Search

The plantation of fast-growing tree species plays a crucial role in supplying forest products to growing economies while relieving pressure on native forests reducing the overexploitation of native ecosystems. Grown in more than 90 countries, Eucalyptus spp. are fast-growing tree species driving economic production comprising pulp, wood, or thermal energy. Climate change is increasing the frequency and severity of extreme drought episodes: the 2019 drought in Mato Grosso, Brazil, was the second driest episode ever recorded. Forest inventory data comprising thousands of individual tree measurements collected in consecutive surveys - years 2019, 2020, 2021 – were modelled with mixed-effects models to identify significant factors influencing tree mortality after drought. Time-series of growth dynamics of the four eucalypt commercial clones were tested. For the landscape assessment, surveys using unmanned aerial vehicle (UAV) supported a high-resolution image mosaicking to derive digital surface models and the vegetation indexes driving segmentation and classification methods using ground plot-level observations as training data. The impact of drought was measured in terms of mortality, growth dynamics and the financial losses computed when valuing the 1400-ha plantation along the 3-year series. The modelling results showed high-stocking plantations suffered more from extreme water-stress conditions. The interaction between stocking and clone was analysed. On average, the 2019 drought triggered an estimate loss of $3500 per hectare. The estimation of live and dead conditions using UAV-based outcomes reached an overall accuracy of 89% and 0.7 in the Cohen's kappa used to map forest health wall-to-wall. Our findings advocate for a reduction of tree planting density and enhanced clone selection to turn eucalypt plantations more resilient to extreme water-stress. Combining UAV-based remote sensing technology, ground truth data and management expertise in eucalypt management

Global high-resolution imagery is a well-assimilated technology in forest mapping. The release of the Norway's International Climate & Forests Initiative (NICFI) Planet tropical basemaps time-series starting in 2015 at a 4.77-m resolution represents a unique opportunity to forecast climate change consequences such as drought episodes. Using multi-temporal ground surveys over 144 plots and publicly available high-resolution Planet dove time-series imagery we evaluate forest mortality patterns driven by imaging spectroscopy methods in Mato Grosso (Brazil) over an area planted with eucalypts severely affected by the 2019 drought. Changes in vegetation indexes before and after the 2019 drought were modelled using the effective logistic regression modelling to explain variation in tree mortality between the surveys, the dependent variable. We aimed to straightforwardly model tree mortality using change vectors in Planet's image mosaics co-registering in time with the observed tree mortality measurements in the field. The results showed differences in Normalized Difference Vegetation Index (NDVI) as the most significant predictor variable under the effective logistic regression modelling performed. The efficacy of 80.98% in concordance pairs correctly classified represented 0.81 of area under the Receiver Operating Curve (ROC). The release of the 2015-2020 Planet imagery in the tropics at 4.77-m resolution represents a valuable dataset to better understand previous natural disturbances and a powerful technology to detect in advance, and monthly after September 2020, eucalypt areas prone to harmful and increasingly frequent water-stress episodes.

Earth Observation data are uniquely positioned to estimate forest aboveground biomass density (AGBD) in accordance with the United Nations Framework Convention on Climate Change (UNFCCC) principles of ‘transparency, accuracy, completeness, consistency and comparability’. However, the use of space-based AGBD maps for national-level reporting to the UNFCCC is nearly non-existent as of 2023, the end of the first global stocktake (GST). We conduct an evidence-based comparison of AGBD estimates from the NASA Global Ecosystem Dynamics Investigation and ESA Climate Change Initiative, describing differences between the products and National Forest Inventories (NFIs), and suggesting how science teams must align efforts to inform the next GST. Between the products, in the tropics, the largest differences in estimated AGBD are primarily in the Congolese lowlands and east/southeast Asia. Where NFI data were acquired (Peru, Mexico, Lao PDR and 30 regions of Spain), both products show strong correlation to NFI-estimated AGBD, with no systematic deviations. The AGBD-richest stratum of these, the Peruvian Amazon, is accurately estimated in both. These results are remarkably promising, and to support the operational use of AGB map products for policy reporting, we describe targeted ways to align products with Intergovernmental Panel on Climate Change (IPCC) guidelines. We recommend moving towards consistent statistical terminology, and aligning on a rigorous framework for uncertainty estimation, supported by the provision of open-science codes for large-area assessments that comprehensively report uncertainty. Further, we suggest the provision of objective and open-source guidance to integrate NFIs with multiple AGBD products, aiming to enhance the precision of national estimates. Finally, we describe and encourage the release of user-friendly product documentation, with tools that produce AGBD estimates directly applicable to the IPCC guideline methodologies. With these steps, spac

