This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vege...This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.展开更多
Based on the advantages of the openness,flexibility,high-efficiency,intelligence,and safety of grid,this paper focuses on the methods of marine environmental information sharing and integration in grid environment.Acc...Based on the advantages of the openness,flexibility,high-efficiency,intelligence,and safety of grid,this paper focuses on the methods of marine environmental information sharing and integration in grid environment.According to the characteristics of marine information,which includes multisource,dynamic,and high-dimensional,this paper provides a framework and the technical solution for a multisource marine environmental information grid platform.As an experiment,the prototype takes the region of South China Sea as its study area and chooses three kinds of marine environmental information as the representative types for the marine information.The realization of the prototype of multisource marine environmental information grid platform shows the feasibility and practicality of the framework and the technical solution.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41001363)
文摘This study aims to provide a predictive vegetation mapping approach based on the spectral data, DEM and Generalized Additive Models (GAMs). GAMs were used as a prediction tool to describe the relationship between vegetation and environmental variables, as well as spectral variables. Based on the fitted GAMs model, probability map of species occurrence was generated and then vegetation type of each grid was defined according to the probability of species occurrence. Deviance analysis was employed to test the goodness of curve fitting and drop contribution calculation was used to evaluate the contribution of each predictor in the fitted GAMs models. Area under curve (AUC) of Receiver Operating Characteristic (ROC) curve was employed to assess the results maps of probability. The results showed that: 1) AUC values of the fitted GAMs models are very high which proves that integrating spectral data and environmental variables based on the GAMs is a feasible way to map the vegetation. 2) Prediction accuracy varies with plant community, and community with dense cover is better predicted than sparse plant community. 3) Both spectral variables and environmental variables play an important role in mapping the vegetation. However, the contribution of the same predictor in the GAMs models for different plant communities is different. 4) Insufficient resolution of spectral data, environmental data and confounding effects of land use and other variables which are not closely related to the environmental conditions are the major causes of imprecision.
基金Supported by the National 863 Program of China (No.2009AA12Z148,No.2007AA092202)the Knowledge Innovation Project of Chinese Academy of Sciences (No.KZCX1-YW-12-04)
文摘Based on the advantages of the openness,flexibility,high-efficiency,intelligence,and safety of grid,this paper focuses on the methods of marine environmental information sharing and integration in grid environment.According to the characteristics of marine information,which includes multisource,dynamic,and high-dimensional,this paper provides a framework and the technical solution for a multisource marine environmental information grid platform.As an experiment,the prototype takes the region of South China Sea as its study area and chooses three kinds of marine environmental information as the representative types for the marine information.The realization of the prototype of multisource marine environmental information grid platform shows the feasibility and practicality of the framework and the technical solution.
