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首页> 外文会议>Conference on Ecosystems' Dynamics, Agricultural Remote Sensing and Modeling, and Site-Specific Agriculture; Aug 7, 2003; San Diego, California, USA >Study of a GIS-supported remote sensing method and a model for monitoring soil moisture at depth
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Study of a GIS-supported remote sensing method and a model for monitoring soil moisture at depth

机译：GIS支持的遥感方法和深度土壤水分监测模型的研究

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摘要

Remote sensing techniques for monitoring soil moisture, e.g., that of thermal inertia, are confined to the top level of soil, generally with useful measurements only at the 0～20 cm interval due to the fact that the thermal inertia method is built mainly on the difference in daily temperature, part of whose patterns are limited largely to soil surface level without attacking its depth. The paper makes an approach to the problem, proposing a scheme and a model for estimating soil moisture at depth from NOAA/AVHRR sensings, based upon the apparent thermal inertia (ATI) and the aid of Geographic Information System (GIS), and with the effect of soil quality allowed for. Evidence suggests a rather high nonlinear relationship between the surface and deep levels of soil and its model is in the form S= A x (d - d_0) + S_0 x [1 + Bx (d- d_0 )~2 ] + S_c, with which to estimate the water at depth by means of remotely sensed top-level moisture. As demonstrated in the practical applications to moisture sensing on a long-term and a multi-temporal phase basis in Henan Province, the developed model raises the mean accuracy by 5.5%～8.1% compared to the direct monitoring from satellite sensings of soil moisture at depth. On the other hand, owing to the limitation to the data of deep level moisture the water conditions at depth retrieved from the presented method and the developed model do not exceed 100 cm. And on land just irrigated or after rain the precision would be affected to noticeable degree because of the nonlinear relation available no longer.
机译：监测土壤水分的遥感技术（例如热惯性）仅限于土壤的最高层，通常仅在0〜20 cm的间隔内进行有用的测量，因为热惯性方法主要建立在每日温度的差异，其部分模式在很大程度上不受土壤表层高度的影响而不受其深度的影响。本文提出了解决该问题的方法，提出了一种基于表观热惯性（ATI）和地理信息系统（GIS）并借助表观热惯量（NOAA / AVHRR）估算深度土壤湿度的方案和模型。允许的土壤质量影响。有证据表明，土壤表面和深层之间存在较高的非线性关系，其模型形式为S = A x（d-d_0）+ S_0 x [1 + Bx（d- d_0）〜2] + S_c，其中可以通过遥感的顶级水分来估算深水。如在河南省长期和多时相的湿度感测实际应用中所证明的，与直接从卫星感测土壤湿度的直接监测相比，所开发的模型将平均准确度提高了5.5％〜8.1％。深度。另一方面，由于对深层水汽数据的限制，从本文提出的方法和开发的模型获得的深度水条件不超过100 cm。在刚刚灌溉的土地上或雨后，由于不再存在非线性关系，精度将受到显着影响。

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