document to the best of your abilities.
These are the most freqeuntly used tools and toolboxes I can think of, but if you have any others you would like to add, feel free.

This Repository is meant for documentation, but if you have any scripts or tools you would like to publish here, feel free.

A sample/howto guide can be found in the sample.html file.

Basic GIS Operations

• 1. Adding Data From Different Sources
• 2. Table Operations
• 3. Select By Location
• 4. Select By Expression
• 5. Select By Expression - Advanced
• 6. Editing Features
• 7. Symbology
• 8. Symbology - Advanced
• 9. Plugins
• 10. Labeling Features
• 11. Exporting Data
• 12. Introduction to The Processing Toolbox

Analysis Toolbox

1. Extract:

• 1.1. Clip
• 1.2. Select
• 1.3. Split
• 1.4. Split By Attributes
• 1.5. Tables Select

2. Overlay

• 2.1. Erase
• 2.2. Identity
• 2.3. Intersect
• 2.4. Spatial Join
• 2.5. Symmetrical Difference
• 2.6. Union
• 2.7. Update

3. Proximity

• 3.1. Buffer
• 3.2. Create Thiessen Polygons
• 3.3. Generate Near Table
• 3.4. Graphic Buffer
• 3.5. Multiple Ring Buffer
• 3.6. Near
• 3.7. Point Distance
• 3.8. Polygon Neighbors

4. Statistics

• 4.1. Frequency
• 4.2. Summary Statistics
• 4.3. Tabulate Intersection

Spatial Analyst Toolbox

1. Conditional:

• 1.1. Con
• 1.2. Pick
• 1.3. Set Null

2. Density:

• 2.1. Kernel Density
• 2.2. Line Density
• 2.3. Point Density

3. Distance:

• 3.1. Corridor
• 3.2. Cost Allocation
• 3.3. Cost Back Link
• 3.4. Cost Connectivity
• 3.5. Cost Distance
• 3.6. Cost Path
• 3.7. Cost Path As Polyline
• 3.8. Euclidean Allocation
• 3.9. Euclidean Direction
• 3.10. Euclidean Distance
• 3.11. Path Distance
• 3.12. Path Distance Allocation
• 3.13. Path Distance Back Link

4. Extraction

• 4.1. Extract by Attributes
• 4.2. Extract by Circle
• 4.3. Extract by Mask
• 4.4. Extract by Points
• 4.5. Extract by Polygon
• 4.6. Extract by Rectangle
• 4.7. Extract Multi Values to Points
• 4.8. Extract Values to Points
• 4.9. Sample

5. Generalization

• 5.1. Aggregate
• 5.2. Boundary Clean
• 5.3. Expand
• 5.4. Majority Filter
• 5.5. Nibble
• 5.6. Region Group
• 5.7. Shrink
• 5.8. Thin

6. Groundwater
7. Hydrology
8. Interpolation

• 8.1. IDW (Inverse Distance Weight)
• 8.2. Kriging
• 8.3. Natural Neighbor
• 8.4. Spline
• 8.5. Spline with Barriers
• 8.6. Topo to Raster
• 8.7. Topo to Raster by File
• 8.8. Trend

9. Local

• 9.1. Cell Statistics
• 9.2. Combine
• 9.3. Equal To Frequency
• 9.4. Greater Than Frequency
• 9.5. Highest Position
• 9.6. Less Than Frequency
• 9.7. Lowest Position
• 9.8. Popularity
• 9.9. Rank

10. Map Algebra

• 10.1. Raster Calculator

11. Math (General)
12. Math Bitwise
13. Math Logical
14. Math Trigonometric
15. Multivariate

• 15.1. Band Collection Statistics
• 15.2. Class Probability
• 15.3. Create Signatures
• 15.4. Dendrogram
• 15.5. Edit Signatures
• 15.6. Iso Cluster
• 15.7. Iso Cluster Unsupervised Classification
• 15.8. Maximum Likelihood Classification
• 15.9. Principal Components

16. Neighborhood

• 16.1. Block Statistics
• 16.2. Filter
• 16.3. Focal Flow
• 16.4. Focal Statistics
• 16.5. Line Statistics
• 16.6. Point Statistics

17. Overlay

• 17.1. Fuzzy Membership
• 17.2. Fuzzy Overlay
• 17.3. Locate Regions
• 17.4. Weighted Overlay
• 17.5. Weighted Sum

18. Raster Creation

• 18.1. Create Constant Raster
• 18.2. Create Normal Raster
• 18.3. Create Random Raster

