Assesment of biomass and carbon dynamics in pine forests of the Spanish central range: A remote sensing approach

Forests play a dynamic role in the terrestrial carbon (C) budget, by means of the biomass stock and C fluxes involved in photosynthesis and respiration. Remote sensing in combination with data analysis constitute a practical means for evaluation of forest implications in the carbon cycle, providing spatially explicit estimations of the amount, quality, and spatio-temporal dynamics of biomass and C stocks. Medium and high spatial resolution optical data from satellite-borne sensors were employed, supported by field measures, to investigate the carbon role of Mediterranean pines in the Central Range of Spain during a 25 year period (1984-2009). The location, extent, and distribution of pine forests were characterized, and spatial changes occurred in three sub-periods were evaluated. Capitalizing on temporal series of spectral data from Landsat sensors, novel techniques for processing and data analysis were developed to identify successional processes at the landscape level, and to characterize carbon stocking condition locally, enabling simultaneous characterization of trends and patterns of change. High spatial resolution data captured by the commercial satellite QuickBird-2 were employed to model structural attributes at the stand level, and to explore forest structural diversity

Caractérisation spatio-temporelle de la dynamique des trouées et de la réponse de la forêt boréale à l'aide de données lidar multi-temporelles

La forêt boréale est un écosystème hétérogène et dynamique façonné par les perturbations naturelles comme les feux, les épidémies d'insectes, le vent et la régénération. La dynamique des trouées joue un rôle important dans la dynamique forestière parce qu'elle influence le recrutement de nouveaux individus au sein de la canopée et la croissance de la végétation avoisinante par une augmentation des ressources. Bien que l'importance des trouées en forêt boréale fut reconnue, les connaissances nécessaires à la compréhension des relations entre le régime de trouées et la dynamique forestière, en particulier sur la croissance, sont souvent manquantes. Il est difficile d'observer et de mesurer extensivement la dynamique des trouées ou les changements de la canopée simultanément dans le temps et l'espace avec des données terrain ou des images bidimensionnelles (photos aériennes,...) et ce particulièrement dans des systèmes complexes comme les forêts ouvertes ou morcelées. De plus, la plupart des recherches furent menées en s'appuyant sur seulement quelques trouées représentatives bien que les interactions entre les trouées et la structure forestière furent rarement étudiées de manière conjointe. Le lidar est un système qui balaye la surface terrestre avec des faisceaux laser permettant d'obtenir une image dense de points en trois dimensions montrant les aspects structuraux de la végétation et de la topographie sous-jacente d'une grande superficie. Nous avons formulé l'hypothèse que lorsque les retours lidar de tirs quasi-verticaux sont denses et précis, ils permettent une interprétation de la géométrie des trouées et la comparaison de celles-ci dans le temps, ce qui nous informe à propos de leur influence sur la dynamique forestière. De plus, les mesures linéaires prises à différents moments dans le temps permettraient de donner une estimation fiable de la croissance. Ainsi, l'objectif de cette recherche doctorale était de développer des méthodes et d'accroître nos connaissances sur le régime de trouées et sa dynamique, et de déterminer comment la forêt boréale mixte répond à ces perturbations en termes de croissance et de mortalité à l'échelle locale. Un autre objectif était aussi de comprendre le rôle à court terme des ouvertures de la canopée dans un peuplement et la dynamique successionelle. Ces processus écologiques furent étudiés en reconstituant la hauteur de la surface de la canopée de la forêt boréale par l'utilisation de données lidar prises. en 1998, 2003 (et 2007), mais sans spécifications d'études similaires. L'aire d'étude de 6 km² dans la Forêt d'Enseignement et de Recherche du Lac Duparquet, Québec, Canada, était suffisamment grande pour capter la variabilité de la structure de la canopée et de la réponse de la forêt à travers une gamme de peuplements à différents stades de développement. Les recherches menées lors de cette étude ont révélé que les données lidar multi-temporelles peuvent être utilisées a priori dans toute étude de télédétection des changements, dont l'optimisation de la résolution des matrices et le choix de l'interpolation des algorithmes sont essentiels (pour les surfaces végétales et terrestres) afin d'obtenir des limites précises des trouées. Nous avons trouvé qu'une technique basée sur la croissance de régions appliquée à une surface