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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Using Color Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown
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Using Color Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown

机译：使用基于颜色纹理和基于对象的多时相相机数据进行图像分析来监控土壤团聚体的破坏

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Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown.
机译：遥感显示了其评估土壤特性的潜力，是一种监测土壤表面变化的快速且无损的方法。在本文中，我们监测自然条件下土壤团聚体的破坏。从2014年11月到2015年2月，每天从五种容易分离的土壤（含有机质含量不同的淤泥质壤土，壤土和沙质壤土）中收集图像和天气数据。测试了三种在图像处理复杂度和用户交互方式上有所不同的技术来监视聚合崩溃的能力。考虑到土壤表面粗糙度会引起阴影投射，利用蓝/红带比观察土壤团聚体的变化。对于具有高空间分辨率的图像，使用了反映土壤聚集体分解过程的图像纹理熵。此外，还执行了黄阈值技术，该技术可以估算土壤团聚体占据的图像区域。我们的结果表明，所有这三种技术都表明随着时间的推移土壤聚集体发生了破坏。阴影比随时间显示逐渐变化，没有与天气状况有关的详细信息。熵和黄阈值技术都显示了土壤聚集体分解随天气条件的变化。使用常规相机获得的数据，我们发现冻融循环是土壤聚集体分解的原因。

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