In this study, geographic information systems (GIS) and remote sensing (RS)
tools were integrated and used to investigate the plant species diversity of the Nallihan
forest ecosystem. Two distinct indices, Shannon Wiener and Simpson, were employed in
order to express species diversity. The relationships between the indices and pertinent
independent variables (topography, geology, soil, climate, supervised classes, and
Normalized Difference Vegetation Index (NDVI) classes) were investigated to develop
two distinct models for each index. After detecting important components with factor
analysis, two models were developed by using multiple regression statistics. Running the
models, two plant species diversity maps in grid format were produced. The validity of the
models were tested by (1) mapping residuals to predict the locations where the models
work perfectly, and (2) logical interpretations in ecological point of view. Elevation and
climatic factors formed the most important component that are effective on plant species
diversity. Geological formations, soil, land cover and land-use characteristics were also
found influential for both models. Considering the disturbance and potential
evapotranspiration (PET), the model developed for Shannon Wiener index was found out
more suitable comparing the model for Simpson index.
Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/4/1172436/index.pdf |
Date | 01 January 2003 |
Creators | Dogan, Hakan Mete |
Contributors | Dogan, Musa |
Publisher | METU |
Source Sets | Middle East Technical Univ. |
Language | English |
Detected Language | English |
Type | Ph.D. Thesis |
Format | text/pdf |
Rights | To liberate the content for public access |
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