This paper presents a conceptual data model, the STA-model, for handling spatial, temporal and attribute aspects of objects in GIS. The model is developed on the basis of object-oriented modeling approach. This model ...This paper presents a conceptual data model, the STA-model, for handling spatial, temporal and attribute aspects of objects in GIS. The model is developed on the basis of object-oriented modeling approach. This model includes two major parts: (a) modeling the signal objects by STA-object elements, and (b) modeling relationships between STA-objects. As an example, the STA-model is applied for modeling land cover change data with spatial, temporal and attribute components.展开更多
International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural lan...International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural land-use changes and related environmental issues across multi-trading countries together, but most studies rely on statistic data without spatial attributes. However, agricultural land-use changes are spatially heterogeneous. Uncovering spatial attributes can reveal more critical information that is of scientific significance and has policy implications for enhancing food security and protecting the environment. Based on an integrated framework of telecoupling （socioeconomic and environmental interactions over distances）, we studied spatial attributes of soybean land changes within and among trading countries at the same time. Three distant countries -- Brazil, China, and the United States -- constitute an excellent example of telecoupled systems through the process of soybean trade. Our results presented the spatial distribution of soybean land changes-- highlighting the hotspots of soybean gain and soybean loss, and indicated these changes were spatially clustered, different across multi-spatial scales, and varied among the trading countries. Assisted by the results, global challenges like food security and biodiversity loss within and among trading countries can be targeted and managed efficiently. Our work provides simul- taneously spatial information for understanding agricultural land-use changes caused by international food trade globally, highlights the needs of coordination among trading countries, and promotes global sustainability.展开更多
文摘This paper presents a conceptual data model, the STA-model, for handling spatial, temporal and attribute aspects of objects in GIS. The model is developed on the basis of object-oriented modeling approach. This model includes two major parts: (a) modeling the signal objects by STA-object elements, and (b) modeling relationships between STA-objects. As an example, the STA-model is applied for modeling land cover change data with spatial, temporal and attribute components.
基金financial support from the National Science FoundationMichigan State UniversityMichigan AgBio Research,United States
文摘International food trade has become a key driving force of agricultural land-use changes in trading countries, which has influenced food production and the global environment. Researchers have studied agricultural land-use changes and related environmental issues across multi-trading countries together, but most studies rely on statistic data without spatial attributes. However, agricultural land-use changes are spatially heterogeneous. Uncovering spatial attributes can reveal more critical information that is of scientific significance and has policy implications for enhancing food security and protecting the environment. Based on an integrated framework of telecoupling （socioeconomic and environmental interactions over distances）, we studied spatial attributes of soybean land changes within and among trading countries at the same time. Three distant countries -- Brazil, China, and the United States -- constitute an excellent example of telecoupled systems through the process of soybean trade. Our results presented the spatial distribution of soybean land changes-- highlighting the hotspots of soybean gain and soybean loss, and indicated these changes were spatially clustered, different across multi-spatial scales, and varied among the trading countries. Assisted by the results, global challenges like food security and biodiversity loss within and among trading countries can be targeted and managed efficiently. Our work provides simul- taneously spatial information for understanding agricultural land-use changes caused by international food trade globally, highlights the needs of coordination among trading countries, and promotes global sustainability.
