This study presents the utility of remote sensing （RS）, GIS and field observation data to estimate above ground biomass （AGB） and stem volume over tropical forest environment. Application of those data for the mod...This study presents the utility of remote sensing （RS）, GIS and field observation data to estimate above ground biomass （AGB） and stem volume over tropical forest environment. Application of those data for the modeling of forest properties is site specific and highly uncertain, thus further study is encouraged. In this study we used 1460 sampling plots collected in 16 transects measuring tree diameter （DBH） and other forest properties which were useful for the biomass assessment. The study was carded out in tropical forest region in East Kalimantan, Indo- nesia. The AGB density was estimated applying an existing DBH - biomass equation. The estimate was superimposed over the modified GIS map of the study area, and the biomass density of each land cover was calculated. The RS approach was performed using a subset of sample data to develop the AGB and stem volume linear equation models. Pearson correlation statistics test was conducted using ETM bands reflectance, vegetation indices, image transform layers, Principal Component Analysis （PCA） bands, Tasseled Cap （TC）, Grey Level Co-Occurrence Matrix （GLCM） texture features and DEM data as the predictors. Two linear models were generated from the significant RS data. To analyze total biomass and stem volume of each land cover, Landsat ETM images from 2000 and 2003 were preprocessed, classified using maximum likelihood method, and filtered with the majority analysis. We found 158±16 m^3.ha^-1 of stem volume and 168±15 t.ha^-1 of AGB estimated from RS approach, whereas the field measurement and GIS estimated 157±92 m^3.ha^-1 and 167±94 t.ha^-1 of stem volume and AGB, respectively. The dynamics of biomass abundance from 2000 to 2003 were assessed from multi temporal ETM data and we found a slightly declining trend of total biomass over these periods. Remote sensing approach estimated lower biomass abundance than did the GIS and field measurement data. The earlier approach predicted 10.5 Gt and 10.3 Gt of total biomasses in 2000 and 2003, while the later estimated 11.9 Gt and 11.6 Gt of total biomasses, respectively. We found that GLCM mean texture features showed markedly strong correlations with stem volume and biomass.展开更多
This study aimed to develop a biomass equation for estimating the total above-ground biomass for Colophospermum mopane (mopane) based on the pooled data from three study sites. The mopane woodlands in Botswana represe...This study aimed to develop a biomass equation for estimating the total above-ground biomass for Colophospermum mopane (mopane) based on the pooled data from three study sites. The mopane woodlands in Botswana represent 14.6% of Botswana’s total area. The woodlands directly or indirectly support the livelihood of the majority of the rural population by providing wood and non-wood products. However, there is limited information on the pattern, trends and distribution of woody biomass production and their primary, environmental, and climatic determinants in different parts of Botswana. All the data were collected by destructive sampling from three study sites in Botswana. Stratified random sampling was based on the stem diameter at breast height (1.3 m from the ground or Diameter at Breast Height (DBH)). A total of 30 sample trees at each study site were measured, felled and weighed. The data from the three sites were pooled together, and the study employed regression analysis to examine the nature of relationships between total above-ground biomass (dependent variable) and five independent variables: 1) total tree height;2) crown diameter;3) stem diameters at 0.15 m;1.3 m (DBH) and 3 m from the ground respectively. There were significant relationships between all the independent variables and the dependent variable. However, DBH emerged as the strongest predictor of total tree above-ground biomass for mopane. The equation lnBiomass=-1.163+2.190lnDBH was adopted for use in the indirect estimation of total tree above-ground biomass for mopane in Botswana.展开更多
文摘This study presents the utility of remote sensing （RS）, GIS and field observation data to estimate above ground biomass （AGB） and stem volume over tropical forest environment. Application of those data for the modeling of forest properties is site specific and highly uncertain, thus further study is encouraged. In this study we used 1460 sampling plots collected in 16 transects measuring tree diameter （DBH） and other forest properties which were useful for the biomass assessment. The study was carded out in tropical forest region in East Kalimantan, Indo- nesia. The AGB density was estimated applying an existing DBH - biomass equation. The estimate was superimposed over the modified GIS map of the study area, and the biomass density of each land cover was calculated. The RS approach was performed using a subset of sample data to develop the AGB and stem volume linear equation models. Pearson correlation statistics test was conducted using ETM bands reflectance, vegetation indices, image transform layers, Principal Component Analysis （PCA） bands, Tasseled Cap （TC）, Grey Level Co-Occurrence Matrix （GLCM） texture features and DEM data as the predictors. Two linear models were generated from the significant RS data. To analyze total biomass and stem volume of each land cover, Landsat ETM images from 2000 and 2003 were preprocessed, classified using maximum likelihood method, and filtered with the majority analysis. We found 158±16 m^3.ha^-1 of stem volume and 168±15 t.ha^-1 of AGB estimated from RS approach, whereas the field measurement and GIS estimated 157±92 m^3.ha^-1 and 167±94 t.ha^-1 of stem volume and AGB, respectively. The dynamics of biomass abundance from 2000 to 2003 were assessed from multi temporal ETM data and we found a slightly declining trend of total biomass over these periods. Remote sensing approach estimated lower biomass abundance than did the GIS and field measurement data. The earlier approach predicted 10.5 Gt and 10.3 Gt of total biomasses in 2000 and 2003, while the later estimated 11.9 Gt and 11.6 Gt of total biomasses, respectively. We found that GLCM mean texture features showed markedly strong correlations with stem volume and biomass.
文摘This study aimed to develop a biomass equation for estimating the total above-ground biomass for Colophospermum mopane (mopane) based on the pooled data from three study sites. The mopane woodlands in Botswana represent 14.6% of Botswana’s total area. The woodlands directly or indirectly support the livelihood of the majority of the rural population by providing wood and non-wood products. However, there is limited information on the pattern, trends and distribution of woody biomass production and their primary, environmental, and climatic determinants in different parts of Botswana. All the data were collected by destructive sampling from three study sites in Botswana. Stratified random sampling was based on the stem diameter at breast height (1.3 m from the ground or Diameter at Breast Height (DBH)). A total of 30 sample trees at each study site were measured, felled and weighed. The data from the three sites were pooled together, and the study employed regression analysis to examine the nature of relationships between total above-ground biomass (dependent variable) and five independent variables: 1) total tree height;2) crown diameter;3) stem diameters at 0.15 m;1.3 m (DBH) and 3 m from the ground respectively. There were significant relationships between all the independent variables and the dependent variable. However, DBH emerged as the strongest predictor of total tree above-ground biomass for mopane. The equation lnBiomass=-1.163+2.190lnDBH was adopted for use in the indirect estimation of total tree above-ground biomass for mopane in Botswana.
