Forrest Hoffman

Pallandt, Martijn, et al. “Representativeness Assessment of the Pan-Arctic Eddy Covariance Site Network and Optimized Future Enhancements”. Biogeosciences, vol. 19, no. 3, 2022, pp. 559-83, https://doi.org/10.5194/bg-19-559-2022.

Fer, Istem, et al. “Beyond Ecosystem Modeling: A Roadmap to Community Cyberinfrastructure for Ecological data‐model Integration”. Global Change Biology, vol. 27, no. 1, 2021, pp. 13-26, https://doi.org/10.1111/gcb.15409.

Langford, Zachary L., et al. “Arctic Vegetation Mapping Using Unsupervised Training Datasets and Convolutional Neural Networks”. Remote Sensing, vol. 11, no. 1, 2019, p. 69, https://doi.org/10.3390/rs11010069.

Shiklomanov, Alexander N., et al. “Enhancing Global Change Experiments through Integration of remote‐sensing Techniques”. Frontiers in Ecology and the Environment, vol. 17, no. 4, 2019, pp. 215-24, https://doi.org/10.1002/fee.2031.

Langford, Zachary 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, https://doi.org/10.1109/ICDMW.2017.48.

Tang, Guoping, 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, vol. 9, no. 3, 2016, pp. 927-46, https://doi.org/10.5194/gmd-9-927-2016.

Langford, Zachary L., et al. “Mapping Arctic Plant Functional Type Distributions in the Barrow Environmental Observatory Using WorldView-2 and LiDAR Datasets”. Remote Sensing, vol. 8, no. 9, 2016, p. 733, https://doi.org/10.3390/rs8090733.

Hoffman, Forrest M., et al. “Representativeness-Based Sampling Network Design for the State of Alaska”. Landscape Ecology, vol. 28, no. 8, 2013, pp. 1567-86, https://doi.org/10.1007/s10980-013-9902-0.