Knowledge about forest road networks is essential for sustainable forest management and fire management. The aim of this study was to assess the accuracy of a new hierarchical-hybrid classification tool (HyClass) for mapping paved and unpaved forest roads with LiDAR data. Bare-earth and low-lying vegetation were also identified. For this purpose, a rural landscape (area 70 ha) in northwestern Spain was selected for study, and a road network map was extracted from the cadastral maps as the ground truth data. The HyClass tool is based on a decision tree which integrates segmentation processes at local scale with decision rules. The proposed approach yielded an overall accuracy (OA) of 96.5%, with a confidence interval (CI) of 94.0–97.6%, representing an improvement over pixel-based classification (OA = 87.0%, CI = 83.7–89.8%) using Random Forest (RF). In addition, with the HyClass tool, the classification precision varied significantly after reducing the original point density from 8.7 to 1 point/m2. The proposed method can provide accurate road mapping to support forest management as an alternative to pixel-based RF classification when the LiDAR point density is higher than 1 point/m2

This essay launches a critique of the concept of identity in which modern Latin American national states have been founded. The reflection proposed here is articulated from the conception that the Ecuadorian Marxist philosopher Bolívar Echeverría developed about the concept of culture. It is postulated that the identity (personal and collective) is not to be understood through the static accumulation of traits and characteristics, but as the result of a violent confrontation between the same and the other, the identity, thus, is dynamic, evanescent and is in permanent construction. For this purpose, the concept of miscegenation, fundamental in the Echeverria conception of culture, is the center of reflection, and allows, in order to support the concept of identity that is presented here, to integrate, explain and develop the reflections of George Bataille about death and eroticism., Este ensayo pone en marcha una crítica del concepto de identidad en el que los estados nacionales modernos latinoamericanos se han fundado. La reflexión que aquí se propone, se articula desde la concepción que el filósofo marxista ecuatoriano, Bolívar Echeverría, desarrolló sobre el concepto de cultura. Se postula que la identidad (personal y colectiva) no ha de entenderse mediante la acumulación estática de rasgos y características, sino como el resultado de un enfrentamiento violento entre lo mismo y lo ‘otro’. La identidad, así, es dinámica, evanescente y está en permanente construcción. Para tal efecto, el concepto de mestizaje, fundamental en la concepción echeverriana de la cultura, es el centro de la reflexión, y permite, con el fin de respaldar el concepto de identidad que aquí se expone, integrar, explicitar y desarrollar las reflexiones de George Bataille sobre la muerte y el erotismo.

This essay launches a critique of the concept of identity in which modern Latin American national states have been founded. The reflection proposed here is articulated from the conception that the Ecuadorian Marxist philosopher Bolívar Echeverría developed about the concept of culture. It is postulated that the identity (personal and collective) is not to be understood through the static accumulation of traits and characteristics, but as the result of a violent confrontation between the same and the other, the identity, thus, is dynamic, evanescent and is in permanent construction. For this purpose, the concept of miscegenation, fundamental in the Echeverria conception of culture, is the center of reflection, and allows, in order to support the concept of identity that is presented here, to integrate, explain and develop the reflections of George Bataille about death and eroticism., Este ensayo pone en marcha una crítica del concepto de identidad en el que los estados nacionales modernos latinoamericanos se han fundado. La reflexión que aquí se propone, se articula desde la concepción que el filósofo marxista ecuatoriano, Bolívar Echeverría, desarrolló sobre el concepto de cultura. Se postula que la identidad (personal y colectiva) no ha de entenderse mediante la acumulación estática de rasgos y características, sino como el resultado de un enfrentamiento violento entre lo mismo y lo ‘otro’. La identidad, así, es dinámica, evanescente y está en permanente construcción. Para tal efecto, el concepto de mestizaje, fundamental en la concepción echeverriana de la cultura, es el centro de la reflexión, y permite, con el fin de respaldar el concepto de identidad que aquí se expone, integrar, explicitar y desarrollar las reflexiones de George Bataille sobre la muerte y el erotismo.

