Publications

  1. 🆕 Dhakal, A., Ahmad, A., Khanal, S., Sastry, S., Kerner, H., and Jacobs, N. (2024). Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images. To appear in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, EarthVision 2024.

  2. 🆕 Rolnick, D., Aspuru-Guzik, A., Beery, S., Dilkina, B., Donti, P. L., Ghassemi, M., Kerner, H., Monteleoni, C., Rolf, E., Tambe, M., White, A. (2024). Application-Driven Innovation in Machine Learning. To appear in Proceedings of the International Conference on Machine Learning (ICML), link.

  3. 🆕 Rolf, E., Klemmer, K., Robinson, C., and Kerner, H. (2024). Mission Critical–Satellite Data is a Distinct Modality in Machine Learning. To appear in Proceedings of the International Conference on Machine Learning (ICML), link.

  4. 🆕 Kebede, E. A., Abou Ali, H., Clavelle, T., Froehlich, H. E., Gephart, J. A., Hartman, S., Herrero, M., Kerner, H., Mehta, P., Nakalembe, C., Ray, D. K., Siebert, S., Thornton, P., Davis, K. F. (2024). Nature Reviews Earth & Environment, p. 1-17, link.

  5. Kerner, H., Nakalembe, C., Yeh, B., Zvonkov, I., Skakun, S., Becker-Reshef, I., and McNally, A. (2023). Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War. arXiv preprint, link.

  6. Prieur, N. C., Amaro, B., Gonzalez, E., Kerner, H., Medvedev, S., Rubanenko, L., Werner, S., Xiao, Z., Zastrozhnov, D., and Lapôtre, M. G. (2023). Automatic Characterization of Boulders on Planetary Surfaces From High‐Resolution Satellite Images. Journal of Geophysical Research: Planets, 128(11), e2023JE008013, link.

  7. Tseng, G., Zvonkov, I., Purohit, M., Rolnick, D., and Kerner, H. (2023). Lightweight, Pre-trained Transformers for Remote Sensing Timeseries. Neural Information Processing Systems (NeurIPS), Climate Change AI Workshop, link.

  8. Purohit, M., Adler, J., and Kerner, H. (2023). ConeQuest: A Benchmark for Cone Detection on Mars. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp. 6026-6035, link.

  9. Malvi, S., Shah, H., Chandarana, N., Purohit, M., Adler, J., Kerner, H. (2023). Automated Multi-class Crater Segmentation in Mars Orbital Images. Proceedings of the 31st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2023), GeoAI Workshop, pp. 110-120, link.

  10. Kerner, H., Nakalembe, C., Yang, A., Zvonkov, I., McWeeny, R., Tseng, G., and Becker-Reshef, I. (2023). How accurate are existing land cover maps for agriculture in Sub-Saharan Africa? Nature Scientific Data, 11(486), link.

  11. Tseng, G., Zvonkov, I., Purohit, M., Rolnick, D., and Kerner, H. (2023). Lightweight, Pre-trained Transformers for Remote Sensing Timeseries. arXiv preprint, link.

  12. Lacoste, A., Lehmann, N., Rodriguez, P., Sherwin, E. D., Kerner, H., Lütjens, B., Irvin, J. A., Dao, D., Alemohammad, H., Drouin, A., Gunturkun, M., Huang, G., Vazquez, D., Newman, D., Bengio, Y., Ermon, S., Zhu, X. (2023). GEO-Bench: Toward Foundation Models for Earth Monitoring. In Proceedings of the Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, link.

  13. Nakalembe, C. and Kerner, H. (2023). Considerations for AI-EO for agriculture in Sub-Saharan Africa. Environmental Research Letters, 18(4), link.

  14. Zvonkov, I., Tseng, G., Nakalembe, C., and Kerner, H. (2023). OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data. In Proceedings of the AAAI Conference on Artificial Intelligence, 37(12), 14655-14663, link.

  15. Kerner, H., Sundar, S., and Satish, M. (2023). Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels. In Proceedings of the AAAI Conference on Artificial Intelligence Workshops, link.

  16. Manimurugan, S., Singaram, R., Nakalembe, C., and Kerner, H. (2022). Geo-referencing crop labels from street-level images using Structure from Motion. In Proceedings of the 73rd International Astronautical Congress (IAC), link.