lidar peut être utilisée pour délimiter les trouées avec une géométrie précise et pour éliminer les espaces entre les arbres représentant de fausses trouées. La comparaison de trouées avec leur délimitation Iidar le long de transects linéaires de 980 mètres montre une forte correspondance de 96,5%. Le lidar a été utilisé avec succès pour délimiter des trouées simples (un seul arbre) ou multiples (plus de 5 m²). En utilisant la combinaison de séries temporelles de trouées dérivées du lidar, nous avons développé des méthodes afin de délimiter les divers types d'évènements de dynamique des trouées: l'occurrence aléatoire de trouées, l'expansion de trouées et la fermeture de trouées, tant par la croissance latérale que la régénération. La technique proposée pour identifier les hauteurs variées arbre/gaulis sur une image lidar d'un Modèle de Hauteur de Couvert (MHC) a montré près de 75 % de correspondance avec les localisations photogrammétriques. Les taux de croissance libre suggérés basés sur les donnés lidar brutes après l'élimination des sources possibles d'erreur furent utilisés subséquemment pour des techniques statistiques afin de quantifier les réponses de croissance en hauteur qui ont été trouvées afin de faire varier la localisation spatiale en respect de la bordure de la trouée. À partir de la combinaison de donnés de plusieurs groupes d'espèces (de conifères et décidues) interprétée à partir d'images à haute résolution avec des données structurales lidar nous avons estimé les patrons de croissance en hauteur des différents groupes arbres/gaulis pour plusieurs contextes de voisinage. Les résultats on montré que la forêt boréale mixte autour du lac Duparquet est un système hautement dynamique, où la perturbation de la canopée joue un rôle important même pour une courte période de temps. La nouvelle estimation du taux de formation des trouées était de 0,6 %, ce qui correspond à une rotation de 182 ans pour cette forêt. Les résultats ont montré aussi que les arbres en périphérie des trouées étaient plus vulnérables à la mortalité que ceux à l'intérieur du couvert, résultant en un élargissement de la trouée. Nos résultats confirment que tant la croissance latérale que la croissance en hauteur de la régénération contribuent à la fermeture de la canopée à un taux annuel de 1,2 %. Des évidences ont aussi montré que les trouées de conifères et de feuillus ont des croissances latérales (moyenne de 22 cm/an) et verticales similaires sans tenir compte de leur localisation et leur hauteur initiale. La croissance en hauteur de tous les gaulis était fortement positive selon le type d'évènement et la superficie de la trouée. Les résultats suggèrent que la croissance des gaulis de conifères et de feuillus atteint son taux de croissance maximal à des distances respectives se situant entre 0,5 et 2 m et 1,5 et 4 m à partir de la bordure d'une trouée et pour des ouvertures de moins de 800 m² et 250 m² respectivement. Les effets des trouées sur la croissance en hauteur d'une forêt intacte se faisaient sentir à des distance allant jusqu'à à 30 m et 20 m des trouées, respectivement pour les feuillus et les conifères. Des analyses fines de l'ouverture de la canopée montrent que les peuplements à différents stades de développement sont hautement dynamiques et ne peuvent systématiquement suivre les mêmes patrons successionels. Globalement, la forêt est presqu'à l'équilibre compositionnel avec une faible augmentation de feuillus, principalement dû à la régénération de type infilling plutôt qu'une transition successionelle de conifères tolérants à l'ombre. Les trouées sont importantes pour le maintien des feuillus puisque le remplacement en sous-couvert est vital pour certains résineux. L'étude à démontré également que la dernière épidémie de tordeuse des bourgeons de l'épinette qui s'est terminée il y a 16 ans continue d'affecter de vieux peuplements résineux qui présentent toujours un haut taux de mortalité. Les résultats obtenus démontrent que lidar est un excellent outil pour acquérir des détails rapidement sur les dynamiques spatialement extensives et à court terme des trouées de structures complexes en forêt boréale. Les évidences de cette recherche peuvent servir tant à l'écologie, la sylviculture, l'aménagement forestier et aux spécialistes lidar. Ces idées ajoutent une nouvelle dimension à notre compréhension du rôle des petites perturbations et auront une implication directe pour les aménagistes forestiers en quête d'un aménagement forestier écologique et du maintien des forêts mixtes. ______________________________________________________________________________ MOTS-CLÉS DE L’AUTEUR : Perturbation naturelle, Dynamique forestière, Dynamique des trouées, Croissances latérales, Régénération, Succession, Lidar à retours discrets, Grande superficie, Localisation des arbres individuels, Croissance en hauteur

