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Understanding the Interplay of Land Surface Temperature, Soil Moisture and Air Temperature in Diverse Ecosystems
Organization(s):Chonprathan Wittaya
Country:Thailand
Student(s):Mathawin Waew-ngam, Phonnaphat Khamai, Wachirawit Lor-prasert, Chonlathit Phumcharoen, Peerapat Eiamkleab, Peeradech Jantanudech, Phopha Rattanamanee, Vijja Soontornwong, Puttipong Munjitt,Chanya Pornpipith, Waratchaya Thongtanom, Chitapa Chanthokun, Pornchanok Chaiwut, Pitcharporn Chalermphun, Chanyanut Noomrit, Nipitpon Panpitpat, Varunya Rueangchai, Pimpitchaya Ruamboon.
Grade Level:Secondary School (grades 9-12, ages 14-18)
GLOBE Teacher:Kaset Bubphapasom
Contributors:Dueanchai Charoenruangsakul, Waralee Phunwichai,Assoc.Prof.Dr.Krisanadej Jaorensutasinee, Assoc.Prof.Dr. Mullica Jaroensutasinee, Dr.Watcharapong Srisaeng and Miss Chonthicha Khongthong, Center of Excellence for Ecoinformatics, School of Science, Walailak University.
Report Type(s):International Virtual Science Symposium Report
Protocols:Air Temperature, Clouds
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Optional Badges:I am a Data Scientist, I make an Impact, I work with a STEM Professional
Language(s):English
Date Submitted:01/19/2024
The intricate relationships among land surface temperature (LST), soil moisture, and air temperature are fundamental to understanding the dynamics of Earth's ecosystems. This study delves into these interconnections, focusing on four dam areas in Thailand—Kaeng Krachan, Sirikit, UbolRatana, and Rajjaprabha. Three distinct land cover types—forest, dam water body, and urban areas—are investigated using a combination of satellite data and ground surveys.Research questions address the insights gained from satellite data, the evolution of temperature and moisture variations over time, and the existence of relationships between LST and soil moisture. Hypotheses propose significant influences of land cover type and the province where the dam is located on LST and soil moisture.Thailand's diverse ecosystems offer a unique backdrop for this study, with four dam sites providing distinct geographical characteristics. Data collection involves ground surveys and satellite observations, focusing on temperature, cloud cover, and soil moisture.The analysis utilizes a two-way ANOVA to examine how land use and location impact surface temperature and soil moisture. Results demonstrate significant variations in both daytime and nighttime LST across land cover types and dam locations. Soil moisture exhibits substantial differences influenced by land cover type and dam location, emphasizing the interconnectedness of these environmental factors.Visualization of time series data reveals a reverse correlation between LST and soil moisture, highlighting the dynamic nature of their relationship. The study identifies the role of dam reservoirs in mitigating land surface temperature, making them valuable tools for urban heat management.Discussion encompasses the seasonal patterns observed, emphasizing the impact of dam reservoirs on surrounding temperatures. The study underscores the transformative potential of data science in urban planning, water resource management, and budget allocation, envisioning a future where informed decisions based on environmental data contribute to sustainable and resilient development.In conclusion, this research outlines a data-driven approach to reshape urban planning, optimize water resource management around dams, and foster ecologically responsible development. It envisions cities that are not only aesthetically pleasing but also better equipped to face the challenges of climate change.