2022
- Pallandt, M., et al. “Representativeness Assessment Of The Pan-Arctic Eddy Covariance Site Network And Optimized Future Enhancements”. Biogeosciences, 2022, pp. 559 - 583.
2021
- Fer, I., et al. “Beyond Ecosystem Modeling: A Roadmap To Community Cyberinfrastructure For Ecological Data‐Model Integration”. Global Change Biology, 2021, pp. 13 - 26.
2019
- Langford, Z. L., et al. “Arctic Vegetation Mapping Using Unsupervised Training Datasets And Convolutional Neural Networks”. Remote Sensing, 2019, p. 69.
- Shiklomanov, A. N., et al. “Enhancing Global Change Experiments Through Integration Of Remote‐Sensing Techniques”. Frontiers In Ecology And The Environment, 2019, pp. 215 - 224.
2017
- Langford, Z. L., et al. “Convolutional Neural Network Approach For Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion”. 2017 Ieee International Conference On Data Mining Workshops (Icdmw)2017 Ieee International Conference On Data Mining Workshops (Icdmw), IEEE, 2017.
- Langford, Z. L., et al. “Convolutional Neural Network Approach For Mapping Arctic Vegetation Using Multi-Sensor Remote Sensing Fusion”. 2017 Ieee International Conference On Data Mining Workshops (Icdmw), 2017, pp. 770-778.
2016
- Tang, G., et al. “Addressing Numerical Challenges In Introducing A Reactive Transport Code Into A Land Surface Model: A Biogeochemical Modeling Proof-Of-Concept With Clm–Pflotran 1.0”. Geoscientific Model Development, 2016, pp. 927 - 946.
- Langford, Z. L., et al. “Mapping Arctic Plant Functional Type Distributions In The Barrow Environmental Observatory Using Worldview-2 And Lidar Datasets”. Remote Sensing, 2016, p. 733.