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UAV multispectral survey to map soil and crop for precision farming applications

机译:无人机多光谱勘测可绘制土壤和农作物的地图,用于精准农业

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摘要

New sensors mounted on UAV and optimal procedures for survey, data acquisition and analysis are continuously developed and tested for applications in precision farming. Procedures to integrate multispectral aerial data about soil and crop and ground-based proximal geophysical data are a recent research topic aimed to delineate homogeneous zones for the management of agricultural inputs (i.e., water, nutrients). Multispectral and multitemporal orthomosaics were produced over a test field (a 100 m × 200 m plot within a maize field), to map vegetation and soil indices, as well as crop heights, with suitable ground resolution. UAV flights were performed in two moments during the crop season, before sowing on bare soil, and just before flowering when maize was nearly at the maximum height. Two cameras, for color (RGB) and false color (NIR-RG) images, were used. The images were processed in Agisoft Photoscan to produce Digital Surface Model (DSM) of bare soil and crop, and multispectral orthophotos. To overcome some difficulties in the automatic searching of matching points for the block adjustment of the crop image, also the scientific software developed by Politecnico of Milan was used to enhance images orientation. Surveys and image processing are described, as well as results about classification of multispectral-multitemporal orthophotos and soil indices.
机译:不断开发和测试用于无人机的新型传感器以及用于测量,数据采集和分析的最佳程序,并针对精密农业进行了测试。整合有关土壤和农作物的多光谱航空数据以及基于地面的近端地球物理数据的程序是最近的研究主题,旨在划定用于管理农业投入物(即水,养分)的均匀区域。在一个试验场(玉米田内一个100 m×200 m的地块)上制作了多光谱和多时间的正镶嵌图,以适当的地面分辨率绘制植被和土壤指数以及作物高度的图。在作物季节的两分钟内,在裸露的土地上播种之前,以及在玉米接近最大高度的开花期之前,进行无人机飞行。使用了两个用于彩色(RGB)和伪彩色(NIR-RG)图像的相机。图像在Agisoft Photoscan中进行处理,以产生裸露的土壤和农作物的数字表面模型(DSM),以及多光谱正射照片。为了克服自动寻找匹配点进行作物图像块调整的一些困难,还使用了米兰理工大学开发的科学软件来增强图像方向。描述了调查和图像处理,以及有关多光谱-多时间正射影像和土壤指数分类的结果。

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