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Monitoring soil aggregates dynamics at a plot scale using multi-temporal image texture and colour analysis

机译:使用多时相图像纹理和颜色分析在样地规模上监测土壤团聚体动态

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摘要

Monitoring of soil aggregate breakdown remains, even at the micro-plot scale, a challenge. Remote sensing has shown its potential to assess many different soil properties and is a fast and non-destructive method to investigate soil susceptibility to water erosion. We designed an outdoor experiment to monitor soil aggregates breakdown under natural rainfall at a micro-plot scale using a regular camera. Five soils susceptible to detachment (silty loam with various organic matter content, loam and sandy loam) were photographed once per day. We collected images and rainfall data from November 2014 until February 2015. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is used to observe the soil aggregates changes. In addition, a Gray Level Co-occurrence Matrix (GLCM) is used to extract the image texture entropy which reflects the process of soil aggregates breakdown. In our research the entropy calculated at 135 degrees along the direction of shadows gives best results. Our results show that both entropy and shadow index follow the wetting and drying cycles with a decrease due to a rain event. This decrease is small due to low rainfall intensity (< 2.5 mmh~(-1)) for the entire period that the experiment ran. However, the biggest rain event of 20 mmday"~(-1) resulted in a decrease in entropy, meaning that sufficient rainfall energy was present to trigger the soil aggregates break down. This research concludes that both entropy and shadow index obtained with a regular camera enable the monitoring of soil aggregate breakdown at a high spatial resolution.
机译:即使在微样规模上,对土壤聚集体分解的监测仍然是一个挑战。遥感显示了其评估许多不同土壤特性的潜力,并且是研究土壤对水蚀敏感性的一种快速且无损的方法。我们设计了一个户外实验,使用常规相机在微图规模下监控自然降雨下土壤聚集体的分解。每天拍摄五种容易脱离的土壤(具有各种有机质含量的粉质壤土,壤土和沙质壤土)。我们收集了2014年11月至2015年2月的图像和降雨数据。考虑到土壤表面粗糙度会导致阴影投射,蓝/红带比用于观察土壤聚集体的变化。此外,使用灰度共生矩阵(GLCM)提取反映土壤团聚体分解过程的图像纹理熵。在我们的研究中,沿阴影方向在135度处计算出的熵给出了最佳结果。我们的结果表明,熵和阴影指数都遵循润湿和干燥周期,并且由于降雨事件而降低。由于整个实验期间的降雨强度较低(<2.5 mmh〜(-1)),因此减少幅度很小。然而,最大的降雨事件“ 20 mmday”〜(-1)导致熵降低,这意味着存在足够的降雨能量来触发土壤团聚体分解。本研究得出的结论是,利用常规规则获得的熵和阴影指数摄像机可以以高空间分辨率监控土壤团聚体的破坏。

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  • 会议地点 Edinburgh(GB)
  • 作者单位

    Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands;

    Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands;

    Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands;

    Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, University of Twente, PO Box 217, 7500 AE Enschede, The Netherlands;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    soil aggregate breakdown; GLCM; entropy; shadow index; rainfall;

    机译:土壤骨料分解; GLCM;熵;阴影指数雨量;

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