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Estimation of bioclimatic variables of Mongolia derived from remote sensing data

Frontiers of Earth Science 2022年第2期16卷 323-339页

作者： Munkhdulam OTGONBAYAR Clement ATZBERGER Erdenesukh SUMIYA Sainbayar DALANTAI Jonathan CHAMBERS Institute of Geography and Geoecology Mongolian Academy of Sciences(MAS)Ulaanbaatar 15170Mongolia Institute of Geomatics University of Natural Resources and Life Sciences(BOKU)Vienna 1190Austria School of Arts and Sciences National University of Mongolia(NUM)Ulaanbaatar 14201Mongolia Cooperazione Internazionale Milan 5020151Italy

Global maps of bioclimatic variables currently exist only at very coarse spatial resolution(***).For ecological studies requiring higher resolved information,this spatial resolution is often *** aim of this study is to estimate important bioclimatic variables of Mongolia from Earth Observation(EO)data at a higher spatial resolution of 1 *** analysis used two different satellite time series data sets:land surface temperature(LST)from Moderate Resolution Imaging Spectroradiometer(MODIS),and precipitation(P)from Climate Hazards Group Infrared precipitation with Stations(chirps).Monthly maximum,mean,and minimum air temperature were estimated from Terra MODIS satellite(collection 6)LST time series product using the random forest(RF)regression *** total precipitation data were obtained from chirps version *** on this primary data,spatial maps of 19 bioclimatic variables at a spatial resolution of 1 km were generated,representing the period *** tested the relationship between estimated bioclimatic variables(SatClim)and WorldClim bioclimatic variables version 2.0(WorldClim)using determination coefficient(R^(2)),root mean square error(RMSE),and normalized root mean square error(nRMSE)and found overall good *** the set of 19 WorldClim bioclimatic variables,17 were estimated with a coefficient of determination(R^(2))higher than 0.7 and normalized RMSE(nRMSE)lower than 8%,confirming that the spatial pattern and value ranges can be retrieved from satellite data with much higher spatial resolution compared to *** the two bioclimatic variables related to temperature extremes(i.e.,annual mean diurnal range and isothermality)were modeled with only moderate accuracy(R^(2) of about 0.4 with nRMSE of about 11%).Generally,precipitation-related bioclimatic variables were closer correlated with WorldClim compared to temperature-related bioclimatic *** overall success of the modeling was attributed to the f

关键词： bioclimatic variables MODIS land surface temperature chirps precipitation

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