Primary Production Estimation of Cankiri Province's Rangelands Using Light Use Efficiency (LUE) Model with Satellite Data and AgrometShell Module


Unal E., BAYRAMİN İ.

JOURNAL OF AGRICULTURAL SCIENCES-TARIM BILIMLERI DERGISI, cilt.22, sa.4, ss.555-565, 2016 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 4
  • Basım Tarihi: 2016
  • Doi Numarası: 10.1501/tarimbil_0000001414
  • Dergi Adı: JOURNAL OF AGRICULTURAL SCIENCES-TARIM BILIMLERI DERGISI
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.555-565
  • Anahtar Kelimeler: Biomass, Cankiri, Range, Remote sensing, Vegetation, REMOTE, GRASSLANDS
  • Ankara Üniversitesi Adresli: Evet

Özet

In this study, monthly and annual gross primary production (GPP) of rangelands in Cankiri province for the period of 2000-2009 was calculated using light use efficiency (LUE) model with the inputs of satellite data and AgrometShell module. The average production of rangelands varied seasonally and annually (from 12630 to 37701 tons) and was approximately 17800 tons for the last ten years. The amount of rainfall and changing number of animal grazing in the region probably led to the variation. Model performance was tested with integrated normalized difference vegetation index (INDVI) approach which produced a moderate significant correlation (R-2= 0.69, P<0.05) between LUE model gross primary productivity (GPP) output and INDVI values. On the other hand, comparison of modelled results of annual gross primary production (GPP) with above ground measurements, indicated that correlation between the variables were insignificant (r = 0.60, P>0.05 for 2008, r= 0.41, P>0.05 for 2009) due to some factors such as sampled plant type, scale differences between satellite data and ground sample size, and subjective sampling errors. This study indicates that LUE Model together with the inputs of AgrometShell module is suitable tool for estimation of rangeland primary production.