Embedded Files
BLOG 02 | Meet the Team Behind Remote Sensing Cookbook, Q&A Style
BLOG 02 | Meet the Team Behind Remote Sensing Cookbook, Q&A Style
At Remote Sensing Cookbook, we are a multidisciplinary team of early-career researchers and geospatial professionals dedicated to advancing applied remote sensing through open, reproducible, and accessible methods. With backgrounds spanning across physics, biology, and geography, our team is united by a shared commitment to translating complex satellite data into practical tools and insights. This Q&A series offers a behind-the-scenes look at the individuals driving our work—exploring their research interests, motivations, and the collaborative vision guiding our efforts in Earth observation. Enjoy!
Q: What drew you into the field of remote sensing?
A [Hayley]: "I was initially introduced into the world of remote sensing when I took a Geography course during my undergraduate studies. Coming from a world of only taking mostly physics courses, I wasn’t completely aware of the applications that physics had in other disciplines, such as geography. When I learned that you can use satellites to study the earth (and not just other planets, stars, and everything else in outer space), I became really excited about the potential that this area of research had. Remote sensing is so interesting to me because it involves so much physics, and a decent amount of math, but you can see the real-world applications of it right in front of you. It also feels great to be able to study what happens on Earth, especially to be able to track issues surrounding climate change."
Q: If you could use remote sensing to study any location or phenomenon on Earth (or beyond!), what would it be and why?
A [Sukhdip]: "I would be very interested in using (or I would love to use) remote sensing to study Antarctica’s subglacial lakes. Buried beneath kilometers of ice, these isolated systems provide a glimpse into how life might exist in extreme environments. Remote sensing tools like satellite altimetry and radar can reveal how these lakes interact and help improve predictions of ice sheet stability. These tools also provide valuable analogs, aiding in the search for life on icy moons like Europa!. I’m also interested in using polarimetric SAR to study Lake Baikal during the winter. With the use of polarimetric SAR, radar signals could potentially reveal ice dynamics, pressure ridge migration, and methane bubbles within the lake. As the world’s deepest freshwater lake, Baikal presents a unique testbed where results may differ from other lakes, providing insight into how factors like size and depth affect ice structure and surface features."
Xingdong Li, Di Long, Yanhong Cui, Tingxi Liu, Jing Lu, Mohamed A. Hamouda, and Mohamed M. Mohamed
Publisher: European Geosciences Union (EGU)
In their 2023 study, Li et al. introduced a novel method for estimating lake ice thickness (LIT) and water levels in ice-covered lakes using satellite altimetry data, specifically focusing on waveforms and backscattering coefficients. This approach does not rely on in situ measurements, making it applicable to ungauged lakes. The researchers developed a logarithmic regression model to transform backscattering coefficients into LIT, effectively addressing complex initial ice conditions and providing accurate measurements even for thin ice layers that traditional waveform analysis might miss. Validation against in situ data and cross-referencing with modeled LIT demonstrated an accuracy of approximately 0.2 meters. Additionally, the study explored the impact of lake surface snow on water level estimations, revealing that different threshold retracking methods correspond to varying backscattering surfaces; the 0.1 threshold aligns with the snow–ice interface, while the 0.5 threshold is closer to the air–snow interface. By merging water level data derived from these different thresholds, the researchers improved the overall estimation accuracy. This work enhances the interpretation of satellite altimetry signals from ice-covered lakes and broadens the potential applications of altimetry data in cryospheric studies.
Reference:
Li, X., Long, D., Cui, Y., Liu, T., Lu, J., Hamouda, M. A., & Mohamed, M. M. (2023). Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients. Cryosphere, 17(1), 349–369. Scopus. https://doi.org/10.5194/tc-17-349-2023
Page updated
Google Sites
Report abuse