Predicting macroalgal pigments (chlorophyll a, chlorophyll b, chlorophyll a + b, carotenoids) in various environmental conditions using high-resolution hyperspectral spectroradiometers. Issue 17 (2nd September 2018)

• Record Type: Journal Article
• Authors: Vahtmäe, Ele; Kotta, Jonne; Orav-Kotta, Helen; Kotta, Ilmar; Pärnoja, Merli; Kutser, Tiit
• Is Part Of: International journal of remote sensing. Volume 39:Issue 17(2018)
• Page Start: 5716
• Page End: 5738
• Publication Date: 2018-09-02
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2017.1399481
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Photosynthetic pigments may indicate the health and productivity of vegetation and thereby are among the most important targets of the remote-sensing science. We studied the relationship between macroalgae pigment concentration measured in situ and spectral reflectance, to develop predictive remote-sensing methods for macroalgal pigments. The measurements of spectral reflectance of macroalgae were made using both a field portable spectrometer Ramses built by TriOS GmbH (Germany) and a laboratory hyperspectral imaging device HySpex built by Norsk Elektro Optikk (Norway). Our results showed that differences in total chlorophyll (Chl- a + b ) concentrations resulted in the consistent change of spectral reflectance for studied brown ( Fucus vesiculosus ) and green ( Cladophora glomerata, Ulva intestinalis ) macroalgae species. Charophytes ( Chara aspera, Chara horrida ) were also studied, and the relationship was much weaker for this taxon. If spectral indices predicted relatively well the concentration of Chl- a + b ( R 2 = 0.64–0.73) and the carotenoid to total chlorophyll ratio (Car:Chl- a + b, R 2 = 0.80) across the five studied macroalgae species, then the concentration of chlorophyll a (Chl- a ), chlorophyll b (Chl- b ), and carotenoids (Car) were more difficult to model ( R 2 = 0.004–0.51). The HySpex imaging system yielded systematically better results in predicting pigment concentrations compared to the Ramses spectroradiometer. By using traditional assessment of pigment concentration along with the Hyspex imaging device, we were able to build models with a capability to predict the spatial patterns of pigment concentration for Baltic Sea macroalgae.