Degree of Master of


CEU eTD Collection GIS data mining


Download 1.89 Mb.
bet33/86
Sana28.03.2023
Hajmi1.89 Mb.
#1302318
1   ...   29   30   31   32   33   34   35   36   ...   86
Bog'liq
rodina kristina-sergeyevna (1)


CEU eTD Collection
GIS data mining


Data mining is the essential ingredient in the more general process of Knowledge in Databases (KDD). The idea is that by automatically sifting through large quantities of data it should be possible “to extract nuggets of knowledge” (Read 2005). Data mining can be defined as a process of analyzing data which is already presented in database (Witten and Frank 2005). Currently, data mining is becoming an increasingly important “tool to transform this data into information”. It is commonly used in a wide range of “profiling practices, such as marketing, scientific discovery, surveillance”, and others.
In the present research, data mining was used for searching the different aerial satellite images of the Aydar-Arnasay lakes system in numerous databases of such international organizations and institutions as the US Geological Survey (USGS), Satellite and Information Service of National Oceanic and Atmospheric Administration (NOAA), the database of The National Aeronautics and Space Administration (NASA), the US Berkley Earth Science and Map Library, and others. During data mining, a set of high-quality AALS satellite images starting from the 1970s was found. The method of data mining of the aerial satellite images allows us to accurately analyze the changes of the AALS water surface area during 1969- 2009, thus contributing to the present research.
    1. Methods of data analysis


Among the main methods for data analysis, the following have been applied:

    • scenario approach for elaboration of the water management scenarios;

    • environmental modeling assisted by the STELLA software;

    • GIS methods using the Arcview program;

    • Remote Sensing using the MultiSpec program.

      1. Scenario approach as an analytical method for predicting



CEU eTD Collection
The scenario approach is one of the methods used of analyzing data in the course of the study. For the present research it is important to outline that the scenario approach was used in combination with environmental modeling assisted by the STELLA software. To clarify why this method has been chosen for data analysis in the present research, let us firstly briefly repeat the concept of scenario approach and its features.
The scenario approach, introduced by the Shell Planning Group in the 1970s, has developed as a powerful method which provides a simple concise tool for “painting a picture” of how actors (clients), components and messages act together to complete one or more system goals (Foster 2006). Defining the “scenario approach” we should emphasize that it is primarily a structured process of thinking about and anticipating the unknown future, “without the pretense of being able to predict the future or being able to influence the environment” in a major way. Instead, this approach “navigates through the uncertainties and large-scale driving forces” that are impacting on the future (Schoemaker 1995). The main goal of the scenario approach is to examine possible future developments that could impact on
individuals, organizations or societies, in order to find directions for decisions that would be most “beneficial no matter how the future unfolds” (Schoemaker and Van der Heijden 1992).
In the current research we will try to apply the scenario approach as the major analytical method for presenting the future development of the Aydar-Arnasay lakes system. Scenario approach let us elaborate a number of possible future water management scenarios which propose completely different development ways of the AALS. In other words, in our research we have assumed that this method will demonstrate a wide range of possible environmental changes in the Aydar-Arnasay lakes in future, varying from imperceptible and harmless changes to severe and destructive ones.

      1. Download 1.89 Mb.

        Do'stlaringiz bilan baham:
1   ...   29   30   31   32   33   34   35   36   ...   86




Ma'lumotlar bazasi mualliflik huquqi bilan himoyalangan ©fayllar.org 2024
ma'muriyatiga murojaat qiling