I am pretty new in remote sensing and I am trying to identify/classify coniferous forest cover from single date Landsat scene. According to my preliminary web research I have these possibilities:
- convert scene to NDVI values. Using modal values of NDVI histogram, I can separate scene pixels into forested and non-forested area
- use modal value of band 2,3 and 5 (B2) to identify "forest peak" and class scene to forest/non-forest (Huang, 2008: Use of a dark object concept and support vector machines to automate forest cover change analysis). Other scenes characteristics (rocks, rivers) have to be removed using Tasseled cap brightness values
Do you know another simple approach to classify forest cover in mountainous area? I dont really want to apply maximum likelihood classification. Maybe it is better to used unsupervised classification?
I am using ERDAS, ArcGIS 10.2 and R