Swath analysis has been useful for linking topography to geomorphic and tectonic processes in a variety of landscapes. Established swath methods have been limited to rectangular or simplified curvilinear sampling blocks despite most geologic structures having complex boundaries and orientations. Moreover, swath boundaries and intervals are commonly defined by arbitrary boundaries and without defined corner points, which makes reproducibility difficult. To address these shortcomings we developed PyOSP (Python Library for Object-oriented Swath Profile), an open-source library that can objectively characterize complex geomorphic boundaries using elevation, slope angle, topographic position index, or other raster calculations by intelligently assimilating geoprocessing information into swath analysis. In addition, PyOSP has post-processing tools (cross-swath, data reclassification, slice, histogram analysis, etc.) and the ability to communicate easily with other GIS software. To evaluate the utility of PyOSP, we used it in three case studies (Teton Range in Wyoming, Licking River in Kentucky, and Olympus Mons on Mars) that illustrate the library's robustness, from objective quantitative description of the topography to improved insights with post-processing capabilities.

测绘分析对于将地形与各种景观中的地貌和构造过程联系起来很有用。尽管大多数地质结构具有复杂的边界和方向，但既定的条带方法仅限于矩形或简化的曲线采样块。此外，条带边界和间隔通常由任意边界定义且没有定义的拐角点，这使得重现性变得困难。为了解决这些缺点，我们开发了PyOSP（面向对象的条幅图Python库），这是一个开放源代码库，可以通过将地理处理信息智能化地吸收到地面中，使用仰角，坡度角，地形位置索引或其他栅格计算来客观地表征复杂的地貌边界。测幅分析。此外，PyOSP具有后处理工具（跨范围，数据重新分类，切片，直方图分析等），并具有与其他GIS软件轻松通信的能力。为了评估PyOSP的效用，我们在三个案例研究（怀俄明州的Teton Range，肯塔基州的Licking River和火星的Olympus Mons）中使用了PyOSP，这些实例说明了该库的强大功能，从客观的地形定量描述到对后期数据的更深入了解。处理能力。