Estimating forest inventory variables is important in monitoring forest resources and mitigating climate change. In this respect, forest managers require flexible, non-destructive methods for estimating volume and biomass. High-resolution and low-cost remote sensing data are increasingly available to measure three-dimensional (3D) canopy structure and to model forest structural attributes. The main objective of this study was to evaluate and compare the individual tree volume estimates derived from high-density point clouds obtained from airborne laser scanning (ALS) and digital aerial photogrammetry (DAP) in Eucalyptus spp. plantations. Object-based image analysis (OBIA) techniques were applied for individual tree crown (ITC) delineation. The ITC algorithm applied correctly detected and delineated 199 trees from ALS-derived data, while 192 trees were correctly identified using DAP-based point clouds acquired from Unmanned Aerial Vehicles (UAV), representing accuracy levels of respectively 62% and 60%. Addressing volume modelling, non-linear regression fit based on individual tree height and individual crown area derived from the ITC provided the following results: Model Efficiency (Mef) = 0.43 and 0.46, Root Mean Square Error (RMSE) = 0.030 m3 and 0.026 m3, rRMSE = 20.31% and 19.97%, and an approximately unbiased results (0.025 m3 and 0.0004 m3) using DAP and ALS-based estimations, respectively. No significant difference was found between the observed value (field data) and volume estimation from ALS and DAP (p-value from t-test statistic = 0.99 and 0.98, respectively). The proposed approaches could also be used to estimate basal area or biomass stocks in Eucalyptus spp. plantations.

This essay launches a critique of the concept of identity in which modern Latin American national states have been founded. The reflection proposed here is articulated from the conception that the Ecuadorian Marxist philosopher Bolívar Echeverría developed about the concept of culture. It is postulated that the identity (personal and collective) is not to be understood through the static accumulation of traits and characteristics, but as the result of a violent confrontation between the same and the other, the identity, thus, is dynamic, evanescent and is in permanent construction. For this purpose, the concept of miscegenation, fundamental in the Echeverria conception of culture, is the center of reflection, and allows, in order to support the concept of identity that is presented here, to integrate, explain and develop the reflections of George Bataille about death and eroticism., Este ensayo pone en marcha una crítica del concepto de identidad en el que los estados nacionales modernos latinoamericanos se han fundado. La reflexión que aquí se propone, se articula desde la concepción que el filósofo marxista ecuatoriano, Bolívar Echeverría, desarrolló sobre el concepto de cultura. Se postula que la identidad (personal y colectiva) no ha de entenderse mediante la acumulación estática de rasgos y características, sino como el resultado de un enfrentamiento violento entre lo mismo y lo ‘otro’. La identidad, así, es dinámica, evanescente y está en permanente construcción. Para tal efecto, el concepto de mestizaje, fundamental en la concepción echeverriana de la cultura, es el centro de la reflexión, y permite, con el fin de respaldar el concepto de identidad que aquí se expone, integrar, explicitar y desarrollar las reflexiones de George Bataille sobre la muerte y el erotismo.

