| A review of earth artificial intelligence Z Sun, L Sandoval, R Crystal-Ornelas, SM Mousavi, J Wang, C Lin, ... Computers & Geosciences 159, 105034, 2022 | 166 | 2022 |
| Sweep: Accelerating scientific research through scalable serverless workflows A John, K Ausmees, K Muenzen, C Kuhn, A Tan Proceedings of the 12th IEEE/ACM International Conference on Utility and …, 2019 | 37 | 2019 |
| Leveraging organismal biology to forecast the effects of climate change LB Buckley, AF Cannistra, A John Integrative and comparative biology 58 (1), 38-51, 2018 | 37 | 2018 |
| Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes C Kuhn, M Bogard, SE Johnston, A John, E Vermote, R Spencer, ... Environmental Research Letters 15 (10), 105001, 2020 | 29 | 2020 |
| Detecting montane flowering phenology with CubeSat imagery A John, J Ong, EJ Theobald, JD Olden, A Tan, J HilleRisLambers Remote Sensing 12 (18), 2894, 2020 | 18 | 2020 |
| High-resolution snow-covered area mapping in forested mountain ecosystems using planetscope imagery A John, AF Cannistra, K Yang, A Tan, D Shean, J Hille Ris Lambers, ... Remote Sensing 14 (14), 3409, 2022 | 12 | 2022 |
| TrenchR: An R package for modular and accessible microclimate and biophysical ecology LB Buckley, BA Briones Ortiz, I Caruso, A John, O Levy, AV Meyer, ... PLoS Climate 2 (8), e0000139, 2023 | 11 | 2023 |
| Climate change impacts on natural icons: Do phenological shifts threaten the relationship between peak wildflowers and visitor satisfaction? JHR Lambers, AF Cannistra, A John, E Lia, RD Manzanedo, M Sethi, ... Climate Change Ecology 2, 100008, 2021 | 10 | 2021 |
| BAMSI: a multi-cloud service for scalable distributed filtering of massive genome data K Ausmees, A John, SZ Toor, A Hellander, C Nettelblad BMC bioinformatics 19, 1-11, 2018 | 9 | 2018 |
| Evaluation of serverless computing for scalable execution of a joint variant calling workflow A John, K Muenzen, K Ausmees Plos one 16 (7), e0254363, 2021 | 8 | 2021 |
| High-resolution mapping of snow cover in montane meadows and forests using Planet imagery and machine learning K Yang, A John, D Shean, JD Lundquist, Z Sun, F Yao, S Todoran, ... Frontiers in Water 5, 1128758, 2023 | 7 | 2023 |
| Kupfer. Application of spherical statistics to change vector analysis of Landsat data: Southern Appalachian Spruce-Fir Forests TR Allen, A John International Journal of Remote Sensing 74 (3), 482-493, 2000 | 6 | 2000 |
| 868 mhz wireless sensor network-A study PA John, R Agren, YJ Chen, C Rohner, E Ngai arXiv preprint arXiv:1609.00475, 2016 | 5 | 2016 |
| CT dosimetry: Comparison of measurement techniquesand devices A John, J Thomas, N Andrew RADIOGRAPHICS 28, 245-253, 2008 | 5 | 2008 |
| Using photographs and deep neural networks to understand flowering phenology and diversity in mountain meadows A John, EJ Theobald, N Cristea, A Tan, J Hille Ris Lambers Remote Sensing in Ecology and Conservation 10 (4), 480-499, 2024 | 4 | 2024 |
| Machine learning for snow cover mapping K Yang, A John, Z Sun, N Cristea Artificial intelligence in earth science, 17-39, 2023 | 3 | 2023 |
| Making machine learning-based snow water equivalent forecasting research productive and reusable by Geoweaver Z Sun, NC Cristea, K Yang, A Alnuaim, LCG Bikshapathireddy, A John, ... AGU fall meeting abstracts 2022, IN23A-04, 2022 | 3 | 2022 |
| MeadoWatch: a long-term community-science database of wildflower phenology in Mount Rainier National Park RD Manzanedo, A John, ML Sethi, EJ Theobald, B Brosi, J Jenkins, ... Scientific Data 9 (1), 151, 2022 | 3 | 2022 |
| Topography influences diurnal and seasonal microclimate fluctuations in hilly terrain environments of coastal California A John, JD Olden, MF Oldfather, MM Kling, DD Ackerly Plos one 19 (3), e0300378, 2024 | 2 | 2024 |
| Arctic-Boreal Lake phenology shows a relationship between earlier lake ice-out and later green-up C Kuhn, A John, J Hille Ris Lambers, D Butman, A Tan Remote Sensing 13 (13), 2533, 2021 | 2 | 2021 |