Forest Leaf Mass per Area (LMA) through the Eye of Optical Remote Sensing: A Review and Future Outlook

Abstract

Quantitative remote sensing of leaf traits offers an opportunity to track biodiversity changes from space. Augmenting field measurement of leaf traits with remote sensing provides a pathway for monitoring essential biodiversity variables (EBVs) over space and time. Detailed information on key leaf traits such as leaf mass per area (LMA) is critical for understanding ecosystem structure and functioning, and subsequently the provision of ecosystem services. Although studies on remote sensing of LMA and related constituents have been conducted for over three decades, a comprehensive review of remote sensing of LMA—a key driver of leaf and canopy reflectance—has been lacking. This paper reviews the current state and potential approaches, in addition to the challenges associated with LMA estimation/retrieval in forest ecosystems. The physiology and environmental factors that influence the spatial and temporal variation of LMA are presented. The scope of scaling LMA using remote sensing systems at various scales, i.e., near ground (in situ), airborne, and spaceborne platforms is reviewed and discussed. The review explores the advantages and disadvantages of LMA modelling techniques from these platforms. Finally, the research gaps and perspectives for future research are presented. Our review reveals that although progress has been made, scaling LMA to regional and global scales remains a challenge. In addition to seasonal tracking, three-dimensional modeling of LMA is still in its infancy. Over the past decade, the remote sensing scientific community has made efforts to separate LMA constituents in physical modelling at the leaf level. However, upscaling these leaf models to canopy level in forest ecosystems remains untested. We identified future opportunities involving the synergy of multiple sensors, and investigated the utility of hybrid models, particularly at the canopy and landscape levels.

Morphoanatomical Responses and Stomatal Conductance in Shaded and Sun-Exposed Broussonetia papyrifera Seedlings

“…Moreover, larger LA and LMA of sun-exposed seedlings than shaded seedlings may contribute to its overall large, dense canopy restricting understory growth (Bosu et al 2013). It might be due to the larger values of these two leaf traits indicating an economic spectrum strategy regarding nutrient uptake and use, light capture, and carbon sequestration (Gara et al 2021). Additionally, a positive correlation is usually observed between a species' capacity to have a larger LA and a higher relative RGR (Pepe et al 2022).…”

High-throughput Soxhlet extraction method applied for analysis of leaf lignocellulose and non-structural substances

“…To do this, field samples are collected and subsequently analysed in the laboratory to measure the studied biochemicals. Field data measurements are pivotal in the parametrisation, calibration, validation, and upscaling of remote sensing models [ 19 , 20 ]. However, acquiring ground truth data through fieldwork poses a substantial challenge.…”

Estimation of Oak Leaf Functional Traits for California Woodland Savannas and Mixed Forests: Comparison between Statistical, Physical, and Hybrid Methods Using Spectroscopy

“…EWT is therefore a determining factor for thermal regulation, drought resistance, and flammability [17]. LMA is the inverse of the specific leaf area (SLA) and is a key indicator of resource allocation and plant strategies since it aggregates a wide range of organic compounds that can be separated into nitrogen-based constituents (proteins) and carbon-based constituents (including cellulose, lignin, hemicellulose, starch, and sugars) [18,19]. All of these four traits have specific spectral absorption features over the visible and near-infrared to short-wave infrared range (VSWIR) or 0.4-2.5 µm range [20]: pigments absorb light mainly in the visible range from 400 to 750 nm, while both EWT and LMA absorb light in the near-infrared (NIR) and more strongly in the short-wave infrared range (SWIR).…”