Rice phenology monitoring using PIA time series MODIS imagery

Conference proceedings article

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Publication Details

Author list: Khobkhun B., Prayote A., Rakwatin P., Dejdumrong N.

Publisher: Hindawi

Publication year: 2013

Start page: 84

End page: 87

Number of pages: 4

ISBN: 9780769550510

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892665544&doi=10.1109%2fCGIV.2013.12&partnerID=40&md5=8ebde6fb4b8852f1ba9325c67a318c8b

Languages: English-Great Britain (EN-GB)

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Abstract

This paper presents the method to determine rice cropping pattern in Thailand for future prediction of water supply demand, pricing, and other related issues including governmental policies. Datasets was obtained from an orbital instrument called a Moderate-Resolution Imaging Spectroradiometer (MODIS) operated by NASA. A Normalized Difference Vegetation Index (NDVI) was derived from MODIS datasets once every 16 days. This image data has been analyzed using image processing techniques in order to determine rice cropping area in Thailand. Rice cropping data is represented as a time series displaying type of rice crop in which peak data points indicate rice cropping cycle in each year. A Progressive Iterative Approximation (PIA) is used for signal smoothing and reducing noise by providing a B้zier curve representation of time-series data. The experimental results show that using PIA technique for noise reduction yields better results comparing with a common filtering method like Savitzky Golay filter. ฉ 2013 IEEE.

Keywords

Time series smoothing