Este ensayo pone en marcha una crítica del concepto de identidad en el que los estados nacionales modernos latinoamericanos se han fundado. La reflexión que aquí se propone, se articula desde la concepción que el filósofo marxista ecuatoriano, Bolívar Echeverría, desarrolló sobre el concepto de cultura. Se postula que la identidad (personal y colectiva) no ha de entenderse mediante la acumulación estática de rasgos y características, sino como el resultado de un enfrentamiento violento entre lo mismo y lo ‘otro’. La identidad, así, es dinámica, evanescente y está en permanente construcción. Para tal efecto, el concepto de mestizaje, fundamental en la concepción echeverriana de la cultura, es el centro de la reflexión, y permite, con el fin de respaldar el concepto de identidad que aquí se expone, integrar, explicitar y desarrollar las reflexiones de George Bataille sobre la muerte y el erotismo.,   This essay launches a critique of the concept of identity in which modern Latin American national states have been founded. The reflection proposed here is articulated from the conception that the Ecuadorian Marxist philosopher Bolívar Echeverría developed about the concept of culture. It is postulated that the identity (personal and collective) is not to be understood through the static accumulation of traits and characteristics, but as the result of a violent confrontation between the same and the other, the identity, thus, is dynamic, evanescent and is in permanent construction. For this purpose, the concept of miscegenation, fundamental in the Echeverria conception of culture, is the center of reflection, and allows, in order to support the concept of identity that is presented here, to integrate, explain and develop the reflections of George Bataille about death and eroticism.

Este ensayo pone en marcha una crítica del concepto de identidad en el que los estados nacionales modernos latinoamericanos se han fundado. La reflexión que aquí se propone, se articula desde la concepción que el filósofo marxista ecuatoriano, Bolívar Echeverría, desarrolló sobre el concepto de cultura. Se postula que la identidad (personal y colectiva) no ha de entenderse mediante la acumulación estática de rasgos y características, sino como el resultado de un enfrentamiento violento entre lo mismo y lo ‘otro’. La identidad, así, es dinámica, evanescente y está en permanente construcción. Para tal efecto, el concepto de mestizaje, fundamental en la concepción echeverriana de la cultura, es el centro de la reflexión, y permite, con el fin de respaldar el concepto de identidad que aquí se expone, integrar, explicitar y desarrollar las reflexiones de George Bataille sobre la muerte y el erotismo.,   This essay launches a critique of the concept of identity in which modern Latin American national states have been founded. The reflection proposed here is articulated from the conception that the Ecuadorian Marxist philosopher Bolívar Echeverría developed about the concept of culture. It is postulated that the identity (personal and collective) is not to be understood through the static accumulation of traits and characteristics, but as the result of a violent confrontation between the same and the other, the identity, thus, is dynamic, evanescent and is in permanent construction. For this purpose, the concept of miscegenation, fundamental in the Echeverria conception of culture, is the center of reflection, and allows, in order to support the concept of identity that is presented here, to integrate, explain and develop the reflections of George Bataille about death and eroticism.

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases.

High spatial resolution imagery provided by unmanned aerial vehicles (UAVs) can yield accurate and efficient estimation of tree dimensions and canopy structural variables at the local scale. We flew a low-cost, lightweight UAV over an experimental Pinus pinea L. plantation (290 trees distributed over 16 ha with different fertirrigation treatments) to determine the tree positions and to estimate individual tree height (h), diameter (d), biomass (wa), as well as changes in these variables between 2015 and 2017. We used Structure from Motion (SfM) and 3D point cloud filtering techniques to generate the canopy height model and object-based image analysis to delineate individual tree crowns (ITC). ITC results were validated using accurate field measurements over a subsample of 50 trees. Comparison between SfM-derived and field-measured h yielded an R2 value of 0.96. Regressions using SfM-derived variables as explanatory variables described 79% and 86–87% of the variability in d and wa, respectively. The height and biomass growth estimates across the entire study area for the period 2015–2017 were 0.45 m ± 0.12 m and 198.7 ± 93.9 kg, respectively. Significant differences (t-test) in height and biomass were observed at the end of the study period. The findings indicate that the proposed method could be used to derive individual-tree variables and to detect spatio-temporal changes, highlighting the potential role of UAV-derived imagery as a forest management tool

