styfler

Well, its funny. After almost lost all my hair, I figure that when I got the landsat 8 images on the "wrong" projection (wgs_84_zone_23N) that somehow messed my data frame extent. Since I like to work with the data frame "clipped" to the region of my interest by a polygon,and yesterday I shut of this option, today I clipped the data frame again and the shape opened "on the fly" in the right extent..... Finally. Thanks!!

Thank you very much guys Now I'm having problems to import the results of ecognition on Arcmap. I exported the pansharped landsat8 rgb composition from arcmap to Ecognition. I made a really nice map, but when I import the shap result to arcmap, its came with a "inconstant extent error". I've tried some projection tools, change the project at arcatalog, but the classified map doesn't show neither on the right extent or on the fly.

Hi guys, hows doing? A old problem that I have with both landsat 5 (bands 543) and landsat8 (654) in classification of urban areas is a confusion of the classification (maximum likehood classifcation) about some low albedo features, mainly shallow water and asphalt. I tryed a thousand times, with the most accurate samples I could do (fusion image with pancromatich), both at envi and arcmap. The only software I could obtain a better result was Ecognation with segmentation, but I only have the trial version, so I can't export the file. How can I minimize this problem to have a better classification at least of this features: urban, soil, grass, forest and water. The classifications are failing at the edges shallow areas of some huge urban lakes that I'm trying to study. Thanks

Hello guys, I'm a brazilian student and I'm learning to use spatial data for my researchs in urban ecology/landscape ecology/ urban forestry areas. Looks like this forum will be very usefull to me and I wish to learn a lot of stuff and share them too. Thanks