Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data. - Itiya P. Aneece; Howard Epstein (Remote. Sens., 2015)

Accuracies Achieved in Classifying Five Leading World Crop Types and their Growth Stages Using Optimal Earth Observing-1 Hyperion Hyperspectral Narrowbands on Google Earth Engine. - Itiya P. Aneece; Prasad S. Thenkabail (Remote. Sens., 2018)

A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades. - Daniel J. Foley; Prasad S. Thenkabail; Itiya P. Aneece; Pardhasaradhi Teluguntla; Adam J. Oliphant (Int. J. Digit. Earth, 2020)

DESIS and PRISMA: A study of a new generation of spaceborne hyperspectral sensors in the study of world crops. - Itiya P. Aneece; Prasad S. Thenkabail (IGARSS, 2021)

Classifying Crop Types Using Two Generations of Hyperspectral Sensors (Hyperion and DESIS) with Machine Learning on the Cloud. - Itiya P. Aneece; Prasad S. Thenkabail (Remote. Sens., 2021)

New Generation and Old Generation Hyperspectral Remote Sensing Data and their Comparisons with Multispectral Data in the Study of Global Agriculture and Vegetation. - Prasad S. Thenkabail; Itiya P. Aneece; Pardhasaradhi Teluguntla; Adam J. Oliphant; Daniel J. Foley (IGARSS, 2022)

New Generation Hyperspectral Data From DESIS Compared to High Spatial Resolution PlanetScope Data for Crop Type Classification. - Itiya P. Aneece; Daniel J. Foley; Prasad S. Thenkabail; Adam J. Oliphant; Pardhasaradhi Teluguntla (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Crop Water Productivity from Cloud-Based Landsat Helps Assess California's Water Savings. - Daniel J. Foley; Prasad S. Thenkabail; Adam J. Oliphant; Itiya P. Aneece; Pardhasaradhi Teluguntla (Remote. Sens., 2023)

Automated Cropland Fallow Algorithm (ACFA) for the Northern Great Plains of USA. - Adam J. Oliphant; Prasad S. Thenkabail; Pardhasaradhi Teluguntla; Itiya P. Aneece; Daniel J. Foley; Richard L. McCormick (Int. J. Digit. Earth, 2024)