4 papers
SuperRivolution: Fine-Scale Rivers from Coarse Temporal Satellite Imagery
Rangel Daroya, Subhransu Maji
Satellite missions provide valuable optical data for monitoring rivers at diverse spatial and temporal scales. However, accessibility remains a challenge: high-resolution imagery i…
RiverScope: High-Resolution River Masking Dataset
Rangel Daroya, Taylor Rowley, Jonathan Flores +14
Surface water dynamics play a critical role in Earth's climate system, influencing ecosystems, agriculture, disaster resilience, and sustainable development. Yet monitoring rivers…
Improving Satellite Imagery Masking using Multi-task and Transfer Learning
Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons +5
Many remote sensing applications employ masking of pixels in satellite imagery for subsequent measurements. For example, estimating water quality variables, such as Suspended Sedim…
WildSAT: Learning Satellite Image Representations from Wildlife Observations
Rangel Daroya, Elijah Cole, Oisin Mac Aodha +2
Species distributions encode valuable ecological and environmental information, yet their potential for guiding representation learning in remote sensing remains underexplored. We…