This study aimed to develop ALS-based models for estimating stem, crown and aboveground biomass in three types of Mediterranean forest, based on low density ALS data. Two different modelling approaches were used: (i) linear models with different variable selection methods (Stepwise Selection [SS], Clustering/Exhaustive search [CE] and Genetic Algorithm [GA]), and (ii) previously Published Models (PM) applicable to diverse types of forest. Results indicated more accurate estimations of biomass components for pure Pinus pinea L. (rRMSE = 25.90-26.16%) than for the mixed (30.86-36.34%) and Quercus pyrenaica Willd. forests (32.78-34.84%). All the tested approaches were valuable, but SS and GA performed better than CE and PM in most cases

Aim of study: The study aims to analyse the potential use of lowcost unmanned aerial vehicle (UAV) imagery for the estimation of Pinus pinea L. variables at the individual tree level (position, tree height and crown diameter). Area of study: This study was conducted under the PINEA project focused on 16 ha of umbrella pine afforestation (Portugal) subjected to different treatments. Material and methods: The workflow involved: a) image acquisition with consumer-grade cameras on board an UAV; b) orthomosaic and digital surface model (DSM) generation using structure-from-motion (SfM) image reconstruction; and c) automatic individual tree segmentation by using a mixed pixel‑and region‑based algorithm. Main results: The results of individual tree segmentation (position, height and crown diameter) were validated using field measurements from 3 inventory plots in the study area. All the trees of the plots were correctly detected. The RMSE values for the predicted heights and crown widths were 0.45 m and 0.63 m, respectively. Research highlights: The results demonstrate that tree variables can be automatically extracted from high resolution imagery. We highlight the use of UAV as a fast, reliable and cost-effective technique for small scale applications.

Este estudio presenta avances en la metodología de inventario forestal a nivel de masa (area-based approach, ABA) con datos LiDAR aerotransportado de baja densidad y destaca la utilidad de los datos LiDAR disponibles para España a escala nacional para realizar cartografía de las principales variables dasométricas en un bosque Mediterráneo de pino piñonero, caracterizado por una compleja orografía. Para ello, se ajustaron modelos lineales de regresión en cada tipo de bosque, a partir de los datos LiDAR de baja densidad (0,5 primeros retornos m–2), proporcionados por el PNOA (Plan Nacional de Ortofotografía Aérea) y los datos obtenidos en campo. Además, se investigó la influencia de los umbrales de altura usados en la extracción de los estadísticos de la nube de puntos LiDAR (MHT: Minimun Height ThresholdyBHT: Break Height Threshold). Los mejores modelos de regresión explicaron un 61-85%, 67-98%, 74-98% de la variabilidad en altura de masa, área basimétrica y volumen, respectivamente. El error de estimación en las variables de masa fue mayor en bosques cerrados mixtos y puros de caducifolias que en los bosques más homogéneos de coníferas. Los resultados demostraron que los umbrales de altura no fueron especialmente críticos en la estimación de las variables de masa en bosques de coníferas, pero hubo diferencias sustanciales en el caso de volumen, cuando aumentaron los umbrales de altura (HBTy MHT) en las masas de estructura más compleja (bosque mixto y puro de caducifolias). Un análisis métrica a métrica reveló la existencia de diferencias significativas en la mayor parte de las variables explicativas extraídas a partir de diferentes umbrales de altura (HBTy MHT). Los mejores modelos de predicción se aplicaron a los rodales de referencia y se elaboró una cartografía espacialmente explícita que representa las principales variables de masa, facilitando así la toma de decisiones para la gestión forestal sostenible en los ecosistemas de bosque mediterráneo, This study reports progress in forest inventory methods involving the use of low density airborne LiDAR data and an area-based approach (ABA). It also emphasizes the usefulness of the Spanish countrywide LiDAR dataset for mapping forest stand attributes in Mediterranean stone pine forest characterized by complex orography. Lowdensity airborne LiDAR data (0.5 first returns m–2) was used to develop individual regression models for a set of forest stand variables in different types of forest. LiDAR data is now freely available for most of the Spanish territory and is provided by the Spanish National Aerial Photography Program (Plan Nacional de Ortofotografía Aérea, PNOA). The influence of height thresholds (MHT: Minimun Height Threshold and BHT: Break Height Threshold) used in extracting LiDAR metrics was also investigated. The best regression models explained 61-85%, 67-98% and 74-98% of the variability in ground-truth stand height, basal area and volume, respectively. The magnitude of error for predicting structural vegetation parameters was higher in closed deciduous and mixed forest than in the more homogeneous coniferous stands. Analysis of height thresholds (HT) revealed that these parameters were not particularly important for estimating several forest attributes in the coniferous forest; nevertheless, substantial differences in volume modelling were observed when the height thresholds (MHT and BHT) were increased in complex structural vegetation (mixed and deciduous forest). A metric-by-metric analysis revealed that there were significant differences in most of the explanatory variables computed from different height thresholds (HBT and MHT).The best models were applied to the reference stands to yield spatially explicit predictions about the forest resources. Reliable mapping of biometric variables was implemented to facilitate effective and sustainable management strategies and practices in Mediterranean Forest ecosystem

