{"title":"元胞自动机模型——GaÚCha城市土地利用/覆被变化过程中的景观动态模拟工具","authors":"E. Pinheiro, N. A. Camini, M. Soares, S. Sumida","doi":"10.1109/LAGIRS48042.2020.9165590","DOIUrl":null,"url":null,"abstract":"The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.","PeriodicalId":111863,"journal":{"name":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Cellular Automata Model - Landscape Dynamics Simulation Tool in the Process of Change in Land Use and Cover in the City of GaÚCha Do Norte – Mt\",\"authors\":\"E. Pinheiro, N. A. Camini, M. Soares, S. Sumida\",\"doi\":\"10.1109/LAGIRS48042.2020.9165590\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.\",\"PeriodicalId\":111863,\"journal\":{\"name\":\"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/LAGIRS48042.2020.9165590\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LAGIRS48042.2020.9165590","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
导致Gaúcha do Norte - MT市土地利用变化的因素与经济进程和农业生产完全相关。由于森林砍伐和热带森林的丧失,这一过程使巴西处于警戒状态。2000 - 2010年,森林转农面积占13.3%,直接加剧毁林的主要因素是种植大豆,大豆反过来又占据了原来畜牧业占据的地方,将畜牧林推向内部。土地利用变化和土地覆盖现象是从环境和经济背景下的多维问题出发的。通过元胞自动机使用环境建模来分析土地利用变化现象,并通过未来土地利用模拟和演变再现轨迹,建立了与数学模型和流量集成系统相关的集成。预测土地利用变化的轨迹,从而产生一个动态模型,能够通过复制景观演变的可能模式来预测未来的土地利用变化,并能够评估未来对环境的生态影响。
Cellular Automata Model - Landscape Dynamics Simulation Tool in the Process of Change in Land Use and Cover in the City of GaÚCha Do Norte – Mt
The factors that contribute to land use change in the municipality of Gaúcha do Norte - MT, are entirely linked to the economic process and agricultural production. This process has left brazil in a state of alert due to the process of deforestation and loss of tropical forests. From 2000 to 2010, the forest areas converted into agriculture accounted for 13.3%, the main factor that directly potentiated with deforestation was the cultivation of soybeans, which in turn was occupying places previously occupied by livestock and pushing the livestock forest inside. The phenomena of land use change and land cover start from multidimensional issues in the environmental and economic context. The use of environmental modeling through cellular automata to analyze land use change phenomena and reproduce the trajectory through future land use simulations and evolution establishes an integration associated by mathematical models and flow integration systems. That predict the trajectory of land use change, thus generating a dynamic model capable of predicting future land use changes by replicating possible patterns of landscape evolution and enabling assessments of future ecological implications for the environment.