Science education
Infographics to communicate basic concepts about Remote sensing and water.
"Por el camino va el dorado de mi pasado
Cuenta la leyenda de sequías y subiendas
Y su esperanza y condena
Brillan por el Magdalena"
Mónica Giraldo
About me
I am a Ph.D. student at the University of North Carolina - Chapel Hill. I joined the Global Hydrology Lab (GHL) in August 2022
after earning a Fulbright Scholarship.
I was born in Colombia, in the so-called "eternal spring city," Medellin, the second larger city in Colombia and home
of the Universidad de Antioquia, where I got my B.S. in Sanitary Engineering and my master's in
Environmental Engineering.
In doing my master, I researched the erosion, progradation, and evolution of the Atrato River Delta, located in the west of Colombia,
using Landsat imagery, image segmentation (Otsu method), and Google Earth Engine.
Currently, I'm working in two areas: in assessing water quality from remote sensing, specifically total suspended sediments;
and in understanding how rivers work (fluvial morphology) worldwide using data from the new NASA
Surface Water
and Ocean Topography satellite -SWOT-
launched on December 2022. In this topic, I want to know rivers' cross-sectional variation (width to depth ratio) worldwide.
Projects and Recent Work
Curriculum Vitae
Erosion and progradation in the Atrato River delta: A spatiotemporal analysis
I analyzed the geomorphological changes in the shoreline of the Atrato River Delta in Northwestern Colombia, associated with erosion and progradation, using Landsat imagery, image segmentation, and Google Earth Engine (GEE) to automatically identify the changes on an annual basis over 33 years (1986–2019). Click on the title to download it.
Unlike NDVI, Total Suspended Sediment (TSS) indices from remote sensing do not work well universally on inland waters
Like NDVI Normalized Difference Vegetation Index (NDVI) in remote sensing of land, researchers have been looking for universal Total Suspended Sediments (TSS) water quality indices.
A simple Google Earth Engine app to track the area of the Sierra Nevada de Santa Marta Glacier - Colombia
Using the Random Forest algorithm, Landsat imagery (bands: B3, B5, and B7) was classified into two classes: snow - not snow, to track the evolution of the glacier. It needs improvements (Click on the title to open it)
Risus ornare lacinia
Lorem ipsum dolor sit amet nisl sed nullam feugiat.