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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >CHARACTERIZATION OF SALINE SOILS USING AIRBORNE RADAR IMAGERY
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CHARACTERIZATION OF SALINE SOILS USING AIRBORNE RADAR IMAGERY

机译:利用机载雷达成像表征盐渍土

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摘要

Complex dielectric constants determined by inversion of the polarized returns of AIRSAR images acquired in wet conditions delineate the distribution of saline soils in irrigated regions around the town of Pyramid Hill, in western Victoria, Australia. There is good agreement between the areas delineated as having anomalous dielectric constants by the radar backscatter inversion techniques with saline areas as defined by electrical conductivity and as inferred from dielectric constants determined in the field. Surface roughness maps and vegetation classification maps derived from AIRSAR data provide useful ancillary information regarding the extent of salinity in the region, but they are not as diagnostic as the determined dielectric constants. The magnitudes of P band radar-determined dielectric constants most closely approach those expected from field determinations, although the distribution of L-band-determined dielectric constants gives the best discrimination between saline and nonsaline areas as seen at the surface. C-band-determined dielectric constants are much lower than expected from field determinations and show saline areas as anomalous only in the bare, most severely affected, areas. The more general regional distribution of high dielectric areas seen at P band may be a more accurate indication of the salinity at. depth. The AIRSAR image inversion techniques generally underestimate the magnitude of the complex dielectric constant. AIRSAR data for salinity mapping should be acquired under wet conditions. In such conditions there is an electrical continuum between the wet ground surface and saline water within the pores in the upper soil horizons. A wet ground surface results in a higher total power return than that which would occur under dry conditions and in a higher contrast between the radar-dark and radar bright areas within the scene. [References: 20]
机译:通过在潮湿条件下获取的AIRSAR图像的极化返回值的反演而确定的复介电常数,描绘了澳大利亚维多利亚西部金字塔山镇周围灌溉区域的盐渍土壤分布。由雷达反向散射反演技术描绘为具有异常介电常数的区域与由电导率定义并根据现场确定的介电常数推断出的盐分区域之间具有良好的一致性。从AIRSAR数据得出的表面粗糙度图和植被分类图可提供有关该地区盐度程度的有用辅助信息,但它们不如所确定的介电常数具有诊断性。 P波段雷达确定的介电常数的幅度最接近现场确定的期望值,尽管L波段确定的介电常数的分布提供了最佳的盐水和非盐渍区之间的区别,如在表面看到的那样。 C波段测定的介电常数远低于现场测定的预期值,并且仅在受灾最严重的裸露区域显示盐渍区域为异常。在P波段看到的高电介质区域的更一般的区域分布可能更准确地指示了盐度。深度。 AIRSAR图像反演技术通常会低估复数介电常数的大小。用于盐度制图的AIRSAR数据应在潮湿条件下获取。在这种情况下,在潮湿的地面和上部土壤层的孔隙内的盐水之间存在电连续性。潮湿的地面比在干燥条件下产生的总功率返回更高,并且场景中雷达暗区和雷达亮区之间的对比度更高。 [参考:20]

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