An Integrated Assessment Model for Exploring Potential Impacts of Global Change Scenarios on the Canadian Agricultural System. - Nathaniel K. Newlands; David S. Zamar; Brian McConkey; Lawrence Townley-Smith; O. Grant Clark (HICSS, 2013)

Assessing the Performance of MODIS NDVI and EVI for Seasonal Crop Yield Forecasting at the Ecodistrict Scale. - Louis Kouadio; Nathaniel K. Newlands; Andrew M. Davidson; Yinsuo Zhang; Aston Chipanshi (Remote. Sens., 2014)

Building capacity for assessing spatial-based sustainability metrics in agriculture. - Louis Kouadio; Nathaniel K. Newlands (Decis. Anal., 2015)

Statistical Modeling of Soil Moisture, Integrating Satellite Remote-Sensing (SAR) and Ground-Based Data. - Reza Hosseini; Nathaniel K. Newlands; Charmaine B. Dean; Akimichi Takemura (Remote. Sens., 2015)

A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty. - David S. Zamar; R. Bhushan Gopaluni; Shahab Sokhansanj; Nathaniel K. Newlands (Comput. Chem. Eng., 2017)

Deep Learning for Improved Agricultural Risk Management. - Nathaniel K. Newlands; Azar Ghahari; Yulia R. Gel; Vyacheslav Lyubchich; Tahir Mahdi (HICSS, 2019)

Learning Space-Time Crop Yield Patterns with Zigzag Persistence-Based LSTM: Toward More Reliable Digital Agriculture Insurance. - Tian Jiang; Meichen Huang; Ignacio Segovia-Dominguez; Nathaniel K. Newlands; Yulia R. Gel (AAAI, 2022)

Quantifying error in fine-scale crop yield forecasts to guide data and algorithm improvements: case study of mango in Tamil Nadu, India. - Louis Kouadio; Bhuvaneswari Kulanthaivel; Thanh Mai; Thong Nguyen-Huy; Qingxia (jenny) Wang; Vivekananda Byrareddy; Shahbaz Mushtaq; Alagarswamy Senthil; Nathaniel K. Newlands; Vellingiri Geethalakshmi (Comput. Electron. Agric., 2025)