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Rapid Mapping of the Leaf Area Index in Agricultural Crops
Author(s) -
Gebbers Robin,
Ehlert Detlef,
Adamek Rolf
Publication year - 2011
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2011.0201
Subject(s) - leaf area index , biomass (ecology) , environmental science , precision agriculture , agronomy , remote sensing , agriculture , field trial , secale , agricultural engineering , geography , engineering , biology , archaeology
The leaf area index (LAI), as the ratio of the leaf area to a given unit of land area, is an essential parameter to describe plant productivity and make management decisions. Most methods for estimating the LAI are not suitable for practical agricultural management at the field scale due to delayed availability of data, high costs, or inaccuracy at late growth stages. Therefore, a new approach for rapid LAI mapping by ground‐based laser rangefinders mounted on a vehicle was evaluated. Two types of laser rangefinders were tested in various configurations. Field trials were conducted to evaluate whether these sensors were capable of capturing temporal and spatial variability of LAI, biomass, and crop height. Crops included in the trials were winter wheat ( Triticum aestivum L.), winter rye ( Secale cereale L.), and oilseed rape ( Brassica napus L. ssp. napus ). Correlation coefficients ranging from 0.3 to more than 0.9 (Pearson's r) between sensor readings, LAI, and biomass were observed. Best correlations were achieved with the time‐of‐flight based rangefinder in winter wheat. This study demonstrated that vehicle‐based laser distance sensors offer potential for rapid mapping of LAI in crops. The sensors are robust and allow for real‐time data processing. It is anticipated that they will become affordable in the near future, for example, due to mass production for collision avoidance in automobile industry. Thus, vehicle‐based laser distance sensors might be used for precision agriculture applications like fertilizing, crop protection, and yield prediction.