Accuracy and efficiency evaluation of point-centered quarter method variations for vegetation sampling in an araucaria forest

In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.

Using aster multispectral imagery for mapping woody invasive species in pico da vara natural reserve (Azores Islands, Portugal)

This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.

DYNAMICS OF LEAF FALL FROM RIPARIAN VEGETATION AND THE ACCUMULATION IN BENTHIC STOCK IN NEOTROPICAL STREAMS1

ABSTRACT Considering the importance of the riparian vegetation leaves as an energetic source to first order streams, the aim of the present study was to evaluate the leaf biomass contribution to the system and its temporal dynamics. With this purpose, monthly samples from July 2008 to June 2009 were collected using four sampling devices installed in three streams, in order to collect the vertical, lateral and terrestrial loads, and the benthic stock. We tested the following hypothesis: (1) leaf biomass input is higher after hydric stress periods; and (2) benthic stock biomass increase with higher loads from vertical and lateral entrances. Leaves represented 71.9% (on average) of all sampled allochthonous matter, with seasonal significant variation along the studied year. Peaks of leaf input were registered in September-October, after an increase in rainfall, and also in January, after a decrease in rainfall. Leaf input was higher in the lateral load.

METHODOLOGY FOR AUTOMATICALLY DELIMITING PERMANENT PRESERVATION AREAS ALONG WATER COURSES - THE USE OF GIS IN THE HYDROLOGICAL BASIN OF THE SERGIPE RIVER, BRAZIL

ABSTRACT Permanent Preservation Areas (PPAs) along watercourses have been the focus of numerous studies, not only because of the fragility and ecological relevance of riverine vegetation, but also because of the inefficiency demonstrated in conforming to the legislation protecting it. One of the major difficulties encountered in terms of guaranteeing the effective conservation of these riverside areas is the absence of methodologies that can be used to define them rapidly and accurately without manually determining the widths of the rivers or assigning only uniform linear values for the entire watercourse. The present work sought to develop a spatial analysis methodology capable of automatically defining permanent preservation areas along watercourses using geographic information system (GIS) software. The present study was undertaken in the Sergipe River basin, "considering the river itself and its principal affluents. We used the database of the Digital Atlas of Hydrological Resources (SEMARH/SE), and the delimitations of the PPAs were performed using ArcGIS 10.1 and the XToolPro 9.0 extension. A total of 5,003.82 hectares of Permanent Preservation Areas were delimited along the margins of the rivers analyzed, with a margin of error of <1% in delimiting the widths of the rivers within the entire area considered. The methodology described here can be used to define PPAs efficiently, relatively rapidly, and with very small margins of error, thus representing a technological advance in terms of using GIS for land management.

Environmental adaptation of the source of the subbasin of Rico Stream, Monte Alto - SP, Brazil

The aim of this study was to define the photographic patterns that represent the use and occupation of the landcover of the "spring" of the Rico Stream subbasin, located at Monte Alto, state of São Paulo (SP), Brazil, for environmental adaptation regarding the Brazilian Forest Law. The mapping was performed using remote sensing techniques and visual interpretation of the World View image, followed by the digitalization of the net of drainage and vegetation (natural and agricultural) at the AutoCad software with documents and field work. The study area has 2141.53 ha and the results demonstrated that the main crop is sugarcane with 546.34 ha, followed by 251.22 ha of pastures, 191.71 ha of perennial crops, 57.31 ha of Eucalyptus and 49.52 ha of onion, confirming the advance of sugarcane culture in the region. The region has 375.04 ha of areas of permanent preservation (APPs), and of this area it was found that only 72.17 ha (19.24%) has arboreal vegetation or natural forest, and 302.87 ha of these areas need to be enriched and reforested with native vegetation from the region, according to the current legislation. The data of the area enable future proposals of models for environmental adaptation to the microbasin according to the current environmental legislation.

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil

The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.

Using fraction images derived from modis data for coffee crop mapping

Coffee production was closely linked to the economic development of Brazil and, even today, coffee is an important product of the national agriculture. The State of Minas Gerais currently accounts for 52% of the whole coffee area in Brazil. Remote sensing data can provide information for monitoring and mapping of coffee crops, faster and cheaper than conventional methods. In this context, the objective of this study was to assess the effectiveness of coffee crop mapping in Monte Santo de Minas municipality, Minas Gerais State, Brazil, from fraction images derived from MODIS data, in both dry and rainy seasons. The Spectral Linear Mixing Model was used to derive fraction images of soil, coffee, and water/shade. These fraction images served as input data for the supervised automatic classification using the SVM - Support Vector Machine approach. The best results concerning Overall Accuracy and Kappa Index were obtained in the classification of the dry season, with 67% and 0.41, respectively.

