Running CODED using a Javascript template¶
A template for running the change detection for CODED Version 2 is found in the coded repo in the file ‘Templates/Change Detection Template’. The repo must be added on Google Earth Engine by following this link. To run CODED, you must define the parameters below, click ‘Run’, and submit the export Tasks.
Parameters for defining the study area
| Parameter | Type | Description |
|---|---|---|
| countryStudyArea | boolean | Use a country boundary for the study area |
| country | string | Name of country to use as study area |
| studyArea | string | Asset to use if countryStudyArea is false |
Note: studyArea will be ignored if countryStudyArea is true.
Parameters for filtering the input Landsat data
| Parameter | Type | Description |
|---|---|---|
| startDoy | integer | Start day of year |
| endDoy | integer | End day of year |
| startYear | integer | Start year |
| endYear | integer | End year |
Parameters for defining a forest mask
| Parameter | Type | Description |
|---|---|---|
| useMask | boolean | Whether or not to apply a forest mask |
| getMaskFromHansen | boolean | Whether or not to generate a forest mask from UMD dataset |
| forestMask | string | Path to asset if using mask and not from UMD |
| focalMode | integer | Focal mode window size to apply to mask |
| treeCoverThreshold | integer | Tree cover threshold for UMD dataset |
Note: All parameters will be ignored if useMask is false. getMaskFromHansen, focalMode, and treeCoverThreshold will be ignored if forestMask is defined.
Parameters for defining training data
| Parameter | Type | Description |
|---|---|---|
| getTrainingFromHansen | boolean | Whether or not to sample the UMD dataset for training data |
| training | string | Path to feature collection with training data |
| prepTraining | boolean | Whether or not to cache predictor data and export asset |
| forestValue | number | The number associated with forest points |
| numberOfPoints | number | Number of points to sample from UMD layer |
Note: training will be ignored if getTrainingFromHansen is true. numberOfPoints will be ignored if getTrainingFromHansen is false. The first time running CODED, prepTraining must be true.
Parameters for CODED change detection
| Parameter | Type | Description |
|---|---|---|
| minObservations | integer | # of consecutive observations to flag a change |
| chiSquareProbability | float | Threshold that controls sensitivity to change |
Parameters for exporting and saving results
| Parameter | Type | Description |
|---|---|---|
| outName | string | Output asset ID |
| numberOfChangesToExport | integer | # of disturbances to keep in output dataset |
| dateInt | boolean | Standardized dates to be 8 bit integers |
| maskProb | boolean | Mask changes that do not have a change probability of 1 |
| flipMag | boolean | Make NDFI change magnitude positive |
| exportLayers | object | Layers to export in image stack |
Note: dateInt will convert dates so that the date = date - startYear + 1.
Parameters for exporting the results in grid cells
| Parameter | Type | Description |
|---|---|---|
| exportInGrids | boolean | Whether or not to split output into multiple tasks |
| gridFolder | string | Path to folder to save gridded results |
| gridSize | number | Length of grid edge in degrees |
| gridPrefix | string | Prefix for name to output grid assets |
| gridMin | number | Index of first grid to export |
| gridMax | number | Index of last grid to export |
| predefinedGrid | string | Path to feature collection with predefined grid |
Note: All grid parameters will be ignored and the results will be exported in a single task if exportInGrids is false.