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Mapping coastal ecosystems and features using a low-cost standard drone: case study, Nayband Bay, Persian gulf, Iran

机译:使用低成本标准寄生虫映射沿海生态系统和特征:案例研究,Nayband Bay,波斯湾,伊朗

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A low-cost standard drone (DJI (TM) Phantom 4 Pro) has been employed to map the ecosystems and features in coastal areas in the northern Persian Gulf. The Pix4Dcapture (R) mobile application was selected as a user friendly and simple app to perform an automated and customized drone flight over the selected study area in Nayband Bay, Bushehr province. The flight altitude was selected to be 100 m with 80% overlap for images, which led to the imaging of an area similar to 22 ha (413 x 525 m) in similar to 13 min (from takeoff to landing the drone). Agisoft (TM) Metashape PC software was then used to create the orthophoto mosaic from 213 taken photos. Consequently, the ground sampling distance (GSD) of the created orthophoto mosaic was similar to 3 cm which means it was possible to visually identify the features on the images with a size of 30 cm and more. The orthophoto mosaic was then converted to a topological GIS-based map (in the format of ESRI (TM) shapefile) by a 2-step procedure including a supervised image classification method coupled with manual editing with an on-screen visual editing method. The final results demonstrated that the overall accuracy of the classified mosaic raster map was 87.6% where the kappa(Kappa coefficient) was 0.84. The results also showed that the applied methodology in this study can be used to differentiate the coastal ecosystems and features such as mangrove forests, vegetations, sandy beaches, and deep and shallow water bodies. As a comparison with alternative methods, the cost of implementing drone-based methodology was lower than field surveying and covers a larger area in less time.
机译:低成本的标准无人机(DJI(TM)幻影4 Pro)已被用于映射北部波斯湾沿海地区的生态系统和特色。选择PIX4DCAPTURE(R)移动应用程序被选为用户友好和简单的应用程序,以在BushR省的Nayband Bay所选的学习区域上执行自动化和定制的无人机航班。选择飞行高度为100米,用于图像的80%重叠,这导致了类似于22公顷(413×525米)的区域的成像,类似于13分钟(从起飞到降落寄生虫)。然后使用Agisoft(TM)Metashape PC软件从213拍摄的照片中创建正轨马赛克。因此,所产生的矫正马赛克的地面采样距离(GSD)类似于3cm,这意味着可以在目视识别图像上的图像上的特征,尺寸为30厘米。然后通过包括带有屏幕上的手动编辑的监督图像分类方法,将正轨马赛克转换为基于拓扑GIS的映射(以ESRI(TM)Shapefile的格式)转换为基于拓扑GIS的映射(以ESRI(TM)Shapefile)的格式,包括具有屏幕上的视觉编辑方法的手动编辑。最终结果表明,分类的马赛克光栅地图的总体准确性为87.6%,其中κ(kappa系数)为0.84。结果还表明,本研究的应用方法可用于区分红树林,植被,沙滩和深层和浅水机构等沿海生态系统和特征。作为与替代方法的比较,实施无人机的方法的成本低于现场测量,并在更短的时间内覆盖更大的区域。

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