The objectives of this research are to propose a model for estimating and detecting rice yields in Thailand to investigate the factors related to the rice yields to find the trend and to construct the maps of rice yields in Thailand. A linear mixed model (LMM) including the spatial effects which follow the conditional autoregressive model (CAR) and the time effects which follow the first-order linear autoregressive (AR(1)) model is proposed. The estimated rice yields are used to construct the rice yield maps in Thailand. The dependent variables are the rice yield in each month of each province. The factors considered are rainfall average temperatures and regions. The results indicate that the factors enfluencing the rice yields are rainfall average temperatures and regions (North Northeast South East West Central region is a refrence region). The trend also effects the rice yields. The rice yeilds maps are easy for readers to identify which areas have high or low yields and easy to compare the yields among areas by looking at their different colors.

The objectives of this research are to propose a linear mixed model including spatial effects to present the distribution of air pollution of each gas being Sulphur dioxide (SO2) Nitrogen dioxide (NO2) Carbon monoxide (CO) and Ozone (O3) and particulate matter (PM10) and to investigate the factors related to those air pollution in each area of Bangkok Metropolitan Region. The spatial effects are assumed to be a conditional autoregressive (CAR) model. The dependent variables are the amount of SO2 NO2 CO O3 and PM10 in each area and the independents considered are Industrial area business area and suburb area. The results indicate that the factors influencing the amount of air pollution ranking from most to least are industrial area suburb area and business area respectively.

This study the purpose of this research is to study a network of tourism of the central provinces in Thailand by topological analysis. Using the Gephi program to find that the trip by car or tour bus connects each province in the central region. Either 22 provinces. When analyzed with Gephi there are Nodes: 22 Edges: 43 and Undirected Graph. The results of the analysis concluded that Phranakhon Si Ayutthaya and Nakhon Sawan provinces are the provinces with the most significant relationships with the provinces. There are many routes connecting to various tourist attractions. It can travel to many provinces. And to study was conducted to analyze the tourist information of each province in the central region. Either 22 provinces. When analyzed with Gephi there are Nodes: 122 Edges: 145 and Undirected Graph. The overall conclusion was that Bangkok is the province with the most influential relationships with the nearest tourist attractions. The province is a popular tourist destination of the tour. There are tourist attractions that are of interest. It is a center that can travel to many provinces.