Simulation And Analysis Of The Adaptive Geographical Environment Of Living Organisms Based On GIS

The adaptive geographical environment of living organisms is a virtual geographical environment which can adapt to a certain living organisms.Adaptive geographical environment modeling show the intrinsic connection between living organisms- geographic environment based on GIS and other spatial data mining algorithms and simulate the the various geographical environment which adapt to survive and maintain the population development of living organisms(including natural, economic,social and cultural environment) to predict the potential distribution of the living organisms. The simulation of adaptive geographical environment in disease forecasting, management of biodiversity, ecological security assessment and other research direction has great potential.Adaptive geographical environment is not a static geographical environment, in addition to having intrinsic spatial attribute, climate,economy, social environment initiative to change gives important time properties and dynamic characteristics to adaptive geographical environment. The characteristics of space and time put forward two challenges to the simulation and prediction of the adaptive geographical environment: 1) The dynamic simulation of the living organisms in different life cycles. 2) Significant changes in the environment(e.g.,global climate change) and the dynamic interaction of the adaptive geographical environment. In view of the above challenges, this paper takes epidemiology(H7N9 avian influenza) and biodiversity conservation(invasive plants) for example. Using GARP to simulate the dynamic adaptive environment H7N9 in different life cycles and explore adaptive geographical environment simulation of 90 main types of invasive plants in China in the context of global climate change1. We analysis the characteristics of the two aspects of H7N9 avian influenza in space and time based on GIS. The outbreak of H7N9 avian influenza is carried out in stages, there is a strong seasonal. There are three outbreak peak periods from 2013 to 2015 which all outbreaks are divided into 6 stages of the epidemic cycle. In this paper, we use GARP and other spatial data mining method to simulate the potential outbreak situation of H7N9 in different epidemic stage and explore the importance of each variable which affected the H7N9 avian influenza.2. Under the background of global climate change, The 90 main types of invasive plants in China were simulated in the current climate conditions,three greenhouse gas emission levels(A2, A1 B, B1) / four time periods(2020-2040-2060-2080).Using GIS spatial analysis and statistical analysis,we analysis the migration area, migration velocity and migration direction of the invasive plants in different time series and different scene. The basic characteristics of 90 invasive plants in different climatic conditions in the future are explored(include diffusion, atrophy and displacement). Two starting point are analyzed from the overall quantity and the direction of diffusion, 90 main types of invasive plants in China in the future increase in the area mainly distributed in China's southwest- northeast direction of45 degree line. The reduction of the area is mainly in Sichuan and the South / southeast coastal provinces of China. The overall migration direction will be northwest and northeast, and the northwest is the main migration route.