LandCoverClassify

Classifies aerial land imagery data into different types of surfaces: Water, Tree, Low Vegetation, Barren, Impervious-Other, and Impervious-Road. The classified data is returned as a new raster layer.

This function is part of the machine learning toolset and requires large additional binary files for its operation. If these binaries aren’t detected in the SDK’s working directory at runtime, Global Mapper will attempt to automatically download them. You may receive a pop-up prompt to permit the download.

Land cover classification can benefit from hardware acceleration if you have a CUDA compatible GPU and choose to enable the aUseCUDADevice boolean parameter.

Parameters:

• aLayerList ([GM_LayerHandle_t32]) – List of imagery layers to use for land cover classification (if empty, all loaded layers will be used)

• aWorldBounds (GM_Rectangle_t) – Bounds to run land cover classification within (if None, whole extent of input layers will be used)

• aLandCoverType (GM_LandCoverType_t8) – Type of terrain data being classified, based on its general climate and environment

• aUseCUDADevice (boolean) – If true, will attempt to run on CUDA GPU if available, but will fall back to CPU if not. If false, will run on CPU

• aCustomModelName (string) – (Optional) Filename of a custom model created by previous experimentation to use for this inference. Empty string will use built-in model

• aParentWnd (HWND) – Handle to parent window to attach the inference progress dialog to

• aReserved (uint32) – Reserved for future use; defaults to 0

Returns:

Error Code

Return type:

GM_Error_t32

Returns:

Handle to a new raster layer colored to show classifications of identified land areas

Return type:

GM_LayerHandle_t32