Predicting and modeling urban expansion have been the subject of different studies since the 1990s. The study of land use/land cover changes is important in various aspects, such as floods, land surface temperatures, climate change, reduced plant and animal diversity and other issues. Population structure and the dynamism of motivations affect the land use especially, the migration of the rural population to the urban suburbs turns rural areas to urban land uses. Accurate and up-to-date land cover information is necessary for understanding and evaluating the changes, which are important for development planners. It is very important for urban planning and landscape development to have a spatial understanding about urban expansion. Land Use (LU) and Land Cover (LC) changes have been happening due to natural and social factors which impact ecosystems considerably. Decision-makers usually wish to manage and predict land use and land cover changes. Land use change is an important part of global environmental changes. Land cover maps were predicted for 2030, which demonstrate the city’s expansion from 5500 ha in 2000 to more than 9000 ha in 2030. Overall accuracy of MLC was higher than others at about 0.94 accuracy, although, SVMs were slightly more accurate for large area segments. Cellular Automata Artificial neural network method was used to predict land cover changes. The MLC performed slightly better than SVMs’ classifier. The results demonstrated 0.93–0.94 overall accuracies for MLC and SVMs’ algorithms, but it was around 0.79 for the SAM algorithm. Landsat images of 2000, 2010, and 2020 have been used to provide land cover information. Maximum Likelihood classifier (MLC), Spectral Angle Mapper (SAM), and Support Vector Machines (SVMs) algorithms are used as the representatives for parametric, non-parametric and subpixel capable methods for change detection and change prediction of Urmia City (Iran) and its suburbs. This study is focusing on land cover classification and prediction using three well known classifiers and remote sensing data. The U.S.-China trade spat has been at the center of the oil market demise, which has sent the global economy to the brink of recession and negatively impacted oil demand forecasts.A reliable land cover (LC) map is essential for planners, as missing proper land cover maps may deviate a project. The U.S.-China trade spat seems to be hotting up again after yesterday's announcement from the White House, the global growth and demand outlook does not need a new political/financial crisis in Europe and a potential trade war between the world's two biggest economies. We are going to see more of this and this will be the worst the relationship has been since diplomatic relations began. Until now it has been a diplomatic spat, we haven't seen it play out beyond the diplomatic and political realm, now it is imposing regulatory barriers without contravening the free trade agreement. The trade spat is driving the market crazy, $1,500 (for gold) is now the new normal unless trade relations take a turn in a right direction. A CNN insider confirmed Buck went to CNN boss Jeff Zucker and asked to be taken off Cuomo’s show and moved to another department, which he agreed to, the insider denied rumors that Buck was given a significant pay-off to stay silent over her spat with the agitable anchor.
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