LiDAR remote sensing applied to forest resources assessment

Disponer de información precisa y actualizada de inventario forestal es una pieza clave para mejorar la gestión forestal sostenible y para proponer y evaluar políticas de conservación de bosques que permitan la reducción de emisiones de carbono debidas a la deforestación y degradación forestal (REDD). En este sentido, la tecnología LiDAR ha demostrado ser una herramienta perfecta para caracterizar y estimar de forma continua y en áreas extensas la estructura del bosque y las principales variables de inventario forestal. Variables como la biomasa, el número de pies, el volumen de madera, la altura dominante, el diámetro o la altura media son estimadas con una calidad comparable a los inventarios tradicionales de campo. La presente tesis se centra en analizar la aplicación de los denominados métodos de masa de inventario forestal con datos LIDAR bajo diferentes condiciones y características de masa forestal (bosque templados puros y mixtos) y utilizando diferentes bases de datos LiDAR (información proveniente de vuelo nacionales e información capturada de forma específica). Como consecuencia de lo anterior, se profundiza en la generación de inventarios forestales continuos con LiDAR en grandes áreas. Los métodos de masa se basan en la búsqueda de relaciones estadísticas entre variables predictoras derivadas de la nube de puntos LiDAR y las variables de inventario forestal medidas en campo con el objeto de generar una cartografía continua de inventario forestal. El rápido desarrollo de esta tecnología en los últimos años ha llevado a muchos países a implantar programas nacionales de captura de información LiDAR aerotransportada. Estos vuelos nacionales no están pensados ni diseñados para fines forestales por lo que es necesaria la evaluación de la validez de esta información LiDAR para la descripción de la estructura del bosque y la medición de variables forestales. Esta información podría suponer una drástica reducción de costes en la generación de información continua de alta resolución de inventario forestal. En el capítulo 2 se evalúa la estimación de variables forestales a partir de la información LiDAR capturada en el marco del Plan Nacional de Ortofotografía Aérea (PNOA-LiDAR) en España. Para ello se compara un vuelo específico diseñado para inventario forestal con la información de la misma zona capturada dentro del PNOA-LiDAR. El caso de estudio muestra cómo el ángulo de escaneo, la pendiente y orientación del terreno afectan de forma estadísticamente significativa, aunque con pequeñas diferencias, a la estimación de biomasa y variables de estructura forestal derivadas del LiDAR. La cobertura de copas resultó más afectada por estos factores que los percentiles de alturas. Considerando toda la zona de estudio, la estimación de la biomasa con ambas bases de datos no presentó diferencias estadísticamente significativas. Las simulaciones realizadas muestran que las diferencias medias en la estimación de biomasa entre un vuelo específico y el vuelo nacional podrán superar el 4% en áreas abruptas, con ángulos de escaneo altos y cuando la pendiente de la ladera no esté orientada hacia la línea de escaneo. En el capítulo 3 se desarrolla un estudio en masas mixtas y puras de pino silvestre y haya, con un enfoque multi-fuente empleando toda la información disponible (vuelos LiDAR nacionales de baja densidad de puntos, imágenes satelitales Landsat y parcelas permanentes del inventario forestal nacional español). Se concluye que este enfoque multi-fuente es adecuado para realizar inventarios forestales continuos de alta resolución en grandes superficies. Los errores obtenidos en la fase de ajuste y de validación de los modelos de área basimétrica y volumen son similares a los registrados por otros autores (usando un vuelo específico y parcelas de campo específicas). Se observan errores mayores en la variable número de pies que los encontrados en la literatura, que pueden ser explicados por la influencia de la metodología de parcelas de radio variable en esta variable. En los capítulos 4 y 5 se evalúan los métodos de masa para estimar biomasa y densidad de carbono en bosques tropicales. Para ello se trabaja con datos del Parque Nacional Volcán Poás (Costa Rica) en dos situaciones diferentes: i) se dispone de una cobertura completa LiDAR del área de estudio (capitulo 4) y ii) la cobertura LiDAR completa no es técnica o económicamente posible y se combina una cobertura incompleta de LiDAR con imágenes Landsat e información auxiliar para la estimación de biomasa y carbono (capitulo 5). En el capítulo 4 se valida un modelo LiDAR general de estimación de biomasa aérea en bosques tropicales y se compara con los resultados obtenidos con un modelo ajustado de forma específica para el área de estudio. Ambos modelos están basados en la variable altura media de copas (TCH por sus siglas en inglés) derivada del modelo digital LiDAR de altura de la vegetación. Los resultados en el área de estudio muestran que el modelo general es una alternativa fiable al ajuste de modelos específicos y que la biomasa aérea puede ser estimada en una nueva zona midiendo en campo únicamente la variable área basimétrica (BA). Para mejorar la aplicación de esta metodología es necesario definir en futuros trabajos procedimientos adecuados de medición de la variable área basimétrica en campo (localización, tamaño y forma de las parcelas de campo). La relación entre la altura media de copas del LiDAR y el área basimétrica (Coeficiente de Stock) obtenida en el área de estudio varía localmente. Por tanto es necesario contar con más información de campo para caracterizar la variabilidad del Coeficiente de Stock entre zonas de vida y si estrategias como la estratificación pueden reducir los errores en la estimación de biomasa y carbono en bosques tropicales. En el capítulo 5 se concluye que la combinación de una muestra sistemática de información LiDAR con una cobertura completa de imagen satelital de moderada resolución (e información auxiliar) es una alternativa efectiva