Coastal benthic habitat mapping and monitoring by integrating aerial and water surface low-cost drones

Accurate data on community structure is a priority issue in studying coastal habitats facing human pressures. The recent development of remote sensing tools has offered a ground-breaking way to collect ecological information at a very fine scale, especially using low-cost aerial photogrammetry. Although coastal mapping is carried out using Unmanned Aerial Vehicles (UAVs or drones), they can provide limited information regarding underwater benthic habitats. To achieve a precise characterisation of underwater habitat types and species assemblages, new imagery acquisition instruments become necessary to support accurate mapping programmes. Therefore, this study aims to evaluate an integrated approach based on Structure from Motion (SfM) photogrammetric acquisition using low-cost Unmanned Aerial (UAV) and Surface (USV) Vehicles to finely map shallow benthic communities, which determine the high complexity of coastal environments. The photogrammetric outputs, including both UAV-based high (sub-meter) and USV-based ultra-high (sub-centimetre) raster products such as orthophoto mosaics and Digital Surface Models (DSMs), were classified using Object-Based Image Analysis (OBIA) approach. The application of a supervised learning method based on Support Vector Machines (SVM) classification resulted in good overall classification accuracies > 70%, proving to be a practical and feasible tool for analysing both aerial and underwater ultra-high spatial resolution imagery. The detected seabed cover classes included above and below-water key coastal features of ecological interest such as seagrass beds, “banquettes” deposits and hard bottoms. Using USV-based imagery can considerably improve the identification of specific organisms with a critical role in benthic communities, such as photophilous macroalgal beds. We conclude that the integrated use of low-cost unmanned aerial and surface vehicles and GIS processing is an effective strategy for allowing fully remote detailed data on shallow water benthic communities

