Indicadores de floresta urbana a partir de imagens aéreas multiespectrais de alta resolução

The present work evaluated urban forest indicators, acquired through airborne high-resolution multiespectral images, on the quality of the urban design and its vegetative fraction, in special its trees, in nine neighborhoods of Piracicaba, SP. There were made supervised classifications for characterization of intra-urban elements and the proportions obtained, as exposed soil, tree cover, lawns, asphalt, concrete pavements and roofs. They were studied for the measurement of the urban forest in each place. These variables were related to each other, as well as with the independent variables: population density, people with more than fifteen years of study and family heads with income above twenty minimum wages, obtained through population census. Through the analysis of linear regression variables were identified for intra-urban areas evaluation. Correlations were made and linear regressions among the data obtained from the image and among the proposed indicators. Negative correlations were obtained among population density and arboreal covering and the evaluated indices, in accordance with the predicted in the literature. Composite indicators are proposed, as: the proportion between arboreous space on waterproof space (PAW) and the proportion between arboreous space on building space (PAB). It is concluded by the possibility of the use of those indicators for evaluation of the urban forest and definition of priorities in the execution of ordinances to the improvement of the urban forestry, being prioritized the application of resources in the most lacking neighborhoods.

Análise da incerteza na representação de classes de cobertura do solo urbano resultantes da aplicação de uma rede neural artificial

The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.

Sensoriamento remoto e geoestatística na caracterização espaço-temporal de plantas aquáticas

Pós-graduação em Ciências Cartográficas - FCT

Estudo comparativo de métodos geoestatísticos aplicados em agricultura de precisão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Caracterización de variables geoespaciales mediante teledetección multiespectral y su integración en la modelización hidráulica de la cuenca del río Tinguiririca (Chile)

Este proyecto tiene como objetivo ampliar, mediante la caracterización espectral y multitemporal por técnicas de teledetección y medidas in situ, el estudio del corredor fluvial para el río Tinguiririca en Chile. Consiste en estudiar la cobertura del terreno, evaluar su dinámica de cambio e identificar zonas de acumulación de materiales de alteración hidrotermal arcillosos y óxidos de hierro, presentes en la cuenca durante las últimas tres décadas que puedan explicar su evolución temporal. Se pretenden obtener nuevas variables geoespaciales que ayuden a comprender las posibles causas de variación del cauce, elaborando cartografía para una posterior fase de investigación mediante modelización hidráulica que vaya dirigida a paliar el impacto de las riadas periódicas. Para ello, se han empleado, tratado y explotado imágenes de los sensores remotos TM, ETM+, OLI y TIRS tomadas en un período comprendido entre 1993 y 2014, que se han contrastado con perfiles batimétricos, datos GPS, supervisión y muestreo tomados sobre el terreno. Se ha realizado así mismo, un estudio prospectivo de caso sobre cómo afectarían las variables obtenidas por teledetección a la modelización hidráulica, en particular, la rugosidad, proponiendo un marco metodológico global de integración de las tres técnicas: sistemas de información geográfica, teledetección y modelización hidráulica. ABSTRACT This project aims to develop the study of Tinguiririca River corridor in Chile, through spectral characterization and multitemporal remote sensing and other measurements. This involves studying the land cover, its dynamic changes and identifies clayey materials and iron oxides accumulations of hydrothermal alteration, present in the basin during the last three decades to explain their evolution. It aims to obtain new geospatial variables in order to understand the possible causes of channel variation, developing mapping to a later research stage using hydraulic modeling so as to mitigate the impact of periodic floods. In this way, it has used processed and exploited images of TM, ETM +, OLI and TIRS remote sensing, taken in a period between 1993 and 2014 which it has been compared with bathymetric profiles, GPS, monitoring and sampling data collected in the field . It has done a prospective study about the variables obtained condition on hydraulic modeling, roughness in particular, proposing IX a complete methodological framework about the integration of the three techniques: geographic information systems, remote sensing and modeling hydraulics

