Prediction of urban land use evolution using temporal remote sensing data analysis and a spatial logistic model
Refereed conference paper presented and published in conference proceedings

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AbstractUrban land use systems are complex systems with components, factors and agents from natural, environmental, social and economic systems. In this paper, we developed a remote sensing and GIS-based integrated approach to modeling and predicting spatially-explicit urban land use changes. The model was built using temporal remote sensing data land use analysis coupled with a Markov model and a spatial multinomial logistic regression framework. Experiments were performed in the Shenzhen Special Zone to substantiate the accuracy of the proposed method. We show that integration of a Markov model and a spatial logistic model is an effective method to describe urban land use evolution and meet the needs of land use early warning and annual land supply planning. © 2010 IEEE.
All Author(s) ListLi H., Huang X., Huang B., Ping L.
Name of Conference2010 30th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2010
Start Date of Conference25/07/2010
End Date of Conference30/07/2010
Place of ConferenceHonolulu, HI
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IEEE International ,
Pages2751 - 2753
LanguagesEnglish-United Kingdom
KeywordsLand use evolution, Markov model, Spatial multinomial logistic regression

Last updated on 2020-20-10 at 03:26