Optimización de la Exactitud Geométrica al Integrar Diversas Fuentes de Datos en Proyectos de Inventario Forestal Basados en Escaneo Laser Aerotransportado=Optimizing Geometric Accuracy in Data Source Integration for Airborne Laser Scanning-based Forest Inventory Projects

La mayoría de las aplicaciones forestales del escaneo laser aerotransportado (ALS, del inglés airborne laser scanning) requieren la integración y uso simultaneo de diversas fuentes de datos, con el propósito de conseguir diversos objetivos. Los proyectos basados en sensores remotos normalmente consisten en aumentar la escala de estudio progresivamente a lo largo de varias fases de fusión de datos: desde la información más detallada obtenida sobre un área limitada (la parcela de campo), hasta una respuesta general de la cubierta forestal detectada a distancia de forma más incierta pero cubriendo un área mucho más amplia (la extensión cubierta por el vuelo o el satélite). Todas las fuentes de datos necesitan en ultimo termino basarse en las tecnologías de sistemas de navegación global por satélite (GNSS, del inglés global navigation satellite systems), las cuales son especialmente erróneas al operar por debajo del dosel forestal. Otras etapas adicionales de procesamiento, como la ortorectificación, también pueden verse afectadas por la presencia de vegetación, deteriorando la exactitud de las coordenadas de referencia de las imágenes ópticas. Todos estos errores introducen ruido en los modelos, ya que los predictores se desplazan de la posición real donde se sitúa su variable respuesta. El grado por el que las estimaciones forestales se ven afectadas depende de la dispersión espacial de las variables involucradas, y también de la escala utilizada en cada caso. Esta tesis revisa las fuentes de error posicional que pueden afectar a los diversos datos de entrada involucrados en un proyecto de inventario forestal basado en teledetección ALS, y como las propiedades del dosel forestal en sí afecta a su magnitud, aconsejando en consecuencia métodos para su reducción. También se incluye una discusión sobre las formas más apropiadas de medir exactitud y precisión en cada caso, y como los errores de posicionamiento de hecho afectan a la calidad de las estimaciones, con vistas a una planificación eficiente de la adquisición de los datos. La optimización final en el posicionamiento GNSS y de la radiometría del sensor óptico permitió detectar la importancia de este ultimo en la predicción de la desidad relativa de un bosque monoespecífico de Pinus sylvestris L. ABSTRACT Most forestry applications of airborne laser scanning (ALS) require the integration and simultaneous use of various data sources, pursuing a variety of different objectives. Projects based on remotely-sensed data generally consist in upscaling data fusion stages: from the most detailed information obtained for a limited area (field plot) to a more uncertain forest response sensed over a larger extent (airborne and satellite swath). All data sources ultimately rely on global navigation satellite systems (GNSS), which are especially error-prone when operating under forest canopies. Other additional processing stages, such as orthorectification, may as well be affected by vegetation, hence deteriorating the accuracy of optical imagery’s reference coordinates. These errors introduce noise to the models, as predictors displace from their corresponding response. The degree to which forest estimations are affected depends on the spatial dispersion of the variables involved and the scale used. This thesis reviews the sources of positioning errors which may affect the different inputs involved in an ALS-assisted forest inventory project, and how the properties of the forest canopy itself affects their magnitude, advising on methods for diminishing them. It is also discussed how accuracy should be assessed, and how positioning errors actually affect forest estimation, toward a cost-efficient planning for data acquisition. The final optimization in positioning the GNSS and optical image allowed to detect the importance of the latter in predicting relative density in a monospecific Pinus sylvestris L. forest.

An estimate of biometric parameters in eucalyptus clone plantations in Southern Bahia: an application of the airborne laser scanning (ALS) technology

The application of airborne laser scanning (ALS) technologies in forest inventories has shown great potential to improve the efficiency of forest planning activities. Precise estimates, fast assessment and relatively low complexity can explain the good results in terms of efficiency. The evolution of GPS and inertial measurement technologies, as well as the observed lower assessment costs when these technologies are applied to large scale studies, can explain the increasing dissemination of ALS technologies. The observed good quality of results can be expressed by estimates of volumes and basal area with estimated error below the level of 8.4%, depending on the size of sampled area, the quantity of laser pulses per square meter and the number of control plots. This paper analyzes the potential of an ALS assessment to produce certain forest inventory statistics in plantations of cloned Eucalyptus spp with precision equal of superior to conventional methods. The statistics of interest in this case were: volume, basal area, mean height and dominant trees mean height. The ALS flight for data assessment covered two strips of approximately 2 by 20 Km, in which clouds of points were sampled in circular plots with a radius of 13 m. Plots were sampled in different parts of the strips to cover different stand ages. The clouds of points generated by the ALS assessment: overall height mean, standard error, five percentiles (height under which we can find 10%, 30%, 50%,70% and 90% of the ALS points above ground level in the cloud), and density of points above ground level in each percentile were calculated. The ALS statistics were used in regression models to estimate mean diameter, mean height, mean height of dominant trees, basal area and volume. Conventional forest inventory sample plots provided real data. For volume, an exploratory assessment involving different combinations of ALS statistics allowed for the definition of the most promising relationships and fitting tests based on well known forest biometric models. The models based on ALS statistics that produced the best results involved: the 30% percentile to estimate mean diameter (R(2)=0,88 and MQE%=0,0004); the 10% and 90% percentiles to estimate mean height (R(2)=0,94 and MQE%=0,0003); the 90% percentile to estimate dominant height (R(2)=0,96 and MQE%=0,0003); the 10% percentile and mean height of ALS points to estimate basal area (R(2)=0,92 and MQE%=0,0016); and, to estimate volume, age and the 30% and 90% percentiles (R(2)=0,95 MQE%=0,002). Among the tested forest biometric models, the best fits were provided by the modified Schumacher using age and the 90% percentile, modified Clutter using age, mean height of ALS points and the 70% percentile, and modified Buckman using age, mean height of ALS points and the 10% percentile.

Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

Canonical Correlation Analysis for Interpreting Airborne Laser Scanning Metrics along the Lorenz Curve of Tree Size Inequality

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Airborne Laser Scanning and the Archaeological Interpretation of Ireland’s First World War Landscape”:The Case Study of Randalstown Training Camp

The training of Irish soldiers for service in the British Army during the First World War required the establishment of training camps across the island, such as at Shane’s Castle Estate, close to Randalstown in County Antrim, Northern Ireland. The camp saw active use from 1914 to 1918 but after the war it was demilitarised and returned to use as farmland. Archaeological investigations have revealed that earthwork traces of the camp can still be identified in the modern landscape. Comparison of a map of the camp from 1915, Airborne Laser Scanning data and aerial photographs has enabled the footprint of the camp to be re-established, while also helping to identify the location of specific elements such as the remains of barrack huts, stores, mess halls and officers’ quarters.

Use of airborne laser scanner data in demanding forest conditions

Most of the applications of airborne laser scanner data to forestry require that the point cloud be normalized, i.e., each point represents height from the ground instead of elevation. To normalize the point cloud, a digital terrain model (DTM), which is derived from the ground returns in the point cloud, is employed. Unfortunately, extracting accurate DTMs from airborne laser scanner data is a challenging task, especially in tropical forests where the canopy is normally very thick (partially closed), leading to a situation in which only a limited number of laser pulses reach the ground. Therefore, robust algorithms for extracting accurate DTMs in low-ground-point-densitysituations are needed in order to realize the full potential of airborne laser scanner data to forestry. The objective of this thesis is to develop algorithms for processing airborne laser scanner data in order to: (1) extract DTMs in demanding forest conditions (complex terrain and low number of ground points) for applications in forestry; (2) estimate canopy base height (CBH) for forest fire behavior modeling; and (3) assess the robustness of LiDAR-based high-resolution biomass estimation models against different field plot designs. Here, the aim is to find out if field plot data gathered by professional foresters can be combined with field plot data gathered by professionally trained community foresters and used in LiDAR-based high-resolution biomass estimation modeling without affecting prediction performance. The question of interest in this case is whether or not the local forest communities can achieve the level technical proficiency required for accurate forest monitoring. The algorithms for extracting DTMs from LiDAR point clouds presented in this thesis address the challenges of extracting DTMs in low-ground-point situations and in complex terrain while the algorithm for CBH estimation addresses the challenge of variations in the distribution of points in the LiDAR point cloud caused by things like variations in tree species and season of data acquisition. These algorithms are adaptive (with respect to point cloud characteristics) and exhibit a high degree of tolerance to variations in the density and distribution of points in the LiDAR point cloud. Results of comparison with existing DTM extraction algorithms showed that DTM extraction algorithms proposed in this thesis performed better with respect to accuracy of estimating tree heights from airborne laser scanner data. On the other hand, the proposed DTM extraction algorithms, being mostly based on trend surface interpolation, can not retain small artifacts in the terrain (e.g., bumps, small hills and depressions). Therefore, the DTMs generated by these algorithms are only suitable for forestry applications where the primary objective is to estimate tree heights from normalized airborne laser scanner data. On the other hand, the algorithm for estimating CBH proposed in this thesis is based on the idea of moving voxel in which gaps (openings in the canopy) which act as fuel breaks are located and their height is estimated. Test results showed a slight improvement in CBH estimation accuracy over existing CBH estimation methods which are based on height percentiles in the airborne laser scanner data. However, being based on the idea of moving voxel, this algorithm has one main advantage over existing CBH estimation methods in the context of forest fire modeling: it has great potential in providing information about vertical fuel continuity. This information can be used to create vertical fuel continuity maps which can provide more realistic information on the risk of crown fires compared to CBH.