[EN] Knowledge about forest road networks is essential for sustainable forest management and fire management. The aim of this study was to assess the accuracy of a new hierarchical-hybrid classification tool (HyClass) for mapping paved and unpaved forest roads with LiDAR data. Bareearth and low-lying vegetation were also identified. For this purpose, a rural landscape (area 70 ha) in northwestern Spain was selected for study, and a road network map was extracted from the cadastral maps as the ground truth data. The HyClass tool is based on a decision tree which integrates segmentation processes at local scale with decision rules. The proposed approach yielded an overall accuracy (OA) of 96.5%, with a confidence interval (CI) of 94.0-97.6%, representing an improvement over pixel-based classification (OA = 87.0%, CI = 83.7-89.8%) using Random Forest (RF). In addition, with the HyClass tool, the classification precision varied significantly after reducing the original point density from 8.7 to 1 point/m2. The proposed method can provide accurate road mapping to support forest management as an alternative to pixel-based RF classification when the LiDAR point density is higher than 1 point/m2

[EN] In this study, we used data from a thinning trial conducted on 34 different sites and 102 sample plots established in pure and even-aged Pinus radiata and Pinus pinaster stands, to test the potential use of low-density airborne laser scanning (ALS) metrics and terrestrial laser scanning (TLS) metrics to provide accurate estimates of variables related to surface and canopy fires. An exhaustive field inventory was carried out in each plot to estimate the main stand variables and the main variables related to fire hazard: surface fuel loads by layers, fuel strata gap, surface fuel height, stand mean height, canopy base height, canopy fuel load and canopy bulk density. In addition, the point clouds from low-density ALS and single-scan TLS of each sample plot were used to calculate metrics related to the vertical and horizontal distribution of forest fuels. The comparative performance of the following three non-parametric machine learning techniques used to estimate the main stand-and fire-related variables from those metrics was evaluated: (i) multivariate adaptive regression splines (MARS), (ii) support vector machine (SVM), and (iii) random forest (RF). The selection of the best modeling approach was based on a comparison of the root mean square error (RMSE), obtained by optimizing the parameters of each technique and performing crossvalidation. Overall, the best results were obtained with the MARS techniques for data from both sensors. The TLS data provided the best results for variables associated with the internal characteristics of canopy structure and understory fuel but were less reliable for estimating variables associated with the upper canopy, due to occlusion by mid-canopy foliage. The combination of ALS and TLS metrics improved the accuracy of estimates for all variables analyzed, except the height and the biomass of the understory shrubs. The variability demonstrated by the combined use of both types of metrics ranged from 43.11% for the biomass of du

