Pixel-based and object-based classifications using high- and medium-spatial-resolution imageries in the urban and suburban landscapes |
| |
| Authors: | Ronald C Estoque Yuji Murayama Chiaki Mizutani Akiyama |
| |
| Institution: | 1. Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan;2. National Institute for Environmental Studies, Tsukuba, Japan |
| |
| Abstract: | With the increasing availability of high-spatial-resolution remote sensing imageries and with the observed limitations of pixel-based techniques, the development and testing of geographic object-based image analysis (GEOBIA) techniques for image classification have become one of the main research areas in geospatial science. This paper examines and compares the classification performance of a pixel-based method and an object-based method as applied to high- (QuickBird satellite image) and medium- (Landsat TM image) spatial-resolution imageries in the context of urban and suburban landscapes. For the pixel-based classification, the maximum-likelihood supervised classification approach was employed. And for the object-based classification, the pixel-based classified maps were integrated with a set of image segments produced using various calibrations. The results show evidence that the object-based method can produce classifications that are more accurate for both high- and medium-spatial- resolution imageries in the context of urban and suburban landscapes. |
| |
| Keywords: | GEOBIA land cover land use object-based image analysis pixel-based image analysis |
|
|
