A mobile sensor for leaf area index estimation from canopy light transmittance in wheat crops

2015 ◽  
Vol 140 ◽  
pp. 23-33 ◽  
Author(s):  
Michael Schirrmann ◽  
André Hamdorf ◽  
Antje Giebel ◽  
Karl-Heinz Dammer ◽  
Andreas Garz
2014 ◽  
Vol 60 (3) ◽  
pp. 10-18 ◽  
Author(s):  
Jan Sabol ◽  
Zdeněk Patočka ◽  
Tomáš Mikita

Abstract Leaf area index (LAI) can be measured either directly, using destructive methods, or indirectly using optical methods that are based on the tight relationship between LAI and canopy light transmittance. Third, innovative approach for LAI measuring is usage of remote sensing data, especially airborne laser scanning (ALS) data shows itself as a advisable source for purposes of LAI modelling in large areas. Until now there has been very little research to compare LAI estimated by the two different approaches. Indirect measurements of LAI using hemispherical photography are based on the transmission of solar radiation through the vegetation. It can thus be assumed that the same is true for the penetration of LiDAR laser beams through the vegetation canopy. In this study we use ALS based LiDAR penetration index (LPI) and ground based measurement of LAI obtained from hemispherical photographs as a reference in-situ method. Several regression models describing the corellation LAI and LPI were developed with various coefficients of determination ranging up to 0,81. All models were validated and based on the tests performed, no errors were drawn that would affect their credibility.


Author(s):  
Rahul Raj ◽  
Jeffrey P. Walker ◽  
Rohit Pingale ◽  
Rohit Nandan ◽  
Balaji Naik ◽  
...  

Author(s):  
Rahul Raj ◽  
Saurabh Suradhaniwar ◽  
Rohit Nandan ◽  
Adinarayana Jagarlapudi ◽  
Jeffrey Walker

2020 ◽  
Vol 58 (2) ◽  
pp. 826-840 ◽  
Author(s):  
Yuanheng Sun ◽  
Qiming Qin ◽  
Huazhong Ren ◽  
Tianyuan Zhang ◽  
Shanshan Chen

2013 ◽  
Vol 51 (7) ◽  
pp. 3899-3909 ◽  
Author(s):  
Terhikki Manninen ◽  
Pauline Stenberg ◽  
Miina Rautiainen ◽  
Pekka Voipio

Author(s):  
Shezhou Luo ◽  
Jing M. Chen ◽  
Cheng Wang ◽  
Alemu Gonsamo ◽  
Xiaohuan Xi ◽  
...  

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