Monitorización de emisiones de CO2 en análogos naturales de almacenamientos geológicos a través de la vegetación mediante técnicas de teledetección multiespectral

Uno de los problemas más importantes a los que se enfrenta nuestra sociedad es el de la degradación del medioambiente por la emisión de gases de efecto invernadero. La captura de CO2 en los puntos de emisión y su enterramiento mediante inyección en reservorios geológicos profundos se plantea como una solución hasta que a medio o largo plazo pueda ser mitigada la actual dependencia de la quema de combustibles fósiles. Pero la estabilidad de esos reservorios debe ser monitorizada adecuadamente. En esta tesis se ha estudiado el problema de la detección de fugas de CO2 en un análogo natural de un emplazamiento de almacenamiento profundo a través del análisis de imágenes de satélite multiespectrales. El análogo utilizado ha sido la zona de Campo de Calatrava (Ciudad Real, España), donde, por efecto de la actividad volcánica remanente, aún se pueden encontrar numerosos puntos de emisión de CO2. Se han caracterizado los puntos de emisión de CO2 identificándose dos tipologías con características y manifestaciones claramente diferenciadas: puntos de emisión húmeda o hervideros, y puntos de emisión seca o fumarolas. Para el estudio se han utilizado índices de vegetación y su relación de éstos con los contenidos atmosféricos de CO2. Se han utilizado imágenes multiespectrales de los satélites QuickBird y WorldView‐2. Se ha realizado una preselección de doce índices de vegetación especialmente adecuados para la detección de puntos de emisión de CO2. Mediante análisis y comparación de imágenes de índices de vegetación sobre puntos de emisión conocidos se ha seleccionado los cinco índices con mayor sensibilidad frente al fenómeno. Atendiendo a los principales factores condicionantes de la aparición de nuevos puntos de emisión de CO2 se ha realizado sobre las imágenes de índices de vegetación una predicción de nuevos puntos de emisión. Entre los puntos candidato se han encontrado tres nuevos puntos de emisión de CO2 no descritos previamente en la bibliografía. ABSTRACT One of the most important issues facing our society is the degradation of the environment caused by the emission of greenhouse gases. Capturing CO2 emissions, injection and burial in deep geological reservoirs is presented as a solution until the medium or long term, when the problem of the current dependence on fossil fuels burning can be mitigated. But the stability of these reservoirs should be properly monitored. In this work we study the problem of detecting CO2 leakage in a natural analogue of a deep storage site through analysis of multispectral satellite imagery. The analogue used is in the Campo de Calatrava (Ciudad Real, Spain) where, due to the remaining volcanic activity, it can still be found numerous CO2 emission points. CO2 emission points have been characterized identifying two types having distinct characteristics and effects: wet emission points or hotbeds, and dry emission points or fumaroles. For this study it has been used vegetation indices and its relationship with atmospheric CO2 contents. It has been used multispectral images from QuickBird and WorldView‐2 satellites. It has been done a preselection of twelve vegetation indices especially suitable for the detection of CO2 emission points. Using analysis and comparison of vegetation index images on real emission points it has been selected the five indexes with greater sensitivity to this phenomenon. Based upon the main factors of the emergence of new CO2 emission points it has been made a prediction of new emission points over the vegetation index images. Among the candidate points it has been found three new CO2 emission points not previously described in the literature.

Advancing Bag-of-visual-words Representations For Lesion Classification In Retinal Images.

Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.

The Biopsychosocial Spiritual Model Applied To The Treatment Of women With Breast Cancer, Through Rime Intervention (relaxation, mental Images, Spirituality).

