caa a22 4500 445893656 CHVBK 20180317145624.0 cr unu---uuuuu 170323e20110201xx s 000 0 eng 10.1007/s10750-010-0465-7 doi (NATIONALLICENCE)springer-10.1007/s10750-010-0465-7 Accuracy assessment of supervised classification of submersed macrophytes: the case of the Gavaraget region of Lake Sevan, Armenia [Elektronische Daten] [T. Agyemang, J. Heblinski, K. Schmieder, H. Sajadyan, L. Vardanyan] The necessity of assessing the accuracy of spatial data derived from remote sensing methods and used in geographic information system (GIS) analyses has been regarded as a critical component of many projects. In this article, supervised classified QuickBird satellite imageries of submersed macrophytes of the Gavaraget region of Lake Sevan (Armenia) during 2006-2008 are validated in a GIS environment. The results of this assessment are represented by error matrices presenting the overall accuracy, the user and producer accuracies in each category, as well as the kappa coefficients. The assessments were done at three levels: the vegetation types, the growth (vertical) type, and the species levels. At the vegetation level, an overall accuracy of more than 86% was achieved in 2006 and 2007, while that in 2008 was about 72%. Substantial agreements were achieved between the classified remote sensing data and the reference (groundtruth) data for both 2006 and 2007. Only a fair agreement was attained in 2008. The kappa coefficients ranged from 0.39 to 0.89. At the growth type level, only the 2006 classification attained a substantial agreement, with an overall accuracy of 80%. The 2007 and 2008 classifications had above average and average overall accuracies of 72 and 64%, respectively. The kappa coefficient had a lowest value of 0.35 and a highest value of 0.70 at the growth type level. At the species level, Chara spp. or Zannichellia palustris and Potamogeton pectinatus had high user accuracies of more than 90% and a high overall accuracy of 82% in 2006. High user accuracies (>80%) occurred for P. pectinatus (for 2007 and 2008) and No Vegetation (for 2007). The remaining species, however, had low user and producer accuracies of less than 64%. The kappa coefficients ranged between 0.36 and 0.73 at the species level. Springer Science+Business Media B.V., 2010 Submersed macrophytes nationallicence Lake Sevan nationallicence GIS nationallicence Accuracy assessment nationallicence Supervised classification nationallicence Error matrix nationallicence Agyemang T. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut Heblinski J. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut Schmieder K. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut Sajadyan H. State Agrarian University, Yerevan, Armenia aut Vardanyan L. Department of Biology, University of Venevan, Martuni, Armenia aut Hydrobiologia Springer Netherlands 661/1(2011-02-01), 85-96 0018-8158 661:1<85 2011 661 10750 https://doi.org/10.1007/s10750-010-0465-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10750-010-0465-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Agyemang T. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut NATIONALLICENCE 700 1- Heblinski J. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut NATIONALLICENCE 700 1- Schmieder K. Institute of Landscape & Plant Ecology, University of Hohenheim, Stuttgart, Germany aut NATIONALLICENCE 700 1- Sajadyan H. State Agrarian University, Yerevan, Armenia aut NATIONALLICENCE 700 1- Vardanyan L. Department of Biology, University of Venevan, Martuni, Armenia aut NATIONALLICENCE 773 0- Hydrobiologia Springer Netherlands 661/1(2011-02-01), 85-96 0018-8158 661:1<85 2011 661 10750 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer