Indexing remote sensing image retrieval using clustering and vegetation indices

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ภาวิดา ยะโสวงษ์
ชุลีรัตน์ จรัสกุลชัย


- Currently, Satellite images has been increasingly and available to download. Additionally, retrieving by latitude and longitude is not sufficiently, a new retrieval method is challenged in this area. Retrieving by specified type of object in remote sensing image such as vegetation, river etc is required. To support this process, an automatic indexing to classify object is need to study. This paper presents techniques of indexing SMMS satellite images retrieval which is a type of multi- spectral images. K-mean clustering technique and vegetation indices are explored with five types of objects. Then indexing techniques are compared between using vegetation index technique and clustering combine with vegetation index technique.

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ยะโสวงษ์ ภ. and จรัสกุลชัย ช., “Indexing remote sensing image retrieval using clustering and vegetation indices”, JIST, vol. 4, no. 2, pp. 1–8, Dec. 2013.
Research Article: Soft Computing (Detail in Scope of Journal)


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