para la realización de inventarios continuos en bosques tropicales. Esta metodología permite estimar altura de la vegetación, biomasa y carbono en grandes zonas donde la captura de una cobertura completa de LiDAR y la realización de un gran volumen de trabajo de campo es económica o/y técnicamente inviable. Las alternativas examinadas para la predicción de biomasa a partir de imágenes Landsat muestran una ligera disminución del coeficiente de determinación y un pequeño aumento del RMSE cuando la cobertura de LiDAR es reducida de forma considerable. Los resultados indican que la altura de la vegetación, la biomasa y la densidad de carbono pueden ser estimadas en bosques tropicales de forma adecuada usando coberturas de LIDAR bajas (entre el 5% y el 20% del área de estudio). ABSTRACT The availability of accurate and updated forest data is essential for improving sustainable forest management, promoting forest conservation policies and reducing carbon emissions from deforestation and forest degradation (REDD). In this sense, LiDAR technology proves to be a clear-cut tool for characterizing forest structure in large areas and assessing main forest-stand variables. Forest variables such as biomass, stem volume, basal area, mean diameter, mean height, dominant height, and stem number can be thus predicted with better or comparable quality than with costly traditional field inventories. In this thesis, it is analysed the potential of LiDAR technology for the estimation of plot-level forest variables under a range of conditions (conifer & broadleaf temperate forests and tropical forests) and different LiDAR capture characteristics (nationwide LiDAR information vs. specific forest LiDAR data). This study evaluates the application of LiDAR-based plot-level methods in large areas. These methods are based on statistical relationships between predictor variables (derived from airborne data) and field-measured variables to generate wall to wall forest inventories. The fast development of this technology in recent years has led to an increasing availability of national LiDAR datasets, usually developed for multiple purposes throughout an expanding number of countries and regions. The evaluation of the validity of nationwide LiDAR databases (not designed specifically for forest purposes) is needed and presents a great opportunity for substantially reducing the costs of forest inventories. In chapter 2, the suitability of Spanish nationwide LiDAR flight (PNOA) to estimate forest variables is analyzed and compared to a specifically forest designed LiDAR flight. This study case shows that scan angle, terrain slope and aspect significantly affect the assessment of most of the LiDAR-derived forest variables and biomass estimation. Especially, the estimation of canopy cover is more affected than height percentiles. Considering the entire study area, biomass estimations from both databases do not show significant differences. Simulations show that differences in biomass could be larger (more than 4%) only in particular situations, such as steep areas when the slopes are non-oriented towards the scan lines and the scan angles are larger than 15º. In chapter 3, a multi-source approach is developed, integrating available databases such as nationwide LiDAR flights, Landsat imagery and permanent field plots from SNFI, with good resultos in the generation of wall to wall forest inventories. Volume and basal area errors are similar to those obtained by other authors (using specific LiDAR flights and field plots) for the same species. Errors in the estimation of stem number are larger than literature values as a consequence of the great influence that variable-radius plots, as used in SNFI, have on this variable. In chapters 4 and 5 wall to wall plot-level methodologies to estimate aboveground biomass and carbon density in tropical forest are evaluated. The study area is located in the Poas Volcano National Park (Costa Rica) and two different situations are analyzed: i) available complete LiDAR coverage (chapter 4) and ii) a complete LiDAR coverage is not available and wall to wall estimation is carried out combining LiDAR, Landsat and ancillary data (chapter 5). In chapter 4, a general aboveground biomass plot-level LiDAR model for tropical forest (Asner & Mascaro, 2014) is validated and a specific model for the study area is fitted. Both LiDAR plot-level models are based on the top-of-canopy height (TCH) variable that is derived from the LiDAR digital canopy model. Results show that the pantropical plot-level LiDAR methodology is a reliable alternative to the development of specific models for tropical forests and thus, aboveground biomass in a new study area could be estimated by only measuring basal area (BA). Applying this methodology, the definition of precise BA field measurement procedures (e.g. location, size and shape of the field plots) is decisive to achieve reliable results in future studies. The relation between BA and TCH (Stocking Coefficient) obtained in our study area in Costa Rica varied locally. Therefore, more field work is needed for assessing Stocking Coefficient variations between different life zones and the influence of the stratification of the study areas in tropical forests on the reduction of uncertainty. In chapter 5, the combination of systematic LiDAR information sampling and full coverage Landsat imagery (and ancillary data) prove to be an effective alternative for forest inventories in tropical areas. This methodology allows estimating wall to wall vegetation height, biomass and carbon density in large areas where full LiDAR coverage and traditional field work are technically and/or economically unfeasible. Carbon density prediction using Landsat imaginery shows a slight decrease in the determination coefficient and an increase in RMSE when harshly decreasing LiDAR coverage area. Results indicate that feasible estimates of vegetation height, biomass and carbon density can be accomplished using low LiDAR coverage areas (between 5% and 20% of the total area) in tropical locations.

