Arcview Gis 3.3 User Manual

2021. 1. 18. 07:40카테고리 없음



What's New in ArcView 3.1, 3.2, and 3.3 Welcome to ArcView® 3.x. Whether you are an experienced user or getting started with ArcView 3.x, this white paper will introduce you to all of the new features and capabilities of ArcView 3.x. Each new release exemplifies ESRI's commitment to enhancing the user experience with ArcView. ArcGIS Data Interoperability for Desktop - Enables ArcGIS to read and process over 115 GIS and CAD formats supported by Safe Software's FME. ArcGIS Data Reviewer for Desktop - Provides tools to manage quality control and makes data quality a component of your overall data management strategy.

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ArcViewGIS is the central tool used by this second group, along with several add-ons to the program, specifically 3D Analyst, Image Analysis and Spatial Analyst. We worked through the basics with Sarah E. Williams, GIS specialist at MIT. She has given us permission to have licensed copies for ArcView for ourpersonal computers, as well as given us online tutorials to begin with.

Arcview Gis 3.3

What is ArcView?

'ArcView gives you the power to visualize, explore, query,and analyze data geographically. In no time, you'll be working withyour data in a completely new way, seeing patterns you couldn't see before,understanding geographic relationships that were previously hidden, gaininginsights, solving problems, and achieving new results . . .' ~ ArcViewGIS User Manual by ESRI (Environmental Systems Research Institute Inc.)

Our group develops a model that allows us to determinethe probability that a specific species has of going extinct under certainconditions during a fixed time span given its current population size.This process is known as PopulationViability Analysis (PVA). We use ArcView GIS 3.3 for developingthis model. More specifically, we use one of ArcView's extensionsor add-on programs that provides specialized GIS funcionality, called ArcViewSpatial Analyst. This extension contains a tool known as Population ViabilityAnalysis that allows one to create life tables based on overall populationparameters or utilize a fully populated life table to conduct multiplepopulation simulations. [From ArcView GIS manual, Environmental SystemsResearch Institute Inc., 1996]

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It is important to understand that the extinction processinvolves both deterministic processes as well as stochastic processes.Deterministic processes include over-harvest, habitat destruction, competitionor predation from introduced species, while stochastic processes coverrandom variation of demographic and genetic events and the effect of environmentalvariation on demographic and genetic events. Keeping this in mind, a PVAshould concentrate on the identification of natural and human factors thathave a direct influence on the specific population under study, as wellas conservation and management options. The main objectives when developinga PVA are creating a way to minimize the species' risk of extinction andalso to promote conditions in which species retain their potential forevolutionary change without intensive management.

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Policymaking and Biological Modeling

In order to allocate conservation resourcesefficiently, it is necessary to know whether various preservation plansare likely to succeed, and what their overall effect will be. Theeffect of different plans may not be easily predictable. Modellingcan help in the creation of environmental policy by providing better informationabout the likely effects of various ecological policies. As an example,this page presents an application of a type of modelling known as PopulationViability Analysis, but the results are applicable to all types of biologicalmodels.

Population Viability Analysis, orPVA, is a broad class of techniques for predicting whether or not a populationwill survive, and for how long. Simple PVA techniques include linearextrapolation of current population trends, as well as fitting to morecomplex curves. The approach used here is a more sophisticated modelbuilt from first principles. For this demonstration, we simulateda hypothetical animal species, computing its population each year fromthe age structure of the population during the previous year, as well asthe probability that an individual at a given age will die or reproduce.Additionally, the population was assumed to have a density-dependent birthrate,such that while the species remained above the theoretical carrying capacityof its environment, any newborns would not survive past one year.

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We used prototype software knownas PVA Table Tools for ArcView GIS developed by Dr. Phillip Hooge of theBiological Science Office at the US Geological Survey's Alaska ScienceCenter to simulate the response of two species with identical overall deathrate, birth rate, and other parameters to a drastic reduction in carryingcapacity. Both populations were initialized at 10,000 individuals,with an environment carrying capacity of 1500. The only differencein the simulation was the age-specific reproduction rates. One specieswas reproductive from age 4 until death, at age 20. The other specieswas twice as fertile, but only over the first half of that range.