2026-04-13T14:25:44Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4168212026-03-20T05:41:59Zcom_2072_1033col_2072_452950

urn:hdl:2117/416821 An efficient technique for rapid estimation of flood water levels: combining CYGNSS GNSS-R L1 data with DTMS Ma, Zhongmin Zhang, Shuangcheng Hyuk, Park Camps Carmona, Adriano José Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços GNSS-R CYGNSS Flood Water level Water extent Numerous studies have demonstrated the effectiveness of CYGNSS data for flood detection and mapping. However, the vast majority of the studies only focuses on flood extent detection, ignoring the importance of flood water levels in post-disaster relief. Meanwhile, most of the existing studies on inland water levels altimetry using CYGNSS data are based on the CYGNSS raw IF data using either the time-delay method or the phase method for altimetry. Although high accuracy can be obtained, at present the CYGNSS raw IF data is not a standard data, so it cannot be applied to the study of emergency flooding events. Given the above research gaps, this study proposes an effective method to combine CYGNSS L1 standard data with DTM for rapid estimation of flood water levels. The effectiveness of the proposed methodology is validated using the case of the 2022 Pakistan mega-flood. Comparison with ICESat-2 altimetry data gives encouraging results. This research was funded by the National Natural Science Foundation of China Projects (Grant No.42074041); The National Key Research and Development Program of China (Grant No.2020YFC1512000); State Key Laboratory of GeoInformation Engineering (Grant No. SKLGIE2022-ZZ2-07); The Fundamental Research Funds for the Central Universities (CHD300102263715). This research has also been partially funded by the project “GENESIS: GNSS Environmental and Societal Missions – Subproject UPC”, Grant PID2021-126436OB-C21 funded by the Ministerio de Ciencia e Investigación (MCIN)/Agencia Estatal de Investigación (AEI)/10.13039/501100011033 and EU FEDER “Una manera de hacer Europa”. Zhongmin Ma's work was partly supported by the China Scholarship Council (CSC) through a State Scholarship Fund (No. 202306560073). Peer Reviewed Postprint (author's final draft) 2024 Conference report https://ieeexplore.ieee.org/document/10641722 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126436OB-C21/ES/GNSS ENVIRONMENTAL AND SOCIETAL MISSIONS - SUBPROJECT UPC/ Open Access Institute of Electrical and Electronics Engineers (IEEE)