Predição de sombras de edifícios sobre vias urbanas com base em modelos digitais de elevações e dados de imagens aéreas de alta resolução

This research presents a methodology for prediction of building shadows cast on urban roads existing on high-resolution aerial imagery. Shadow elements can be used in the modeling of contextual information, whose use has become more and more common in image analysis complex processes. The proposed methodology consists in three sequential steps. First, the building roof contours are manually extracted from an intensity image generated by the transformation of a digital elevation model (DEM) obtained from airborne laser scanning data. In similarly, the roadside contours are extracted, now from the radiometric information of the laser scanning data. Second, the roof contour polygons are projected onto the adjacent roads by using the parallel projection straight lines, whose directions are computed from the solar ephemeris, which depends on the aerial image acquisition time. Finally, parts of shadow polygons that are free from building perspective obstructions are determined, given rise to new shadow polygons. The results obtained in the experimental evaluation of the methodology showed that the method works properly, since it allowed the prediction of shadow in high-resolution imagery with high accuracy and reliability.

Aplicação de técnicas de processamento e análise de imagens para detecção de edificações e vegetação a partir de dados LiDAR

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Micromorphology of Resin-Dentin Interfaces Using One-Bottle Etch&Rinse and Self-Etching Adhesive Systems on Laser-Treated Dentin Surfaces: A Confocal Laser Scanning Microscope Analysis

Background and Objectives: This study evaluated the hybrid layer (HL) morphology created by three adhesive systems (AS) on dentin surfaces treated with Er:YAG laser using two irradiation parameters. Study Design: Occlusal flat dentin surfaces of 36 human third molars were assigned into nine groups (n = 4) according to the following ASs: one bottle etch&rinse Single Bond Plus (3M ESPE), two-step Clearfil Protect Bond (Kuraray), and all-in-one S3 Bond (Kuraray) self-etching, which were labeled with rhodamine B or fluorescein isothiocyanate dextran and were applied to dentin surfaces that were irradiated with Er:YAG laser at either 120 (38.7 J/cm(2)) or 200 mJ/pulse (64.5 J/cm(2)), or were applied to untreated dentin surfaces (control group). The ASs were light-activated following MI and the bonded surfaces were restored with resin composite Z250 (3M ESPE). After 24 hours of storage in vegetable oil, the restored teeth were vertically, serially sectioned into 1-mm thick slabs, which had the adhesive interfaces analyzed with confocal laser microscope (CLSM-LSM 510 Meta). CLSM images were recorded in the fluorescent mode from three different regions along each bonded interface. Results: Non-uniform HL was created on laser-irradiated dentin surfaces regardless of laser irradiation protocol for all AS, while regular and uniform HL was observed in the control groups. ""Stretch mark""-like red lines were found within the HL as a result of resin infiltration into dentin microfissures, which were predominantly observed in 200 mJ/pulse groups regardless of AS. Poor resin infiltration into peritubular dentin was observed in most regions of adhesive interfaces created by all ASs on laser-irradiated dentin, resulting in thin resin tags with neither funnel-shaped morphology nor lateral resin projections. Conclusion: Laser irradiation of dentin surfaces at 120 or 200 mJ/pulse resulted in morphological changes in HL and resin tags for all ASs evaluated in the study. Lasers Surg. Med. 42:662-670, 2010. (C) 2010 Wiley-Liss, Inc.

Diffusion in heterogeneous systems studied by laser scanning confocal microscopy and fluorescence correlation spectroscopy

Understanding and controlling the mechanism of the diffusion of small molecules, macromolecules and nanoparticles in heterogeneous environments is of paramount fundamental and technological importance. The aim of the thesis is to show, how by studying the tracer diffusion in complex systems, one can obtain information about the tracer itself, and the system where the tracer is diffusing. rnIn the first part of my thesis I will introduce the Fluorescence Correlation Spectroscopy (FCS) which is a powerful tool to investigate the diffusion of fluorescent species in various environments. By using the main advantage of FCS namely the very small probing volume (<1µm3) I was able to track the kinetics of phase separation in polymer blends at late stages by looking on the molecular tracer diffusion in individual domains of the heterogeneous structure of the blend. The phase separation process at intermediate stages was monitored with laser scanning confocal microscopy (LSCM) in real time providing images of droplet coalescence and growth. rnIn a further project described in my thesis I will show that even when the length scale of the heterogeneities becomes smaller than the FCS probing volume one can still obtain important microscopic information by studying small tracer diffusion. To do so, I will introduce a system of star shaped polymer solutions and will demonstrate that the mobility of small molecular tracers on microscopic level is nearly not affected by the transition of the polymer system to a “glassy” macroscopic state. rnIn the last part of the thesis I will introduce and describe a new stimuli responsive system which I have developed, that combines two levels of nanoporosity. The system is based on poly-N-isopropylacrylamide (PNIPAM) and silica inverse opals (iOpals), and allows controlling the diffusion of tracer molecules. rn

PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.

Detecção de regiões de via integrando dados de varredura a LASER aerotransportado e imagens de alta resolução

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Montagem e avaliação de um sistema de varredura a LASER embarcado em VANT

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)