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
By taking Daan city in Jilin Province as a research object and by using TM image in 1989 and ETM + image in 2001 from American LANDSAT satellite,all kinds of maps and documentation,information of grassland,saline-alka...By taking Daan city in Jilin Province as a research object and by using TM image in 1989 and ETM + image in 2001 from American LANDSAT satellite,all kinds of maps and documentation,information of grassland,saline-alkalized land,cropland,water area and forestland is extracted by man-computer interactive interpretation method with ArcView and ArcInfo GIS software, and statistics data is acquired. On the basis of this the changing trend of land use types in the next ten years is forecasted and analyzed with Markov model. The results indicate that the problem of grassland degradation in the study area is quite serious.展开更多
High resolution remote sensing data has been applied in many fields such as national security, economic construction and in the daily life of the general public around the world, creating a huge market. Commercial rem...High resolution remote sensing data has been applied in many fields such as national security, economic construction and in the daily life of the general public around the world, creating a huge market. Commercial remote sensing cameras have been developed vigorously throughout the world over the last few decades, resulting in resolutions down to 0.31 m. In 2010, the Chinese government approved the implementation of the China High-resolution Earth Observation System(CHEOS) Major Special Project, giving priority to development of high resolution remote sensing satellites. More than half of CHEOS has been constructed to date and 5 satellites operate in orbit. These cameras have different characteristics. A number of innovative technologies have been adopted, which have led to camera performance increasing in leaps and bounds. The products and the production capability enables the remote sensing technical level to increase making it on a par with Europe and the US.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By taking Daan city in Jilin Province as a research object and by using TM image in 1989 and ETM + image in 2001 from American LANDSAT satellite,all kinds of maps and documentation,information of grassland,saline-alkalized land,cropland,water area and forestland is extracted by man-computer interactive interpretation method with ArcView and ArcInfo GIS software, and statistics data is acquired. On the basis of this the changing trend of land use types in the next ten years is forecasted and analyzed with Markov model. The results indicate that the problem of grassland degradation in the study area is quite serious.
文摘High resolution remote sensing data has been applied in many fields such as national security, economic construction and in the daily life of the general public around the world, creating a huge market. Commercial remote sensing cameras have been developed vigorously throughout the world over the last few decades, resulting in resolutions down to 0.31 m. In 2010, the Chinese government approved the implementation of the China High-resolution Earth Observation System(CHEOS) Major Special Project, giving priority to development of high resolution remote sensing satellites. More than half of CHEOS has been constructed to date and 5 satellites operate in orbit. These cameras have different characteristics. A number of innovative technologies have been adopted, which have led to camera performance increasing in leaps and bounds. The products and the production capability enables the remote sensing technical level to increase making it on a par with Europe and the US.
