![]() The multiband imagery of the Louisville neighborhood currently uses the natural color band combination to display the imagery the way the human eye would see it. Next, you'll look extract specific spectral bands from the imagery. National Agriculture Imagery Program (NAIP). The Louisville_Neighborhood.tif imagery comes from the U.S. The map includes Louisville_Neighborhood.tif, a 6-inch resolution image, 4-band aerial photograph of the area, and the Parcels layer, a feature class of land parcels. The project contains a map of a neighborhood near Louisville, Kentucky. If you don't have ArcGIS Pro or an ArcGIS account, you can sign up for an ArcGIS free trial. This data includes imagery of the study area and land parcel features. To get started, you'll download data supplied by the local government of Louisville, Kentucky. Then, you will reclassify those land-use types intoīefore you classify the imagery, you will change the band combination to distinguish features clearly. You will firstĬlassify the image into broad land-use types, such as roofs or Once you segment the imagery, you will performĪ supervised classification of the segments. Which will generalize the image and significantly reduce the number Instead, you'll group pixels into segments, Which almost every pixel has a unique combination of spectralĬharacteristics, you are likely to encounter errors and However, if you try to classify an image in ![]() Using multispectral imagery for this kind of classification works well because each land-use type tends to have unique spectral characteristics, also called spectral signature. Pervious surfaces include vegetation, water bodies, and bare soil. Impervious surfaces are generally human-made: buildings, roads, parking lots, brick, or asphalt. To determine which parts of the ground are pervious and impervious, you will classify the imagery into land-use types.
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