Return to search

Island Karst Classification: Spatial Modeling-Oriented Approach with Multispectral Satellite Imageries

This project developed a series of spatial models to classify the island karst landforms and predict the island karst feature distribution. Spatial models with unsupervised classified images, and fuzzy-based spatial models were used in this study. Forecasting verification and spatial regressions were used to validate the models. The case study was conducted on San Salvador Island, the Bahamas, a recognized carbonate island with island karst features. Fieldwork data on banana holes on the island were used for model validation. The results showed that most models had accuracy higher than 90%, and were statistically proved that they could be used as predictors of island karst features. Further study may be conducted to solve the Modified Areal Unit Problem (MAUP) in the future.

Identiferoai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-3877
Date12 May 2012
CreatorsHo, Hung Chak
PublisherScholars Junction
Source SetsMississippi State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceTheses and Dissertations

Page generated in 0.0024 seconds