Susana Martín-Fernández

Relationship between LiDAR-derived forest canopy height and Landsat images

The mean and standard deviation (SD) of light detection and ranging (LiDAR)-derived canopy height are related to forest structure. However, LiDAR data typically cover a limited area and have a high economic cost compared with satellite optical imagery. Optical images may be required to extrapolate LiDAR height measurements across a broad landscape. Different spectral indices were obtained from three Landsat scenes. The mean, median, SD and coefficient of variation (CV) of LiDAR canopy height measurements were calculated in 30-m square blocks corresponding with Landsat Enhanced Thematic Mapper Plus (ETM+) pixels. Correlation and forward stepwise regression analysis was applied to these data sets. Mean and median LiDAR height versus normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), normalized burn ratio (NBR) and wetness Tasseled Cap showed the best correlation coefficients (R 2 ranging between −0.62 and −0.76). Nineteen regression models were obtained (R 2 = 0.65–0.70). These results show that LiDAR-derived canopy height may be associated with Landsat spectral indices. This approach is of interest in sustainable forest management, although further research is required to improve accuracy.

Patterns of covariance between airborne laser scanning metrics and Lorenz curve descriptors of tree size inequality

The Lorenz curve, as a descriptor of tree size inequality within a stand, has been suggested as a reliable means for characterizing forest structure and distinguishing even from uneven-sized areas. The aim of this study was to achieve a thorough understanding on the relations between airborne laser scanning (ALS) metrics and indicators based on Lorenz curve ordering: Gini coefficient (GC) and Lorenz asymmetry (S). Exploratory multivariate analysis was carried out using correlation tests, partial least squares (PLS), and an information-theoretic approach for multimodel inference (MMI). Best subset linear model was selected for GC and S prediction, as variable transformations yielded no improvement in the relation of ALS with the given response. Relative variable importance based on the MMI model showed that GC is best predicted by ALS metrics expressing canopy coverage, return dispersion, and low–high percentile combinations. Although ALS metrics showed no correlation with S, they did so against its constituting components: the proportions of basal area ( ) and stem density ( ) stocked above the mean quadratic diameter. The study of PLS loading vectors illustrated how ALS metrics explain variance in opposing directions for each of these components, so that their effects cancel each other out in the overall S. Cross-validation showed that only marginal differences are nevertheless found between predicting S directly or as the sum and estimations. The differing relation of diverse ALS metrics was therefore observed for and . The conclusions obtained by this research may assist in selecting relevant Lorenz curve descriptors for forest structure characterization, as well as in variable reduction strategies for their wall-to-wall prediction by means of ALS metrics.

Fusion of airborne LiDAR and multispectral sensors reveals synergic capabilities in forest structure characterization

Forest stand structure is an important concept for ecology and planning in sustainable forest management. In this article, we consider that the incorporation of complementary multispectral information from optical sensors to Light Detection and Ranging (LiDAR) may be advantageous, especially through data fusion by back-projecting the LiDAR points onto the multispectral image. A multivariate data set of both LiDAR and multispectral metrics was related with a multivariate data set of stand structural variables measured in a Scots pine forest through canonical correlation analysis (CCA). Four statistically significant pairs of canonical variables were found, which explained 83.0% accumulated variance. The first pair of canonical variables related indicators of stand development, i.e. height and volume, with LiDAR height metrics. CCA also found attributes describing stand density to be related to LiDAR and spectral variables determining canopy coverage. Other canonical variables pertained to Lorenz curve-derived attributes, which are measures of within-stand tree size variability and heterogeneity, able to discriminate even-sized from uneven-sized stands. The most relevant result was to find that metrics derived from the multispectral sensor showed significant explanatory potential for the prediction of these structural attributes. Therefore, we concluded that metrics derived from the optical sensor have potential for complementing the information from the LiDAR sensor in describing structural properties of forest stands. We recommend the use of back-projecting for jointly exploiting the synergies of both sensors using similar types of metrics as they are customary in forestry applications of LiDAR.

Stand structure, competition and growth of Scots pine (Pinus sylvestris L.) in a Mediterranean mountainous environment

The relationship between competition and tree growth was studied in four stands of Pinus sylvestris L. occurring in a continental Mediterranean mountain area (in the Guadarrama range, Spain), i.e., an uneven-aged stand, a stand with oak (Quercus pyrenaica Willd.) understorey, a plantation, and a mature even-aged stand. Competition was measured by a simple size-ratio distance-independent index and was negatively associated with tree diameter. This negative association was stronger in the uneven-aged, plantation and mature even-aged stands than in the stand with oak understorey. Competition was also negatively associated with current diameter increment. This relationship was moderately strong in the mature even-aged stand and weak in the uneven-aged stand and the plantation. In the uneven-aged and the mature even-aged stands, a weakly significant relationship was found between diameter growth and tree size, whereas these parameters were not associated in the stand with oak understorey. The competition index provided a better prediction of growth rate than the alternative use of diameter. Both diameter and basal area growth were greater in the uneven-aged than in the even-aged stands.RésuméLa relation entre compétition et croissance a été étudiée dans quatre peuplements de Pinus sylvestris L. que l’on rencontre dans la zone continentale des montagnes méditerranéennes (dans la région de Guadarrama en Espagne). Ont été pris en compte un peuplement inéquienne, un peuplement avec du chêne (Quercus pyrenaica Willd.) en sous—étage, une plantation, et un peuplement équienne âgé. La compétition a été mesurée par un index indépendant, simple rapport taille/distance, et était corrélée négativement avec le diamètre des arbres. Cette corrélation négative était plus forte dans le peuplement inéquienne, la plantation et le peuplement équienne âgé que dans le peuplement avec sous-étage de chêne. L’index de compétition était aussi corrélé négativement avec l’accroissement courant en diamètre. La relation était modérément forte dans le peuplement équienne âgé et faible dans le peuplement inéquienne et la plantation. Dans le peuplement inéquienne et le peuplement équienne âgé une relation faiblement significative a été trouvée entre croissance en diamètre et taille de l’arbre, alors que ces paramètres n’étaient pas corrélés dans le peuplement avec sous-étage de chêne. L’index de compétition fournit une meilleure prédiction du taux de croissance que le simple diamètre. La croissance en diamètre et en surface terrière était plus importante dans le peuplement inéquienne que dans le peuplement équienne âgé.

Sustainability assessment in forest management based on individual preferences

This paper presents a methodology to elicit the preferences of any individual in the assessment of sustainable forest management at the stand level. The elicitation procedure was based on the comparison of the sustainability of pairs of forest locations. A sustainability map of the whole territory was obtained according to the individuals preferences. Three forest sustainability indicators were pre-calculated for each point in a study area in a Scots pine forest in the National Park of Sierra de Guadarrama in the Madrid Region in Spain to obtain the best management plan with the sustainability map. We followed a participatory process involving fifty people to assess the sustainability of the forest management and the methodology. The results highlighted the demand for conservative forest management, the usefulness of the methodology for managers, and the importance and necessity of incorporating stakeholders into forestry decision-making processes.