A novel quantitative cellular automata (CA) model that simulates and predicts hillslope runoff and soil erosion caused by rainfall events was developed by integrating the local interaction rules and the hillslope surf...A novel quantitative cellular automata (CA) model that simulates and predicts hillslope runoff and soil erosion caused by rainfall events was developed by integrating the local interaction rules and the hillslope surface hydraulic processes. In this CA model, the hillslope surface was subdivided into a series of discrete spatial cells with the same geometric features. At each time step, water and sediment were transported between two adjacent spatial cells. The flow direction was determined by a combination of water surface slope and stochastic assignment. The amounts of interchanged water and sediment were computed using the Chezy-Manning formula and the empirical sediment transport equation. The water and sediment discharged from the open boundary cells were considered as the runoff and the sediment yields over the entire hillslope surface. Two hillslope soil erosion experiments under simulated rainfall events were carried out. Cumulative runoff and sediment yields were measured, respectively. Then, the CA model was applied to simulate the water and soil erosion for these two experiments. Analysis of simulation results indicated that the size of the spatial cell, hydraulic parameters, and the setting of time step and iteration times had a large impact on the model accuracy. The comparison of the simulated and measured data suggested that the CA model was an applicable alternate for simulating the hillslope water flow and soil erosion.展开更多
Mesoscale eddies are an important component of oceanic features.How to automatically identify these mesoscale eddies from available data has become an important research topic.Through careful examination of existing m...Mesoscale eddies are an important component of oceanic features.How to automatically identify these mesoscale eddies from available data has become an important research topic.Through careful examination of existing methods,we propose an improved,SSH-based automatic identification method.Using the inclusion relation of enclosed SSH contours,the mesoscale eddy boundary and core(s) can be automatically identified.The time evolution of eddies can be examined by a threshold search algorithm and a tracking algorithm based on similarity.Sea-surface height(SSH) data from Naval Research Laboratory Layered Ocean Model(NLOM) and sea-level anomaly(SLA) data from altimeter are used in the many experiments,in which different automatic identification methods are compared.Our results indicate that the improved method is able to extract the mesoscale eddy boundary more precisely,retaining the multiple-core structure.In combination with the tracking algorithm,this method can capture complete mesoscale eddy processes.It can thus provide reliable information for further study of reconstructing eddy dynamics,merging,splitting,and evolution of a multi-core structure.展开更多
Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined accordi...Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined according to the topographic profile maps for the ridge and piedmont lines, and then the topographic gradient characteristics are analyzed according to the representative topographic profile acquisition method.Based on the geomorphologic database data, the regions between the ridge and the piedmont lines are divided into four geomorphologic zones; and the topographic characteristics are finally analyzed for the different geomorphologic zones regions using the DEM data. The research results show that from the piedmont to the ridge, there exist four geomorphologic zones: arid, fluvial, periglacial and glacial. The arid has the lowest elevation, topographic gradient, relief and slope characteristics. The fluvial has lower elevation and the highest topographic gradient, but with lower relief and slope characteristics. With higher elevation, the periglcial has lower topographic gradient, but the highest relief and slope characteristics. The glacial has the highest elevation with higher topographic gradient, relief and slope characteristics.展开更多
Case-Based Reasoning (CBR) is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This pa...Case-Based Reasoning (CBR) is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR (Geo-CBR). First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.展开更多
基金Project supported by the National Science Fund for Distinguished Young Scholars of China (No. 40225004)the National Natural Science Foundation of China (No. 40471048)
文摘A novel quantitative cellular automata (CA) model that simulates and predicts hillslope runoff and soil erosion caused by rainfall events was developed by integrating the local interaction rules and the hillslope surface hydraulic processes. In this CA model, the hillslope surface was subdivided into a series of discrete spatial cells with the same geometric features. At each time step, water and sediment were transported between two adjacent spatial cells. The flow direction was determined by a combination of water surface slope and stochastic assignment. The amounts of interchanged water and sediment were computed using the Chezy-Manning formula and the empirical sediment transport equation. The water and sediment discharged from the open boundary cells were considered as the runoff and the sediment yields over the entire hillslope surface. Two hillslope soil erosion experiments under simulated rainfall events were carried out. Cumulative runoff and sediment yields were measured, respectively. Then, the CA model was applied to simulate the water and soil erosion for these two experiments. Analysis of simulation results indicated that the size of the spatial cell, hydraulic parameters, and the setting of time step and iteration times had a large impact on the model accuracy. The comparison of the simulated and measured data suggested that the CA model was an applicable alternate for simulating the hillslope water flow and soil erosion.
基金jointly supported by a grant from the National Natural Science Foundation of China(General Program)(41071250)Innovation Program of State Key Laboratory of Resources and Environmental Information System,Institute of Geographic SciencesNatural Resources Research,Chinese Academy of Sciences(088RA500KA)
文摘Mesoscale eddies are an important component of oceanic features.How to automatically identify these mesoscale eddies from available data has become an important research topic.Through careful examination of existing methods,we propose an improved,SSH-based automatic identification method.Using the inclusion relation of enclosed SSH contours,the mesoscale eddy boundary and core(s) can be automatically identified.The time evolution of eddies can be examined by a threshold search algorithm and a tracking algorithm based on similarity.Sea-surface height(SSH) data from Naval Research Laboratory Layered Ocean Model(NLOM) and sea-level anomaly(SLA) data from altimeter are used in the many experiments,in which different automatic identification methods are compared.Our results indicate that the improved method is able to extract the mesoscale eddy boundary more precisely,retaining the multiple-core structure.In combination with the tracking algorithm,this method can capture complete mesoscale eddy processes.It can thus provide reliable information for further study of reconstructing eddy dynamics,merging,splitting,and evolution of a multi-core structure.
基金supported by the strategic plan project of science and technology of Institute of Geographic Sciences and Natural Resources Research (Grant No. 2012ZD009)the National Science Technology Support Plan Project (Grant No. 2012BAH28B01-03)+1 种基金the National Natural Science Foundation of China (Grant No. 41171332)the National Science Technology Basic Special Project (Grant No.2011FY110400-2)
文摘Based on geomorphologic and digital elevation model(DEM) data, the topographic characteristics of the northwestern edge of the Qinghai-Tibet Plateau are analyzed. Five representative peaks are first determined according to the topographic profile maps for the ridge and piedmont lines, and then the topographic gradient characteristics are analyzed according to the representative topographic profile acquisition method.Based on the geomorphologic database data, the regions between the ridge and the piedmont lines are divided into four geomorphologic zones; and the topographic characteristics are finally analyzed for the different geomorphologic zones regions using the DEM data. The research results show that from the piedmont to the ridge, there exist four geomorphologic zones: arid, fluvial, periglacial and glacial. The arid has the lowest elevation, topographic gradient, relief and slope characteristics. The fluvial has lower elevation and the highest topographic gradient, but with lower relief and slope characteristics. With higher elevation, the periglcial has lower topographic gradient, but the highest relief and slope characteristics. The glacial has the highest elevation with higher topographic gradient, relief and slope characteristics.
文摘Case-Based Reasoning (CBR) is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR (Geo-CBR). First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.