Very High Resolution (VHR) Satellite Imagery: Processing and Applications

Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing

A Study of African Savanna Vegetation Structure, Patterning, and Change

African savannas cover roughly half of the continent, are home to a great diversity of wildlife, and provide ecosystem services to large populations. Savannas showcase a great diversity in vegetation structure, resulting from variation in climatic, edaphic, topographic, and biological factors. Fires play a large role as savannas are the most frequently burned ecosystems on Earth. To study how savanna vegetation structure shifts with environmental factors, it is necessary to gather site data covering the full gradient of climatic and edaphic conditions. Several earlier studies have used coarse resolution satellite remote sensing data to study variation in woody cover. These woody cover estimates have limited accuracy in drylands where the woody component is relatively small, and the data cannot reveal more detailed information on the vegetation structure. We therefore know little about how other structural components, tree densities, crown sizes, and the spatial pattern of woody plants, vary across environmental gradients. This thesis aimed to examine how woody vegetation structure and change in woody cover vary with environmental conditions. The analyses depended on access to very high spatial resolution (\u3c1 \u3em) satellite imagery from sites spread across African savannas. The high resolution data combined with a crown delineation method enabled me to estimate variation in tree densities, mean crown size and the level of aggregation among woody plants. With overlapping older and newer imagery at most of the sites, I was also able to estimate change in woody cover over a 10-year period. I found that higher woody plant aggregation is associated with drier climates, high rainfall variability, and fine-textured soils. These same factors were also indicative of the areas where highly organized periodic vegetation patterns were found. The study also found that observed increases in woody cover across the rainfall gradient is more a result of increasing crown sizes than variation in tree density. The analysis of woody cover change found a mean increase of 0.25 % per year, indicating an ongoing trend of woody encroachment. I could not attribute this trend to any of the investigated environmental factors and it may result from higher atmospheric CO₂ concentrations, which has been proposed in other studies. The most influential predictor of woody cover change in the analysis was the difference between potential woody cover and initial woody cover, which highlights the role of competition for water and density dependent regulation when studying encroachment rates. The second most important predictor was fire frequency. To better understand and explain the dominant ecosystem processes controlling savanna vegetation structure, I constructed a spatially explicit model that simulates the growth of herbaceous and woody vegetation in a landscape. The model reproduced several of the trends in woody vegetation structure earlier found in the remote sensing analysis. These include how tree densities and crowns sizes respond differently to increases in precipitation along the full rainfall range, and the factors controlling the spatial pattern of trees in a landscape

Spatial and Spectral Separability of Grasslands in the inner Turku Archipelago using Landsat Thematic Mapper Satellite Imagery

The present study investigates the spatial and spectral discrimination potential for grassland patches in the inner Turku Archipelago using Landsat Thematic Mapper satellite imagery. The spatial discrimination potential was computed through overlay analysis using official grassland parcel data and a hypothetical 30 m resolution satellite image capturing the site. It found that Landsat TM imagery’s ability to retrieve pure or near-pure pixels (90% purity or more) from grassland patches smaller than 1 hectare was limited to 13% success, compared to 52% success when upscaling the resolution to 10 x 10 m pixel size. Additionally, the perimeter/area patch metric is proposed as a predictor for the suitability of the spatial resolution of input imagery. Regression analysis showed that there is a strong negative correlation between a patch’s perimeter/area ratio and its pure pixel potential. The study goes on to characterise the spectral response and discrimination potential for the five main grassland types occurring in the study area: recreational grassland, traditional pasture, modern pasture, fodder production grassland and overgrown grassland. This was done through the construction of spectral response curves, a coincident spectral plot and a contingency matrix as well as by calculating the transformed divergence for the spectral signatures, all based on training samples from the TM imagery. Substantial differences in spectral discrimination potential between imagery from the beginning of the growing season and the middle of summer were found. This is because the spectral responses for these five grassland types converge as the peak of the growing season draws nearer. Recreational grassland shows a consistent discrimination advantage over other grassland types, whereas modern pasture is most easily confused. Traditional pasture land, perhaps the most biologically valuable grassland type, can be spectrally discriminated from other grassland types with satisfactory success rates provided early growing season imagery is used.Siirretty Doriast

Proceedings of the 6th International Workshop of the EARSeL Special Interest Group on Forest Fires Advances in Remote Sensing and GIS Applications in Forest Fire Management Towards an Operational Use of Remote Sensing in Forest Fire Management

