{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T16:57:21Z","timestamp":1732035441639},"reference-count":50,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,12,24]],"date-time":"2014-12-24T00:00:00Z","timestamp":1419379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The aims are to validate and assess the performances of MODIS gross primary production (MODIS-GPP) and evapotranspiration (MODIS-ET) products in China\u2019s different land cover types and their sensitivity to remote sensing input data. In this study, MODIS-GPP and -ET are evaluated using flux derived\/measured data from eight sites of ChinaFLUX. Results show that MODIS-GPP generally underestimates GPP (R2 is 0.58, bias is \u22126.7 gC\/m2\/8-day and RMSE is 19.4 gC\/m2\/8-day) at all sites and MODIS-ET overestimates ET (R2 is 0.36, bias is 6 mm\/8-day and RMSE is 11 mm\/8-day) when comparing with derived GPP and measured ET, respectively. For evergreen forests, MODIS-GPP gives a poor performance with R2 varying from 0.03 to 0.44; in contrast, MODIS-ET provides more reliable results. In croplands, MODIS-GPP can explain 80% of GPP variance, but it overestimates flux derived GPP in non-growing season and underestimates flux derived GPP in growing season; similar overestimations also presented in MODIS-ET. For grasslands and mixed forests, MODIS-GPP and -ET perform good estimating accuracy. By designing four experimental groups and taking GPP simulation as an example, we suggest that the maximum light use efficiency of croplands should be optimized, and the differences of meteorological data have little impact on GPP estimation, whereas remote sensing leaf area index\/fraction of photo-synthetically active radiation (LAI\/FPAR) can greatly affect GPP\/ET estimations for all land cover types. Thus, accurate remote sensing parameters are important for achieving reliable estimations.<\/jats:p>","DOI":"10.3390\/rs70100135","type":"journal-article","created":{"date-parts":[[2014,12,26]],"date-time":"2014-12-26T10:52:39Z","timestamp":1419591159000},"page":"135-152","source":"Crossref","is-referenced-by-count":65,"title":["The Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR\/LAI)"],"prefix":"10.3390","volume":"7","author":[{"given":"Zhengjia","family":"Liu","sequence":"first","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Quanqin","family":"Shao","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jiyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2014,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1016\/j.rse.2007.02.004","article-title":"Comparison of MODIS gross primary production estimates for forests across the U.S.A. with those generated by a simple process model, 3-PGS","volume":"109","author":"Nightingale","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"D08S11","DOI":"10.1029\/2005JD006017","article-title":"Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity","volume":"111","author":"Gitelson","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1126\/science.1192666","article-title":"Drought-induced reduction in global terrestrial net primary production from 2000 through 2009","volume":"329","author":"Zhao","year":"2010","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1126\/science.1184984","article-title":"Terrestrial gross carbon dioxide uptake: Global distribution and covariation with climate","volume":"329","author":"Beer","year":"2010","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3424","DOI":"10.1016\/j.rse.2011.08.006","article-title":"Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration","volume":"115","author":"Wu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1016\/S0034-4257(02)00074-3","article-title":"Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data","volume":"83","author":"Myneni","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.rse.2007.08.004","article-title":"A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS","volume":"112","author":"Sims","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.rse.2004.03.010","article-title":"Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data","volume":"91","author":"Xiao","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0022-1694(99)00202-4","article-title":"SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey","volume":"229","author":"Bastiaanssen","year":"2000","journal-title":"J. Hydrol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"D15107","DOI":"10.1029\/2006JD008351","article-title":"A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature","volume":"112","author":"Wang","year":"2007","journal-title":"J. Geophys. Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3187","DOI":"10.1016\/j.rse.2011.07.004","article-title":"An intercomparison of three remote sensing-based energy balance models using Large Aperture Scintillometer measurements over a wheat-corn production region","volume":"115","author":"Tang","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.rse.2014.03.006","article-title":"A MODIS-based Photosynthetic Capacity Model to estimate gross primary production in Northern China and the Tibetan Plateau","volume":"148","author":"Gao","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.rse.2013.03.033","article-title":"Phenology and gross primary production of two dominant savanna woodland ecosystems in Southern Africa","volume":"135","author":"Jin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1016\/j.rse.2007.04.015","article-title":"Development of a global evapotranspiration algorithm based on MODIS and global meteorology data","volume":"111","author":"Mu","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1781","DOI":"10.1016\/j.rse.2011.02.019","article-title":"Improvements to a MODIS global terrestrial evapotranspiration algorithm","volume":"115","author":"Mu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.rse.2003.06.005","article-title":"Scaling gross primary production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation","volume":"88","author":"Turner","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.rse.2004.12.011","article-title":"Improvements of the MODIS terrestrial gross and net primary production global data set","volume":"95","author":"Zhao","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1416","DOI":"10.1016\/j.rse.2010.01.022","article-title":"Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data","volume":"114","author":"Yuan","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2925","DOI":"10.1016\/j.rse.2010.07.012","article-title":"Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest","volume":"114","author":"Wu","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.agrformet.2006.02.011","article-title":"Overview of ChinaFLUX and evaluation of its eddy covariance measurement","volume":"137","author":"Yu","year":"2006","journal-title":"Agric. For. Meteorol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1111\/gcb.12079","article-title":"Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China","volume":"19","author":"Yu","year":"2013","journal-title":"Glob. Chang. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"G01002","DOI":"10.1029\/2004JG000004","article-title":"Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalyses","volume":"111","author":"Zhao","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_23","first-page":"205","article-title":"Evaporation and environment","volume":"19","author":"Monteith","year":"1965","journal-title":"Symp. Soc. Exp. Biol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"2436","DOI":"10.3390\/rs5052436","article-title":"The Global Land Surface Satellite (GLASS) remote sensing data processing system and products","volume":"5","author":"Zhao","year":"2013","journal-title":"Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1080\/17538947.2013.805262","article-title":"A long-term global land surface satellite (GLASS) data-set for environmental studies","volume":"6","author":"Liang","year":"2013","journal-title":"Int. J. Dight. Earth"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/TGRS.2013.2237780","article-title":"Use of general regression neural networks for generating the GLASS leaf area index product from time-series MODIS surface reflectance","volume":"52","author":"Xiao","year":"2014","journal-title":"IEEE Tran. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"GB1019","DOI":"10.1029\/2010GB003996","article-title":"Effects of foliage clumping on the estimation of global terrestrial gross primary productivity","volume":"26","author":"Chen","year":"2012","journal-title":"Glob. Biogeochem. Cy."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"10215","DOI":"10.3390\/rs61010215","article-title":"Comparison of different GPP models in China using MODIS Image and ChinaFLUX data","volume":"6","author":"Liu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1111\/j.1365-2486.2008.01538.x","article-title":"Calibration of Terra\/MODIS gross primary production over an irrigated cropland on the North China Plain and an alpine meadow on the Tibetan Plateau","volume":"14","author":"Zhang","year":"2008","journal-title":"Glob. Chang. Biol."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"8280","DOI":"10.1080\/01431161.2013.834394","article-title":"A method for estimating the gross primary production of alpine meadows using MODIS and climate data in China","volume":"34","author":"Li","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"303","DOI":"10.3390\/rs4010303","article-title":"Exploring simple algorithms for estimating gross primary production in forested areas from satellite data","volume":"4","author":"Hashimoto","year":"2012","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.1109\/36.868894","article-title":"Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data","volume":"38","author":"Tian","year":"2000","journal-title":"IEEE Tran. Geosci. Remote"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1046\/j.1365-2486.1999.00007.x","article-title":"Comparing global models of terrestrial net primary productivity (NPP): Analysis of differences in light absorption and light-use efficiency","volume":"5","author":"Ruimy","year":"1999","journal-title":"Glob. Chang. Biol."