[EN] Remotely sensed data are increasingly used together with National Forest Inventory (NFI) data to improve the spatial precision of forest variable estimates. In this study, we combined data from the 4th Spanish National Forest Inventory (SNFI-4) and from the 2nd nationwide Airborne Laser Scanning (ALS) survey to develop predictive forest inventory variables (total over bark volume (V), basal area (G), and annual increase in total volume (IAVC)) and aboveground biomass (AGB) models for the eight major forest strata in the region of Extremadura that are included in the Spanish Forest Map (SFM). We generated maps at 25 m resolution by applying an area‐based approach (ABA) and 758 sample plots measured with good positional accuracy within the SNFI-4 in Extremadura (Spain). Inventory performance is mainly influenced by spatial scale and vegetation structure. Therefore, in this study, we conducted a comparative analysis of statistical inference methods that can characterize forest inventory variables and AGB uncertainty across multiple spatial scales and types of vegetation structure. Predictions at pixel level were used to produce county, provincial, and regional model-based estimates, which were then compared with design-based estimates at different scales for different types of forest. We developed and tested both methods for forested area (cover, 19,744.15 km2), one province (9126.78 km2), and two counties (1594.42 km2 and 2076.76 km2, respectively) in Extremadura. The resulting relative standard error (SE) for regional level forest type-specific model-based estimates of V, G, IAVC, and AGB ranged from 3.34%–14.46%, 3.22%–12.50%, 4.46%–16.67%, and 3.63%–12.58%, respectively. The performance of the model-based approach, as assessed by the relative SE, was similar to that of the design-based approach at regional and provincial levels. However, the precision of SNFI model-based estimates was higher than that of estimates based on only the plot observations in small a

[EN] The analysis of the diameter distribution is important for forest management since the knowledge of tree density and growing stock by diameter classes is essential to define management plans and to support operational decisions. The modeling of diameter distributions from airborne laser scanning (ALS) data has been performed through the two-parameterWeibull probability density function (PDF), but the more flexible PDF Johnson's SB has never been tested for this purpose until now. This study evaluated the performance of the Johnson's SB to predict the diameter distributions based on ALS data from two of the most common forest plantations in the northwest of the Iberian Peninsula (Eucalyptus globulus Labill. and Pinus radiata D. Don). The Weibull PDF was taken as a benchmark for the diameter distributions prediction and both PDFs were fitted with ALS data. The results show that the SB presented a comparable performance to the Weibull for both forest types. The SB presented a slightly better performance for the E. globulus, while theWeibull PDF had a small advantage when applied to the P. radiata data. The Johnson's SB PDF is more flexible but also more sensitive to possible errors arising from the higher number of stand variables needed for the estimation of the PDF parameters

[EN], Global Ecosystem Dynamics Investigation (GEDI) satellite mission is expanding the spatial bounds and temporal resolution of large-scale mapping applications. Integrating the recent GEDI data into Airborne Laser Scanning (ALS)-derived estimations represents a global opportunity to update and extend forest models based on area based approaches (ABA) considering temporal and spatial dynamics. This study evaluates the effect of combining ALS-based aboveground biomass (AGB) estimates with GEDI-derived models by using temporally coincident datasets. A gradient of forest ecosystems, distributed through 21,766 km2 in the province of Badajoz (Spain), with different species and structural complexity, was used to: (i) assess the accuracy of GEDI canopy height in five Mediterranean Ecosystems and (ii) develop GEDI-based AGB models when using ALS-derived AGB estimates at GEDI footprint level. In terms of Pearson’s correlation (r) and rRMSE, the agreement between ALS and GEDI statistics on canopy height was stronger in the denser and homogeneous coniferous forest of P. pinaster and P. pinea than in sparse Quercus-dominated forests. The GEDI-derived AGB models using relative height and vertical canopy metrics yielded a model efficiency (Mef) ranging from 0.31 to 0.46, with a RMSE ranging from 14.13 to 32.16 Mg/ha and rRMSE from 38.17 to 84.74%, at GEDI footprint level by forest type. The impact of forest structure confirmed previous studies achievements, since GEDI data showed higher uncertainty in highly multilayered forests. In general, GEDI-derived models (GEDI-like Level4A) underestimated AGB over lower and higher ALS-derived AGB intervals. The proposed models could also be used to monitor biomass stocks at large-scale by using GEDI footprint level in Mediterranean areas, especially in remote and hard-to-reach areas for forest inventory. The findings from this study serve to provide an initial evaluation of GEDI data for estimating AGB in Mediterranean forest

