The uncertainty in the estimatation of chlorophyll content with the use of normalized difference vegetation index (NDVI) has been described. To determine the chlorophyll content, model 1 for LANDSAT and model 2 for NO...The uncertainty in the estimatation of chlorophyll content with the use of normalized difference vegetation index (NDVI) has been described. To determine the chlorophyll content, model 1 for LANDSAT and model 2 for NOAA AVHRR wavebands were presented and have been verified by field experiments. Model 1 was also validated by the distribution of chlorophyll content using LANDSAT images around the Yucheng remote sensing experimental station. Using these models to estimate the chlorophyll content in the vegetation community is benefitiated by the increased precision and decreased uncertainty.展开更多
The Zoige wetland is the biggest alpine wetland in the world,and an important water resource of the Yellow River.Due to natural and human factors,the Zoige wetland has been seriously degraded.Existing studies on the Z...The Zoige wetland is the biggest alpine wetland in the world,and an important water resource of the Yellow River.Due to natural and human factors,the Zoige wetland has been seriously degraded.Existing studies on the Zoige wetland mainly focus on the macro features of the wetland,while the influence of the surrounding faults on the Zoige wetland degradation is rarely studied.This study uses terrain data to analyze the cover change and the water loss caused by the Wqie-Seji fault based on the distributed hydrological model.The simulated water loss demonstrates that the Normalized Difference Vegetation Index(NDVI) is the most important factor for inducing water loss.The fault is also a factor that cannot be neglected,which has caused 33% of the wetland water loss.Therefore,it is of importance to study the influence of the fault on the wetland degradation.展开更多
Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegi...Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.展开更多
Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of tre...Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.展开更多
Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is...Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.展开更多
文摘The uncertainty in the estimatation of chlorophyll content with the use of normalized difference vegetation index (NDVI) has been described. To determine the chlorophyll content, model 1 for LANDSAT and model 2 for NOAA AVHRR wavebands were presented and have been verified by field experiments. Model 1 was also validated by the distribution of chlorophyll content using LANDSAT images around the Yucheng remote sensing experimental station. Using these models to estimate the chlorophyll content in the vegetation community is benefitiated by the increased precision and decreased uncertainty.
基金supported by the National Key Project of Scientific and Technical Supporting Programs of the Ministry of Science&Technology of China(Grant No.2007BAC18B01)the Project of Ministry of Environmental Protection of China(Grant No.200809086),the Project of Ministry of Environmental Protection of China(Grant No.200909060)the Project of Scientific Research and Technological Development of Guangxi(Grant NO.GKG1140002-2-4)
文摘The Zoige wetland is the biggest alpine wetland in the world,and an important water resource of the Yellow River.Due to natural and human factors,the Zoige wetland has been seriously degraded.Existing studies on the Zoige wetland mainly focus on the macro features of the wetland,while the influence of the surrounding faults on the Zoige wetland degradation is rarely studied.This study uses terrain data to analyze the cover change and the water loss caused by the Wqie-Seji fault based on the distributed hydrological model.The simulated water loss demonstrates that the Normalized Difference Vegetation Index(NDVI) is the most important factor for inducing water loss.The fault is also a factor that cannot be neglected,which has caused 33% of the wetland water loss.Therefore,it is of importance to study the influence of the fault on the wetland degradation.
基金Under the auspices of Key Program of Chinese Academy of Sciences(No.KZZD-EW-08-02)CAS/SAFEA(Chinese Academy of Science/State Administration of Foreign Experts Affairs)International Partnership Program for Creative Research Teams(No.KZZD-EW-TZ-07)Strategic Frontier Program of Chinese Academy of Sciences-Climate Change:Carbon Budget and Relevant Issues(No.XDA05050101)
文摘Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.
文摘Spatio-temporal assessment of the above ground biomass （AGB） is a cumbersome task due to the difficulties associated with the measurement of different tree parameters such as girth at breast height and height of trees. The present research was conducted in the campus of Birla Institute of Technology, Mesra, Ranchi, India, which is predomi- nantly covered by Sal （Shorea robusta C. F. Gaertn）. Two methods of regression analysis was employed to determine the potential of remote sensing parameters with the AGB measured in the field such as linear regression analysis between the AGB and the individual bands, principal components （PCs） of the bands, vegetation indices （VI）, and the PCs of the VIs respectively and multiple linear regression （MLR） analysis be- tween the AGB and all the variables in each category of data. From the linear regression analysis, it was found that only the NDVI exhibited regression coefficient value above 0.80 with the remaining parameters showing very low values. On the other hand, the MLR based analysis revealed significantly improved results as evidenced by the occurrence of very high correlation coefficient values of greater than 0.90 determined between the computed AGB from the MLR equations and field-estimated AGB thereby ascertaining their superiority in providing reliable estimates of AGB. The highest correlation coefficient of 0.99 is found with the MLR involving PCs of VIs.
文摘Vegetation information is seldom considered in lumped conceptual rainfall-runoff models.This paper uses two modified rainfall-runoff models,the Xinanjiang-ET and SIMHYD-ET models in which vegetation leaf area index is incorporated,to investigate impacts of vegetation change and climate variability on streamflow in a Southern Australian catchment,the Crawford River experimental catchment,where Tasmanian blue gum plantations were introduced gradually from 1998 till 2005.The Xinanjiang-ET and SIMHYD-ET models incorporate remotely-sensed leaf area index(LAI) data obtained from the Advanced Very High Resolution Radiometer(AVHRR) on board NOAA polar orbiting satellites.Compared to the original versions,the Xinanjiang-ET and SIMHYD-ET models show marginal improvements in runoff simulations in the pre-plantation period(1882-1997).The calibrated Xinanjaing-ET and SIMHYD-ET models are then used to simulate plantation impact on streamflow in the post-plantation period.The total change in streamflow between the pre-plantation and post-plantation periods is 32.4 mm/a.The modelling results from the two models show that plantation reduces streamflow by 20.5 mm/a,and climate variability reduces streamflow by 11.9 mm/a.These results suggest that increase in plantations can reduce streamflow substantially,even more than climate variability.
