首页> 外文会议>2012 IEEE International Geoscience amp; Remote Sensing Symposium. >Mathematical morphology approach to detect farmland conditions from ALOS/PALSAR data after the 2011 off the pacific coast of Tohoku Japan earthquake and Tsunami
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Mathematical morphology approach to detect farmland conditions from ALOS/PALSAR data after the 2011 off the pacific coast of Tohoku Japan earthquake and Tsunami

机译:从2011年日本东北太平洋地震和海啸后的太平洋ALOS / PALSAR数据中检测农田状况的数学形态学方法

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The north-eastern coast of main island of Japan, Tohoku region, was hit by the great earthquake and the big Tsunami on March 11th, 2011. There are farm lands, mainly paddy fields, along the coast line in many places of Tohoku region. The Tsunami made those lands along the seashore a vacant lot. The grounds have been sinking in some areas after the earthquake. The ALOS/PALSAR was observed on March 13rd, March 17th of 2011 in this region. Those data are HH polarization, pixel spacing 6.25m. After the Tsunami tidal wave, the fields became flat because of soil sediment. The difference of back scattering DN value between the Tsunami inundated and not inundated areas is not big. So the boundary line is obscure by only amplitude information. The terrain feature recognition procedure of the SAR data should be improved. The improved procedure combined with adaptive threshold and morphological opening filtering shows fairly good result. This procedure required only a few minutes for each image by using an ordinary PC.
机译:2011年3月11日,日本东北地区东北地区的东北海岸袭击了大地震和大海啸。在往北地区的许多地方,有农场土地,主要是稻田,沿着海岸线。海啸使那些沿着海边的土地留下空缺。地震后的某些地区一直在沉没。 Alos / Palsar于2011年3月13日在该地区观察到。这些数据是HH极化,像素间隔6.25m。在海啸潮汐之后,由于土壤沉积物,田地变得平坦。海啸淹没在海啸之间的散射DN值的差异并不大。因此,边界线仅被幅度信息模糊不清。应提高SAR数据的地形功能识别过程。改进的过程与自适应阈值和形态开口过滤相结合,表现出相当好的结果。使用普通PC,此过程仅需要几分钟的每个图像。

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