Raster To Polygons
Overview
Converts raster data to polygon features by merging connected cells with the same value into polygons. It is best suited to categorical rasters, such as land-use or vegetation-type data.
Use Cases
- Land-use and land-cover vectorization: Convert classified data such as GlobeLand30 or ESA CCI to vector polygons.
- Extract remote sensing classification results: Extract forest, farmland, urban, or other regions from supervised classification results.
- Hydrology analysis: Convert flow-direction or watershed rasters to polygon boundaries where applicable.
- Administrative region vectorization: Convert raster-based administrative or population-zone data to polygon features.
Parameters
Basic settings (required)
| Parameter | Description | Data type |
|---|---|---|
| Input raster file | Raster to convert to polygon features. | Raster |
| Field for raster values | Field used to store converted raster cell values. | Field |
| Use 8-connectedness | Connectivity rule used when deciding which cells belong to the same polygon. 4-connectedness uses only the four direct neighbors: up, down, left, and right. 8-connectedness also includes the four diagonal neighbors. | Boolean |
| Output path | Folder where the result file is saved. | Folder path |
| Output file name | Name of the output vector file. | Vector |
Steps
- Start the tool: Open Geoprocessing Toolbox > Data Management Tools > Data Conversion > Raster To Vector, then start Raster To Polygons.
- Set parameters: In Basic settings, select the input raster and configure the value field and connectivity rule. The tool uses 8-connectedness by default.
- Set advanced options if needed: Configure output format, output fields, or reprojection options if they are available in the interface.
- Run and monitor the task: Click Run. You can view progress, runtime, and status in Task List.
- Handle failures if needed: If the run fails, review the error message and use Edit to return to the tool pane.
Notes
- Data volume: High-resolution rasters, such as 1 m rasters, may create many small polygons and reduce performance.
- Boundary simplification: If simplification is applied, geometric precision may decrease. This is suitable for generalized analysis but not precise mapping.
- Categorical rasters are preferred: Integer rasters, such as land-use classes, are the best input. Floating-point rasters, such as DEMs, may create too many fragmented polygons.
- Topology checks: Converted polygons may contain overlaps or gaps. Run topology checks and repair tools when needed.