ABSTRACT

To examine the drought affected area is highly challenging because the drought is a natural disaster that starts and expands slowly. The severity of the drought is different when the rainfall is imbalance in the area. The objective of this study was to analyze the drought around Chi watershed with total area of 49,131.920 km 2 by using data from Terra/MODIS satellite during 10 years (2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016). On part of method operation, the NDVI data was obtained from Terra/MODIS satellite, and VCI (Vegetation Condition Index) analysis was performed to examine the condition of plants which could identify the condition of drought in the area. According to the study, it was found that in 2015, it was the time when the drought affected area was at most which was equal to 91.54 percent, or 44975.23 km 2 . When the analysis results of these ten years were brought to find relationship with rainfall, it was found that the decision coefficient was R 2 = 0.913. It can be concluded from the results of this study that VCI could be used as indicator and could identify the drought in Chi watershed in terms of area and time reasonably.

No abstract

At present, the climate has constantly been changing, especially the increase in global average temperature that results in the risk of severe climatic conditions such as heat wave, drought and flood. The objective of this study is to estimate land surface temperature (LST) by applying Landsat satellite data in Mueang Maha Sarakham District, Maha Sarakham Province, Thailand. The study focuses on investigating the temperature changes for the years 2006 and 2015. The research was conducted by analyzing the satellite data in the thermal infrared band with a geo-informatics package software mutually with mathematical models. The operation results indicated that the average LST was at 26.28°C in 2006 and 27.15°C in 2015. In order to verify the accuracy of the data in this study, the results of the annual satellite data analysis were brought to find out a statistical correlation with the LST data from the Meteorological Station of Thai Meteorological Department (TMD). The results indicated that there was a correlation of the data at a high level in 2006 and 2015. The results of this study indicated that the satellite data analysis method is reliable and can be used to analyze, track, and verify data to predict surface temperatures effectively.

Phytoplankton are tiny creatures floating on water mass. Inside their cells, there is the pigment chlorophyll-a, a kind of substance used in photosynthesis. As a result, it is essential for the ecosystem of water sources because it is considered as the primary producer. This research aims to analyze the content and distribution of chlorophyll-a on the sea surface. It uses data from the Aqua/MODIS Satellite in a case study of the upper Gulf of Thailand in 2020. The SeaWiFS Data Analysis System (SeaDAS) program analyzed the obtained data. The results revealed that the content and distribution of chlorophyll-a on the sea surface in the area of the upper Gulf of Thailand were based on seasons and the influence of monsoons. It was found that the content of chlorophyll-a was highest in the southwest monsoon period (May-October) and lowest in the northeast monsoon period (November-April). The content of chlorophyll-a was highest in October with a mean of 3.148 mg/m 3 , followed by November, and it was lowest in February with a mean of 1.514 mg/m 3 . Moreover, it was also found that, if the sea surface temperature was higher than 30°C, phytoplankton exhibited proper growth and propagation. As a result, the content and distribution of chlorophyll-a were consistent with seasonal changes and weather variability.