IDENTIFICATION OF SUITABLE AREAS FOR IRRIGATED RICE CROPPING USING MODIS IMAGES AND HAND MODEL

ABSTRACT One of the most relevant activities of Brazilian economy is agriculture. Among the main crops in Brazil, rice is one of high relevance. The state of Rio Grande do Sul, in Southern Brazil, is responsible for 68.7% of domestic production (IBGE, 2013). The goal of this study was to develop a low-cost methodology with a regional scope to identify suitable areas for irrigated rice cropping in this state, using spectro-temporal behavior of vegetation index by means of MODIS images and HAND model. The rice-cropped area of this study was the southern half of the State. Using the HAND model, flood areas were mapped to identify irrigated rice cultivation. We used multi-temporal images of vegetation index from MODIS sensor, covering the period from August 2001 to May 2012. To assess the results, we used data collected in the fields and cropped area information from IBGE. The results showed that the proposed methodology was satisfactory, with Kappa 0.92 and global accuracy of 98.18%. As result, MODIS sensor data and flood areas delineation by means of HAND model generated the estimate irrigated rice area for the area of study.

Mapping the translation needs and practices in development co-operation projects of NGOs

Tämän pro gradu -tutkielman aiheena on kääntäminen ja viestintä vieraalla kielellä Suomen ulkoasiainministeriön rahoittamissa kansalaisjärjestöjen kehitysyhteistyöhankkeissa. Tutkielman on tarkoitus kartoittaa kyseisten kehitysyhteistyöhankkeiden kääntämiseen ja vieraskieliseen viestintään liittyviä tarpeita ja -käytäntöjä. Aihetta ei ole tutkittu laajasti muutoin, joten empiirinen osuus on erityisen merkittävässä roolissa. Tutkielman alussa esitellään ulkoasiainministeriön laatimia suomalaisten kansalaisjärjestöjen kehitysyhteistyöhankkeiden ehtoja ja ohjeita, jotka ovat kyseiselle tutkimukselle olennaisia. Tutkielman teoreettinen osuus koostuu lähinnä metodologisesta pohdinnasta, koska aiempaa tutkimustietoa on vähän. Tutkimusmetodien analysointia on painotettu myös siksi, että empiirisellä osuudella on niin suuri merkitys. Tutkielman empiirinen aineisto on yhtäältä peräisin tutkijan havainnoista, jotka saatiin omia varhaisempia hankehallinnointikokemuksia hyödyntäen sekä osallistuvan havainnoinnin menetelmää käyttäen kahden opiskelijajärjestön kehitysyhteistyöhankkeista vuosien 2009 ja 2012 välisenä aikana. Toisaalta aineisto on kerätty kyselytutkimuksen vastauksista. Kysely lähetettiin 35 suomalaiselle kansalaisjärjestölle, joiden kehitysyhteistyöhankkeita Suomen ulkoasiainministeriö rahoittaa. Järjestöt valittiin satunnaisotannalla. Empiirisen aineiston analyysistä ilmeni muun muassa, että tutkijan alkuperäinen hypoteesi kehitysyhteistyöhön liittyvien tekstien kääntämisen yleisyydestä pitää osittain paikkansa, vaikka tekstejä käännettiinkin kansalaisjärjestöissä vähemmän kuin tutkija odotti. Tutkimusaineisto ei ole kuitenkaan tarpeeksi laaja, jotta tuloksia voitaisiin yleistää, sillä kansalaisjärjestöt, niiden hankkeet, käännöstarpeet ja asiantuntemus osoittautuivat odotetusti hyvin erilaisiksi. Tulokset sisältävät asiaa myös esimerkiksi järjestöissä kääntävien ja vieraalla kielellä viestivien taustoista. Jatkotutkimukset ovat kuitenkin tarpeen, ja mahdollisia tutkimusaiheita on runsaasti.

