The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging(LiDAR) data.A digi...The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging(LiDAR) data.A digital canopy model(DCM),generated from the LiDAR data,was combined with aerial photography for segmenting crowns of individual trees.To eliminate errors in over and under-segmentation,the combined image was smoothed using a Gaussian filtering method.The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method.After measuring the crown area from the segmented individual trees,the individual tree diameter at breast height(DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area.The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute.The carbon storage,based on individual trees,was estimated by simple multiplication using the carbon conversion index(0.5),as suggested in guidelines from the Intergovernmental Panel on Climate Change.The mean carbon storage per individual tree was estimated and then compared with the field-measured value.This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.展开更多
To predict changes in South Korean vegetation distribution,the Warmth Index(WI) and the Minimum Temperature of the Coldest Month Index(MTCI) were used.Historical climate data of the past 30 years,from 1971 to 2000,was...To predict changes in South Korean vegetation distribution,the Warmth Index(WI) and the Minimum Temperature of the Coldest Month Index(MTCI) were used.Historical climate data of the past 30 years,from 1971 to 2000,was obtained from the Korea Meteorological Administration.The Fifth-Generation National Center for Atmospheric Research(NCAR) /Penn State Mesoscale Model(MM5) was used as a source for future climatic data under the A1B scenario from the Special Report on Emission Scenario(SRES) of the Intergovernmental Panel on Climate Change(IPCC).To simulate future vegetation distribution due to climate change,the optimal habitat ranges of Korean tree species were delimited by the thermal gradient indices,such as WI and MTCI.To categorize the Thermal Analogy Groups(TAGs) for the tree species,the WI and MTCI were orthogonally plotted on a two-dimensional grid map.The TAGs were then designated by the analogue composition of tree species belonging to the optimal WI and MTCI ranges.As a result of the clustering process,22 TAGs were generated to explain the forest vegetation distribution in Korea.The primary change in distribution for these TAGs will likely be in the shrinkage of areas for the TAGs related to Pinus densiflora and P.koraiensis,and in the expansion of the other TAG areas,mainly occupied by evergreen broad-leaved trees,such as Camellia japonica,Cyclobalanopsis glauca,and Schima superba.Using the TAGs to explain the effects of climate change on vegetation distribution on a more regional scale resulted in greater detail than previously used global or continental scale vegetation models.展开更多
基金the support of the ‘Public Applications Research of Satellite Data Project’ (Grant No. FR09662). provided by the Korea Aerospace Research Institutesupported by a research grant from the Korea Science and Engineering Foundation (KOSEF) (Grant No. A307-K001)
文摘The objective of this study was to estimate the carbon storage capacity of Pinus densiflora stands using remotely sensed data by combining digital aerial photography with light detection and ranging(LiDAR) data.A digital canopy model(DCM),generated from the LiDAR data,was combined with aerial photography for segmenting crowns of individual trees.To eliminate errors in over and under-segmentation,the combined image was smoothed using a Gaussian filtering method.The processed image was then segmented into individual trees using a marker-controlled watershed segmentation method.After measuring the crown area from the segmented individual trees,the individual tree diameter at breast height(DBH) was estimated using a regression function developed from the relationship observed between the field-measured DBH and crown area.The above ground biomass of individual trees could be calculated by an image-derived DBH using a regression function developed by the Korea Forest Research Institute.The carbon storage,based on individual trees,was estimated by simple multiplication using the carbon conversion index(0.5),as suggested in guidelines from the Intergovernmental Panel on Climate Change.The mean carbon storage per individual tree was estimated and then compared with the field-measured value.This study suggested that the biomass and carbon storage in a large forest area can be effectively estimated using aerial photographs and LiDAR data.
基金supported by the Korea Forest Research Institute research project "Impact Assessment of Climate Change on Forest Ecosystem and Development of Adaptation Strategies" (Grant No. FE 0100-2009-01) a research grant from the Korea Science and Engineering Foundation (Grant No. A307-K001)
文摘To predict changes in South Korean vegetation distribution,the Warmth Index(WI) and the Minimum Temperature of the Coldest Month Index(MTCI) were used.Historical climate data of the past 30 years,from 1971 to 2000,was obtained from the Korea Meteorological Administration.The Fifth-Generation National Center for Atmospheric Research(NCAR) /Penn State Mesoscale Model(MM5) was used as a source for future climatic data under the A1B scenario from the Special Report on Emission Scenario(SRES) of the Intergovernmental Panel on Climate Change(IPCC).To simulate future vegetation distribution due to climate change,the optimal habitat ranges of Korean tree species were delimited by the thermal gradient indices,such as WI and MTCI.To categorize the Thermal Analogy Groups(TAGs) for the tree species,the WI and MTCI were orthogonally plotted on a two-dimensional grid map.The TAGs were then designated by the analogue composition of tree species belonging to the optimal WI and MTCI ranges.As a result of the clustering process,22 TAGs were generated to explain the forest vegetation distribution in Korea.The primary change in distribution for these TAGs will likely be in the shrinkage of areas for the TAGs related to Pinus densiflora and P.koraiensis,and in the expansion of the other TAG areas,mainly occupied by evergreen broad-leaved trees,such as Camellia japonica,Cyclobalanopsis glauca,and Schima superba.Using the TAGs to explain the effects of climate change on vegetation distribution on a more regional scale resulted in greater detail than previously used global or continental scale vegetation models.
