activity
20152023
most citedObservations of cyclone-induced storm surge in coastal Bangladesh

29 citations · 57 across the 10 of their papers we have counts for

collaborators

13 papers

physics.geo-ph2023★ 1 cited

Multiscale Topology of the Spectroscopic Mixing Space: Impervious Substrates

Christopher Small, Daniel Sousa

Characterization of topology and dimensionality of spectral feature spaces provides insight into information content. The objective of this study is to characterize topology and sp…

physics.geo-ph2023★ 2 cited

Topological Generality and Spectral Dimensionality in the Earth Mineral Dust Source Investigation (EMIT) using Joint Characterization and the Spectral Mixture Residual

Daniel Sousa, Christopher Small

NASA's Earth Surface Mineral Dust Source Investigation (EMIT) mission seeks to use spaceborne imaging spectroscopy (hyperspectral imaging) to map the mineralogy of arid dust source…

physics.geo-ph2022

Linking Common Multispectral Vegetation Indices to Hyperspectral Mixture Models: Results from 5 nm, 3 m Airborne Imaging Spectroscopy in a Diverse Agricultural Landscape

Daniel Sousa, Christopher Small

For decades, agronomists have used remote sensing to monitor key crop parameters like biomass, fractional cover, and plant health. Vegetation indices (VIs) are popular for this pur…

cs.CV2022

A multiscale spatiotemporal approach for smallholder irrigation detection

Terence Conlon, Christopher Small, Vijay Modi

In presenting an irrigation detection methodology that leverages multiscale satellite imagery of vegetation abundance, this paper introduces a process to supplement limited ground-…

physics.geo-ph2021

Joint Characterization of the Cryospheric Spectral Feature Space

Christopher Small, Daniel Sousa

Hyperspectral feature spaces are useful for many remote sensing applications ranging from spectral mixture modeling to discrete thematic classification. In such cases, characteriza…

cs.LG2021

Joint Characterization of Spatiotemporal Data Manifolds

Daniel Sousa, Christopher Small

Spatiotemporal (ST) image data are increasingly common and often high-dimensional (high-D). Modeling ST data can be a challenge due to the plethora of independent and interacting p…