| A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades DJ Foley, PS Thenkabail, IP Aneece, PG Teluguntla, AJ Oliphant International Journal of Digital Earth 13 (8), 939-975, 2020 | 82 | 2020 |
| Does the document matter? The evolving role of syllabi in higher education MS Palmer, LB Wheeler, I Aneece Change: The Magazine of Higher Learning 48 (4), 36-47, 2016 | 73 | 2016 |
| 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 I Aneece, P Thenkabail Remote Sensing 10 (12), 2027, 2018 | 62 | 2018 |
| Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on … PS Thenkabail, PG Teluguntla, J Xiong, A Oliphant, RG Congalton, ... Professional Paper, 2021 | 51 | 2021 |
| Classifying crop types using two generations of hyperspectral sensors (Hyperion and DESIS) with machine learning on the cloud I Aneece, PS Thenkabail Remote Sensing 13 (22), 4704, 2021 | 30 | 2021 |
| Students’ perceptions of course syllabi: The role of syllabi in motivating students LB Wheeler, M Palmer, I Aneece International Journal for the Scholarship of Teaching and Learning 13 (3), 7, 2019 | 28 | 2019 |
| Correlating species and spectral diversities using hyperspectral remote sensing in early‐successional fields IP Aneece, H Epstein, M Lerdau Ecology and Evolution 7 (10), 3475-3488, 2017 | 28 | 2017 |
| New generation hyperspectral sensors DESIS and PRISMA provide improved agricultural crop classifications I Aneece, PS Thenkabail Photogrammetric Engineering & Remote Sensing 88 (11), 715-729, 2022 | 24 | 2022 |
| New generation hyperspectral data from DESIS compared to high spatial resolution PlanetScope data for crop type classification I Aneece, D Foley, P Thenkabail, A Oliphant, P Teluguntla IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2022 | 22 | 2022 |
| Hyperspectral remote sensing for terrestrial applications PS Thenkabail, I Aneece, P Teluguntla, R Upadhyay, A Siddiqui, ... Remote Sensing Handbook, Volume III, 285-358, 2016 | 21 | 2016 |
| Identifying invasive plant species using field spectroscopy in the VNIR region in successional systems of north-central Virginia I Aneece, H Epstein International Journal of Remote Sensing 38 (1), 100-122, 2017 | 17 | 2017 |
| Hyperspectral narrowband data propel gigantic leap in the earth remote sensing PS Thenkabail, I Aneece, P Teluguntla, A Oliphant Photogrammetric Engineering & Remote Sensing 87 (7), 461-467, 2021 | 13 | 2021 |
| Distinguishing early successional plant communities using ground-level hyperspectral data I Aneece, H Epstein Remote Sensing 7 (12), 16588-16606, 2015 | 12 | 2015 |
| Landsat-Derived Global Rainfed and Irrigated-Cropland Product 30m V001 (V001), NASA EOSDIS Land Processes DAAC IP148728 P Teluguntla, P Thenkabail, A Oliphant, M Gumma, I Aneece, D Foley, ... | 10 | 2023 |
| Global Hyperspectral Imaging Spectral-Library of Agricultural Crops for Conterminous United States V001 [Data Set] P Thenkabail, I Aneece NASA EOSDIS Land Processes DAAC, 2019 | 10 | 2019 |
| Introduction to the Python hyperspectral analysis tool (PyHAT) JR Laura, LR Gaddis, RB Anderson, IP Aneece Machine learning for planetary science, 55-90, 2022 | 8 | 2022 |
| Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on … PS Thenkabail, PG Teluguntla, J Xiong, A Oliphant, RG Congalton, ... US Geological Survey, Reston, VA, https://doi. org/10.3133/pp1868, 2021 | 8 | 2021 |
| Spaceborne hyperspectral EO-1 Hyperion data pre-processing: Methods, approaches, and algorithms IP Aneece, PS Thenkabail, JG Lyon, A Huete, T Slonecker Fundamentals, Sensor Systems, Spectral Libraries, and Data Mining for …, 2018 | 7 | 2018 |
| Crop Water Productivity from Cloud-Based Landsat Helps Assess California’s Water Savings D Foley, P Thenkabail, A Oliphant, I Aneece, P Teluguntla Remote Sensing 15 (19), 4894, 2023 | 6 | 2023 |
| Crop water productivity estimation with hyperspectral remote sensing M Marshall, I Aneece, D Foley, C Xueliang, T Biggs Advanced Applications in Remote Sensing of Agricultural Crops and Natural …, 2018 | 4 | 2018 |