During the last two decades, interest in forest fire research has grown steadily, as more and more local and global impacts of burning are being identified. The definition of fire regimes as well as the identification of factors explaining spatial and temporal variations in these fire characteristics are recently hot fields of research. Changes in these fire regimes have important social and ecological implications. Whether these changes are mainly caused by land use or climate warming, greater efforts are demanded to manage forest fires at different temporal and spatial scales. The European Association of Remote Sensing Laboratories (EARSeL)’s Special Interest Group (SIG) on Forest Fires was created in 1995, following the initiative of several researchers studying Mediterranean fires in Europe. It has promoted five technical meetings and several specialised publications since then, and represents one of the most active groups within the EARSeL. The SIG has tried to foster interaction among scientists and managers who are interested in using remote sensing data and techniques to improve the traditional methods of fire risk estimation and the assessment of fire effect. The aim of the 6th international workshop is to analyze the operational use of remote sensing in forest fire management, bringing together scientists and fire managers to promote the development of methods that may better serve the operational community. This idea clearly links with international programmes of a similar scope, such as the Global Monitoring for Environment and Security (GMES) and the Global Observation of Forest Cover/Land Dynamics (GOFC-GOLD) who, together with the Joint Research Center of the European Union sponsor this event. Finally, I would like to thank the local organisers for the considerable lengths they have gone to in order to put this material together, and take care of all the details that the organization of this event requires.JRC.H.3-Global environement monitorin

Red squirrel habitat mapping using remote sensing

The native Eurasian red squirrel is considered endangered in the UK and is under strict legal protection. Long-term management of its habitat is a key goal of the UK conservation strategy. Current selection criteria of reserves and subsequent management mainly consider species composition and food availability. However, there exists a critical gap in understanding and quantifying the relationship between squirrel abundance, their habitat use and forest structural characteristics. This has partly resulted from the limited availability of structural data along with cost-efficient data collection methods. This study investigated the relationship between squirrel feeding activity and structural characteristics of Scots pine forests. Field data were collected from two study areas: Abernethy and Aberfoyle Forests. Canopy closure, diameter at breast height, height and number of trees were measured in 56 plots. Abundance of squirrel feeding signs was used as an index of habitat use. A GLM was used to model the response of cones stripped by squirrels in relation to the field collected structural variables. Results show that forest structural characteristics are significant predictors of feeding sign presence, with canopy closure, number of trees and tree height explaining 43% of the variation in stripped cones. The GLM was also implemented using LiDAR data to assess at wider scales the number of cones stripped by squirrels. The use of remote sensing -in particular Light Detection and Ranging (LiDAR) - enables cost efficient assessments of forest structure at large scales and can be used to retrieve the three variables explored in this study; canopy cover, tree height and number of trees, that relate to red squirrel feeding behaviour. Correlation between field-predicted and LiDAR-predicted number of stripped cones was performed to assess LiDAR-based model performance. LiDAR data acquired at Aberfoyle and Abernethy Forests had different characteristics (in particular pulse density), which influences the accuracy of LiDAR derived metrics. Therefore correlations between field predicted and LiDAR predicted number of cones (LSC) were assessed for each study area separately. Strong correlations (rs=0.59 for Abernethy and 0.54 for Aberfoyle) suggest that LiDAR-based model performed relatively well over the study areas. The LiDAR-based model was not expected to provide absolute numbers of cones stripped by squirrels but a relative measure of habitat use. This can be interpreted as different levels of habitat suitability for red squirrels. LiDAR-based GLM maps were classified into three levels of suitability: unsuitable (LSC = 0), Low (LSC =10). These thresholds were defined based on expert knowledge. Such a classification of habitat suitability allows for further differentiation of habitat quality for red squirrels and therefore for a refined estimation of the carrying capacity that was used to inform population viability analysis (PVA) at Abernethy Forest. PVA assists the evaluation of the probability of a species population to become extinct over a specified period of time, given a set of data on environmental conditions and species characteristics. In this study, two scenarios were modelled in a PVA package (VORTEX). For the first scenario (Basic) carrying capacity was calculated for the whole forest, while for the second scenario (LiDAR) only Medium-to-High suitable patches were considered. Results suggest a higher probability of extinction for the LiDAR scenario (74%) than for the Basic scenario (55%). Overall the findings of this study highlight 1) the importance of considering forest structure when managing habitat for squirrel conservation and 2) the usefulness of LiDAR remote sensing as a tool to assist red squirrel, and potentially other species, habitat management