Geografía del carbono en alta resolución en bosque tropical amazónico del Ecuador mediante sensores aerotransportados

La estimación de la biomasa de la vegetación terrestre en bosque tropical no sólo es un área de investigación en rápida expansión, sino también es un tema de gran interés para reducir las emisiones de carbono asociadas a la deforestación y la degradación forestal (REDD+). Las estimaciones de densidad de carbono sobre el suelo (ACD) en base a inventarios de campo y datos provenientes de sensores aerotransportados, en especial con sensores LiDAR, han conducido a un progreso sustancial en el cartografiado a gran escala de las reservas de carbono forestal. Sin embargo, estos mapas de carbono tienen incertidumbres considerables, asociadas generalmente al proceso de calibración del modelo de regresión utilizado para producir los mapas. En esta tesis se establece una metodología para la calibración y validación de un modelo general de estimación de ACD usando LiDAR en un sector del Parque Nacional Yasuní en Ecuador. En el proceso de calibración del modelo se considera el tamaño y la ubicación de las parcelas, la influencia de la topografía y la distribución espacial de la biomasa. Para el análisis de los datos se utilizan técnicas geoestadísticas en combinación con variables geomorfométricas derivadas de datos LiDAR, y se propone un esquema de muestreo estratificado por posiciones topográficas (valle, ladera y cima). La validación del modelo general para toda la zona de estudio presentó valores de RMSE = 5.81 Mg C ha-1, R2 = 0.94 y sesgo = 0.59, mientras que, al considerar las posiciones topográficas, el modelo presentó valores de RMSE = 1.67 Mg C ha-1, R2 = 0.98 y sesgo = 0.23 para el valle; RMSE = 3.13 Mg C ha-1, R2 = 0.98 y sesgo = - 0.34 para la ladera; y RMSE = 2.33 Mg C ha-1, R2 = 0.97 y sesgo = 0.74 para la cima. Los resultados obtenidos demuestran que la metodología de muestreo estratificado por posiciones topográficas propuesto, permite calibrar de manera efectiva el modelo general con las estimaciones de ACD en campo, logrando reducir el RMSE y el sesgo. Los resultados muestran el potencial de los datos LiDAR para caracterizar la estructura vertical de la vegetación en un bosque altamente diverso, permitiendo realizar estimaciones precisas de ACD, y conocer patrones espaciales continuos de la distribución de la biomasa aérea y del contenido de carbono en la zona de estudio. ABSTRACT Estimating biomass of terrestrial vegetation in tropical forest is not only a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD+). The aboveground carbon density estimates (ACD) based on field inventories and airborne sensors, especially LiDAR sensors have led to a substantial progress in large-scale mapping of forest carbon stocks. However, these carbon maps have considerable uncertainties generally associated with the calibration of the regression model used to produce these maps. This thesis establishes a methodology for calibrating and validating a general ACD estimation model using LiDAR in Ecuador´s Yasuní National Park. The size and location of the plots are considered in the model calibration phase as well as the influence of topography and spatial distribution of biomass. Geostatistical analysis techniques are used in combination with geomorphometrics variables derived from LiDAR data, and then a stratified sampling scheme considering topographic positions (valley, slope and ridge) is proposed. The validation of the general model for the study area showed values of RMSE = 5.81 Mg C ha-1, R2 = 0.94 and bias = 0.59, while considering the topographical positions, the model showed values of RMSE = 1.67 Mg C ha-1, R2 = 0.98 and bias = 0.23 for the valley; RMSE = 3.13 Mg C ha-1, R2 = 0.98 and bias = - 0.34 for the slope; and RMSE = 2.33 Mg C ha-1, R2 = 0.97 and bias = 0.74 for the ridge. The results show that the stratified sampling methodology taking into account topographic positions, effectively calibrates the general model with field estimates of ACD, reducing RMSE and bias. The results show the potential of LiDAR data to characterize the vertical structure of vegetation in a highly diverse forest, allowing accurate estimates of ACD, and knowing continuous spatial patterns of biomass distribution and carbon stocks in the study area.

