Rob Austin

Optimizing unmanned aerial vehicle–based stand counts in soybean: Effects of flight timing, altitude, and analytical method

Ermish, S., Vann, R., Ward, J., Everman, W., & Austin, R. (2026, January 1). Agronomy Journal.

A Canopy Height Model Derived from Unmanned Aerial System Imagery Provides Late-Season Weed Detection and Explains Variation in Crop Yield

Teasley, F., Woodley, A. L., & Austin, R. (2025, December 16). Agronomy.

Automated pipeline for leaf spot severity scoring in peanuts using segmentation neural networks

Larsen, J., Dunne, J., Austin, R., Newman, C., & Kudenov, M. (2025, February 20). Plant Methods, Vol. 21.

Drone‐based polarization imaging system for leaf spot severity determination in peanut plants

Larsen, J., Dunne, J., Austin, R., Newman, C., & Kudenov, M. (2025, February 21). The Plant Phenome Journal.

Evaluating UAV captured RGB and multispectral imagery as a proxy for visual rating of leaf spot in cultivated peanut

Newman, C., Austin, R., Andres, R., Read, Q., Garrity, N., Fritz, K., … Dunne, J. (2025, May 21). The Plant Phenome Journal, Vol. 8.

Integration of multi‐omics approaches reveals candidate genes for drought stress in St. Augustinegrass (Stenotaphrum secundatum)

Crop Science, 65(1).

Polarimetric peanut drone images of peanut crop infected with leaf spot

Larsen, J., Dunne, J., Austin, R., Newman, C., & Kudenov, M. (2025, November 17). Zenodo (CERN European Organization for Nuclear Research).

Polarimetric peanut drone images of peanut crop infected with leaf spot

Larsen, J., Dunne, J., Austin, R., Newman, C., & Kudenov, M. (2025, November 17). Zenodo (CERN European Organization for Nuclear Research).

Polarimetric peanut drone images of peanut crop infected with leaf spot

Larsen, J., Dunne, J., Austin, R., Newman, C., & Kudenov, M. (2025, October 12). Figshare.

Predicting Maize Yield Loss with Crop–weed Leaf Cover Ratios Determined with Uas Imagery

Goldsmith, A., Austin, R., Cahoon, C. W., & Leon, R. G. (2025, March 28). Munich Personal RePEc Archive (Ludwig Maximilian University of Munich), Vol. 73.

Predicting arsenic and manganese contamination in private well water with Machine Learning: An integrated analysis of geologic, well construction, and permitting data

Payton, A., Harrington, C. E., Miller, S. L., Colley, T., Serre, M. L., Fry, R. C., … Rager, J. E. (2025, November 18). The Science of The Total Environment.

Compost incorporation and wildflowers introduction for stormwater infiltration and erosion-control vegetation cover establishment in post-construction landscapes

Islam, M. M., McLaughlin, R. A., Austin, R., Kranz, C. N., & Heitman, J. L. (2024, September 1). Journal of Environmental Management, Vol. 369.

Sorption and Phase Associations of Chromate and Vanadate with Two Contrasting North Carolina Saprolites

Balogun, F. O., Peel, H. R., Austin, R. E., Okunlola, I. G., Vinson, D. S., Duckworth, O. W., & Polizzotto, M. L. (2024, December 3). Soil Systems, Vol. 8.

Assessing unmanned aerial vehicle‐based imagery for breeding applications in St. Augustinegrass under drought and non‐drought conditions

Crop Science, 64(1), 496–510.

Discrimination between protoporphyrinogen oxidase–inhibiting herbicide-resistant and herbicide-susceptible redroot pigweed (Amaranthus retroflexus) with spectral reflectance

Jones, E. A. L., Austin, R., Dunne, J. C., Leon, R. G., & Everman, W. J. (2023, May 1). Weed Science, Vol. 5.

Assessing the Agricultural Conservation Planning Framework toolbox in a Southern Piedmont landscape of the United States

Respess, Z. M., Austin, R., Gatiboni, L., & Osmond, D. (2022, August 1). Journal of Soil and Water Conservation, Vol. 77, pp. 441–449.

Combining Survey, Soil Coring, and GIS Methods to Improve Reservoir Capacity Estimates in the Maya Lowlands

Marken, D. B., Ricker, M. C., & Austin, R. (2022, May 1). Advances in Archaeological Practice, Vol. 10, pp. 187–199.

Drone-based polarization imaging for phenotyping peanut in response to leaf spot disease

Larsen, J., Austin, R., Dunne, J., & Kudenov, M. W. (2022, June 3). Polarization: Measurement, Analysis, and Remote Sensing XV, Vol. 12112, pp. 105–109.