  17. Rice, M.S., Seeger, C., Bell, J., Calef, F., St Clair, M., Eng, A., Fraeman, A.A., Hughes, C., Horgan, B., Jacob, S., Johnson, J., Kerner, H., Kinch, K., Lemmon, M., Million, C., Starr, M., and Wellington, D. (2022). Spectral diversity of rocks and soils in Mastcam observations along the Curiosity rover’s traverse in Gale crater, Mars. Journal of Geophysical Research: Planets, e2021JE007134, link.

  18. Kerner, H. R. and Adler, J. B. (2022). Guiding Field Exploration on Earth and Mars with Outlier Detection. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS 2022), pp. 5333-5336, link.

  19. Manheim, M. R., Henriksen, M. R., Robinson, M. S., Kerner, H. R., Karas, B. A., Becker, K. J., Chojnacki, M., Sutton, S. S., Blewett, D. T. (2022). High-Resolution Regional Digital Elevation Models and Derived Products from MESSENGER MDIS Images. Remote Sensing, 14, 3564, link.

  20. Kerner, H. R., Sahajpal, R., Pai, D. B., Skakun, S., Puricelli, E., Hosseini, M., Meyer, S., and Becker-Reshef, I. (2022). Phenological normalization can improve in-season classification of maize and soybean: A case study in the central US Corn Belt. Science of Remote Sensing, 6, 100059, link.

  21. Kerner, H. R., Rebbapragada, U., Wagstaff, K. L., Lu, S., Dubayah, B., Huff, E., Raman, V., and Kulshrestha, S. (2022). Domain-Agnostic Outlier Ranking Algorithms—A Configurable Pipeline for Facilitating Outlier Detection in Scientific Datasets. Frontiers in Astronomy and Space Sciences, 9, 867947, link.

  22. Nakalembe, C. L. and Kerner, H. R. (2022). Applications and Considerations for AI-EO for Agriculture in Sub-Saharan Africa. Association for the Advancement of Artificial Intelligence (AAAI) Workshops, International Workshop on Social Impact of AI for Africa.

  23. Tseng, G., Kerner, H., Rolnick, D. (2022). TIML: Task-Informed Meta-Learning for crop type mapping. Association for the Advancement of Artificial Intelligence (AAAI) Workshops, AI for Agriculture and Food Systems (AIAFS).

  24. Handwerger, A. L., Jones, S. Y., Amatya, P., Kerner, H. R., Kirschbaum, D. B., and Huang, M. H. (2021). Strategies for landslide detection using open-access synthetic aperture radar backscatter change in Google Earth Engine. Natural Hazards and Earth System Sciences Discussions, 22, pp. 753-773, link.

  25. Tseng, G., Zvonkov, I., Nakalembe, C., Kerner, H. (2021). CropHarvest: a global satellite dataset for crop type classification. Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks, link.

  26. Lacoste, A., Sherwin, E., Kerner, H., Alemohammad, H., Lutjens, B., Irvin, J., Dao, D., Chang, A., Gunturkun, M., Drouin, A., Rodriguez, P., Vazquez, D. (2021). Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark. Proceedings of the Neural Information Processing Systems (NeurIPS) Workshops, Tackling Climate Change with AI, link.

  27. Shirzaei, M., Khoshmanesh, M., Ojha, C., Werth, S., Kerner, H., Carlson, G., Sherpa, S. F., Zhai, G., and Lee, J. Persistent impact of spring floods on crop loss in U.S. Midwest. Weather and Climate Extremes, 34, 100392, link.

  28. Huppertz, R., Nakalembe, C., Kerner, H. (2021). Using transfer learning to study burned area dynamics: A case study of Refugee settlements in West Nile, Northern Uganda. Proceedings of the ACM/SIGKIDD Conference on Knowledge Discover and Data Mining (KDD) Workshops, Humanitarian Mapping, link.

  29. Paliyam, M., Nakalembe, C., Kerner, H. (2021). Street2Sat: A Machine Learning Pipeline for Generating Ground-truth Geo-referenced Labeled Datasets from Street-Level Images. Proceedings of the International Conference on Machine Learning (ICML) Workshops, Tackling Climate Change with AI, link.

  30. Gray, P. C., Chamorro, D. F., Ridge, J. T., Kerner, H. R., Ury, E. A., and Johnston, D. W. Temporally Generalizable Land Cover Classification: A Recurrent Convolutional Neural Network Unveils Major Coastal Change through Time. Remote Sensing, 13(19), 3953, link.

  31. Tseng, G., Kerner, H., Nakalembe, C., and Becker-Reshef, I. (2021). Learning to predict crop type from heterogeneous sparse labels using meta-learning. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, EarthVision 2021, link.

