11/28/2017

05/24/2018

Thomasson

 

Yang, C., G. N. Odvody, J. A. Thomasson, T. S. Isakeit, R. R. Minzenmayer, D. R. Drake, and R. L. Nichols.  2018.  Site-specific management of cotton root rot using airborne and high resolution satellite imagery and variable rate technology.  Trans. ASABE (in press).

Thomasson, J. A., T. Wang, X. Wang, R. Collett, C. Yang, R. L. Nichols.  Disease detection and mitigation in a cotton crop with UAV remote sensing.  Defense and Commercial Sensing Conf.  Bellingham, WA: SPIE.

 

Han, X., J. A. Thomasson, G. C. Cody Bagnall, N. A. Pugh, D. W. Horne, W. L. Rooney, L. Malambo, A Chang, J. Jung, and D. A. Cope.  2018.  Calibrated plant height estimates with structure from motion from fixed-wing UAV images.  Defense and Commercial Sensing Conf.  Bellingham, WA: SPIE.

 

Bagnall, G. C., J. A. Thomasson, C. Sima, and C. Yang.  2018.  Quality assessment of radiometric calibration of UAV image mosaics.  Defense and Commercial Sensing Conf.  Bellingham, WA: SPIE.

 

Shi, Y., J. A. Thomasson, C. Sima, C. Yang, and D. A. Cope.  2017.  A case study of comparing radiometrically

calibrated reflectance of animage mosaic from unmanned aerial system with that of a single image from manned aircraft over a same area.  Defense and Commercial Sensing Conf.  Bellingham, WA: SPIE.

 

Thomasson, J. A. Y. Shi, C. Sima, C. Yang, and D. A. Cope.  2017.  Automated geographic registration and radiometric correction for UAV-based mosaics.  Defense and Commercial Sensing Conf.  Bellingham, WA: SPIE.

 

Hession

 

Grutter, B., W.C. Hession, R. Grisso, L. Lehmann, and D. Morgan. 2017. Best Management Practices Utilizing Unmanned Aircraft Vehicles in Aerial Spraying. Final Project Report submitted to E.I. Dupont De Nemours and Co., Wilmington, DE.

 

Kurouski

 

Farber, C. and Kurouski, D. (2018) Detection and Identification of Plant Pathogens on Maize Kernels with a Handheld Raman Spectrometer Anal. Chem., 90, 3009-3012. 

 

Khot

 

Chandel, A., L. R. Khot*, Y. Osroosh and R. T. Peters. 2018. Thermal-RGB imager derived in-field apple surface temperature estimates for sunburn management. Agricultural and Forest Meteorology, 253-254: 132-140 (5-Year IF: 4.753).

 

Osroosh, Y., L. R. Khot*, and R. T. Peters. 2018. Economical thermal-RGB imaging system for monitoring agricultural crops. Computers and Electronics in Agriculture, 147: 34-43. (5-Year IF: 2.502).

 

Boydston*, R., L. D. Porter, B. Chaves-Cordoba, P. N. Miklas and L. R. Khot. 2018. The impact of tillage on pinto bean cultivar response to drought induced by deficit irrigation. Soil & Tillage Research, 180: 63-72. (5-Year IF: 3.856).

 

Zhou, J., L. R. Khot*, R. A. Boydston, P. N. Miklas, and L. Porter. 2017. Low altitude remote sensing technologies for crop stress monitoring: a case study on spatial and temporal monitoring of irrigated pinto bean. Precision Agriculture, DOI: 10.1007/s11119-017-9539-0 (5-Year IF: 2.012).

 

Zúñiga, C. E., L. R. Khot*, S. Sankaran, and P. Jacoby. 2017. High resolution multispectral and thermal remote sensing-based water stress assessment in subsurface irrigated grapevines. Remote Sensing, 9(9): 961-976. doi:10.3390/rs9090961 (5-Year IF: 3.749).

 

Khot, L. R. 2017. FS285E Unmanned aerial systems in agriculture: part II (Sensors) - UAS in Ag Series (2015-1493).

 

Khot, L. R. and R. T. Peters. 2018. Advances in UAS based imagery and its applications in irrigated agriculture. Irrigation Today Magazine, April, 2018. 23-24.

