Soil salinization is a ubiquitous global problem. The literature supports the integration of remote sensing (RS) techniques and field measurements as effective methods for developing soil salinity prediction models. The objectives of this study were to (i) estimate the level of soil salinity in Abu Dhabi using spectral indices and field measurements and (ii) develop a model for detecting and mapping soil salinity variations in the study area using RS data. We integrated Landsat 8 data with the electrical conductivity measurements of soil samples taken from the study area. Statistical analysis of the integrated data showed that the normalized difference vegetation index and bare soil index showed moderate correlations among the examined indices. The relation between these two indices can contribute to the development of successful soil salinity prediction models. Results show that 31% of the soil in the study area is moderately saline and 46% of the soil is highly saline. The results support that geoinformatic techniques using RS data and technologies constitute an effective tool for detecting soil salinity by modeling and mapping the spatial distribution of saline soils. Furthermore, we observed a low correlation between soil salinity and the nighttime land surface temperature.

中文翻译：

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利用遥感数据对干旱地区土壤盐分变化进行检测和建模

土壤盐碱化是一个普遍存在的全球性问题。文献支持将遥感（RS）技术和野外测量相结合，作为开发土壤盐分预测模型的有效方法。这项研究的目的是（i）使用光谱指数和野外测量来估算阿布扎比的土壤盐分水平，以及（ii）使用RS数据建立一个用于检测和绘制研究区域土壤盐分变化的模型。我们将Landsat 8数据与从研究区域获取的土壤样品的电导率测量值进行了集成。对综合数据的统计分析表明，归一化的植被指数和裸土指数在所考察的指数之间显示出中等程度的相关性。这两个指标之间的关系可以为成功的土壤盐分预测模型的发展做出贡献。结果表明，研究区域中31％的土壤为中等盐度，而46％的土壤为高盐度。结果支持使用RS数据和技术的地理信息技术构成了通过对盐渍土壤的空间分布进行建模和绘图来检测土壤盐分的有效工具。此外，我们观察到土壤盐度与夜间陆地表面温度之间的相关性较低。结果支持使用RS数据和技术的地理信息技术构成了通过对盐渍土壤的空间分布进行建模和绘图来检测土壤盐分的有效工具。此外，我们观察到土壤盐度与夜间陆地表面温度之间的相关性较低。结果支持使用RS数据和技术的地理信息技术构成了通过对盐渍土壤的空间分布进行建模和绘图来检测土壤盐分的有效工具。此外，我们观察到土壤盐度与夜间陆地表面温度之间的相关性较低。