Advancing ecohydrology in the 21st century: A convergence of opportunities AJ Guswa, D Tetzlaff, JS Selker, DE Carlyle‐Moses, EW Boyer, M Bruen, ... Ecohydrology 13 (4), e2208, 2020 | 48 | 2020 |
Remote sensing of ploidy level in quaking aspen (Populus tremuloides Michx.) B Blonder, BJ Graae, B Greer, M Haagsma, K Helsen, RE Kapás, H Pai, ... Journal of Ecology 108 (1), 175-188, 2020 | 34 | 2020 |
Field trials to detect drainage pipe networks using thermal and RGB data from unmanned aircraft CB Kratt, DK Woo, KN Johnson, M Haagsma, P Kumar, J Selker, S Tyler Agricultural Water Management 229, 105895, 2020 | 26 | 2020 |
Using Hyperspectral Imagery to Detect an Invasive Fungal Pathogen and Symptom Severity in Pinus strobiformis Seedlings of Different Genotypes M Haagsma, GFM Page, JS Johnson, C Still, KM Waring, RA Sniezko, ... Remote Sensing 12 (24), 4041, 2020 | 15 | 2020 |
HyperRail: Modular, 3D printed, 1–100 m, programmable, and low-cost linear motion control system for imaging and sensor suites JML Alcala, M Haagsma, CJ Udell, JS Selker HardwareX 6, e00081, 2019 | 11 | 2019 |
Advancing ecohydrology in the 21st century: A convergence of opportunities, Ecohydrology, 13, e2208 AJ Guswa, D Tetzlaff, JS Selker, DE Carlyle-Moses, EW Boyer, M Bruen, ... | 10 | 2020 |
Detection of soil-borne wheat mosaic virus using hyperspectral imaging: from lab to field scans and from hyperspectral to multispectral data M Haagsma, CH Hagerty, DR Kroese, JS Selker Precision Agriculture 24 (3), 1030-1048, 2023 | 7 | 2023 |
Model selection and timing of acquisition date impacts classification accuracy: A case study using hyperspectral imaging to detect white pine blister rust over time M Haagsma, GFM Page, JS Johnson, C Still, KM Waring, RA Sniezko, ... Computers and Electronics in Agriculture 191, 106555, 2021 | 5 | 2021 |
The NEON daily isotopic composition of environmental exchanges dataset CE Finkenbiner, B Li, L Spencer, Z Butler, M Haagsma, RP Fiorella, ... Scientific Data 9 (1), 353, 2022 | 3 | 2022 |
Mapping potentially acid generating material on abandoned mine lands using remotely piloted aerial systems AS Cramer, WM Calvin, SW McCoy, RJ Breitmeyer, M Haagsma, C Kratt Minerals 11 (4), 365, 2021 | 3 | 2021 |
Hyperspectral imagery of Pinus strobiformis infected with fungal pathogen M Haagsma, GFM Page, JS Johnson | 2 | 2020 |
Is more data better? A comparison of multi-and hyperspectral imaging in phenotyping. M Haagsma, G Page, J Johnson, C Still, K Waring, R Sniezko, J Selker EGU General Assembly Conference Abstracts, 10673, 2020 | 2 | 2020 |
Crop monitoring with Radar M Haagsma Master’s Thesis, 2015 | 2 | 2015 |
Relationship between isotope ratios in precipitation and stream water across watersheds of the National Ecological Observation Network Z Butler, S Good, M Haagsma, C Segura, H Hu Hydrological Processes 37 (11), e15018, 2023 | 1 | 2023 |
Bayesian Rebalancing of Fluxes from Existing Hydrologic Models using Stable Water Isotope Data M Haagsma, SP Good, MA Scholl, A Putman, GD Jones WaterSciCon24, 2024 | | 2024 |
Using Stable Water Isotope Data to Evaluate Opportunities for Improvement in Existing Land Surface Models M Haagsma, CE Finkenbiner, D Noone, GJ Bowen, CJ Still, SP Good AGU Fall Meeting Abstracts 2022, H25C-08, 2022 | | 2022 |
Hyperspectral approaches for monitoring disease progression and resistance in five-needle pines J Johnson, M Haagsma, RA Sniezko, K Waring PHYTOPATHOLOGY 111 (10), 180-180, 2021 | | 2021 |
Hyperspectral reflectance data of wheat in situ and lab scans infected with soilborne wheat mosaic virus M Haagsma, CH Hagerty, DR Kroese, ER Jachens | | 2021 |
Hyperspectral Disease Detection-Strategies Addressing Time, Space, Machine Learning, and Plant Susceptibility M Haagsma | | 2021 |
New Frontiers in Forestry: Combining Phenomics, Common Gardens, and Landscape Genomics to Address Disease Resistance and Climate Change JS Johnson, S Cushman, A Eckert, L Flores-Rentería, R Sniezko, C Still, ... Genetics of Host-Parasite Interactions in Forestry, 66, 2020 | | 2020 |