Avaliação e depreciação do Ativo Imobilizado no Governo do Estado do Rio de Janeiro: desafios na implantação dos procedimentos contábeis.

No Brasil, o início do processo de convergência às normas internacionais de contabilidade no setor público ocorre desde 2007 na União, nos Estados e nos Municípios, o que acaba gerando muitas mudanças e também muitos desafios na adoção dos novos procedimentos. Um dos novos procedimentos envolve a avaliação e depreciação do Ativo Imobilizado. Nota técnica divulgada recentemente pela STN descreve que os Entes estão encontrando dificuldades em adotar as novas regras. Nesse contexto, este estudo se propõe a responder a seguinte questão de pesquisa: como superar os desafios na implantação dos procedimentos contábeis sobre avaliação e depreciação do Ativo Imobilizado no Governo do Estado do Rio de Janeiro? Tem como objetivo geral identificar os desafios na implantação dos procedimentos contábeis sobre avaliação e depreciação do Ativo Imobilizado no Governo do Estado do Rio de Janeiro e como objetivo específico investigar e analisar a estrutura contábil e patrimonial, assim como propor soluções básicas e essenciais para a aplicação dos procedimentos contábeis. Quanto aos fins, foi realizada pesquisa descritiva e quanto aos meios, foi realizada pesquisa bibliográfica, documental e o estudo de caso, com a realização de entrevistas com os responsáveis de patrimônio e almoxarifado de 23 órgãos da Administração Direta do Estado do Rio de Janeiro. A análise dos dados coletados revela que não há integração entre o setor contábil, o setor de patrimônio e o setor de almoxarifado nestes órgãos. Os setores possuem baixo quantitativo de funcionários e estes são pouco valorizados, não existindo padronização dos procedimentos sobre gestão patrimonial. O desafio de adotar esses procedimentos ultrapassa a competência do setor de contabilidade e exige a integração dos setores de patrimônio, almoxarifado e contábil. Assim, o estudo propõe a aquisição ou desenvolvimento de um sistema integrado de controle de bens, em que a contabilidade, o patrimônio e o almoxarifado acessem os mesmos dados e possuam uma ferramenta de comunicação confiável, que possibilite a elaboração de relatórios que gerem informações úteis ao gestor e aos demais interessados. Propõe também a regulamentação dos novos procedimentos, o fortalecimento da carreira dos funcionários que atuam no patrimônio e no almoxarifado e orienta sobre a adoção de procedimentos iniciais, para o período de transição.

Infra-estrutura para informações espaciais.

Atualmente o Brasil conta com um volume imenso de dados sobre o território nacional. Entretanto, grande parte dos dados existentes encontra-se dispersa, fragmentada, sem compatibilização cartográfica e, em alguns casos, duplicada em vários locais. O grande desafio é compartilhar dados geograficamente dispersos e comunicar conceitos importantes entre departamentos dentro da organização ou entre organizações diferentes usando, para isso, tecnologias de informação. Assim, esse trabalho tem como objetivo geral contribuir para o desenvolvimento de uma infra-estrutura para informação geográfica, que possa ser amplamente disseminada via Internet através de Web Services e que atenda os requisitos de interoperabilidade, de modo que diversos usuários possam usufruir dos dados disponíveis, integrando-os quando necessários. Este trabalho incidirá inicialmente nas necessidades de informação geográfica para o Zoneamento Ecológico e Econômico do Brasil. Entretanto, como se trata de um sistema de infra-estrutura de dados espaciais poderá, então, agregar dados para qualquer trabalho que envolva a informação espacial.

Uso de web services e softwares livres na disseminação de informações georreferenciadas sobre produtos da floresta amazônica.

Georreferenced information has been increasingly required for the planning and decision-making in different sectors of society. New ways of dissemination of data, such as the Open Geospatial Consortium (OGC) web services, have contributed to the ease of access to this information. Even with all the technological advances in the area of data distribution, there is still low availability of georreferenced data about the Amazon. The goal of the present work is the development of a spatial data infrastructure (SDI), that is, an environment of sharing and use of georreferenced data based on the technology of web services, metadata and interfaces that allow the user easy access to these data. The present work discussess the OGC patterns, the most relevant georeferrenced data servers, the main web clients, and the revolution in the dissemination of georeferrenced data which geobrowsers and web clients offered to regular users. Data to be released for the case study come from the project Exploitation of Non-wooden Forest Products-PFNM-in progress at the National Institute of Research in the Amazon-INPA-as well as from inventories of NGOs and other government bodies. Besides contributing to the enhancement of PFNM, this project aims at encouraging the use of GIS in the state of Amazonas offering tech support for the deployment of geographic databases and sharing between agencies, optimizing the resources applied in this area through the use of free software and integration of diffuse information currently available.

