GISAUS1.ppt

Assisting Australian indigenous resource management and sustainable utilization of species through the use of GIS and environmental modeling techniques.,测绘0911 第八组 2012.5.3,First of all, let us grasp a good overview of Australia,Introduction Background and study site Methods Results conclusion,Introduction,The continent of Australia with a Coastline-30 000 kilometers,a land area-7 682 300 km,it is the largest island in the world. The country also includes Tasmania ,the Torres Straits Islands and a small number of islands in the Pacific and the Indian Oceans.So, Therefore, Australias geographical situation is very complex,A complex continent,Western Australia,Northern Territory,South Australia,New South Wales,Queensland,Victoria,Tasmania,Australia Capital,The indigenous resouces are used by the local people for a long time,but,how can they manage them proberly and keep it sustainable?,THE SPECIES OF AUS,Some of them are threatened with extinction now!,kangaroo,camel,crocodile,shark,koala,Unusual animals in Australia,OTHER RESOUCES,Livestock,Forestry,HOU DOES LOCALS UES THEM IN THE PAST,Hunting,Logging,Mining,The problem,Today, a lot of resources can not be rational exploitation.Also there are many species threatened with extinction, a huge waste of resources is existed! Meanwhile,to manage them is such a difficult thing for the local people!,THE BAKCGROUND AND STUDY SITE,There is an example of a kind of species:Cycads Study site:The study area is the Maningrida region of central Arnhem Land,500KM landscape is dominated by the Arnhenm Land sandstone escarpment to the south Enviomental model and GIS application,Method,The type of survey data that is available plays a major role in determining the type of modeling method that can be applied. Presence-absence models have been noted as being superior to presence-only models.,Collet date Data Classification Modeling,Australias geographical situation,In this situation ,there should be a enviromental model,Enviomental model,The complexity of the environment of the survey is the need for innovative tools. Innovation is the IDRISI software development goals. The IDRISI innovation including the establishment of advanced modeling tools. The application of the integrated Earth trend modeling tools (ETM) provides observation, detection and time series analysis tools to discover the trend of environmental change, especially the study of global climate change.,Integrated land change module (LCM) to lead the operator through the complicated steps to create change models. Uses advanced algorithms and tools, and past land cover change to predict future changes of the land. This feature as REDD (Reducing emissions from deforestation and forest degradation) project. LCM project also includes the evaluation of the impact of land use change on biodiversity. Model system for other applications by the macro modeling.,Field Obvervation,To try and minimize the influence of the road/hunting tracks the quadrats were positioned 50 m nto the bush in a random direction without regard for the presence of the target secies. The coordinates of the middle of each quadrat was taken using Garmin GPS 12XL.,Enviomental/predictor data sets,Data were selected from available mapped environmental themes to reflect the factoes thought most likely to influence species distribution ,based on both a knowledge of the species ecology from consultation with experts,and indigenous knowledge of the species . A mixture of raster and broad scale vector data was used . AS data is only captured at one recording station in the vicinity. Afain data for this area is not available at a scale where differences in elevation (and its derivation of slope and aspect)would have much influence on the output .so this data was not included in the model.,Validation,Validation of the predictive maps involved independent additional ground sampling. This involved surveying 271 and 235 quadrats(50*50 m) within each of the C.arnhem and B.diversifolius study sites.respectively and recorded presence or absence of the species. We used Arc View 3.3 to a place 1 200 m buffer around the road and hunting tracks and generate random points,In each of the three probability classes.At each study site a number of random points were chosen for each of the high,medium or low probability categories(in totil 22 for C.arnhem and 16 B.diversifolius)and these were used as start points from which a further 12 50*50 m quardrats were sampled every 100 m,the 100 m mark being the center of the smaller quardrat.,The direction of the quadrats from these staeting points was randomly chosen(from degrees on paperand chosen in a hat) with possible directions being between 0 and 180 from the road to ensure transects did not cross over the roadSubsequntly,the individual 50*50 m quadrats fell in the same direction as the larger quadrat.This method was used to survey away from the road/track whilestill minimizing the time spent collecting the validation data.,Testing the model,Cohens kappa statistics were to test overall model performation and provide a simples , effective ,standardized and appropriate statistic for evaluating presence-abences models . a descripition of this methodology is available in fielding and bell(1997)so with not be describled in this paper. It has been suggested that when calculating Kappa statistic, instead of using an arbitrary threshold of 50% to distinguish simulated presence from simulated absence ,a probability thresgold that maximizes the models performance should be determined by evaluating k at successive probability increments. In using Kappa statistics to test the accuracy of the models generated in this study we have adopted a similar approach.,Result,Map showing predicted probability of occurrence of bracyhiton divesifolius using byesian modeling landis and Koch(1997)suggest the folloeing agreement mensures for categorical data using Kappa statistic. A kappa statistic below 0.00 equates to a poor strength of agreement;between 0.00 and 0.20 equates to slight agreement ;,between 0.21 and 0.40 equates to fair agreement ; between 0.41 and 0.60 equates to moderate agreement ; between 0.61 and 0.80 equates to substantial agreement ; and between 0.81; and 1.0 0 equates to almost perfect agreement .,Conclusion,The result of this study that GIS and enviomental modeling techniques are useful for predicting the distrbution of species that may be of interst to Australian indigenous grouops wanting to engage in susta