I am an undergraduate student working with a very large data set (to me), and who has NO experience with R, but is fairly comfortable with ArcMap.
I have about 60GB of 8band 1m satellite imagery of African rainforest, and a shapefile of about 90 GPS points taken by park rangers on the ground. The GPS shapefile contains a column with the land cover type at each point. There are 9 different land-cover types, which are not easily distinguished by eye from the imagery. My goal is to create a map showing the distribution of these cover types over the entire scene.
Can anyone provide me with near-step-by-step instructions on how to use Duke's Marine Geospatial Ecology Tools (MGET), or potentially any other free Arc add-in, to run a Random Forest classification? Note that I have absolutely no idea how to use R, which seems to be the most-referenced way to process this information.
I know that running a simpler form of classification would be simpler, but since this is not just a typical undergraduate arbitrary product for an assignment (It will actually end up being used by several NGOs working with wildlife in the area), I would like to produce the most accurate product that I can, and a Random Forest model seems to be the most appropriate for this goal.
Any help would be appreciated!
أكثر...
I have about 60GB of 8band 1m satellite imagery of African rainforest, and a shapefile of about 90 GPS points taken by park rangers on the ground. The GPS shapefile contains a column with the land cover type at each point. There are 9 different land-cover types, which are not easily distinguished by eye from the imagery. My goal is to create a map showing the distribution of these cover types over the entire scene.
Can anyone provide me with near-step-by-step instructions on how to use Duke's Marine Geospatial Ecology Tools (MGET), or potentially any other free Arc add-in, to run a Random Forest classification? Note that I have absolutely no idea how to use R, which seems to be the most-referenced way to process this information.
I know that running a simpler form of classification would be simpler, but since this is not just a typical undergraduate arbitrary product for an assignment (It will actually end up being used by several NGOs working with wildlife in the area), I would like to produce the most accurate product that I can, and a Random Forest model seems to be the most appropriate for this goal.
Any help would be appreciated!
أكثر...