EFFECT OF PANSHARPENED IMAGE ON SOME OF PIXEL BASED AND OBJECT BASED CLASSIFICATION ACCURACY
| Autor: | Hakan Karabork, pınar karakus |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
lcsh:Applied optics. Photonics
010504 meteorology & atmospheric sciences Multispectral image 0211 other engineering and technologies 02 engineering and technology Sharpening 01 natural sciences lcsh:Technology Multispectral pattern recognition Computer vision Image resolution 021101 geological & geomatics engineering 0105 earth and related environmental sciences Pixel business.industry Color image lcsh:T lcsh:TA1501-1820 Pattern recognition Panchromatic film Support vector machine Geography lcsh:TA1-2040 Artificial intelligence business lcsh:Engineering (General). Civil engineering (General) |
| Zdroj: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B7, Pp 235-239 (2016) |
| ISSN: | 2194-9034 1682-1750 |
| Popis: | Classification is the most important method to determine type of crop contained in a region for agricultural planning. There are two types of the classification. First is pixel based and the other is object based classification method. While pixel based classification methods are based on the information in each pixel, object based classification method is based on objects or image objects that formed by the combination of information from a set of similar pixels. Multispectral image contains a higher degree of spectral resolution than a panchromatic image. Panchromatic image have a higher spatial resolution than a multispectral image. Pan sharpening is a process of merging high spatial resolution panchromatic and high spectral resolution multispectral imagery to create a single high resolution color image. The aim of the study was to compare the potential classification accuracy provided by pan sharpened image. In this study, SPOT 5 image was used dated April 2013. 5m panchromatic image and 10m multispectral image are pan sharpened. Four different classification methods were investigated: maximum likelihood, decision tree, support vector machine at the pixel level and object based classification methods. SPOT 5 pan sharpened image was used to classification sun flowers and corn in a study site located at Kadirli region on Osmaniye in Turkey. The effects of pan sharpened image on classification results were also examined. Accuracy assessment showed that the object based classification resulted in the better overall accuracy values than the others. The results that indicate that these classification methods can be used for identifying sun flower and corn and estimating crop areas. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|