Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data in...
Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model
About this item
Full title
Author / Creator
Han, Shaoyu , Zhao, Yu , Cheng, Jinpeng , Zhao, Fa , Yang, Hao , Feng, Haikuan , Li, Zhenhai , Ma, Xinming , Zhao, Chunjiang and Yang, Guijun
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
Rapidly developing remote sensing techniques are shedding new light on large-scale crop growth status monitoring, especially in recent applications of unmanned aerial vehicles (UAVs). Many inversion models have been built to estimate crop growth variables. However, the present methods focused on building models for each single crop stage, and the f...
Alternative Titles
Full title
Monitoring Key Wheat Growth Variables by Integrating Phenology and UAV Multispectral Imagery Data into Random Forest Model
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_8d9ac97510ed4952862ba146506fa3bc
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_8d9ac97510ed4952862ba146506fa3bc
Other Identifiers
ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs14153723
