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An automatic method to extract Populus Euphratica forest in a large area using remote sensing

机译:使用遥感的大面积中提取杨树般euphratica林的自动化方法

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Populus Euphratica is a haloduric desert vegetation growing in arid regions. It is a drought-enduring plant and it is also a wind barrier to fix sands in desert areas. The distribution of Populus Euphratica forest is required to carry out the management of water resources in the arid region, such characteristics make it play an important role in maintaining the hydrological ecological balance in desert. However, they are distributed discretely and the single tree is very small, so it is difficult or even impossible to be extracted at a large scale based by using moderate to high spatial resolution remote sensing data. Thus, the high spatial resolution remote sensing data are required for extracting Populus Euphratica. However, the utilization of high and very high spatial resolution remote sensing data in a large area is usually not implementable because of the high costs and low processing speed. In addition, the manual procedure is usually incorporated, which is further lower its implementalbilty. Therefore, there is hardly any related research for extracting Populus Euphratica in a large area. In this context, this paper proposes an automatic method to extract the populus euphratica forest in lower-stream of the Heihe River (total area of approximately 21646.6km~2) by using object-oriented classification method. Firstly, high spatial resolution data (higher than 2 m) are extracted from Google Earth (the data are used for free and the high level product based on Google Earth images don't have copyright issues). The extracted images are mosaicked automatically using the application programming interface provided by Google Earth. Thirdly, based on analyzing the characteristics of Populus Euphratica as image objects, a set of rules for extracting Populus Euphratica by employing object oriented method are constructed. Finally, the manual inspection method is employed to verify the accuracy of the extracting results and it shows an accuracy better than 87%. The proposed method is capable of extracting populus euphratica forest using Google Earth automatically with low-cost and high-precision and it will become a feasible technical solution to extract thematic information automatically with low-cost and high-precision. Moreover, it will lead a large amount of applications, which are able to provide high-precision and high-resolution thematic products at a very low cost for the sic-economic development in the future; therefore, it has great values on remote sensing applications.
机译:胡杨是一种耐盐荒漠植被的干旱地区的增长。它是一种耐旱植物,它也是一个风障,以修复砂沙漠地区。需要胡杨林的分布,开展水资源管理的干旱地区,这样的特性使得它在维持沙漠水文生态平衡具有重要作用。然而,它们是离散分布和单一树非常小,因此它是难以或者甚至不可能在通过使用中度到高空间分辨率遥感数据基于大规模地被提取。因此,高空间分辨率的遥感数据被要求用于提取胡杨。然而,高和非常高的空间分辨率的遥感数据的大面积的利用一般是因为成本高,处理速度低的无法实施。此外,手动过程通常并入,其被进一步降低其implementalbilty。因此,很难说是在一个大的区域提取胡杨任何相关的研究。在此背景下,提出了一种自动方法来提取胡杨林黑河的低流(约21646.6公里〜2总面积),通过使用面向对象的分类方法。首先,高空间分辨率的数据(超过2米以上)从谷歌地球中提取(数据用于免费和高层次的产品基于谷歌地球的图像没有版权问题)。提取的图像使用由谷歌地球提供的应用程序编程接口自动镶嵌。第三,基于分析胡杨的特性作为图像对象,用于通过采用面向对象的方法提取胡杨一组规则构造。最后,采用人工检查方法来验证所述提取结果的准确性,它显示了一个精确度高于87%更好。该方法能够自动提取使用谷歌地球具有低成本和高精密的胡杨林,它会成为一个可行的技术解决方案,以低成本,高精密自动提取专题信息。此外,它会导致大量的应用程序,它能够以非常低的成本在未来的SiC-经济发展提供高精度和高清晰度的主题产品;因此,对遥感应用极大值。

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