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首页> 外文期刊>International journal of applied earth observation and geoinformation >Extracting aquaculture ponds from natural water surfaces around inland lakes on medium resolution multispectral images
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Extracting aquaculture ponds from natural water surfaces around inland lakes on medium resolution multispectral images

机译：在中线分辨率上从内陆湖泊周围的天然水面提取水产养殖池

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摘要

A considerable portion of the natural inland lakes has been gradually transformed into aquaculture ponds to meet the enormous demand for aquaculture products. The changes in ponds area can be used to measure the impact of human activities on inland lakes. However, aquaculture ponds and inland lakes are often intermingled with each other especially in the areas close to the lake shore, posing great difficulties for the extraction of aquaculture ponds from medium resolution (15-30 m) multispectral imagery, such as Landsat TM, OLI, and Geofen-1 WFV images. This study proposes a contour-based regularity measurement for water segments, which evaluates the zero-curvature portions of the boundaries, to distinguish aquaculture ponds from natural water. Water surfaces are firstly extracted from satellite images, and then boundary trace of each water segment is carried out to evaluate the geometrical feature of its contour, including perimeter, curvature and the proposed contour-based regularity. Eventually, SVM classification based on these geometrical features separates the aquaculture ponds from inland lakes. Experiments on Landsat TM, OLI, and Geofen-1 WFV images showed that the combination of perimeter, area and proposed contour-based regularity outperforms other feature combinations and produced the most accurate classification. Therefore, the proposed method can be used to extract all aquaculture ponds from all historic Landsat images to monitor the changes in inland aquaculture.
机译：一部分自然内陆湖泊已经逐渐转化为水产养殖池塘，以满足对水产养殖产品的巨大需求。池塘地区的变化可用于衡量人类活动对内陆湖泊的影响。然而，水产养殖池塘和内陆湖泊通常互相混合，特别是在靠近湖岸的地区，从中等分辨率（15-30米）的多光谱图像中提取水产养殖池塘的巨大困难，如Landsat TM，Oli ，以及Geofen-1 WFV图像。本研究提出了水段的基于轮廓的规律性测量，该水段评估了边界的零曲率部分，以区分水产养殖池免于天然水。从卫星图像中首先提取水面，然后进行每个水段的边界轨迹，以评估其轮廓的几何特征，包括周边，曲率和基于轮廓的基于轮廓的规则性。最终，基于这些几何特征的SVM分类将水产养殖池与内陆湖泊分开。 LANDSAT TM，OLI和Geofen-1 WFV图像的实验表明，周边，面积和基于轮廓的规则性的组合优于其他特征组合，并产生了最准确的分类。因此，该方法可用于从所有历史的Landsat图像中提取所有水产养殖池，以监测内陆水产养殖的变化。

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