  32. Horton, P., Kerner, H., Jacobs, S., Cisneros, E., Wagstaff, K. L., and Bell III, J. F. (2021). Integrating Novelty Detection Capabilities with MSL Mastcam Operations to Enhance Data Analysis. IEEE Aerospace Conference, Big Sky, Montana, March 6-13, link.

  33. Lawal, A., Kerner, H., Becker-Reshef, I., Meyer, S. (2021). Mapping the Location and Extent of 2019 Prevent Planting Acres in South Dakota Using Remote Sensing Techniques. Remote Sensing, 13(13), 2430, link.

  34. Tseng, G., Kerner, H., Nakalembe, C., and Becker-Reshef, I. (2020). Annual and in-season mapping of cropland at field scale with sparse labels. Proceedings of the Neural Information Processing Systems (NeurIPS) Workshops, Tackling Climate Change with AI, link.

  35. Azari, A. R., Biersteker, J. B., Dewey, R. M., Doran, G., Forsberg, E., Harris, C. D. K., Kerner, H. R., Skinner, K. A., Smith, A. W. (2020). Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade. White Paper to the NRC Planetary Science and Astrobiology Decadal Survey 2023-2032, link.

  36. Wagstaff, K. L., Francis, R., Kerner, H., Lu, S., Nerrise, F. (2020). Novelty-Driven Onboard Targeting for Mars Rovers. International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS), link.

  37. Hosseini, M., Kerner, H., Sahajpal, R., Puricelli, E., Lu, Y-H., Lawal, A., Humber, M. L., Mitkish, M., Meyer, S., Becker-Reshef, I. Evaluating the Impact of the 2020 Iowa Derecho on Corn and Soybean Fields Using Synthetic Aperture Radar. Remote Sensing, 12(23), 3878, link.

  38. Kerner, H. R., Sahajpal, R., Skakun, S., Becker-Reshef, I., Barker, B., Hosseini, M. (2020). Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage Normalization. Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops, link.

  39. Kerner, H. R., Tseng, G., Becker-Reshef, I., Barker, B., Munshell, B., Paliyam, M., Hosseini, M. (2020). Rapid Response Crop Maps in Data Sparse Regions. Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshops, link.

  40. Kerner, H. R., Wagstaff, K. L., Bue, B. D., Wellington, D. F., Jacob, S., Horton, P., Bell, J. F., Kwan, C. Ben Amor, H. (2020). Comparison of Novelty Detection Methods for Multispectral Images in Rover-Based Planetary Exploration Missions. Data Mining and Knowledge Discovery, 34, pp. 1642–1675, link.

  41. Kerner, H. R., Nakalembe, C., Becker-Reshef, I. (2020). Field-Level Crop Type Classification with k-Nearest Neighbors: A Baseline for a New Kenya Smallholder Dataset. Proceedings of the International Conference on Learning Representations (ICLR) Workshops, link.

  42. Kerner, H. R., Hardgrove, C., Czarnecki, S., Gabriel, T. S. J., Mitrofanov, I., Litvak, M., Sanin, A., Lisov, D. (2020). Analysis of Active Neutron Measurements from the Mars Science Laboratory Dynamic Albedo of Neutrons Instrument: Intrinsic Variability, Outliers, and Implications for Future Investigations. Journal of Geophysical Research: Planets, 125(5), e2019JE006264, link.

  43. Kerner, H. R., Wagstaff, K. L., Bue, B. D., Gray, P., Bell III, J. F., Ben Amor, H (2019). Deep Learning Methods Toward Generalized Change Detection on Planetary Surfaces. Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(10), pp. 3900-3918, link.

  44. Kerner, H. R., Wellington, D. F., Wagstaff, K. L., Bell III, J. F., Kwan, C., Ben Amor, H. (2019). Novelty Detection for Multispectral Images with Application to Planetary Exploration. Proceedings of the AAAI Conference on Artificial Intelligence, pp. 9484-9491, link.

  45. Kerner, H. R., Ben Amor, H., Bell III, J. F. (2018). Context-Dependent Image Quality Assessment of JPEG-Compressed Mars Science Laboratory Mastcam Images using Convolutional Neural Networks. Computers and Geosciences, 118, pp. 109-121, link.

  46. Kwan, C., Chou, B., Kwan, L., Larkin, J., Ayhan, B., Bell III, J. F., Kerner, H. R. (2017). Demosaicing Enhancement using Pixel-Level Fusion. Signal, Image and Video Processing, 12(4), pp. 749-756, link.