This summer, I had the opportunity to study the connection between urbanization and the wildfires in the Santa Monica Mountains in Southern California. Humans have been the leading cause of wildfires since 1992, and this specific region of Southern California has been especially prone to disastrous fires in recent years.
Using the software platform of Google Earth Engine and a modified JavaScript language, I studied the change in urban areas from satellite images taken by Remote Sensing. With the satellite images, Google Earth Engine makes it simple to perform calculations and create classifications on the images. A classification is a way of categorizing the individual pixels in images based on a training image, sorting the image pixels into different classes based on their photo spectrum. The picture above is an example of a classification. A series of different classifications, using different satellite imaging and different time periods, were the main tool that I used to evaluate the urban changes in the region.
Before beginning the project, coding was completely foreign to me, and I had no experience with any form of Remote Sensing or GIS (Geographic Information Systems). As this was my first research experience and I did not have a strong computer background, I was fairly intimated when I began, but my mentor guided me through the learning process and within a short few weeks I was able to confidently operate the platform on my own. From this experience, I not only gained an intimate understanding of the region and computer processing, but I saw how the research process unfolds from learning how to read a research paper, developing a research question, and then determining the best method to test the hypothesis. This research experience has been extremely rewarding,and I am now strongly considering a career in a research based field.
This summer, I had the opportunity to study the connection between urbanization and the wildfires in the Santa Monica Mountains in Southern California. Humans have been the leading cause of wildfires since 1992, and this specific region of Southern California has been especially prone to disastrous fires in recent years.
Using the software platform of Google Earth Engine and a modified JavaScript language, I studied the change in urban areas from satellite images taken by Remote Sensing. With the satellite images, Google Earth Engine makes it simple to perform calculations and create classifications on the images. A classification is a way of categorizing the individual pixels in images based on a training image, sorting the image pixels into different classes based on their photo spectrum. The picture above is an example of a classification. A series of different classifications, using different satellite imaging and different time periods, were the main tool that I used to evaluate the urban changes in the region.
Before beginning the project, coding was completely foreign to me, and I had no experience with any form of Remote Sensing or GIS (Geographic Information Systems). As this was my first research experience and I did not have a strong computer background, I was fairly intimated when I began, but my mentor guided me through the learning process and within a short few weeks I was able to confidently operate the platform on my own. From this experience, I not only gained an intimate understanding of the region and computer processing, but I saw how the research process unfolds from learning how to read a research paper, developing a research question, and then determining the best method to test the hypothesis. This research experience has been extremely rewarding,and I am now strongly considering a career in a research based field.