Current Browsing: Tianlulogui Watershed


Spatial distribution of forest biomass 1m resolution in Tianlaochi watershed (1961-2010)

The sample plot survey data are as follows: in August 2013, 30 forest sample plots were set up in tianlaochi basin, with the sample plot specification of 10 m×20 m, and the long side of the sample plot was parallel to the slope direction, including 26 Qinghai spruce forests, 2 Qilian yuanberlin forests and 2 spruce-cypress mixed forests. within the sample plot, the diameter at breast height (diameter at trunk height of 1.3 m) of each tree was measured by using a ruler. Using hand-held ultrasonic altimeter to measure the tree height and the height under branches (the height of the first living branch at the lower end of the crown) of each tree, measuring the crown width in the north-south direction and the east-west direction by using a tape scale, and positioning the sample plot by using differential GPS. Taking the carbon storage data of the sample plot as the optimal control condition, using Kriging interpolation to obtain the biomass spatial distribution map driving field, using HASM algorithm to simulate the forest biomass spatial distribution map of the waterlogging pool, the simulation results conform to the vegetation distribution law of the study area, and obtain better effects. Resolution 1m

2020-07-29

Spatial distribution data of forest biomass in tianlouchi watershed of Heihe river (August 2013)

The sample plot survey data are as follows: in August 2013, 30 forest sample plots were set up in tianlaochi basin, with the sample plot specification of 10 m×20 m, and the long side of the sample plot was parallel to the slope direction, including 26 Qinghai spruce forests, 2 Qilian yuanberlin forests and 2 spruce-cypress mixed forests. within the sample plot, the diameter at breast height (diameter at trunk height of 1.3 m) of each tree was measured by using a ruler. Using hand-held ultrasonic altimeter to measure the tree height and the height under branches (the height of the first living branch at the lower end of the crown) of each tree, measuring the crown width in the north-south direction and the east-west direction by using a tape scale, and positioning the sample plot by using differential GPS. Taking the carbon storage data of the sample plot as the optimal control condition, using Kriging interpolation to obtain the biomass spatial distribution map driving field, using HASM algorithm to simulate the forest biomass spatial distribution map of the waterlogging pool, the simulation results conform to the vegetation distribution law of the study area, and obtain better effects.

2020-07-28