 

Khot, L. R. 2018. Drone data for agriculture, Good Fruit Grower Magazine, http://www.goodfruit.com/khot-drone-data-for-agriculture/

 

Purcell

 

Bai, H. and L.C. Purcell. 2018. Aerial canopy temperature differences between fast- and slow-wilting soybean genotypes. J. Agron. Crop Sci. 204:243-251.

 

Kaler, A.S., J.D. Ray, W.T. Schapaugh, A.R. Asebedo, C.A. King, E.E. Gbur, and L.C. Purcell. 2018. Association mapping identifies loci for canopy temperature under drought in diverse soybean genotypes. Euphytica (in review).

 

Balota

 

Balota, M., Oakes, J. 2017. UAV remote sensing for phenotyping drought tolerance in peanuts. Proc. Ann. Soc. Photographic Instrumentation Engineers (SPIE) Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II, 102180C (May 16, 2017) Vol 10218 (doi: 10.1117/12.2262496).

 

Oakes, J., Balota, M., 2017.Distinguishing plant population and variety with UAV-derived vegetation indices. Proc. Ann. Soc. Photographic Instrumentation Engineers (SPIE)Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II, 102180G (May 16, 2017) Vol 10218 (doi: 10.1117/12.2262631).

 

Balota, M., Oakes, J. 2016. Exploratory use for a UAV platform for variety selection in peanut. Proc. Ann. Soc. Photographic Instrumentation Engineers (SPIE) Vol 9866 (doi: 10.1117/12.2228872).

 

Freeland

 

Ramirez, M. B., Allen, P. B., Freeland, R. S., and Wilkerson, J. B. (2017). Cotton canopy NDVI: Reducing the ground exposure effect. Transactions of the ASABE, 60(2), 293-301.

 

Allred, B., Eash, N., Freeland, R., Martinez, L., and Wishart, D. (2018). Effective and efficient agricultural drainage pipe mapping with UAS thermal infrared imagery: A case study. Agricultural Water Management, 197, 132-137.

 

05/08/2019

Gauci, A.A., Brodbeck, C.J., Poncet, A.M., Knappenberger, T. 2018.

Assessing the Geospatial Accuracy of Aerial Imagery Collected with Various

UAS Platforms. Trans. ASABE. (61)6:1-7.

Kaler, A.S., J.D. Ray, W.T. Schapaugh, A.R. Asebedo, C.A. King, E.E. Gbur, and L.C. Purcell.

2018. Association mapping identifies loci for canopy temperature under drought in diverse

soybean genotypes. Euphytica 214:135.

Bai, H. and L.C. Purcell. 2018. Aerial canopy temperature differences between fast- and slow wilting soybean genotypes. J. Agron. Crop Sci. 204:243-251.

Dasika, S.S., Sama, M.P., Pampolini, L.F., Good, C.B. 2019. Performance Validation of a

Multi-Channel LiDAR Sensor: Assessing the Effect of Target Height and Sensor Velocity on

Measurement Error. Transactions of the ASABE. Vol. 62(1): 231-244.

Hamidisepehr, A., Sama, M.P. 2019. Moisture Content Classification of Soil and Stalk

Residue Samples from Spectral Data using Machine Learning Algorithms. Transactions of

the ASABE. Vol. 62(1): 1-8.

Samiappan, S., J. M. Prince Czarnecki, H. Foster, B. K. Strickland, J. L. Tegt, and R. J. Moorhead. 2018. Quantifying damage from wild pigs with small unmanned aerial systems. Wildlife Society Bulletin. 42(2):304-309. http://doi.org/10.1002/wsb.868

Zhang, J., S. Virk, W. M. Porter, K. E. Kenworthy and B. M. Schwartz. Application of Unmanned Aerial Vehicle Based Imagery in Turfgrass Variety Trials. 2018. ASA and CSSA Meetings. November 4-7. Baltimore, MD. (Oral)

2018. Czarnecki, A. Linhoss, L. Hathcock, J. Ramirez-Avila, and T. Schauwecker. 2018. Assessing soil erosion with unmanned aerial vehicles for precision conservation. 73^rd Soil and Water Conservation Society International Annual Conference, Albuquerque, NM. (Oral)

Daughtry, D., W. Porter, G. Harris, R. Noland, J. Snider, and S. Virk. 2018. Correlating Plant

Nitrogen Status in Cotton with UAV based Multispectral Imagery. Proceedings of the 14th

International Conference of Precision Agriculture, Montreal, Quebec, Canada. (Oral and Paper)

Daughtry, D.W., W.M. Porter, G.H. Harris, J.L. Snider, and R.L. Noland. 2019. Using an

Unmanned Aerial System to Collect Mid-Season Multispectral Data for Estimation of Plant

Nitrogen Status in Cotton. Proceedings of the Annual Beltwide Cotton Conferences, New

Orleans, LA, US. (Oral and Paper)

Daughtry, D.W., W.M. Porter, G.H. Harris, J.L. Snider, R.L. Noland, and S. Virk. 2018.

