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Identification of windbreaks in Kansas using object-based image analysis, GIS techniques and field survey

机译:使用基于对象的图像分析,GIS技术和现场调查来识别堪萨斯州的防风林

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摘要

Windbreaks are valuable resources in conserving soils and providing crop protection in Great Plains states in the US. Currently, Kansas has no up-to date inventory of windbreaks. The goal of this project was to assist foresters with future windbreak renovation planning and reporting, by outlining a series of semi-automated digital image processing methods that rapidly identify windbreak locations. There were two specific objectives of this research. First, to develop semi-automated methods to identify the location of windbreaks in Kansas, this can be applied to other regions in Kansas and the Great Plains. We used a remote sensing technique known as object-based image analysis (OBIA) to classify windbreaks visible in the color aerial imagery of National Agriculture Imagery Program. We also combined GIS techniques and field survey to complement OBIA in generating windbreak inventory. The techniques successfully located more than 4500, windbreaks covering an approximate area of 2500, hectares in 14 Kansas counties. The second purpose of this research is to determine how well the results of the automated classification schemes match with other available windbreak data and the selected sample collected in the field. The overall accuracy of OBIA method was 58.97 %. OBIA combined with 'heads up' digitizing and field survey method yielded better result in identifying and locating windbreaks in the studied counties with overall accuracy of 96 %.
机译:在美国大平原州,防风林是保护土壤和提供作物保护的宝贵资源。当前,堪萨斯州没有最新的防风衣清单。该项目的目的是通过概述一系列可快速识别防风林位置的半自动数字图像处理方法,帮助林业工作者进行防风林的未来规划和报告。这项研究有两个具体目标。首先,要开发半自动方法来确定堪萨斯州的防风林位置,可以将其应用于堪萨斯州和大平原的其他地区。我们使用了一种称为基于对象的图像分析(OBIA)的遥感技术,对国家农业图像计划的彩色航空图像中可见的防风林进行了分类。我们还将GIS技术和现场调查相结合,以补充OBIA来生成防风衣清单。该技术成功地在堪萨斯州的14个县中找到了4500多处防风林,覆盖了大约2500公顷的土地。这项研究的第二个目的是确定自动分类方案的结果与其他可用的防风数据和现场收集的选定样本的匹配程度。 OBIA方法的总体准确性为58.97%。 OBIA与“平视”数字化和现场调查方法相结合,在被调查县识别和定位防风林方面取得了更好的结果,总体准确率为96%。

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