FLAASH, a MODTRAN4-based atmospheric correction algorithm, its application and validation

By T. Cooley, G. Anderson, G. Felde, Michael L. Hoke, Anthony J. Ratkowski, J. Chetwynd, J. Gardner, S. Adler-Golden, M. Matthew, A. Berk and 4 more. IEEE International Geoscience and Remote Sensing Symposium, 2002

409 citations recorded by the source corpus.

Subfields: Ecology, Global and Planetary Change, Media Technology

View Paper: https://www.semanticscholar.org/paper/89643739d3a4d9cc449b2376bc8be053e298af33

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. William J. Emery
2. Fabio Pacifici

In Media Technology

1. Yuda Song
2. William J. Emery
3. Fabio Pacifici
4. Hui Qian
5. Xin Du
6. Zhuqing He

Citations in the corpus

• Vision Transformers for Single Image Dehazing (2022, methodology): “76 remote sensing images containing diverse topography with good weather conditions and performed atmospheric correction using the FLAASH module [79].”
• Very High Resolution Multiangle Urban Classification Analysis (2012, methodology): “Consequently, in this study, each image is normalized to surface reflectance using Fast Line-ofsight Atmospheric Analysis of Spectral Hypercubes (FLAASH) [14] to account for view-angle atmospheric effects.”