Paper
3 June 2015 Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh
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Abstract
Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world’s fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mohammad Nizamuddin, Kawsar Akhand, Leonid Roytman, Felix Kogan, and Mitch Goldberg "Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh", Proc. SPIE 9488, Sensing for Agriculture and Food Quality and Safety VII, 94880O (3 June 2015); https://doi.org/10.1117/12.2086186
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Cited by 3 scholarly publications.
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KEYWORDS
Gold

Agriculture

Vegetation

Data modeling

Climatology

Remote sensing

Statistical analysis

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