},{"key":"ref_35","first-page":"L17403","article-title":"New developments in the remote estimation of the fraction of absorbed photosynthetically active radiation in crops","volume":"32","author":"Gitelson","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"27735","DOI":"10.1029\/1999JD900768","article-title":"Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data","volume":"104","author":"Liu","year":"1999","journal-title":"J. Geophys. Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.ecolmodel.2007.06.032","article-title":"Remote sensing-based ecosystem-atmosphere simulation scheme (EASS)\u2014Model formulation and test with multiple-year data","volume":"209","author":"Chen","year":"2007","journal-title":"Ecol. Model."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1002\/joc.893","article-title":"The evolution of, and revolution in, land surface schemes designed for climate models","volume":"23","author":"Pitman","year":"2003","journal-title":"Int. J. Climatol."},{"key":"ref_39","first-page":"70","article-title":"Primary production and turnover of organic matter in different forest ecosystems of the western Pacific","volume":"17","author":"Kira","year":"1967","journal-title":"Jap. J. Ecol."},{"key":"ref_40","unstructured":"Waring, R.H., and Schlesinger, W.H. (1985). Forest Ecosystems: Concepts and Management, Academic Press."},{"key":"ref_41","first-page":"49","article-title":"Validation of the feasibility of MOD16 algorithm for estimating crop field vapor flux in North China Plain","volume":"59","author":"Sun","year":"2004","journal-title":"Acta Geogra. Sini."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Prince, S.D., and Goward, S.N. (1995). Global primary production: A remote sensing approach. J. Biogeogr.","DOI":"10.2307\/2845983"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1016\/S0378-1127(97)00026-1","article-title":"A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning","volume":"95","author":"Landsberg","year":"1997","journal-title":"For. Ecol. Manag."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s003820050007","article-title":"Simulated impacts of historical land cover changes on global climate in northern winter","volume":"16","author":"Chase","year":"2000","journal-title":"Clim. Dynam."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/S0034-4257(02)00043-3","article-title":"Estimation of carbon mass fluxes over Europe using the C-Fix model and Euroflux data","volume":"83","author":"Veroustraete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.agrformet.2006.12.001","article-title":"Deriving a light use efficiency model from eddy covariance flux data for predicting daily gross primary production across biomes","volume":"143","author":"Yuan","year":"2007","journal-title":"Agric. For. Meteorol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1016\/j.rse.2005.09.009","article-title":"Estimating light absorption by chlorophyll, leaf and canopy in a deciduous broadleaf forest using MODIS data and a radiative transfer model","volume":"99","author":"Zhang","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.rse.2006.06.013","article-title":"Characterization of seasonal variation of forest canopy in a temperate deciduous broadleaf forest, using daily MODIS data","volume":"105","author":"Zhang","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"880","DOI":"10.1016\/j.rse.2009.01.002","article-title":"Can a satellite-derived estimate of the fraction of PAR absorbed by chlorophyll (FAPARchl) improve predictions of light-use efficiency and ecosystem photosynthesis for a boreal aspen forest?","volume":"113","author":"Zhang","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.agrformet.2014.01.006","article-title":"Impacts of light use efficiency and fPAR parameterization on gross primary production modeling","volume":"189","author":"Cheng","year":"2014","journal-title":"Agric. For. Meteorol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/135\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T01:03:55Z","timestamp":1717376635000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/135"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,24]]},"references-count":50,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,1]]}},"alternative-id":["rs7010135"],"URL":"https:\/\/doi.org\/10.3390\/rs70100135","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,24]]}}}  <script>parent.window.postMessage('ixistenz.url:https://api.crossref.org/works/10.3390%2FRS70100135', '*'); </script> <div id='browserdiffcontainer' style='position: fixed; right: 10px; top: 10vh; min-width: 60px;  border: 1px solid white; background: rgb(251, 189, 0);; opacity: 0.9; font-family: helvetica, arial, sans serif;  font-size: 12px; z-index: 20001; padding-bottom: 20px;'><div onclick="toggle('browserdiffcontainerlist'); return false;" style='background: rgb(151, 89, 0);; color: white; '><strong>&nbsp; <span class='glyphicon glyphicon-minus'></span> NODES</strong></div><div id='browserdiffcontainerlist' style='padding-left: 10px; padding-right: 5px; max-height: 50vh; overflow: auto; '></div></div>
<script>
function toggle( divname ) {
  var x = document.getElementById( divname );
  if (x.style.display === 'none') {
    x.style.display = 'block';
  } else {
    x.style.display = 'none';
  }
} </script>