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Exploring the effects of crop growth differences on radar vegetation index response and crop height estimation using dynamic monitoring model.

Authors :
Wang, Bo
Liu, Yu
Sheng, Qinghong
Li, Jun
Wang, Shuwei
Qiao, Yunfeng
He, Honglin
Source :
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences; 2024, Vol. 10 Issue 1, p225-232, 8p
Publication Year :
2024

Abstract

Synthetic aperture radar (SAR) has emerged as a promising technology for monitoring crop plant height due to its ability to capture the geometric properties of crops. Radar vegetation index (RVI) has been extensively utilized for qualitative and quantitative remote sensing monitoring of vegetation growth dynamics. However, the combination of crop, growing environment, and temporal dynamics makes crop monitoring data a complex task. Despite the relatively simple underlying mechanisms of this phenomenon, there is still a need for more research to identify specific vegetation structures that correspond to changes in the response of vegetation indices. Building upon this premise, this study utilized a dynamic monitoring model to conduct dynamic monitoring of plant height for three common crops: rice, wheat, and maize. The findings revealed that (1) models developed for specific spatial and temporal scales of particular crop varieties may not accurately predict crop growth in different regions or with different varieties in a timely manner, due to growth variations; (2) these models maintain accuracy over a range of plant heights, such as rice at around 70cm, wheat at around 50cm, and maize at around 150cm; (3) among the three crops, planting density was identified as the main factor influencing the differences in RVI response. This research contributes to our comprehension of the dynamic response of RVI to different growth conditions in crops, and offers valuable insights and references for agricultural monitoring. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21949042
Volume :
10
Issue :
1
Database :
Complementary Index
Journal :
ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
177678970
Full Text :
https://doi.org/10.5194/isprs-annals-X-1-2024-225-2024