GEOG 182C
Advanced Remote Sensing
Description: (Formerly numbered 174.) Lecture, three hours; laboratory, two hours. Requisite: course 182A. Remote sensing in visible and infrared wavelength regions to understand basic concepts of radiation propagation and interaction with matter, how digital remote sensing images are acquired, and constraints on available data and data analysis. P/NP or letter grading.
Units: 5.0
Units: 5.0
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Most Helpful Review
Winter 2025 - Despite being challenging and frustrating when debugging code, this class was fascinating and gave me opportunities to develop my coding skills and practice Google Earth Engine thoroughly. If you want to improve your remote sensing skills, TAKE THIS CLASS!! It is one of the most challenging but rewarding GIS classes I have taken in my GIS minor at UCLA. Bo offered two grading schemes: 100% based on weekly projects and discussion posts OR 100% on the independent project. If you do both, he will give 10 points extra credit towards the final grade. Even though the weekly project can be very complex and demanding, Bo offers students many extra credit opportunities when they structure their codes or package the functions outside the main code, for example. These additional credit expectations can vary between each project. If you don’t have any Google Earth Engine experience, surviving each weekly project already offers you enough scores to float in the class ngl. All students complain about the class but we are not that worried about our grades, so I think it is a great place to learn, try, and fail at times, LOL. This is the only geography upper-division class with a mandatory lab session, so it speaks volumes. However, I am grateful for Bo’s quick email or canvas message response whenever I ask him about the class or how to debug the code. William was also very supportive during office hours or when requesting an extension for the weekly project. I think the experience in this class would not have been this positive without great TA support. I have learned so much from this class, and I will never go back to download the Landsat data from USGS or do mosaic manually ever again. GEE is much more efficient and such a powerful free-source remote sensing tool. If you are dreaming of pursuing a job in the remote sensing world, TAKE THIS CLASS. Go to office hours, ask questions, and expect to invest time in this class. Each project can take from 2 to more than 10 hours a week… especially during the machine learning week when you need to add your own training points… but don’t worry about that now. You will know when you get there, and you will not be alone since everyone will also struggle with you LMAOOO. Needless to say, I highly recommend this class if you want a class that is worth every penny you pay for this school. Bo is such a devoted instructor, and lifelong GEE support is guaranteed after taking a class with him.
Winter 2025 - Despite being challenging and frustrating when debugging code, this class was fascinating and gave me opportunities to develop my coding skills and practice Google Earth Engine thoroughly. If you want to improve your remote sensing skills, TAKE THIS CLASS!! It is one of the most challenging but rewarding GIS classes I have taken in my GIS minor at UCLA. Bo offered two grading schemes: 100% based on weekly projects and discussion posts OR 100% on the independent project. If you do both, he will give 10 points extra credit towards the final grade. Even though the weekly project can be very complex and demanding, Bo offers students many extra credit opportunities when they structure their codes or package the functions outside the main code, for example. These additional credit expectations can vary between each project. If you don’t have any Google Earth Engine experience, surviving each weekly project already offers you enough scores to float in the class ngl. All students complain about the class but we are not that worried about our grades, so I think it is a great place to learn, try, and fail at times, LOL. This is the only geography upper-division class with a mandatory lab session, so it speaks volumes. However, I am grateful for Bo’s quick email or canvas message response whenever I ask him about the class or how to debug the code. William was also very supportive during office hours or when requesting an extension for the weekly project. I think the experience in this class would not have been this positive without great TA support. I have learned so much from this class, and I will never go back to download the Landsat data from USGS or do mosaic manually ever again. GEE is much more efficient and such a powerful free-source remote sensing tool. If you are dreaming of pursuing a job in the remote sensing world, TAKE THIS CLASS. Go to office hours, ask questions, and expect to invest time in this class. Each project can take from 2 to more than 10 hours a week… especially during the machine learning week when you need to add your own training points… but don’t worry about that now. You will know when you get there, and you will not be alone since everyone will also struggle with you LMAOOO. Needless to say, I highly recommend this class if you want a class that is worth every penny you pay for this school. Bo is such a devoted instructor, and lifelong GEE support is guaranteed after taking a class with him.
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