## 5 Conclusions  
Recently, Thailand faces with the problem of urban expansion due to the national plan policy that was established to confirm BM as the center for all aspects of the country. Moreover, industrialization and innovation in the globalized world have turned BM into a modern city where everyone would like to live. However, BM does not grow by itself, but rather brings about spatial planning problems in the vicinity, which collectively can be called the BMR. This study used scientific methodology to explore the urban expansion and LULC changes in a specific time period based on the innovation of satellite imagery. Landsat images were utilized to generate LULC maps using the sophisticated maximum likelihood classification in different times. Then, the change detection technique was investigated to develop a pair of LULC maps in order to identify the land transformations. From this study, it can noticeably evident that the major land conversion in this area is agriculture to urban. To explore the future LULC and urban expansion in the future, this study applied the integrated methods of CA-MC and MLP-MC to generate transition probabilities and transition rates for the simulations. The simulated results in the years of 1988, 2003, 2008, and 2011 were validated to identify the best method for the predictions. The accuracy of the simulations showed that MLP-MC yielded higher accuracy than CA-MC. Therefore, the simulation in the years of 2014 and 2035 used the MLP as a platform for the prediction.  
To project the LULC to the year 2035, even though the physical and economic factors were considered as input layers for the engendering the transition potential in each conversion, the future population and economic growth were applied to control the transition rate of the land conversions. The results from the study evidently confirm that in 2014 the predicted LULC maps from the SD and statistics extrapolation shows reliable results with robust accuracy, particularly the projected result from the SD method. Therefore, the transition probability rates, proposed by the SD method, within the MLP environment were used to explore the urban expansion in 2035. The simulation illustrates that urban and built-up area are the main LULC types and occupy about half of the land in the BMR. Most of the agricultural land would be converted to urban or built-up area if proper measures are not taken. This study shows that integration of the LULC modeling approach, remote sensing data, and demographic and economic data can be professionally used to simulate the future LULC change and, hence, the urban expansion phenomena in spatial distribution, direction, and time can be monitored.  
Figure 9: Urban extend overlay with the land transportation system of the BMR in 2035.  
Future LULC is crucial information for planners and organizations to allocate important infrastructures and manage sustainable land use in response to the diverse requirements of the people in this region.  
[PERSON] mainly contributed to analyzing the data, developed the research design, and writing of this paper. [PERSON] mainly suggested the research framework and methodology together with the valuable advice from [PERSON], and [PERSON]. All authors read and approved the manuscript.  
The authors declare no conflict of interest.