Mapping financial stability

The ongoing global financial crisis has demonstrated the importance of a systemwide, or macroprudential, approach to safeguarding financial stability. An essential part of macroprudential oversight concerns the tasks of early identification and assessment of risks and vulnerabilities that eventually may lead to a systemic financial crisis. Thriving tools are crucial as they allow early policy actions to decrease or prevent further build-up of risks or to otherwise enhance the shock absorption capacity of the financial system. In the literature, three types of systemic risk can be identified: i ) build-up of widespread imbalances, ii ) exogenous aggregate shocks, and iii ) contagion. Accordingly, the systemic risks are matched by three categories of analytical methods for decision support: i ) early-warning, ii ) macro stress-testing, and iii ) contagion models. Stimulated by the prolonged global financial crisis, today's toolbox of analytical methods includes a wide range of innovative solutions to the two tasks of risk identification and risk assessment. Yet, the literature lacks a focus on the task of risk communication. This thesis discusses macroprudential oversight from the viewpoint of all three tasks: Within analytical tools for risk identification and risk assessment, the focus concerns a tight integration of means for risk communication. Data and dimension reduction methods, and their combinations, hold promise for representing multivariate data structures in easily understandable formats. The overall task of this thesis is to represent high-dimensional data concerning financial entities on lowdimensional displays. The low-dimensional representations have two subtasks: i ) to function as a display for individual data concerning entities and their time series, and ii ) to use the display as a basis to which additional information can be linked. The final nuance of the task is, however, set by the needs of the domain, data and methods. The following ve questions comprise subsequent steps addressed in the process of this thesis: 1. What are the needs for macroprudential oversight? 2. What form do macroprudential data take? 3. Which data and dimension reduction methods hold most promise for the task? 4. How should the methods be extended and enhanced for the task? 5. How should the methods and their extensions be applied to the task? Based upon the Self-Organizing Map (SOM), this thesis not only creates the Self-Organizing Financial Stability Map (SOFSM), but also lays out a general framework for mapping the state of financial stability. This thesis also introduces three extensions to the standard SOM for enhancing the visualization and extraction of information: i ) fuzzifications, ii ) transition probabilities, and iii ) network analysis. Thus, the SOFSM functions as a display for risk identification, on top of which risk assessments can be illustrated. In addition, this thesis puts forward the Self-Organizing Time Map (SOTM) to provide means for visual dynamic clustering, which in the context of macroprudential oversight concerns the identification of cross-sectional changes in risks and vulnerabilities over time. Rather than automated analysis, the aim of visual means for identifying and assessing risks is to support disciplined and structured judgmental analysis based upon policymakers' experience and domain intelligence, as well as external risk communication.

Mapping the sites of latency and reactivation by bovine herpesvirus 5 (BoHV-5) and a thymidine kinase-deleted BoHV-5 in lambs

A thymidine kinase (tk)-deleted bovine herpesvirus 5 (BoHV-5tkΔ) was previously shown to establish latent infection and reactivate - even poorly - in a sheep model (Cadore et al. 2013). As TK-negative alphaherpesviruses are unlike to reactivate in neural tissue, this study investigated the sites of latency and reactivation by this recombinant in lambs. For this, groups of lambs were inoculated intranasally with the parental BoHV-5 strain (SV-507/99) or with the recombinant BoHV-5tkΔ. During latent infection (40 days post-inoculation, pi), the distribution of recombinant virus DNA in neural and non-neural tissues was similar to that of the parental virus. Parental and recombinant virus DNA was consistently detected by PCR in trigeminal ganglia (TGs); frequently in palatine and pharyngeal tonsils and, less frequently in the retropharyngeal lymph nodes. In addition, latent DNA of both viruses was detected in several areas of the brain. After dexamethasone (Dx) administration (day 40pi), the recombinant virus was barely detected in nasal secretions contrasting with marked shedding of the parental virus. In tissues of lambs euthanized at day 3 post-Dx treatment (pDx), reverse-transcription-PCR (RT-PCR) for a late viral mRNA (glycoprotein D gene) demonstrated reactivation of parental virus in neural (TGs) and lymphoid tissues (tonsils, lymph node). In contrast, recombinant virus mRNA was detected only in lymphoid tissues. These results demonstrate that BoHV-5 and the recombinant BoHV-5tkΔ do establish latent infection in neural and non-neural sites. Reactivation of the recombinant BoHV-5tkΔ, however, appeared to occur only in non-neural sites. In anyway, the ability of a tk-deleted strain to reactivate latent infection deserves attention in the context of vaccine safety.

Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping

In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.