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Research on Soil Moisture Remote Sensing Monitoring Based on EOS/MODIS Data |
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Abstract: Since the plan of EOS was carried out in 1991, the sensor of EOS/MODIS, with high temporal resolution, high spectrum resolution and normalized spatial resolution, has shown its advantages in the drought remote sensing monitoring. The studies on the soil moisture remote sensing monitoring based on EOS/MODIS data are reviewed in the following 5 aspects: ① The models based on the Vegetation Index, such as Simple Vegetation Index, Ratio Vegetation Index, Normalized Difference Vegetation Index, Enhanced Vegetation Index, Normalized Difference Water Index, Vegetation Condition Index, Average Vegetation Index etc. ② The models based on the infrared spectrum, such as Perpendicular Drought Index, Modified Perpendicular Drought Index, etc. ③ The models based on the Land Surface Temperature, such as Appearance Thermal Initial, Temperature Condition Index, Normalized Difference Temperature Index and Appearance Vegetation Drought Index, etc. ④ The models based on the combination of Vegetation Index and Land Surface Temperature. Such as Vegetation-Temperature Condition Index, Vegetation Index/Temperature Trapezoid, Temperature Vegetation Dryness Index, Crop Water Stress Index, etc. ⑤ The models based on the NDVI and soil background. Such as Surface Water Capacity Index, Modified Surface Water Capacity Index, etc. This paper focuses on the models with obvious physical meaning and with wide applications in practical work, such as Modified Perpendicular Drought Index (MPDI), Crop Water Stress Index (CWSI), Surface Water Capacity Index (SWCI) and Appearance Thermal Initial (ATI). The research directions of agricultural drought monitoring based on EOS/MODIS and FY-3 data are discussed. The cycle observation of "Soil-Crop-Atmosphere" and Multi-knowledge syntheses may achieve quantified monitoring. Some future research topics of remote sensing monitoring in soil moisture are proposed.
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Received: 12 May 2009
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