Zobrazeno 1 - 10
of 179
pro vyhledávání: '"Prasad S. Thenkabail"'
Autor:
Adam J. Oliphant, Prasad S. Thenkabail, Pardhasaradhi G. Teluguntla, Itiya P. Aneece, Daniel J. Foley, Richard L. McCormick
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTCropland fallowing is choosing not to plant a crop during a season when a crop is normally planted. It is an important component of many crop rotations and can improve soil moisture and health. Knowing which fields are fallow is critical to a
Externí odkaz:
https://doaj.org/article/d1fa40c8e0fd45f6ac013ac95d388510
Autor:
Neda Abbasi, Hamideh Nouri, Kamel Didan, Armando Barreto-Muñoz, Sattar Chavoshi Borujeni, Christian Opp, Pamela Nagler, Prasad S. Thenkabail, Stefan Siebert
Publikováno v:
Remote Sensing, Vol 15, Iss 4, p 1017 (2023)
Precise knowledge of crop water consumption is essential to better manage agricultural water use, particularly in regions where most countries struggle with increasing water and food insecurity. Approaches such as cloud computing and remote sensing (
Externí odkaz:
https://doaj.org/article/a80290e512ca484491708a794fc515cd
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
Autor:
Murali Krishna Gumma, Prasad S. Thenkabail, Pardhasaradhi G. Teluguntla, Adam Oliphant, Jun Xiong, Chandra Giri, Vineetha Pyla, Sreenath Dixit, Anthony M Whitbread
Publikováno v:
GIScience & Remote Sensing, Vol 57, Iss 3, Pp 302-322 (2020)
The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FA
Externí odkaz:
https://doaj.org/article/5fa1776ca95a4394a98a2779c6425e86
Autor:
Itiya Aneece, Prasad S. Thenkabail
Publikováno v:
Remote Sensing, Vol 13, Iss 22, 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://doaj.org/article/d82fdc9709be4ec697f98da8d86b968d
Autor:
Pardhasaradhi Teluguntla, Prasad S. Thenkabail, Jun Xiong, Murali Krishna Gumma, Russell G. Congalton, Adam Oliphant, Justin Poehnelt, Kamini Yadav, Mahesh Rao, Richard Massey
Publikováno v:
International Journal of Digital Earth, Vol 10, Iss 9, Pp 944-977 (2017)
Mapping croplands, including fallow areas, are an important measure to determine the quantity of food that is produced, where they are produced, and when they are produced (e.g. seasonality). Furthermore, croplands are known as water guzzlers by cons
Externí odkaz:
https://doaj.org/article/4f6cb1ee88df4b00804a3d393b408ac5
Autor:
Prasad S. Thenkabail, Jinyoung Rhee
Publikováno v:
GIScience & Remote Sensing, Vol 54, Iss 2, Pp 141-143 (2017)
Externí odkaz:
https://doaj.org/article/8f8f2f58e958455d853671bed7798e9d
Autor:
Prasad S. Thenkabail
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2442 (2020)
A comparison of various remote sensing, geoscience, and Geographic Information Systems (GIS) international journals is provided in Table 1 [...]
Externí odkaz:
https://doaj.org/article/fcbcb1ebd2b04a81836b9555b05af763
Autor:
Prasad S. Thenkabail
Publikováno v:
Remote Sensing, Vol 6, Iss 8, Pp 7463-7468 (2014)
Remote Sensing, an open access journal (http://www.mdpi.com/journal/remotesensing) has grown at rapid pace since its first publication five years ago, and has acquired a strong reputation. It is a “pathfinder” being the first open access journal
Externí odkaz:
https://doaj.org/article/5c6e0d728e04444fbf3db2998d9b291a
Autor:
Murali Krishna Gumma, Kesava Rao Pyla, Prasad S. Thenkabail, Venkataramana Murthy Reddi, Gundapaka Naresh, Irshad A. Mohammed, Ismail M. D. Rafi
Publikováno v:
Agriculture, Vol 4, Iss 2, Pp 113-131 (2014)
This paper describes an approach to accurately separate out and quantify crop dominance areas in the major command area in the Krishna River Basin. Classification was performed using IRS-P6 (Indian Remote Sensing Satellite, series P6) and MODIS eight
Externí odkaz:
https://doaj.org/article/2b343829c2d8433ba39b558d87ccfe18