Collection, Processing, and Analyses of in-Season Cotton Multispectral and Fertility Data

Utilizing Unmanned Aerial Systems. 2018. ASA-CSSA International Meeting, Baltimore, MD. (Oral)

Sumner, Z., J. J. Varco, J. Czarnecki, and A. A. A. Fox. 2018. Multi-platform comparison of canopy reflectance on corn whole plant and leaf tissue nitrogen status and grain yield. ASA-CSSA International Meeting, Baltimore, MD. (Poster)

Prince Czarnecki, J. M., L. L. Wasson, A. B. Scholtes, S. M. Carver, and J. T. Irby. 2018. Soybean maturity stage estimation with unmanned aerial systems. 14^th International Conference on Precision Agriculture, Montreal, Canada. (Poster and Paper)

Ana I. de Castro, Joe Mari Maja, Jim Owen, James Robbins, Jose M. Peña, "Experimental approach to detect water stress in ornamental plants using sUAS-imagery," Proc. SPIE 10664, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping III, 106640N (21 May 2018); doi: 10.1117/12.2304739

Zúñiga C. E., A. P. Rathnayake, M. Chakraborty, S. Sankaran, P. Jacoby and L. R. Khot*. 2018. Applicability of time-of flight- based ground and multispectral aerial imaging for grapevine canopy vigour monitoring under direct root-zone deficit irrigation, International Journal of Remote Sensing, DOI: 10.1080/01431161.2018.1500047.

Boydston*, R., L. D. Porter, B. Chaves-Cordoba, L. R. Khot and P. N. Miklas. 2018. The impact of tillage on pinto bean cultivar response to drought induced by deficit irrigation. Soil & Tillage Research, 180: 63-72.

Sankaran*, S., J. Zhou, L.R. Khot, J.J. Trapp, E. Mndolwa and P.N. Miklas. 2018. High-throughput field phenotyping in dry bean using small unmanned aerial vehicle based multispectral imagery. Computers and Electronics in Agriculture, 151: 84-92.

Zhou, J., L. R. Khot*, R. A. Boydston, P. N. Miklas, and L. Porter. 2017. Low altitude remote sensing technologies for crop stress monitoring: a case study on spatial and temporal monitoring of irrigated pinto bean. Precision Agriculture, DOI: 10.1007/s11119-017-9539-0.

Zúñiga, C. E., L. R. Khot*, S. Sankaran, and P. Jacoby. 2017. High resolution multispectral and thermal remote sensing based water stress assessment in subsurface irrigated grapevines. Remote Sensing, 9(9): 961-976. doi:10.3390/rs9090961.

Khot, L. R., G.-A. Hoheisel, and J. Zhou. 2018. Unmanned aerial systems in agriculture: part III (Mid-sized UAS) - UAS in Ag Series (2015-1493). In Press.

Khot, L. R. and R. T. Peters. 2018. Advances in UAS based imagery and its applications in irrigated agriculture. Irrigation Today Magazine, April, 2018. 23-24.

Khot, L. R. 2018. Drone data for agriculture, Good Fruit Grower Magazine, http://www.goodfruit.com/khot-drone-data-foragriculture/

Chakraborty*, M., L. R. Khot and R. T. Peters. 2018. Assessment of crop growth under modified center pivot irrigation systems using small unmanned aerial system based imaging techniques. Presentation at 14th International conference on Precision Agriculture, Montreal, Canada. June 24-24, 2018. ICPA full paper no. 5308.

Quirós, J., M. Martello and L. R. Khot*. 2018. Field grown apple nursery tree plant counting based on small uas imagery derived elevation maps. Presentation at 14th International conference on Precision Agriculture, Montreal, Canada. June 24-24, 2018. ICPA full paper no. 5152.

 

02/27/2021

03/08/2022