19. Reclass

• 19.1. Lookup
• 19.2. Reclass by ASCII File
• 19.3. Reclass by Table
• 19.4. Reclassify
• 19.5. Rescale by Function
• 19.6. Slice

20. Solar Radiation
21. Segmentation and Classification

• 21.1. Classify Raster
• 21.2. Compute Confusion Matrix
• 21.3. Compute Segment Attributes
• 21.4. Create Accuracy Assessment Points
• 21.5. Deep Learning Model To Ecd
• 21.6. Export Training Data
• 21.7. Generate Training Samples From Seed Points
• 21.8. Segment Mean Shift
• 21.9. Train Iso Cluster Classifier
• 21.10. Train Maximum Likelihood Classifier
• 21.11. Train Random Trees Classifier
• 21.12. Train Support Vector Machine Classifier
• 21.13. Update Accuracy Assessment Points

22. Surface

• 22.1. Aspect
• 22.2. Contour
• 22.3. Contour List
• 22.4. Contour with Barriers
• 22.5. Curvature
• 22.6. Cut Fill
• 22.7. Hillshade
• 22.8. Observer Points
• 22.9. Slope
• 22.10. Viewshed
• 22.11. Viewshed 2
• 22.12. Visibility

23. Zonal

• 23.1. Tabulate Area
• 23.2. Zonal Fill
• 23.3. Zonal Geometry
• 23.4. Zonal Geometry As Table
• 23.5. Zonal Histogram
• 23.6. Zonal Statistics
• 23.7. Zonal Statistics as Table

Network Analyst Toolbox

1. Analysis:

• 1.1. Add Field To Analysis Layer
• 1.2. Add Locations
• 1.3. Calculate Locations
• 1.4. Copy Traversed Source Features
• 1.5. Directions
• 1.6. Make Closest Facility Layer
• 1.7. Make Location-Allocation Layer
• 1.8. Make OD Cost Matrix Layer
• 1.9. Make Route Layer
• 1.10. Make Service Area Layer
• 1.11. Make Vehicle Routing Problem Layer
• 1.12. Solve
• 1.13. Update Analysis Layer Attribute Parameter

2. Network Dataset:

• 2.1. Build Network
• 2.2. Dissolve Network
• 2.3. Create Network Dataset From Template
• 2.4. Create Template From Network Dataset
• 2.5. Make Network Dataset Layer

3. Server

• 3.1. Find Closest Facilities
• 3.2. Find Routes
• 3.3. Generate Origin Destination Cost Matrix
• 3.4. Generate Service Areas
• 3.5. Solve Location-Allocation
• 3.6. Solve Vehicle Routing Problem
• 3.7. Update Traffic Data
• 3.8. Update Traffic Incidents

4. Turn Feature Class

• 4.1. Create Turn Feature Class
• 4.2. Increase Maximum Edges
• 4.3. Populate Alternate ID Fields
• 4.4. Turn Table To Turn Feature Class
• 4.5. Update By Alternate ID Fields
• 4.6. Update By Geometry

Geocoding Toolbox

Anything other than mmqgis?

• 1. Create Address Locator:
• 2. Create Composite Address Locator
• 3. Geocode Addresses
• 4. Rebuild Address Locator
• 5. Rematch Addresses
• 6. Reverse Geocode
• 7. Standardize Addresses

Spatial Statistics Toolbox

1. Analyzing Patterns:

• 1.1. Average Nearest Neighbor
• 1.2. High/Low Clustering
• 1.3. Incremental Spatial Autocorrelation
• 1.4. Multi-Distance Spatial Cluster Analysis (Ripley's k-function)
• 1.5. Spatial Autocorrelation

2. Mapping Clusters

• 2.1. Cluster and Outlier Analysis
• 2.2. Grouping Analysis
• 2.3. Hot Spot Analysis
• 2.4. Optimized Hot Spot Analysis
• 2.5. Optimized Outlier Analysis
• 2.6. Similarity Search

3. Measuring Geographic Distributions

• 3.1. Central Feature
• 3.2. Directional Distribution
• 3.3. Linear Directional Mean
• 3.4. Mean Center
• 3.5. Median Center
• 3.6. Standard Distance

4. Modeling Spatial Relationships

• 4.1. Exploratory Regression
• 4.2. Generate Network Spatial Weights
• 4.3. Generate Spatial Weights Matrix
• 4.4. Geographically Weighted Regression
• 4.5. Ordinary Least Squares

5. Utilities

• 5.1. Calculate Distance Band from Neighbor Count
• 5.2. Collect Events
• 5.3. Convert Spatial Weights Matrix To Table
• 5.4. Export Feature Attributes To ASCII

Also Needed: Conversion tools, Data Management Tools