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Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

机译:基于NOAA / AVHRR基于NOAA / AVHRR的遥感数据和PCR方法,用于孟加拉国AUS稻米产量的估算

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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.
机译:米饭是孟加拉国占优势粮食作物,占水稻种植的75%的农业用地,目前孟加拉国是世界第四大稻米生产国。米饭提供大约三分之二的热量供应,以及孟加拉国国家收入的一半占农业GDP的一半。 Aus是孟加拉国的主要稻米品种之一。作物生产,尤其是大米,主要食物主食,是最容易受气候变化和变异性的影响。因此,随着气候的任何改变都会增加与水稻生产的不确定性是水稻生产率的主要原因逐年变化。本文展示了遥感数据在孟加拉国估算Aus稻米产量的应用,使用正式统计水稻产量与实时获取来自先进的高分辨率辐射计(AVHRR)传感器的卫星数据和主成分回归(PCR)方法构建一个模型。将模拟结果与官方农业统计数据进行比较,表明AUS水稻产量的估计误差小于10%。因此,遥感是估计作物在收获之前估计作物产量的有价值的工具,并且以低成本。

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