Results 141 to 150 of about 9,036 (210)

Ground-Based Hyperspectral Remote Sensing for Estimating Water Stress in Tomato Growth in Sandy Loam and Silty Loam Soils. [PDF]

Sensors (Basel), 2021
Alordzinu KE, Li J, Lan Y, Appiah SA, Al Aasmi A, Wang H, Liao J, Sam-Amoah LK, Qiao S.   +8 more
europepmc   +1 more source

Estimation and spatial distribution of soil organic carbon content in farmland using unmanned aerial vehicle hyperspectral remote sensing technology. [PDF]

Sci Rep
Song Q, Zhang W.
europepmc   +1 more source

Hyperspectral remote sensing of drought in vineyards

, 2018
In the Mediterranean many parts of karst surfaces have been modified to make them suitable for agricultural use, mostly grapevine and olive production. In karst landscapes rain water percolates rapidly downward through the soil layers, making them highly fragile and vulnerable to anthropogenic as well as climatic stresses.
Žibrat, Uroš, Knapič, Matej, Zovko, Monika   +2 more
openaire   +1 more source

Classification of Nitrogen-Efficient Wheat Varieties Based on UAV Hyperspectral Remote Sensing. [PDF]

Plants (Basel)
Li Y, Wang C, Zhu J, Wang Q, Liu P.
europepmc   +1 more source

Hyperspectral remote sensing image destriping via spectral-spatial factorization. [PDF]

Sci Rep
Zhan Y, Yu Q, Liu J, Wang Z, Yang Z.
europepmc   +1 more source

Design and Construction of UAV-Based Measurement System for Water Hyperspectral Remote-Sensing Reflectance. [PDF]

Sensors (Basel)
Zeng H, He X, Bai Y, Gong F, Wang D, Zhang X.   +5 more
europepmc   +1 more source

Early feature study of Yunnan pine pinewood nematode disease based on hyperspectral remote sensing of ground objects. [PDF]

Sci Rep
Zhang X, Gao Y, Fu L, Zhang Y, Li Z, Shu Q.   +5 more
europepmc   +1 more source

Estimation of Soil Arsenic Content with Hyperspectral Remote Sensing. [PDF]

Sensors (Basel), 2020
Wei L, Pu H, Wang Z, Yuan Z, Yan X, Cao L.   +5 more
europepmc   +1 more source

A new band selection framework for hyperspectral remote sensing image classification. [PDF]

Sci Rep
Phaneendra Kumar BLN, Vaddi R, Manoharan P, Agilandeeswari L, Sangeetha V.   +4 more
europepmc   +1 more source

High-precision inversion of vegetation parameters in the AI era: Integrating hyperspectral remote sensing and deep learning. [PDF]

Innovation (Camb)
Hu J, Peng D, Chen JM, Huete AR, Yu L, Lou Z, Cheng E, Yang X, Zhang B.   +8 more
europepmc   +1 more source