Crown area allometries for estimation of aboveground tree biomass in agricultural landscapes of western Kenya uri icon

abstract

  • Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100 km(2) sentry sites in western Kenya. The equations developed fit the data well with about 85 % of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2 % and lowered the relative error by 7 and 2 %, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8 +/- A 0.02 t C ha(-1); which is about 19 % more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees.
  • Classical allometries determine biomass from measurements of diameter at breast height or volume. Neither of these measurements is currently possible to be derived directly from remote sensing. As biomass estimates at larger scales require remotely sensed data, new allometric relations are required using crown area and/or tree height as predictor of biomass, which can both be derived from remote sensing. Allometric equations were developed from 72 trees semi-randomly selected for destructive sampling in three 100 km2 sentry sites in western Kenya. The equations developed fit the data well with about 85 % of the observed variation in aboveground biomass explained by crown area. Addition of height and wood density as second predictor variables improved model fit by 6 and 2 % and lowered the relative error by 7 and 2 %, respectively. The equation with crown area in combination with height and wood density estimated representative aboveground biomass carbon to be about 20.8 ± 0.02 t C haâ??1; which is about 19 % more than the amount estimated using an allometry with diameter at breast height as predictor. These results form the basis for a new generation of allometries using crown area as a predictor of aboveground biomass in agricultural landscapes. Biomass predictions using crown area should be supported by height and wood density and the application of crown area equations for remote sensing based up-scaling should consider crown interactions with competing or coexisting neighboring trees

publication date

  • 2012
  • 2012
  • 2012