Title of article :
Brown and green LAI mapping through spectral indices
Author/Authors :
Delegido، نويسنده , , Jesْs and Verrelst، نويسنده , , Jochem and Rivera، نويسنده , , Juan P. and Ruiz-Verdْ، نويسنده , , Antonio and Moreno، نويسنده , , José، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2015
Abstract :
When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent croplands. The first step separates green from brown LAI by means of a newly proposed index, ‘Green Brown Vegetation Index (GBVI)’. This index exploits two shortwave infrared (SWIR) spectral bands centred at 2100 and 2000 nm, which fall right in the dry matter absorption regions, thereby providing positive values for senescent vegetation and negative for green vegetation. The second step involves applying linear regression functions based on optimized vegetation indices to estimate green and brown LAI estimation respectively. While the green LAI index uses a band in the red and a band in the red-edge, the brown LAI index uses bands located in the same spectral region as GBVI, i.e. an absorption band located in the region of maximum absorption of cellulose and lignin at 2154 nm, and a reference band at 1635 nm where the absorption of both water and dry matter is low. The two-step approach was applied to a HyMap image acquired over an agroecosystem at the agricultural site Barrax, Spain.
Keywords :
Brown LAI , Vegetation indices , Hyperspectral , Senescent vegetation , Sentinel-2 , Agroecosystem
Journal title :
International Journal of Applied Earth Observation and Geoinformation
Journal title :
International Journal of Applied Earth Observation and Geoinformation