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Mapping Variations in Crop Conditions Using Airborne Videography

机译:使用航空摄影术绘制作物状况的变化图

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Videographic observations can provide useful information at a scale intermediate between the large-scale data collected on the ground and the regional scale data available from satellite imagery. Previous work on agricultural, hydrologic and forestry applications report multi-spectral video as a non-invasive and rapid method for generating timely information that can be integrated with other ancillary data for better management strategies. Accordingly, this study investigates the potential of digital multi-spectral video to identify variations in crop conditions related to farm management, soil types, and terrain conditions. Specific spectral, spatial and temporal remote sensing requirements for mapping variations in crop conditions are addressed as well. Vegetation indices were applied to map different crop types and conditions. The NDVI, plant pigment ratio, plant vigour index and cell density ratio were used to this end. The study examines whether the spectral variability observed in the vegetation indices of paddocks under crops are associated with terrain attributes such as slope and aspect, different soil-landscape types, waterlogging, and crop conditions such as the presence of weeds. It is concluded that qualitative images as provided by the vegetation indices implemented in this study can provide useful information for identifying zones that perform differently within or between paddocks. The indices showed sensitive to variations in drainage conditions, soil-landscape units (e.g. and associated terrain attributes such as slope) and the presence of weeds within a paddock. Thus, it is concluded that rapid mapping of the occurrence of field variations by applying vegetation indices derived from high resolution airborne videography would enable farmers to identify the causes of variability (e.g. waterlogging, weeds, insufficient fertilisers, etc.), helping to decide on appropriate management practices for improving farming conditions.
机译:视频摄影观测可以提供介于地面上收集的大规模数据与可从卫星图像获得的区域尺度数据之间的尺度上的有用信息。先前有关农业,水文和林业应用的工作报告说,多光谱视频是一种无创,快速的方法,可以及时生成信息,可以将其与其他辅助数据集成在一起,以制定更好的管理策略。因此,本研究调查了数字多光谱视频识别与农场管理,土壤类型和地形条件有关的作物条件变化的潜力。还解决了用于绘制作物状况变化的特定光谱,空间和时间遥感要求。植被指数用于绘制不同作物类型和条件的地图。为此,使用了NDVI,植物色素比率,植物活力指数和细胞密度比率。该研究检查了在农作物下围场植被指数中观察到的光谱变异性是否与地形属性(例如坡度和坡度,不同的土壤-景观类型,涝渍)以及作物状况(例如杂草)相关联。结论是,由这项研究中实施的植被指数提供的定性图像可以为识别围场内部或围场之间表现不同的区域提供有用的信息。指数显示对排水条件,土壤-景观单位(例如和相关的地形属性,例如坡度)以及围场内杂草的存在的变化敏感。因此,得出的结论是,通过应用从高分辨率航空摄影获得的植被指数来快速绘制田间变化的发生图,将使农民能够确定变化的原因(例如,涝灾,杂草,肥料不足等),有助于做出决定。适当的管理措施以改善耕种条件。

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