Physical properties and bulk organic geochemical results for sediments from DSDP Hole 96-619

The concentration and carbon isotopic composition (d13C) of sedimentary organic carbon (C_org), N/C ratios, and terrigenous and marine d13C_org endmembers form a basis from which to address problems of Late Quaternary glacial-interglacial climatic variability in a 208.7 m hydraulic piston core (DSDP 619) from the Pigmy Basin in the northern Gulf of Mexico. While interpretations of sedimentary d13C_org time series records are often not unique, paired analyses of d13C_org and N/C are consistent with the hypothesis that the C_org in the Pigmy Basin is a climatically determined mixture of C3-photosynthetic terrigenous and marine organic matter, confirming the earlier d13C_org model of Sackett (1964). A high resolution (~1.4-2.9 Ka/sample) d13C_org record shows that sedimentary organic carbon in interglacial oxygen isotope (sub)stages 1 and 5a-b are enriched in 13C (average +/-1 sigma values are -24.2+/-1.2? and -22.9+/-0.7? relative to PDB, respectively) while glacial isotope stage values 2 are relatively depleted (-25.6+/-0.5?). Concentrations of terrigenous and marine sedimentary organic carbon are calculated for the first time using d13C_org and C_org measurements, and empirically determined terrigenous and marine d13C_org endmembers. The net accumulation rate of terrigenous organic carbon is 4.3+/-2.6 times higher in isotope stages 2-4 than in (sub)stages 1 and 5a-b, recording higher erosion rates of terrigenous organic material in glacial times. The concentration and net accumulation rates of marine and terrigenous C_org suggest that the nutrient-bearing plume of the Mississippi River may have advanced and retreated across the Pigmy Basin as sea level fell and rose in response to glacial-interglacial sea level change.

Sedimentology, organic geochemistry, and stable isotopes of core PS2138-1

We studied variations in terrigenous (TOM) and marine organic matter (MOM) input in a sediment core on the northern Barents Sea margin over the last 30 ka. Using a multiproxy approach, we reconstructed processes controlling organic carbon deposition and investigated their paleoceanographic significance in the North Atlantic-Arctic Gateways. Variations in paleo-surface-water productivity are not documented in amount and composition of organic carbon. The highest level of MOM was deposited during 25-23 ka as a result of scavenging on fine-grained, reworked, and TOM-rich material released by the retreating Svalbard/Barents Sea ice sheet during the late Weichselian. A second peak of MOM is preserved because of sorptive protection by detrital and terrigenous organic matter, higher surface-water productivity due to permanent intrusion of Atlantic water, and high suspension load release by melting sea ice during 15.9-11.2 ka.

Lake sediments from Store Koldewey, Northeast Greenland

A 2.9 m long sedimentary record was studied from a small lake, here referred to as Duck Lake, located at 76°25'N, 18°45'W on Store Koldewey, an elongated island off the coast of Northeast Greenland. The sediments were investigated for their geophysical and biogeochemical characteristics, and for their fossil chironomid assemblages. Organic matter began to accumulate in the lake at 9.1 cal. kyr BP, which provides a minimum age for the deglaciation of the basin. Although the early to mid-Holocene is known as a thermal maximum in East Greenland, organic matter accumulation in the lake remained low during the early Holocene, likely due to late plant immigration and lack of nutrient availability. Organic matter accumulation increased during the middle and late Holocene, when temperatures in East Greenland gradually decreased. Enhanced soil formation probably led to higher nutrient availability and increased production in the lake. Chironomids are abundant throughout the record after 9.1 cal. kyr BP and seem to react sensitively to changes in temperature and nutrient availability. It is concluded that relative temperature reconstructions based on biogeochemical data have to be regarded critically, particularly in the period shortly after deglaciation when nutrient availability was low. Chironomids may be a suitable tool for climatic reconstructions even in those high arctic environments. However, a better understanding of the ecology of chironomids under these extreme conditions is needed.

