By using soil erosion maps of four different time periods and a digital elevation model (DEM), in combination withthe remote sensing and GIS technologies, soil erosion dynamics in Xingguo County of Jiangxi Province in...By using soil erosion maps of four different time periods and a digital elevation model (DEM), in combination withthe remote sensing and GIS technologies, soil erosion dynamics in Xingguo County of Jiangxi Province in South Chinawere analyzed on both temporal and spatial scales in soils of different parent materials, altitudes and slopes. The resultsshowed that from 1958 to 2000 severe soil erosion was coming under control with a decreasing percentage of the land undersevere erosion. It was also found that the soils developed from Quaternary red clay, granite and purple shale were moresusceptible to soil erosion and that areas sitting between 200 to 500 m in altitude with a slope less than 3° or between7° to 20° where human activities were frequent remained to be zones where soil erosion was most likely to occur. Theseareas deserve special attention in monitoring and controlling.展开更多
Support vector machines (SVM) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on rolling optimization method and on-line learning strategies, a novel appr...Support vector machines (SVM) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on rolling optimization method and on-line learning strategies, a novel approach based on weighted least squares support vector machines (WLS-SVM) is proposed for nonlinear dynamic modeling. The good robust property of the novel approach enhances the generalization ability of kernel method-based modeling and some experimental results are presented to illustrate the feasibility of the proposed method.展开更多
Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time...Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate（net primary productivity,NPP） modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.展开更多
基金the National Natural Science Foundation of China (No. 40471081), the Innovation Programme ofChinese Academy of Sciences (No. KZCX3-SW-422), and the Canadian International Development Agency, Canada.
文摘By using soil erosion maps of four different time periods and a digital elevation model (DEM), in combination withthe remote sensing and GIS technologies, soil erosion dynamics in Xingguo County of Jiangxi Province in South Chinawere analyzed on both temporal and spatial scales in soils of different parent materials, altitudes and slopes. The resultsshowed that from 1958 to 2000 severe soil erosion was coming under control with a decreasing percentage of the land undersevere erosion. It was also found that the soils developed from Quaternary red clay, granite and purple shale were moresusceptible to soil erosion and that areas sitting between 200 to 500 m in altitude with a slope less than 3° or between7° to 20° where human activities were frequent remained to be zones where soil erosion was most likely to occur. Theseareas deserve special attention in monitoring and controlling.
基金This work was supportedin part bythe national 973 keyfundamental research project of China under grant 2002CB312200 and national 863high technology projects foundation of China under grant 2002AA412010
文摘Support vector machines (SVM) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on rolling optimization method and on-line learning strategies, a novel approach based on weighted least squares support vector machines (WLS-SVM) is proposed for nonlinear dynamic modeling. The good robust property of the novel approach enhances the generalization ability of kernel method-based modeling and some experimental results are presented to illustrate the feasibility of the proposed method.
文摘Forests have long life cycles of up to several hundred years and longer.They also have very different growth rates at different stages of their life cycles.Therefore the carbon cycle in forest ecosystems has long time scales,making it necessary to consider forest age in estimating the spatiotemporal dynamics of carbon sinks in forests.The focus of this article is to review methods for combining recent remote sensing data with historical climate data for estimating the forest carbon source and sink distribution.Satellite remote sensing provides useful data for the land surface in recent decades. The information derived from remote sensing data can be used for short-term forest growth estimation and for mapping forest stand age for longterm simulations.For short-term forest growth estimation, remote sensing can provide forest structural parameters as inputs to process-based models,including big-leaf,two-leaf,and multi-layered models. These models use different strategies to upscale from leaf to canopy,and their reliability and suitability for remote sensing applications will be examined here.For long-term forest carbon cycle estimation, the spatial distribution of the forest growth rate（net primary productivity,NPP） modeled using remote sensing data in recent years is a critical input.This input can be combined with a forest age map to simulate the historical variation of NPP under the influence of climate and atmospheric changes. Another important component of the forest carbon cycle is heterotrophic respiration in the soil,which depends on the sizes of soil carbon pools as well as climate conditions.Methods for estimating the soil carbon spatial distribution and its separation into pools are described.The emphasis is placed on how to derive the soil carbon pools from NPP estimation in current years with consideration of forest carbon dynamics associated with stand age variation and climate and atmospheric changes.The role of disturbance in the forest carbon cycle and the effects of forest regrowth after disturbance are also considered in this review.An example of national forest carbon budget estimation in Canada is given at the end.It illustrates the importance of forest stand age structure in estimating the national forest carbon budgets and the effects of climate and atmospheric changes on the forest carbon cycle.
