Dynamická korekce vlivu vegetace při modelování půdní vlhkosti ze SAR dat při užití modelu detekce změn

Abstract

In times of climate change, soil moisture monitoring is an important aspect for its understanding and possibly mitigation. SAR data with high spatial resolution is an important tool for this purpose. This thesis deals with their use in SM retrieval from Sentinel-1 satellite data. The applied change detection model is further calibrated in order to remove the influence of vegetation on the resulting SM estimates by using the SAR variable cross-polarisation ratio. The RMSD decreased by 7% and the correlation increased by 8% using the calibration. The results presented do not achieve the accuracy of the ASCAT SM product but indicate the potential for vegetation correction using the Cross-polarization Ratio variable in further research to obtain a higher spatial resolution SM product. Keywords: surface soil moisture, soil moisture retrieval, Sentinel-1, SM Change detection, vegetation correction Abstrakt: V dob klimatick˝ch zm n je sledování p dní vlhkosti d leûit˝m aspektem pro její pochopení. a p ípadné zmírn ní jejího dopadu. Data SAR s vysok˝m pros- torov˝m rozliöením jsou pro tento ú el d leûit˝m nástrojem. Tento práce se zab˝vá jejich vyuûitím p i získávání SM z dat druûice Sentinel-1. Pouûit˝ model detekce zm n je dále kalibrován za ú elem odstran ní vlivu vegetace na v˝sledné odhady SM pomocí...

In times of climate change, soil moisture monitoring is an important aspect for its understanding and possibly mitigation. SAR data with high spatial resolution is an important tool for this purpose. This thesis deals with their use in SM retrieval from Sentinel-1 satellite data. The applied change detection model is further calibrated in order to remove the influence of vegetation on the resulting SM estimates by using the SAR variable cross-polarisation ratio. The RMSD decreased by 7% and the correlation increased by 8% using the calibration. The results presented do not achieve the accuracy of the ASCAT SM product but indicate the potential for vegetation correction using the Cross-polarization Ratio variable in further research to obtain a higher spatial resolution SM product. Keywords: surface soil moisture, soil moisture retrieval, Sentinel-1, SM Change detection, vegetation correction Abstrakt: V dob klimatick˝ch zm n je sledování p dní vlhkosti d leûit˝m aspektem pro její pochopení. a p ípadné zmírn ní jejího dopadu. Data SAR s vysok˝m pros- torov˝m rozliöením jsou pro tento ú el d leûit˝m nástrojem. Tento práce se zab˝vá jejich vyuûitím p i získávání SM z dat druûice Sentinel-1. Pouûit˝ model detekce zm n je dále kalibrován za ú elem odstran ní vlivu vegetace na v˝sledné odhady SM pomocí...