Matthew Maimaitiyiming

Matthew Maimaitiyiming

University of Missouri

H-index: 18

North America-United States

About Matthew Maimaitiyiming

Matthew Maimaitiyiming, With an exceptional h-index of 18 and a recent h-index of 17 (since 2020), a distinguished researcher at University of Missouri, specializes in the field of Remote Sensing Applications.

His recent articles reflect a diverse array of research interests and contributions to the field:

Estimating corn plant nitrogen content from hyperspectral images acquired using UAV and LeafSpec in the field

Grapevine leaf size influences vine canopy temperature

P50-Grapevine leaf size influences vine canopy temperature.

Increases in vein length compensate for leaf area lost to lobing in grapevine

Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning

Early detection of plant viral disease using hyperspectral imaging and deep learning

Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

Modeling Early Indicators of Grapevine Physiology Using Hyperspectral Imaging and Partial Least Squares Regression (PLSR)

Matthew Maimaitiyiming Information

University

Position

___

Citations(all)

1885

Citations(since 2020)

1595

Cited By

782

hIndex(all)

18

hIndex(since 2020)

17

i10Index(all)

19

i10Index(since 2020)

19

Email

University Profile Page

Google Scholar

Matthew Maimaitiyiming Skills & Research Interests

Remote Sensing Applications

Top articles of Matthew Maimaitiyiming

Estimating corn plant nitrogen content from hyperspectral images acquired using UAV and LeafSpec in the field

Authorea Preprints

2023/10/30

Grapevine leaf size influences vine canopy temperature

bioRxiv

2022

P50-Grapevine leaf size influences vine canopy temperature.

Julius-Kühn-Archiv

2022/7/1

Increases in vein length compensate for leaf area lost to lobing in grapevine

American Journal of Botany

2022/7/19

Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning

ISPRS journal of photogrammetry and remote sensing

2021/4/1

Early detection of plant viral disease using hyperspectral imaging and deep learning

Sensors

2021/1/22

Leveraging Very-High Spatial Resolution Hyperspectral and Thermal UAV Imageries for Characterizing Diurnal Indicators of Grapevine Physiology

Remote Sensing

2020/10/2

Modeling Early Indicators of Grapevine Physiology Using Hyperspectral Imaging and Partial Least Squares Regression (PLSR)

2020

Quantifying leaf chlorophyll concentration of sorghum from hyperspectral data using derivative calculus and machine learning

Remote Sensing

2020/6/29

See List of Professors in Matthew Maimaitiyiming University(University of Missouri)