Authors:
Dian Novarina, Rudiyanto, Budi Indra Setiawan and Muhajir Utomo
Book:
Proceedings of the 15th International Peat Congress
Venue:
Kuching
Keywords:
carbon-content, carbon-stock, peat-depth, peatland-hydrological-unit-phu
Documentfile:
ipc16p279a379novarinariduyanto.etal_.pdf
Summary:
Accurate estimates of below ground carbon stocks in peat land strongly depend on the peat depth, bulk density and carbon content of peat. The range values of bulk density and carbon content are well known, while peat depth is quite variable depending on locations. This study was addressed at mapping peat depth and estimation of belowground carbon stocks in Meranti, Palawan Regency, Riau Province, Indonesia. Two regression models, artificial neural networks (ANN) and support vector machine (SVM), were compared in modelling and mapping of peat depth. The peatland was delineated according to peatland hydrological unit (PHU) bounded by rivers. The digital elevation and nearest distance to rivers, used as covariates, were derived from DEM SRTM 1 arc (about 30.7…