[EN] The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) provides an extraordinary opportunity to support global large-scale forest carbon mapping, but further research is needed in order to obtain wall-to-wall forest aboveground biomass (AGB) maps with this technology. The effects of vegetation structure on the performance of canopy height and AGB modeling using ICESat-2 photon-counting light detection and ranging (LiDAR) data in Mediterranean forest areas have not been previously studied in the literature. In this study, we combined recent ICESat-2 vegetation (ATL08) data, Airborne Laser Scanning (ALS)- and field-based estimates, and a multi-sensor earth observation composite for extrapolation of AGB estimates and AGB mapping. A diverse gradient of forest Mediterranean ecosystems, distributed over 19,744.15 km2 of forest area in the region of Extremadura (Spain), with different species and structural complexity forming 5 different forest types (3 Quercus spp. dominated and 2 Pinus spp. dominated forests), was used to (i) evaluate the precision of ICESat-2 canopy height estimations, (ii) develop ICESat-2-based AGB models, and (iii) generate a spatially continuous prediction of AGB by using data from the satellite missions Sentinel-1 (S1), Sentinel-2 (S2), Phased Array L-band Synthetic Aperture Radar (ALOS2/PALSAR2), and Shuttle Radar Topography Mission (SRTM). First, ALS- and ICESat-2-derived metrics that best described canopy height (p98 and rh98, respectively) were compared at the ATL08 segment level. Second, ALS-based AGB values were derived at the ATL08 segment scale. Third, ALS-based AGB estimates at the ICESat-2 segment level were used as dependent variables to fit ICESat-2-based AGB models. Fourth, a multi-sensor approach was then implemented to predict ICESat-2-derived AGB, by means of a Random Forest (RF) modeling technique, with predictors retrieved from S1, S2, ALOS2/PALSAR2, and SRTM. Finally, RF was used to generate wall-to-wall AGB maps that wer

[ES] Contar con una cartografía de hábitats actualizada y precisa es un aspecto clave a la hora de analizar y gestionar espacios naturales, por ello, la teledetección tiene un papel fundamental. En este caso el análisis se ha centrado en una parte de la Ría de Ortigueira y Ladrido (A Coruña), incluida en diversos instrumentos de protección debido a su relevancia ecológica y a la fragilidad de este tipo de ecosistemas. En este trabajo se plantea como objetivo principal realizar clasificaciones supervisadas empleando análisis orientado a objetos a partir de imágenes multiespectrales de dos sensores con diferentes características e información complementaria, en base a las categorías de hábitats establecidas en el sistema EUNIS (European Nature Information System). Posteriormente se analizarán los resultados obtenidos y las variables más representativas en cada caso. Los pasos seguidos han sido los siguientes: descarga y procesado de las imágenes e información complementaria, segmentación de la ortofotografía del PNOA (Plan Nacional de Ortofotografía Aérea) para utilizarla como punto de partida en ambos casos, preparación de la base de datos formada por las diferentes variables y sus métricas, cálculo de estadísticas zonales para cada objeto, realización de clasificaciones supervisadas mediante algoritmos de aprendizaje automático y validación de los resultados empleando diferentes estadísticos. Estos procesos se han realizado empleando una combinación de diferentes softwares, tanto comerciales como libres. Los resultados muestran mayor precisión global en la clasificación generada en base a las imágenes de WorldView 2 en comparación con la realizada con Sentinel 2. Además, en ambos casos se observa la importancia que presentan los índices de vegetación a la hora de caracterizar los diferentes hábitats