Dust Outbreaks across East Iran: Application of Multi-Source Remote Sensing Data (AMSR-E and FengYun3-MWRI) on the Effects of Soil Moisture

Abouzar Mehraban, Yansong Bao, Emmanuel Yeboah, Benedicta Akua Sarfo, Michael Kpakpo Allotey, Charafa El Rhadiouini, B. Aikins, Desmond Nii Ayitey Mettle-Nunoo, Michael Atuahene Djan, A. Okrah, I. Sarfo
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Abstract

One of the most significant hydro-meteorological and agricultural variables is soil moisture, yet measuring it remains a difficult task. Due to the significant spatial fluctuation of soil moisture, it is difficult to quantify it in a particular spot or field across a sizable region. Despite the thermal band's limitations in assessing soil moisture, MODIS and AVHRR, which are inappropriate were utilized in this investigation. The study examined the impact of soil moisture on dust outbreak. Soil moisture in the study domain was monitored using field techniques and the hybrid model. It combined multi-sourced remote sensing data, obtained from AMSER-E and FY-3 satellites.  AMSER-E satellite measures the light temperature in five frequencies ranging from 6. 9 to 89 GHz based on data obtained from AMSER-E. Findings revealed areas with a spatial scale of 25 km2 has a 12-hour time step or variability in dust storm, thereby influencing soil moisture content within the zone of study. In addition to introducing acceptable potentials of the passive microwave band for accurate and applied monitoring of the soil moisture, the present results are viewed as a reliable source for studies on drought in time scale. The study shows that Zabol in Sistan has the highest annual average of 80.7 dust storm days. Soil moisture estimates serve a great deal for preparing soil moisture maps and the evaluation of temporal and spatial variations of soil moisture in study region to address issues related to dust storms. In order to identify the areas affected by dust storms and understand how dust particles are dispersed in the Sistan region, satellite image processing was employed using MODIS 1 sensor images obtained from the TERRA satellite.
伊朗东部沙尘暴发:多源遥感数据(AMSR-E)和风云3- mwri对土壤水分影响的应用
最重要的水文气象和农业变量之一是土壤湿度,但测量它仍然是一项艰巨的任务。由于土壤湿度的空间波动较大,因此很难在一个相当大的区域内对特定地点或田地的土壤湿度进行量化。尽管热带在评估土壤湿度方面存在局限性,但本研究还是采用了不合适的MODIS和AVHRR。该研究考察了土壤湿度对沙尘爆发的影响。采用田间技术和混合模型对研究区土壤水分进行监测。它结合了从AMSER-E和FY-3卫星获得的多源遥感数据。AMSER-E卫星测量从6到6的5个频率的光温度。基于AMSER-E获得的数据。结果表明,在25 km2的空间尺度上,沙尘暴具有12小时的时间步长或变率,从而影响了研究区内的土壤含水量。除了引入被动微波波段对土壤湿度进行准确和应用监测的可接受潜力之外,本研究结果被视为在时间尺度上研究干旱的可靠来源。研究表明,锡斯坦的Zabol年平均沙尘暴天数最高,为80.7天。土壤湿度估算对研究区土壤湿度地图的编制和土壤湿度时空变化的评价具有重要意义,可用于研究沙尘暴相关问题。为了确定锡斯坦地区受沙尘暴影响的区域,了解沙尘颗粒的扩散方式,利用TERRA卫星获得的MODIS 1传感器图像进行卫星图像处理。
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