Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sadeed Hussain"'
Autor:
Mairaj Din, Jin Ming, Sadeed Hussain, Syed Tahir Ata-Ul-Karim, Muhammad Rashid, Muhammad Naveed Tahir, Shizhi Hua, Shanqin Wang
Publikováno v:
Frontiers in Plant Science, Vol 9 (2019)
Non-destructive and rapid estimation of canopy variables is imperative for predicting crop growth and managing nitrogen (N) application. Hyperspectral remote sensing can be used for timely and accurate estimation of canopy physical and chemical prope
Externí odkaz:
https://doaj.org/article/e0216c480c9843528786f9ad54b920f1
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 397 (2020)
Unmanned aerial vehicles (UAVs) equipped with spectral sensors have become useful in the fast and non-destructive assessment of crop growth, endurance and resource dynamics. This study is intended to inspect the capabilities of UAV-onboard multispect
Externí odkaz:
https://doaj.org/article/dee4b29bb6064d9cb5991e7fb70d6f5c
Publikováno v:
Plant and Soil. 477:461-474
Publikováno v:
Geoderma. 429:116271
Publikováno v:
Environmental science and pollution research international. 28(29)
Sugarcane is one of the most important crops in the world and has a major influence on environmental concerns. This study aims to examine the association between sugarcane crop yield, climate change factors, and technical advancement using time serie
Publikováno v:
Remote Sensing, Vol 12, Iss 3, p 397 (2020)
Remote Sensing
Volume 12
Issue 3
Pages: 397
Remote Sensing
Volume 12
Issue 3
Pages: 397
Unmanned aerial vehicles (UAVs) equipped with spectral sensors have become useful in the fast and non-destructive assessment of crop growth, endurance and resource dynamics. This study is intended to inspect the capabilities of UAV-onboard multispect
Autor:
Mairaj Din, Jin Ming, Sadeed Hussain, Syed Tahir Ata-Ul-Karim, Muhammad Rashid, Muhammad Naveed Tahir, Shizhi Hua, Shanqin Wang
Publikováno v:
Frontiers in Plant Science
Frontiers in Plant Science, Vol 9 (2019)
Frontiers in Plant Science, Vol 9 (2019)
Non-destructive and rapid estimation of canopy variables is imperative for predicting crop growth and managing nitrogen (N) application. Hyperspectral remote sensing can be used for timely and accurate estimation of canopy physical and chemical prope