Estimation of surface soil moisture using sar images sentinel 1 satellite with ten cm resolution
محورهای موضوعی : فصلنامه علمی پژوهشی سنجش از دور راداری و نوری و سیستم اطلاعات جغرافیایی
Mehran Alizadeh Pirbasti
1
,
Seyyed Ali Almodaresi
2
1 - Hekmat Institute of Qom
2 - Associate professor, GIS and RS Department, Yazd Branch, Islamic Azad University, Yazd, Iran
کلید واژه: remote sensing, radar images of the SAR, Sentinel 1 , soil moisture,
چکیده مقاله :
In this research, soil moisture determination has been calculated using radar data . In fact, calculate the soil moisture with Sentinel- 1 is done . Soil moisture is very important in the water cycle . Also, in matters related to agriculture Can be an indicator for drought . As a result, decision-making organizations , agricultural institutions and farmers Can use the processed information. One of the applications of soil moisture determination is to identify anomalies and natural disasters such as drought, floods and landslides . To do this, time series images must be analyzed to design a highly reliable method.The main reason given Radar detectors are not dependent on weather conditions and shooting time, they have high performance in different areas. Data Sentinel 1 with a resolution of 10 meters as data The main ones were used . There is currently no satellite other than Sentinel 1 that provides data with this accuracy for free. Also preprocessed data landcover classification As a feature Inputs to the classification algorithm were used . From the data FLDAS We used it as a classification target . Data The use of water-depth of 0 to 10 cm, which operates the Sentinel 1 is close( wavelength of 5 cm ) .For implementation of cloud computing environment GEE ( Google Earth Engine )We benefited . In this category handle Different data sets are available, it has high processing power and its coding space is not complicated.
In this research, soil moisture determination has been calculated using radar data . In fact, calculate the soil moisture with Sentinel- 1 is done . Soil moisture is very important in the water cycle . Also, in matters related to agriculture Can be an indicator for drought . As a result, decision-making organizations , agricultural institutions and farmers Can use the processed information. One of the applications of soil moisture determination is to identify anomalies and natural disasters such as drought, floods and landslides . To do this, time series images must be analyzed to design a highly reliable method.The main reason given Radar detectors are not dependent on weather conditions and shooting time, they have high performance in different areas. Data Sentinel 1 with a resolution of 10 meters as data The main ones were used . There is currently no satellite other than Sentinel 1 that provides data with this accuracy for free. Also preprocessed data landcover classification As a feature Inputs to the classification algorithm were used . From the data FLDAS We used it as a classification target . Data The use of water-depth of 0 to 10 cm, which operates the Sentinel 1 is close( wavelength of 5 cm ) .For implementation of cloud computing environment GEE ( Google Earth Engine )We benefited . In this category handle Different data sets are available, it has high processing power and its coding space is not complicated.
