Identification of mountain snow cover using SSM/I and artificial neural network. - Changyi Sun; Heng-Da Cheng; Jeffrey J. McDonnell; Christopher M. U. Neale (ICASSP, 1995)

Monitoring land-surface snow conditions from SSM/I data using an artificial neural network classifier. - Changyi Sun; Christopher M. U. Neale; Jeffrey J. McDonnell; Heng-Da Cheng (IEEE Trans. Geosci. Remote. Sens., 1997)

Estimating Evapotranspiration of an Apple Orchard Using a Remote Sensing-Based Soil Water Balance. - Magali Odi-Lara; Isidro Campos; Christopher M. U. Neale; Samuel Ortega-Farías; Carlos Poblete-Echeverría; Claudio Balbontín; Alfonso Calera (Remote. Sens., 2016)

Temporal evaluation of evapotranspiration for sugar cane, planted forest and native forest using landsat 8 images and a two-source energy balance. - Raoni W. D. Bosquilia; Christopher M. U. Neale; Sérgio N. Duarte; Solon J. Longhi; Silvio F. de B. Ferraz; Frank E. Müller-Karger; Matthew J. McCarthy (Comput. Electron. Agric., 2018)

Evaluation of the Weak Constraint Data Assimilation Approach for Estimating Turbulent Heat Fluxes at Six Sites. - Xinlei He 004; Tongren Xu; Sayed M. Bateni; Christopher M. U. Neale; Thomas Auligne; Shaomin Liu; Kaicun Wang; Kebiao Mao; Yunjun Yao (Remote. Sens., 2018)

Variable Rate Irrigation of Maize and Soybean in West-Central Nebraska Under Full and Deficit Irrigation. - J. Burdette Barker; Sandeep Bhatti; Derek M. Heeren; Christopher M. U. Neale; Daran R. Rudnick (Frontiers Big Data, 2019)

Spatio-temporal patterns of energy exchange and evapotranspiration during an intense drought for drylands in Brazil. - Carlos Antonio Costa dos Santos; Denis A. Mariano; Francisco das Chagas A. do Nascimento; Fabiane Regina da C. Dantas; Gabriel de Oliveira; Madson T. Silva; Lindenberg L. da Silva; Bernardo B. da Silva; Bergson Guedes Bezerra; Babak Safa; Salomão de S. Medeiros; Christopher M. U. Neale (Int. J. Appl. Earth Obs. Geoinformation, 2020)

Assessment of an Automated Calibration of the SEBAL Algorithm to Estimate Dry-Season Surface-Energy Partitioning in a Forest-Savanna Transition in Brazil. - Leonardo Laipelt; Anderson L. Ruhoff; Ayan Santos Fleischmann; Rafael Henrique Bloedow Kayser; Elisa de Mello Kich; Humberto Ribeiro da Rocha; Christopher M. U. Neale (Remote. Sens., 2020)

Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications. - Mitchell S. Maguire; Christopher M. U. Neale; Wayne E. Woldt (Remote. Sens., 2021)

Evaluating the Latest IMERG Products in a Subtropical Climate: The Case of Paraná State, Brazil. - Jéssica G. Nascimento; Daniel Althoff; Helizani Couto Bazame; Christopher M. U. Neale; Sérgio N. Duarte; Anderson L. Ruhoff; Ivo Z. Gonçalves (Remote. Sens., 2021)

Unmanned Aerial System-Based Data Ferrying over a Sensor Node Station Network in Maize. - Jasreman Singh; Yufeng Ge; Derek M. Heeren; Elizabeth Walter-Shea; Christopher M. U. Neale; Suat Irmak; Mitchell S. Maguire (Sensors, 2022)

Development of novel optimized deep learning algorithms for wildfire modeling: A case study of Maui, Hawai'i. - Fatemeh Rezaie; Mahdi Panahi; Sayed M. Bateni; Saro Lee; Changhyun Jun 001; Clay Trauernicht; Christopher M. U. Neale (Eng. Appl. Artif. Intell., 2023)

Combining Multi-View UAV Photogrammetry, Thermal Imaging, and Computer Vision Can Derive Cost-Effective Ecological Indicators for Habitat Assessment. - Qiao Hu; Ligang Zhang; Jeff Drahota; Wayne Woldt; Dana Varner; Andy Bishop; Ted LaGrange; Christopher M. U. Neale; Zhenghong Tang (Remote. Sens., 2024)