Geospatial modeling of burned area in Tak province of Northern Thailand with vegetation indices and fine particulate matter (PM10) using google earth engine | |
| Author | Proudpisut Sirisut |
| Call Number | AIT Thesis no.RS-23-13 |
| Subject(s) | Burning of land--Thailand, Northern--Data processing Wildfires--Thailand, Northern--Data processing Google Earth |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | Nowadays reducing atmospheric particulate matter is now a global priority, significantly impacting daily life. However, many people overlook this issue, perceiving it as distant and irrelevant to their own lives. This disregard continues until their health starts to suffer. Particulate matter, being microscopic, is invisible to the naked cye, contributing to this lack of awareness. Thailand is among the nations experiencing the repercussions of this issue, which significantly affects the health of its population. This study focusses on the burned area problem primarily caused by natural disasters and human actions, with a particular focus on dust pollution resulting from area burning.The present study this aims to analyze the spatial pattern of burned area, with related to particular meter and vegetation indices during 2018 to 2022 in Tak province, Thailand using google earth engine. From google earth engine, we found that burned area from 500-m MODIS (MCD64AD) were detected in wildfires and Vegetation Indices 16-Day Global from 500-m MODIS (MOD13AI). This research focuses on analyzing the spatial and temporal distribution of PM10 in Tak Province Thailand,utilizing daily data from the Pollution Control Department. The study employs Geographical Information Systems (GIS) to correlate PM10 levels with satellite imagery of burned areas from Google Earth Engine. The findings are presented through sequential maps, illustrating the distribution of PMI0 across Tak Province. The research reveals that Northern Thailand, particularly Tak Province, experiences high PM10 concentrations, primarily due to burned areas. These insights are crucial for alerting and informing the local population about potential health risks during specific times of the year. This study underscores the importance of monitoring air quality in areas with.significant PMIO presence, especially in Tak ProMince, to aid residents in managing their health during periods of elevated pollution. |
| Year | 2023 |
| Type | Thesis |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Tripathi, Nitin Kumar; |
| Examination Committee(s) | Sarawut Ninsawat;Mozumder, Chitrini; |
| Scholarship Donor(s) | Royal Thai Government;AIT Fellowship; |
| Degree | Thesis (M.Sc.) - Asian Institute of Technology, 2023 |