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首页> 外文OA文献 >Mapping Of Soybean (glycine Max (l.) Merr.) Culture By Modis/terra And Tm/landsat 5: A Comparative [mapeamento De Semeaduras De Soja (glycine Max (l.)merr.) Mediante Dados Modis/terra E Tm/landsat 5: Um Comparativo]
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Mapping Of Soybean (glycine Max (l.) Merr.) Culture By Modis/terra And Tm/landsat 5: A Comparative [mapeamento De Semeaduras De Soja (glycine Max (l.)merr.) Mediante Dados Modis/terra E Tm/landsat 5: Um Comparativo]

机译：大豆（甘氨酸最高（升））培养图谱的绘制方法：Modis / terra和Tm / landsat 5：比较landsat 5：比较]

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摘要

The objective of this work was to compare the soybean crop mapping in the western of Parana State by MODIS/Terra and TM/Landsat 5 images. Firstly, it was generated a soybean crop mask using six TM images covering the crop season, which was used as a reference. The images were submitted to Parallelepiped and Maximum Likelihood digital classification algorithms, followed by visual inspection. Four MODIS images, covering the vegetative peak, were classified using the Parallelepiped method. The quality assessment of MODIS and TM classification was carried out through an Error Matrix, considering 100 sample points between soybean or not soybean, randomly allocated in each of the eight municipalities within the study area. The results showed that both the Overall Classification (OC) and the Kappa Index (KI) have produced values ranging from 0.55 to 0.80, considered good to very good performances, either in TM or MODIS images. When OC and KI, from both sensors were compared, it wasn't found no statistical difference between them. The soybean mapping, using MODIS, has produced 70% of reliance in terms of users. The main conclusion is that the mapping of soybean by MODIS is feasible, with the advantage to have better temporal resolution than Landsat, and to be available on the internet, free of charge.
机译：这项工作的目的是通过MODIS / Terra和TM / Landsat 5图像比较巴拉那州西部的大豆作物制图。首先，使用覆盖作物季节的六个TM图像生成大豆作物遮罩，将其用作参考。将图像提交给平行六面体和最大似然数字分类算法，然后进行视觉检查。使用平行六面体方法对覆盖营养峰的四个MODIS图像进行了分类。 MODIS和TM分类的质量评估是通过一个误差矩阵进行的，其中考虑了研究区域内八个城市中每个城市随机分配的大豆之间或非大豆之间的100个采样点。结果表明，总体分类（OC）和Kappa指数（KI）产生的值介于0.55到0.80之间，在TM或MODIS图像中被认为是很好的表现。比较两个传感器的OC和KI时，发现它们之间没有统计学差异。使用MODIS进行的大豆制图已经产生了70％的用户依赖。主要结论是，利用MODIS进行大豆作图是可行的，其优点是比Landsat具有更好的时间分辨率，并且可以免费在互联网上使用。

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