Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing

Uttam Kumar, Sangram Ganguly, Ramakrishna R. Nemani, Kumar S Raja, Cristina Milesi, Ruchita Sinha, Andrew Michaelis, Petr Votava, Hirofumi Hashimoto, Shuang Li, Weile Wang, Subodh Kalia, Shreekant Gayaka

Open source

DOI: 10.3390/rs9111105
Published: 2017-10-29
Container: Remote Sensing
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/rs9111105,
  title = {Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing},
  author = {Uttam Kumar and Sangram Ganguly and Ramakrishna R. Nemani and Kumar S Raja and Cristina Milesi and Ruchita Sinha and Andrew Michaelis and Petr Votava and Hirofumi Hashimoto and Shuang Li and Weile Wang and Subodh Kalia and Shreekant Gayaka},
  year = {2017},
  journal = {Remote Sensing},
  doi = {10.3390/rs9111105},
  url = {https://doi.org/10.3390/rs9111105}
}

RIS

TY  - JOUR
TI  - Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing
AU  - Uttam Kumar
AU  - Sangram Ganguly
AU  - Ramakrishna R. Nemani
AU  - Kumar S Raja
AU  - Cristina Milesi
AU  - Ruchita Sinha
AU  - Andrew Michaelis
AU  - Petr Votava
AU  - Hirofumi Hashimoto
AU  - Shuang Li
AU  - Weile Wang
AU  - Subodh Kalia
AU  - Shreekant Gayaka
PY  - 2017
JO  - Remote Sensing
DO  - 10.3390/rs9111105
UR  - https://doi.org/10.3390/rs9111105
ER  -

APA

Kumar, U., Ganguly, S., Nemani, R. R., Raja, K. S., Milesi, C., Sinha, R., Michaelis, A., Votava, P., Hashimoto, H., Li, S., Wang, W., Kalia, S., & Gayaka, S. (2017). Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing. Remote Sensing. https://doi.org/10.3390/rs9111105

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crossref · retrieved 2026-09-26T22:31:57.346Z