Lucie Homolová

Modelling plant species distribution in alpine grasslands using airborne imaging spectroscopy

Remote sensing using airborne imaging spectroscopy (AIS) is known to retrieve fundamental optical properties of ecosystems. However, the value of these properties for predicting plant species distribution remains unclear. Here, we assess whether such data can add value to topographic variables for predicting plant distributions in French and Swiss alpine grasslands. We fitted statistical models with high spectral and spatial resolution reflectance data and tested four optical indices sensitive to leaf chlorophyll content, leaf water content and leaf area index. We found moderate added-value of AIS data for predicting alpine plant species distribution. Contrary to expectations, differences between species distribution models (SDMs) were not linked to their local abundance or phylogenetic/functional similarity. Moreover, spectral signatures of species were found to be partly site-specific. We discuss current limits of AIS-based SDMs, highlighting issues of scale and informational content of AIS data.

Comparison of remote sensing and plant trait-based modelling to predict ecosystem services in subalpine grasslands

There is a growing demand for spatially explicit assessment of multiple ecosystem services (ES) and remote sensing (RS) can provide valuable data to meet this challenge. In this study, located in the Central French Alps, we used high spatial and spectral resolution RS images to assess multiple ES based on underpinning ecosystem properties (EP) of subalpine grasslands. We estimated five EP (green biomass, litter mass, crude protein content, species diversity and soil carbon content) from RS data using empirical RS methods and maps of ES were calculated as simple linear combinations of EP. Additionally, the RS-based results were compared with results of a plant trait-based statistical modelling approach that predicted EP and ES from land use, abiotic and plant trait data (modelling approach). The comparison between the RS and the modelling approaches showed that RS-based results provided better insight into the fine-grained spatial distribution of EP and thereby ES, whereas the modelling approach reflected the land use signal that underpinned trait-based models of EP. The spatial agreement between the two approaches at a 20-m resolution varied between 16 and 22% for individual EP, but for the total ecosystem service supply it was only 7%. Furthermore, the modelling approach identified the alpine grazed meadows land use class as areas with high values of multiple ES (hot spots) and mown-grazed permanent meadows as areas with low values and only few ES (cold spots). Whereas the RS-based hot spots were a small subset of those predicted by the modelling approach, cold spots were rather scattered, small patches with limited overlap with the modelling results. Despite limitations associated with timing of assessment campaigns and field data requirements, RS offers valuable data for spatially continuous mapping of EP and can thus supply RS-based proxies of ES. Although the RS approach was applied to a limited area and for one type of ecosystem, we believe that the broader availability of high fidelity airborne and satellite RS data will promote RS-based assessment of ES to larger areas and other ecosystems.

Physically-based retrievals of Norway spruce canopy variables from very high spatial resolution hyperspectral data

This study was conducted to answer two research questions: (1) what is the spatial variability of the leaf optical properties between 400-1600 nm (hemispherical-directional reflectance, transmittance, absorption) within young Norway spruce crowns, and (2) how to design a suitable physically-based approach retrieving the total chlorophyll content of a complex coniferous canopy from very high spatial resolution (0.4 m) hyperspectral data? It was proved that sun-exposed needles of current age-class statistically differ (alpha-level = 0.01) from rest of the needles in reflectance between 510-760 nm. Last four age-classes of sun-exposed needles were also found to be significantly different from almost all age-classes of sun-shaded needles in transmittance from 760-1350 nm. An operational estimation of chlorophyll a+b content (Cab) from an airborne AISA Eagle hyperspectral image was proposed by means of a PROSPECT-DART inversion employing an artificial neural network (ANN). A spatial pattern of estimated Cab was successfully validated against the Cab map produced by a vegetation index ANCB650-720. Coefficients of determination (R2) between ground measured and retrieved Cab were 0.81 and 0.83, respectively, with root mean square errors (RMSE) of 2.72 mug cm-2 for ANN and 3.27 mug cm-2 for ANCB650-720.

Spectral Properties of Coniferous Forests: A Review of In Situ and Laboratory Measurements

Coniferous species are present in almost all major vegetation biomes on Earth, though they are the most abundant in the northern hemisphere, where they form the northern tree and forest lines close to the Arctic Circle. Monitoring coniferous forests with satellite and airborne remote sensing is active, due to the forests’ great ecological and economic importance. We review the current understanding of spectral behavior of different components forming coniferous forests. We look at the spatial, directional, and seasonal variations in needle, shoot, woody element, and understory spectra in coniferous forests, based on measurements. Through selected case studies, we also demonstrate how coniferous canopy spectra vary at different spatial scales, and in different viewing angles and seasons. Finally, we provide a synthesis of gaps in the current knowledge on spectra of elements forming coniferous forests that could also serve as a recommendation for planning scientific efforts in the future.

Assessing the consistency of optical properties measured in four integrating spheres

ABSTRACT Leaf optical properties (LOPs) determine the radiation regime of vegetation, thus being key input parameters in leaf and canopy radiative transfer models. It is of great importance to know the uncertainties originating from the LOP measurements. The most common approach to measure LOP uses integrating spheres. They allow measurements of both directional-hemispherical reflectance factor (R) and transmittance factor (T). However, sphere’s design, inner surface coating and measurement protocol differ among the spheres’ models and manufacturers. Our main goal was to evaluate the consistency of optical properties measured in four integrating spheres (Dualsphere, Labspehre, ASD, and Li-cor). Our test samples were three Spectralon® panels, four artificial materials and leaves from six common broadleaf tree species. Results showed that spectra measured in the four integrating spheres were generally similar in the spectral region between 400 and 1600 nm. The average standard deviation computed among the spectra of all samples measured in all spheres was around 0.023 (and varied between 0.005 and 0.044). Statistically significant differences were detected mainly between Dualsphere and Li-cor spheres.