Nutrient Management Effects on Wine Grape Tissue Nutrient Content

Havlin, J. L., Austin, R., Hardy, D., Howard, A., & Heitman, J. L. (2022, January 7). Plants, Vol. 1.

Utilization of image-based spectral reflectance to detect herbicide resistance in glufosinate-resistant and glufosinate-susceptible plants: a proof of concept

Weed Science, 71(1), 11–21.

Remote Sensing for Palmer Amaranth (Amaranthus palmeri S. Wats.) Detection in Soybean (Glycine max (L.) Merr.)

Sanders, J. T., Jones, E. A. L., Austin, R., Roberson, G. T., Richardson, R. J., & Everman, W. J. (2021, September 23). Agronomy, Vol. 10.

The Agricultural Conservation Planning Framework: Opportunities and challenges in the eastern United States

Duncan, J. M., Respess, Z., Ryan, W., Austin, R., Royer, M., Osmond, D., & Kleinman, P. (2021, January 1). Agricultural & Environmental Letters.

The structure of natural biogenic iron (oxyhydr)oxides formed in circumneutral pH environments

Geochimica Et Cosmochimica Acta, 308, 237–255.

Creating Predictive Weed Emergence Models Using Repeat Photography and Image Analysis

Plants, 9(5), 635.

Optimum Nitrogen Rates for Maize and Wheat in North Carolina

Austin, R., Osmond, D., & Shelton, S. (2019, August 1). Agronomy Journal, Vol. 111, pp. 2558–2568.

Weed species differentiation using spectral reflectance land image classification

Sanders, J., Everman, W. J., Austin, R., Roberson, G. T., & Richardson, R. J. (2019, May 10). ADVANCED ENVIRONMENTAL, CHEMICAL, AND BIOLOGICAL SENSING TECHNOLOGIES XV, Vol. 11007.

Evaluation of Adapt‐N and Realistic Yield Expectation Approaches for Maize Nitrogen Management in North Carolina

Osmond, D., Austin, R., Shelton, S., Es, H., & Sela, S. (2018, November 1). Soil Science Society of America Journal, Vol. 82, pp. 1449–1458.

The role of citizen science in addressing grand challenges in food and agriculture research

Proceedings of the Royal Society B: Biological Sciences, 285(1891), 20181977.

Evaluation of Nitrogen‐Loss Prevention Amendments in Maize and Wheat in North Carolina

Rajkovich, S., Osmond, D., Weisz, R., Crozier, C., Israel, D., & Austin, R. (2017, July 27). Agronomy Journal, Vol. 109, pp. 1811–1824.

Soil Weathering as an Engine for Manganese Contamination of Well Water

Gillispie, E. C., Austin, R. E., Rivera, N. A., Bolich, R., Duckworth, O. W., Bradley, P., … Polizzotto, M. L. (2016, August 29). Environmental Science & Technology, Vol. 50, pp. 9963–9971.

Assessment of trace element impacts on agricultural use of water from the Dan River following the Eden coal ash release

Hesterberg, D., Polizzotto, M. L., Crozier, C., & Austin, R. E. (2015, June 1). Integrated Environmental Assessment and Management, Vol. 12, pp. 353–363.

Chemical Composition, Speciation, and Elemental Associations in Coal Fly Ash Samples Related to the Kingston Ash Spill

Rivera, N., Kaur, N., Hesterberg, D., Ward, C. R., Austin, R. E., & Duckworth, O. W. (2014, December 23). Energy & Fuels, Vol. 29, pp. 954–967.

Modeling of ammonia dry deposition to a pocosin landscape downwind of a large poultry facility

Walker, J. T., Robarge, W. P., & Austin, R. (2014, January 24). Agriculture Ecosystems & Environment, Vol. 185, pp. 161–175.

Future directions for hydropedology: quantifying impacts of global change on land use

Vepraskas, M. J., Heitman, J. L., & Austin, R. E. (2009, August 12). Hydrology and Earth System Sciences, Vol. 13, pp. 1427–1438.

Horizontal resolution and data density effects on remotely sensed LIDAR-based DEM

Anderson, E. S., Thompson, J. A., Crouse, D. A., & Austin, R. E. (2005, August 11). Geoderma, Vol. 132, pp. 406–415.

LIDAR density and linear interpolator effects on elevation estimates

Anderson, E. S., Thompson, J. A., & Austin, R. E. (2005, September 20). International Journal of Remote Sensing, Vol. 26, pp. 3889–3900.

The Spatial Information Research Laboratory at North Carolina State University

Proceedings of the 5th International Conference on Precision Agriculture, Bloomington, Minnesota, USA, 16-19 July, 2000, 1.