Modelling Forest α-Diversity and Floristic Composition — On the Added Value of LiDAR plus Hyperspectral Remote Sensing

The decline of biodiversity is one of the major current global issues. Still, there is a widespread lack of information about the spatial distribution of individual species and biodiversity as a whole. Remote sensing techniques are increasingly used for biodiversity monitoring and especially the combination of LiDAR and hyperspectral data is expected to deliver valuable information. In this study spatial patterns of vascular plant community composition and α-diversity of a temperate montane forest in Germany were analysed for different forest strata. The predictive power of LiDAR (LiD) and hyperspectral (MNF) datasets alone and combined (MNF+LiD) was compared using random forest regression in a ten-fold cross-validation scheme that included feature selection and model tuning. The final models were used for spatial predictions. Species richness could be predicted with varying accuracy (R2 = 0.26 to 0.55) depending on the forest layer. In contrast, community composition of the different layers, obtained by multivariate ordination, could in part be modelled with high accuracies for the first ordination axis (R2 = 0.39 to 0.78), but poor accuracies for the second axis (R2 ≤ 0.3). LiDAR variables were the best predictors for total species richness across all forest layers (R2 LiD = 0.3, R2 MNF = 0.08, R2 MNF+LiD = 0.2), while for community composition across all forest layers both hyperspectral and LiDAR predictors achieved similar performances (R2 LiD = 0.75, R2 MNF = 0.76, R2 MNF+LiD = 0.78). The improvement in R2 was small (≤0.07)—if any—when using both LiDAR and hyperspectral data as compared to using only the best single predictor set. This study shows the high potential of LiDAR and hyperspectral data for plant biodiversity modelling, but also calls for a critical evaluation of the added value of combining both with respect to acquisition costs

Article Modelling Forest α-Diversity and Floristic Composition — On the Added Value of LiDAR plus Hyperspectral Remote Sensing

Abstract: The decline of biodiversity is one of the major current global issues. Still, there is a widespread lack of information about the spatial distribution of individual species and biodiversity as a whole. Remote sensing techniques are increasingly used for biodiversity monitoring and especially the combination of LiDAR and hyperspectral data is expected to deliver valuable information. In this study spatial patterns of vascular plant community composition and α-diversity of a temperate montane forest in Germany were analysed for different forest strata. The predictive power of LiDAR (LiD) and hyperspectral (MNF) datasets alone and combined (MNF+LiD) was compared using random forest regression in a ten-fold cross-validation scheme that included feature selection and model tuning. TheRemote Sens. 2012, 4 2819 final models were used for spatial predictions. Species richness could be predicted with varying accuracy (R2 = 0.26 to 0.55) depending on the forest layer. In contrast, communit

Mosses Like It Rough—Growth Form Specific Responses of Mosses, Herbaceous and Woody Plants to Micro-Relief Heterogeneity

Micro-relief heterogeneity can lead to substantial variability in microclimate and hence niche opportunities on a small scale. We explored the relationship between plant species richness and small-scale heterogeneity of micro-relief on the subtropical island of La Palma, Canary Islands. Overall, we sampled 40 plots in laurel and pine forests at four altitudinal bands. Species richness was recorded separately for various growth forms (i.e., mosses, herbaceous and woody plants). Site conditions such as altitude, slope, aspect, and tree density were measured. Micro-relief heterogeneity was characterized by surface structure and a subsequently derived surface heterogeneity index. The effect of micro-relief heterogeneity on species richness was analysed by means of linear mixed effect models and variance partitioning. Effects of micro-relief heterogeneity on species richness varied considerably between growth forms. While moss richness was affected significantly by micro-relief heterogeneity, herbaceous and woody plants richness responded mainly to larger-scale site conditions such as aspect and tree density. Our results stress the importance of small-scale relief heterogeneity for the explanation of spatial patterns of species richness. This poses new challenges as small-scale heterogeneity is largely underrepresented, e.g. with regard to its application in species distribution models

An Overview of the Regional Experiments for Land-atmosphere Exchanges 2012 (REFLEX 2012) Campaign

The REFLEX 2012 campaign was initiated as part of a training course on the organization of an airborne campaign to support advancement of the understanding of land-atmosphere interaction processes. This article describes the campaign, its objectives and observations, remote as well as in situ. The observations took place at the experimental Las Tiesas farm in an agricultural area in the south of Spain. During the period of ten days, measurements were made to capture the main processes controlling the local and regional land-atmosphere exchanges. Apart from multi-temporal, multi-directional and multi-spatial space-borne and airborne observations, measurements of the local meteorology, energy fluxes, soil temperature profiles, soil moisture profiles, surface temperature, canopy structure as well as leaf-level measurements were carried out. Additional thermo-dynamical monitoring took place at selected sites. After presenting the different types of measurements, some examples are given to illustrate the potential of the observations made