I am doing a supervised classification in ArcMap to classify land cover types in a study area in Africa. I am using RapidEye satellite imagery (Planet Labs) and they have 5 bands: blue, green, red, red edge and Near infrared.

I can classify soil and forest cover (see Classified Image) successfully but I'm unable to successfully separate out houses in the classification. I only want to classify the houses that have Iron sheet roofs (they are the small white dots circled in red on the satellite image). However, these houses are being misclassified as soil and road pixels (see classified image). Ideally, I want to classify 4 land cover types: soil, forest, house, and paved road.

Satellite Image with houses (in red circle)

enter image description here

Can anyone suggest a better way to separate out the spectra from human-made surfaces such as the iron sheet house roofs and paved roads? I would prefer to stick to supervised classification if possible, but am willing to try other classification methods. I tried object-based classification (segmentation) in ArcMap I couldn't get the 16 bit RapidEye image to classify properly in ArcMap and it kept showing a black square. And the unsupervised classification methods (e.g. ISO cluster and Class probability) had terrible results in ArcMap.

  • Is QGIS an option? Or ENVI? Or ERDAS Imagine? It looks like you've forced ArcGIS to go as far as it will go, ENVI or ERDAS usually produce better results (in demonstrations, I've not used them myself) QGIS has a classification plugin, see gis.stackexchange.com/questions/228684/… which might be worth at least looking at. – Michael Stimson Dec 11 '18 at 7:04
  • I would recommend using object oriented image analysis rather than pixel based. ArcGIS has several image segmentation and classification approaches available. – Aaron Jan 14 at 18:03

A quick search on Google threw up this blog, they describe their steps using ENVI. This paper discusses the spectral properties they used to separate out man made from natural.

I think you need to play around with these options.

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