This postdoctoral study on the application of the RIME intervention in women that had undergone mastectomy and were in treatment, aimed to promote psychospiritual and social transformations to improve the quality of life, self-esteem and hope. A total of 28 women participated and were randomized into two groups. Brief Psychotherapy (PB) (average of six sessions) was administered in the Control Group, and RIME (three sessions) and BP (average of five sessions) were applied in the RIME Group. The quantitative results indicated a significant improvement (38.3%) in the Perception of Quality of Life after RIME according to the WHOQOL, compared both to the BP of the Control Group (12.5%), and the BP of the RIME Group (16.2%). There was a significant improvement in Self-esteem (Rosenberg) after RIME (14.6%) compared to the BP of the Control Group (worsened 35.9%), and the BP of the RIME Group (8.3%). The improvement in well-being, considering the focus worked on (Visual Analog Scale), was significant in the RIME Group (bad to good), as well as in the Control Group (unpleasant to good). The qualitative results indicated that RIME promotes creative transformations in the intrapsychic and interpersonal dimensions, so that new meanings and/or new attitudes emerge into the consciousness. It was observed that RIME has more strength of psychic structure, ego strengthening and provides a faster transformation that BP, therefore it can be indicated for crisis treatment in the hospital environment.

Vertical Bone Measurements From Cone Beam Computed Tomography Images Using Different Software Packages.

This article aimed at comparing the accuracy of linear measurement tools of different commercial software packages. Eight fully edentulous dry mandibles were selected for this study. Incisor, canine, premolar, first molar and second molar regions were selected. Cone beam computed tomography (CBCT) images were obtained with i-CAT Next Generation. Linear bone measurements were performed by one observer on the cross-sectional images using three different software packages: XoranCat®, OnDemand3D® and KDIS3D®, all able to assess DICOM images. In addition, 25% of the sample was reevaluated for the purpose of reproducibility. The mandibles were sectioned to obtain the gold standard for each region. Intraclass coefficients (ICC) were calculated to examine the agreement between the two periods of evaluation; the one-way analysis of variance performed with the post-hoc Dunnett test was used to compare each of the software-derived measurements with the gold standard. The ICC values were excellent for all software packages. The least difference between the software-derived measurements and the gold standard was obtained with the OnDemand3D and KDIS3D (-0.11 and -0.14 mm, respectively), and the greatest, with the XoranCAT (+0.25 mm). However, there was no statistical significant difference between the measurements obtained with the different software packages and the gold standard (p> 0.05). In conclusion, linear bone measurements were not influenced by the software package used to reconstruct the image from CBCT DICOM data.

Comparative study of dental arch width in plaster models, photocopies and digitized images

The aim of this study was to comparatively assess dental arch width, in the canine and molar regions, by means of direct measurements from plaster models, photocopies and digitized images of the models. The sample consisted of 130 pairs of plaster models, photocopies and digitized images of the models of white patients (n = 65), both genders, with Class I and Class II Division 1 malocclusions, treated by standard Edgewise mechanics and extraction of the four first premolars. Maxillary and mandibular intercanine and intermolar widths were measured by a calibrated examiner, prior to and after orthodontic treatment, using the three modes of reproduction of the dental arches. Dispersion of the data relative to pre- and posttreatment intra-arch linear measurements (mm) was represented as box plots. The three measuring methods were compared by one-way ANOVA for repeated measurements (α = 0.05). Initial / final mean values varied as follows: 33.94 to 34.29 mm / 34.49 to 34.66 mm (maxillary intercanine width); 26.23 to 26.26 mm / 26.77 to 26.84 mm (mandibular intercanine width); 49.55 to 49.66 mm / 47.28 to 47.45 mm (maxillary intermolar width) and 43.28 to 43.41 mm / 40.29 to 40.46 mm (mandibular intermolar width). There were no statistically significant differences between mean dental arch widths estimated by the three studied methods, prior to and after orthodontic treatment. It may be concluded that photocopies and digitized images of the plaster models provided reliable reproductions of the dental arches for obtaining transversal intra-arch measurements.