Geochemistry of sediment core PS2456-4

Sediment core PS2458 from the Laptev Sea continental margin (983-m water depth) stems from a position close to the paleoriver mouth of Lena and Yana rivers. It was dated by AMS-14C and analyzed in high resolution for oxygen isotopes of planktic foraminifers. Except the uppermost 100 cm and possibly the lowermost meter of the 8-m-long core, the sediments were deposited during the last deglaciation (14.5-8.0 cal-ka). According to 210Pb data, the uppermost 100 cm represents only the last 200 years. Planktic foraminifers are present throughout the dated deglacial interval, with the exception of a short time after ca. 13 cal-ka. Taking into account the global "ice volume effect" on the oxygen isotopic composition of the foraminifers, the isotopic record is considered to reflect salinity changes which were influenced by variable freshwater runoff and a growing marine influence during the postglacial transgression of the Laptev Sea shelf. The most conspicuous feature in the isotopic record is an outstanding peak dated to ca. 13 cal-ka. It is proposed that it represents a rapid outburst of large amounts of freshwater, possibly from an ice-dammed lake in the hinterland. Possible correlations to the onset of the cool Younger Dryas event in the northern hemisphere are discussed.

Sedimentology of the southern Bellingshausen Sea

A major trough ('Belgica Trough') eroded by a palaeo-ice stream crosses the continental shelf of the southern Bellingshausen Sea (West Antarctica) and is associated with a trough mouth fan ('Belgica TMF') on the adjacent continental slope. Previous marine geophysical and geological studies investigated the bathymetry and geomorphology of Belgica Trough and Belgica TMF, erosional and depositional processes associated with bedform formation, and the temporal and spatial changes in clay mineral provenance of subglacial and glaciomarine sediments. Here, we present multi-proxy data from sediment cores recovered from the shelf and uppermost slope in the southern Bellingshausen Sea and reconstruct the ice-sheet history since the last glacial maximum (LGM) in this poorly studied area of West Antarctica. We combined new data (physical properties, sedimentary structures, geochemical and grain-size data) with published data (shear strength, clay mineral assemblages) to refine a previous facies classification for the sediments. The multi-proxy approach allowed us to distinguish four main facies types and to assign them to the following depositional settings: 1) subglacial, 2) proximal grounding-line, 3) distal sub-ice shelf/subsea ice, and 4) seasonal open-marine. In the seasonal open-marine facies we found evidence for episodic current-induced winnowing of near-seabed sediments on the middle to outer shelf and at the uppermost slope during the late Holocene. In addition, we obtained data on excess 210Pb activity at three core sites and 44 AMS 14C dates from the acid-insoluble fraction of organic matter (AIO) and calcareous (micro-)fossils, respectively, at 12 sites. These chronological data enabled us to reconstruct, for the first time, the timing of the last advance and retreat of the West Antarctic Ice Sheet (WAIS) and the Antarctic Peninsula Ice Sheet (APIS) in the southern Bellingshausen Sea. We used the down-core variability in sediment provenance inferred from clay mineral changes to identify the most reliable AIO 14C ages for ice-sheet retreat. The palaeo-ice stream advanced through Belgica Trough after ~36.0 corrected 14C ka before present (B.P.). It retreated from the outer shelf at ~25.5 ka B.P., the middle shelf at ~19.8 ka B.P., the inner shelf in Eltanin Bay at ~12.3 ka B.P., and the inner shelf in Ronne Entrance at ~6.3 ka B.P.. The retreat of the WAIS and APIS occurred slowly and stepwise, and may still be in progress. This dynamical ice-sheet behaviour has to be taken into account for the interpretation of recent and the prediction of future mass-balance changes in the study area. The glacial history of the southern Bellingshausen Sea is unique when compared to other regions in West Antarctica, but some open questions regarding its chronology need to be addressed by future work.