A meta-analysis of global crop water productivity of three leading world crops (wheat, corn, and rice) in the irrigated areas over three decades

Autor: Daniel J. Foley, Prasad S. Thenkabail, Itiya P. Aneece, Pardhasaradhi G. Teluguntla, Adam J. Oliphant

Publikováno v: International Journal of Digital Earth, Vol 13, Iss 8, Pp 939-975 (2020)

The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remot

Externí odkaz: https://doaj.org/article/fcda9b8aae9e45e393b9cc55ef438bd7

Classifying Crop Types Using Two Generations of Hyperspectral Sensors (Hyperion and DESIS) with Machine Learning on the Cloud

Autor: Itiya P. Aneece, Prasad S. Thenkabail

Publikováno v: Remote Sensing; Volume 13; Issue 22; Pages: 4704
Remote Sensing, Vol 13, Iss 4704, p 4704 (2021)

Advances in spaceborne hyperspectral (HS) remote sensing, cloud-computing, and machine learning can help measure, model, map and monitor agricultural crops to address global food and water security issues, such as by providing accurate estimates of c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b41ed25871eb937bf2137980f0ee80a8

Identifying invasive plant species using field spectroscopy in the VNIR region in successional systems of north-central Virginia

Autor: Itiya P. Aneece, Howard E. Epstein

Publikováno v: International Journal of Remote Sensing. 38:100-122

Remote sensing can potentially be used to monitor the extent and distribution of invasive species across landscapes and regions, thus aiding conservation efforts. We collected ground-level hyperspectral data of six exotic invasive plant species in ab

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::05310410613cef9a68c61a984b5f2f4e
https://doi.org/10.1080/01431161.2016.1259682

Distinguishing Early Successional Plant Communities Using Ground-Level Hyperspectral Data

Autor: Itiya P. Aneece, Howard E. Epstein

Publikováno v: Remote Sensing, Vol 7, Iss 12, Pp 16588-16606 (2015)
Remote Sensing
Volume 7
Issue 12
Pages 16588-16606
Remote Sensing; Volume 7; Issue 12; Pages: 16588-16606

Abandoned agricultural fields have recently become more abundant in the U.S. and remain susceptible to species invasions after cultivation disturbance. As invasive species become more widespread with increases in anthropogenic activities, we need mor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bf395ecf73f2eb2d81c7f9ec40dc41a1
https://doi.org/10.3390/rs71215850