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首页> 外文期刊>Agricultural Water Management >Detecting subsurface drainage systems and estimating drain spacing in intensively managed agricultural landscapes.
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Detecting subsurface drainage systems and estimating drain spacing in intensively managed agricultural landscapes.

机译：在集约化管理的农业景观中检测地下排水系统并估算排水沟间距。

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Detailed location maps of tile drains in the Midwestern United States are generally not available, as the tile lines in these areas were laid more than 75 years ago. The objective of this study is to map individual tile drains and estimate drain spacing using a combination of GIS-based analysis of land cover, soil and topography data, and analysis of high resolution aerial photographs to within the Hoagland watershed in west-central Indiana. A decision tree classifier model was used to classify the watershed into potentially drained and undrained areas using land cover, soil drainage class, and surface slope data sets. After masking out the potential undrained areas from the aerial image, image processing techniques such as the first-difference horizontal and vertical edge enhance filters, and density slice classification were used to create a detailed tile location map of the watershed. Drain spacings in different parts of the watershed were estimated from the watershed tile line map. The decision tree identified 79% of the watershed as potential tile drained area while the image processing techniques predicted artificial subsurface drainage in approximately 50% of the Hoagland watershed. Drain spacing inferred from classified aerial image vary between 17 and 80 m. Comparison of estimated tile drained areas from aerial image analysis shows a close agreement with estimated tile drained areas from previous studies (50% versus 46% drained area) which were based on GIS analysis and National Resource Inventory survey. Due to lack of sufficient field data, the results from this analysis could not be validated with observed tile line locations. In general, the techniques used for mapping tile lines gave reasonable results and are useful to detect drainage extent from aerial image in large areas. These techniques, however, do not yield precise maps of the systems for individual fields and may not accurately estimate the extent of tile drainage in the presence of crop residue in agricultural fields and/or existence of other spatial features with similar spectral response as tile drains.
机译：通常无法获得美国中西部地区瓷砖排水沟的详细位置图，因为这些地区的瓷砖线条是75年前铺设的。这项研究的目的是通过结合基于GIS的土地覆盖率，土壤和地形数据分析以及高分辨率的航空照片分析到印第安纳中西部的Hoagland流域，来绘制单个瓷砖排水沟并估算排水沟间距。决策树分类器模型用于使用土地覆盖，土壤排水分类和地表坡度数据集将流域分类为潜在排水和不排水区域。在从航空影像中掩盖了潜在的不排水区域之后，图像处理技术（例如一阶水平和垂直边缘增强滤镜）以及密度切片分类被用于创建流域的详细图块位置图。根据分水岭瓷砖线图估算了分水岭不同部分的排水间距。决策树确定了79％的流域为潜在的瓷砖流域，而图像处理技术预测了约50％的Hoagland流域的人工地下流域。从机密航拍图像推断出的排水沟间距在17至80 m之间。航空影像分析估计的瓷砖排水面积的比较表明，其与先前研究的瓷砖排水面积（50％对46％的排水面积）是基于GIS分析和国家资源清单调查得出的。由于缺乏足够的现场数据，无法使用观察到的瓷砖线位置来验证该分析的结果。通常，用于绘制瓷砖线的技术给出了合理的结果，可用于从大面积的航空影像中检测排水程度。但是，这些技术不能为单个田地提供精确的系统地图，并且可能无法准确估算在农田中存在农作物残渣和/或存在与瓷砖排水具有相似光谱响应的其他空间特征时瓷砖排水的程度。

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