Počet záznamů: 1
Synergistic Use of Multispectral Data and Crop Growth Modelling for Spatial and Temporal Evapotranspiration Estimations
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SYSNO ASEP 0543530 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Synergistic Use of Multispectral Data and Crop Growth Modelling for Spatial and Temporal Evapotranspiration Estimations Tvůrce(i) Silvestro, P. C. (IT)
Casa, R. (IT)
Hanuš, Jan (UEK-B) RID, SAI, ORCID
Koetz, B. (IT)
Rascher, U. (DE)
Schuettemeyer, D. (NL)
Siegmann, B. (DE)
Skokovic, D. (ES)
Sobrino, J. (ES)
Tudoroiu, M. (IT)Celkový počet autorů 10 Číslo článku 2138 Zdroj.dok. Remote Sensing. - : MDPI
Roč. 13, č. 11 (2021)Poč.str. 25 s. Jazyk dok. eng - angličtina Země vyd. CH - Švýcarsko Klíč. slova data assimilation ; simple algorithm ; wheat yield ; biomass ; ensemble ; sentinel-2 ; field ; lai ; aquacrop ; support ; ensemble Kalman filter (EnKF) ; Sentinel-2 ; simple algorithm for yield (SAFY) ; land surface temperature monitoring (LSTM) ; data assimilation (DA) ; leaf area index (LAI) Vědní obor RIV EH - Ekologie - společenstva Obor OECD Environmental sciences (social aspects to be 5.7) Výzkumná infrastruktura CzeCOS III - 90123 - Ústav výzkumu globální změny AV ČR, v. v. i. Způsob publikování Open access Institucionální podpora UEK-B - RVO:86652079 UT WOS 000660619600001 EID SCOPUS 85107896635 DOI 10.3390/rs13112138 Anotace The aim of this research is to explore the analysis of methods allowing a synergetic use of information exchange between Earth Observation (EO) data and growth models in order to provide high spatial and temporal resolution actual evapotranspiration predictions. An assimilation method based on the Ensemble Kalman Filter algorithm allows for combining Sentinel-2 data with a new version of Simple Algorithm For Yield (SAFY_swb) that considers the effect of the water balance on yield and estimates the daily trend of evapotranspiration (ET). Our study is relevant in the context of demonstrating the effectiveness and necessity of satellite missions such as Land Surface Temperature Monitoring (LSTM), to provide high spatial and temporal resolution data for agriculture. The proposed method addresses the problem both from a spatial point of view, providing maps of the areas of interest of the main biophysical quantities of vegetation (LAI, biomass, yield and actual Evapotranspiration), and from a temporal point of view, providing a simulation on a daily basis of the aforementioned variables. The assimilation efficiency was initially evaluated with a synthetic, large and heterogeneous dataset, reaching values of 70% even for high measurement errors of the assimilated variable. Subsequently, the method was tested in a case study in central Italy, allowing estimates of the daily Actual Evapotranspiration with a relative RMSE of 18%. The novelty of this research is in proposing a solution that partially solves the main problems related to the synergistic use of EO data with crop growth models, such as the difficult calibration of initial parameters, the lack of frequent high-resolution data or the high computational cost of data assimilation methods. It opens the way to future developments, such as the use of simultaneous assimilation of multiple variables, to deeper investigations using more specific datasets and exploiting the advanced tools. Pracoviště Ústav výzkumu globální změny Kontakt Nikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268 Rok sběru 2022 Elektronická adresa https://www.mdpi.com/2072-4292/13/11/2138
Počet záznamů: 1