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## Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy

#### Dilek Küçük Matcı [1] , Uğur Avdan [2]

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Remote sensing technologies provide very important big data to various science areas such as risk identification, damage detection and prevention studies. However, the classification processes used to create thematic maps to interpret this data can be ineffective due to the wide range of properties that these images provide. At this point, there arises a requirement to optimize the data. The first objective of this study is to evaluate the performance of the Bat Search Algorithm which has not previously been used for improving the classification accuracy of remotely sensed images by optimizing attributes. The second objective is to compare the performance of the Genetic Algorithm, Bat Search Algorithm, Cuckoo Search Algorithm and Particle Swarm Optimization Algorithm, which are used in many areas of the literature for the optimization of the attributes of remotely sensed images. For these purposes, an image from the Landsat 8 satellite is used. The performance of the algorithms is compared by classifying the image using the K-Means method. The analysis shows a 10-22% increase in overall accuracy with the addition of attribute optimization.

Remote Sensing, Classification, Optimization, Unsupervised Classification
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Primary Language en Research Articles Orcid: 0000-0002-4078-8782Author: Dilek Küçük Matcı (Primary Author)Country: Turkey Orcid: 0000-0001-7873-9874Author: Uğur AvdanInstitution: ESKİŞEHİR TEKNİK ÜNİVERSİTESİCountry: Turkey
 Bibtex @research article { ijegeo466985, journal = {International Journal of Environment and Geoinformatics}, issn = {}, eissn = {2148-9173}, address = {Cem GAZİOĞLU}, year = {2019}, volume = {6}, pages = {50 - 56}, doi = {10.30897/ijegeo.466985}, title = {Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy}, key = {cite}, author = {Küçük Matcı, Dilek and Avdan, Uğur} } APA Küçük Matcı, D , Avdan, U . (2019). Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy. International Journal of Environment and Geoinformatics, 6 (1), 50-56. DOI: 10.30897/ijegeo.466985 MLA Küçük Matcı, D , Avdan, U . "Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy". International Journal of Environment and Geoinformatics 6 (2019): 50-56 Chicago Küçük Matcı, D , Avdan, U . "Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy". International Journal of Environment and Geoinformatics 6 (2019): 50-56 RIS TY - JOUR T1 - Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy AU - Dilek Küçük Matcı , Uğur Avdan Y1 - 2019 PY - 2019 N1 - doi: 10.30897/ijegeo.466985 DO - 10.30897/ijegeo.466985 T2 - International Journal of Environment and Geoinformatics JF - Journal JO - JOR SP - 50 EP - 56 VL - 6 IS - 1 SN - -2148-9173 M3 - doi: 10.30897/ijegeo.466985 UR - https://doi.org/10.30897/ijegeo.466985 Y2 - 2019 ER - EndNote %0 International Journal of Environment and Geoinformatics Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy %A Dilek Küçük Matcı , Uğur Avdan %T Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy %D 2019 %J International Journal of Environment and Geoinformatics %P -2148-9173 %V 6 %N 1 %R doi: 10.30897/ijegeo.466985 %U 10.30897/ijegeo.466985 ISNAD Küçük Matcı, Dilek , Avdan, Uğur . "Optimization of Remote Sensing Image Attributes to Improve Classification Accuracy". International Journal of Environment and Geoinformatics 6 / 1 (April 2019): 50-56. https://doi.org/10.30897/ijegeo.466985