Visibility of the mandibular canal on CBCT crosssectional images

The identification of the mandibular canal (MC) is an important prerequisite for surgical procedures involving the posterior mandible. Cone beam computed tomography (CBCT) represents an advance in imaging technology, but distinguishing the MC from surrounding structures may remain a delicate task. OBJECTIVES: The aim of this study was to assess the visibility of the MC in different regions on CBCT cross-sectional images. MATERIAL AND METHODS: CBCT cross-sectional images of 58 patients (116 hemi-mandibles) were analyzed, and the visibility of the MC in different regions was assessed. RESULTS: The MC was clearly visible in 53% of the hemi-mandibles. Difficult and very difficult visualizations were registered in 25% and 22% of the hemi-mandibles, respectively. The visibility of the MC on distal regions was superior when compared to regions closer to the mental foramen. No differences were found between edentulous and tooth-bearing areas. CONCLUSIONS: The MC presents an overall satisfactory visibility on CBCT cross-sectional images in most cases. However, the discrimination of the canal from its surrounds becomes less obvious towards the mental foramen region when cross-sectional images are individually analyzed.

Method for determination of root curvature radius using cone-beam computed tomography images

This article describes and discusses a method to determine root curvature radius by using cone-beam computed tomography (CBCT). The severity of root canal curvature is essential to select instrument and instrumentation technique. The diagnosis and planning of root canal treatment have traditionally been made based on periapical radiography. However, the higher accuracy of CBCT images to identify anatomic and pathologic alterations compared to panoramic and periapical radiographs has been shown to reduce the incidence of false-negative results. In high-resolution images, the measurement of root curvature radius can be obtained by circumcenter. Based on 3 mathematical points determined with the working tools of Planimp® software, it is possible to calculate root curvature radius in both apical and coronal directions. The CBCT-aided method for determination of root curvature radius presented in this article is easy to perform, reproducible and allows a more reliable and predictable endodontic planning, which reflects directly on a more efficacious preparation of curved root canals.

Diagnostic agreement between panoramic radiographs and color doppler images of carotid atheroma

The aim of this study was to investigate the agreement between diagnoses of calcified atheroma seen on panoramic radiographs and color Doppler images. Our interest stems from the fact that panoramic images can show the presence of atheroma regardless of the level of obstruction detected by color Doppler images. Panoramic and color Doppler images of 16 patients obtained from the archives of the Health Department of the city of Valença, RJ, Brazil, were analyzed in this study. Both sides of each patient were observed on the images, with a total of 32 analyzed cervical regions. The level of agreement between diagnoses was analyzed using the Kappa statistics. There was a high level of agreement, with a Kappa value of 0.78. In conclusion, panoramic radiographs can help detecting calcifications in the cervical region of patients susceptible to vascular diseases predisposing to myocardial infarction and cerebrovascular accidents. If properly trained and informed, dentists can refer their patients to a physician for a cardiovascular evaluation in order to receive proper and timely medical treatment.

Computational adjustment technique for digital mammographic images based on the digitizer characteristic curve

We evaluated the performance of a novel procedure for segmenting mammograms and detecting clustered microcalcifications in two types of image sets obtained from digitization of mammograms using either a laser scanner, or a conventional ""optical"" scanner. Specific regions forming the digital mammograms were identified and selected, in which clustered microcalcifications appeared or not. A remarkable increase in image intensity was noticed in the images from the optical scanner compared with the original mammograms. A procedure based on a polynomial correction was developed to compensate the changes in the characteristic curves from the scanners, relative to the curves from the films. The processing scheme was applied to both sets, before and after the polynomial correction. The results indicated clearly the influence of the mammogram digitization on the performance of processing schemes intended to detect microcalcifications. The image processing techniques applied to mammograms digitized by both scanners, without the polynomial intensity correction, resulted in a better sensibility in detecting microcalcifications in the images from the laser scanner. However, when the polynomial correction was applied to the images from the optical scanner, no differences in performance were observed for both types of images. (C) 2008 SPIE and IS&T [DOI: 10.1117/1.3013544]