Literature review for a resource characterization of Cape Romain National Wildlife Refuge

Through research aimed at understanding the coastal environment, surveys designed to help manage the resource, and national programs to monitor environmental condition, we see a picture of a dynamic ecosystem that is Cape Romain National Wildlife Refuge (CRNWR). Currently, there are efforts underway to protect threatened species; monitor fish populations; and quantify the biological, physical, and chemical characteristics of this environment. The potential impacts to this system are just now being understood as ecological responses to human modification are observed and explained. As a starting point, this document compiles existing information about Cape Romain NWR in five topic areas and addresses the potential impacts to the Refuge. This review is intended to serve as a stepping stone to developing a research agenda in support of management of the Refuge. There are various sources of information on which to build a framework for monitoring conditions and detecting change to this environment. For instance, information on basic ecological function in estuarine environments has evolved over several decades. Long-term surveys of Southeast fisheries exist, as well as shellfish and sediment contaminants data from estuaries. Environmental monitoring and biological surveys at the Refuge continue. Recently, studies that examine the impacts to similar coastal habitats have been undertaken. This document puts past studies and ongoing work in context for Refuge managers and researchers. This report recommends that the next phase of this resource characterization focus on: • compiling relevant tabular and spatial data, as identified here, into a Geographic Information System (GIS) framework • assessing the abundance and diversity of fisheries utilizing CRNWR • delineating additional data layers, such as intertidal habitats and subtidal clam beds, from low-level aerial photography, hard copy maps, and other sources • continued inventories of plant and animal species dependent on the Refuge • monitoring physical and chemical environmental parameters using the methodology employed at National Estuarine Research Reserve System (NERRS) and other coastal sites, where appropriate • further definition of the potential risks to the Refuge and preparing responses to likely impacts.

Characterizing Jobos Bay, Puerto Rico: a watershed modeling analysis and monitoring plan

Land-based pollution is commonly identified as a major contributor to the observed deterioration of shallow-water coral reef ecosystem health. Human activity on the coastal landscape often induces nutrient enrichment, hypoxia, harmful algal blooms, toxic contamination and other stressors that have degraded the quality of coastal waters. Coral reef ecosystems throughout Puerto Rico, including Jobos Bay, are under threat from coastal land uses such as urban development, industry and agriculture. The objectives of this report were two-fold: 1. To identify potentially harmful land use activities to the benthic habitats of Jobos Bay, and 2. To describe a monitoring plan for Jobos Bay designed to assess the impacts of conservation practices implemented on the watershed. This characterization is a component of the partnership between the U.S. Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) established by the Conservation Effects Assessment Project (CEAP) in Jobos Bay. CEAP is a multi-agency effort to quantify the environmental benefits of conservation practices used by private landowners participating in USDA programs. The Jobos Bay watershed, located in southeastern Puerto Rico, was selected as the first tropical CEAP Special Emphasis Watershed (SEW). Both USDA and NOAA use their respective expertise in terrestrial and marine environments to model and monitor Jobos Bay resources. This report documents NOAA activities conducted in the first year of the three-year CEAP effort in Jobos Bay. Chapter 1 provides a brief overview of the project and background information on Jobos Bay and its watershed. Chapter 2 implements NOAA’s Summit to Sea approach to summarize the existing resource conditions on the watershed and in the estuary. Summit to Sea uses a GIS-based procedure that links patterns of land use in coastal watersheds to sediment and pollutant loading predictions at the interface between terrestrial and marine environments. The outcome of Summit to Sea analysis is an inventory of coastal land use and predicted pollution threats, consisting of spatial data and descriptive statistics, which allows for better management of coral reef ecosystems. Chapters 3 and 4 describe the monitoring plan to assess the ecological response to conservation practices established by USDA on the watershed. Jobos Bay is the second largest estuary in Puerto Rico, but has more than three times the shoreline of any other estuarine area on the island. It is a natural harbor protected from offshore wind and waves by a series of mangrove islands and the Punta Pozuelo peninsula. The Jobos Bay marine ecosystem includes 48 km² of mangrove, seagrass, coral reef and other habitat types that span both intertidal and subtidal areas. Mapping of Jobos Bay revealed 10 different benthic habitats of varying prevalence, and a large area of unknown bottom type covering 38% of the entire bay. Of the known benthic habitats, submerged aquatic vegetation, primarily seagrass, is the most common bottom type, covering slightly less than 30% of the bay. Mangroves are the dominant shoreline feature, while coral reefs comprise only 4% of the total benthic habitat. However, coral reefs are some of the most productive habitats found in Jobos Bay, and provide important habitat and nursery grounds for fish and invertebrates of commercial and recreational value.

Snow accumulation time series and their climatic interpretation

EXTRACT (SEE PDF FOR FULL ABSTRACT): Several snow accumulation time series derived from ice cores and extending over 3 to 5 centuries are examined for spatial and temporal climatic information. ... A significant observation is the widespread depression of net snow accumulation during the latter part of the "Little Ice Age". This initially suggests sea surface temperatures were significantly depressed during the same period. However, prior to this, the available core records indicate generally higher than average precipitation rates. This also implies that influences such as shifted storm tracks or a dustier atmosphere may have been involved. Without additional spatial data coverage, these observations should properly be studied using a coupled (global) ocean/atmosphere GCM.

新疆阜康地区森林资源与环境的空间分析

研究了新疆阜康地区森林植被资源与环境的特征和其30年来的变化，利用Arcinfo强大的空间分析功能，对资源、DEM模型、景观指数、环境价值和新疆降水量的地统计学规律进行较全面的分析。本文分为五个部分： 1、新疆阜康地区森林资源与环境空间数据库的建立森林资源与环境空间数据库的建立是它们空问分析的基础。利用多期的遥感图象和该区的地形图，建立森林分类图形和属性库（包括森林和环境自变量集）一体化的GIS空间数据库。为了提高TM遥感图象的分类精度，利用ERDAS图象处理软件，对它进行包括主成分、降噪、去条带和自然色彩变换等增强处理，采用监督分类和人工判读相结合的方法进行分类，采用R2V、ERDAS、Arcview、Arcinfo等软件的集成，使得小班面层与某些线层的无缝联接。成功地形成一套适于西部GIS的森林资源与环境空间数据库的技术路径。此外，对新疆阜康北部地区森林资源动态进行初步分析。 2、新疆阜康地区数字高程模型(DEM)及其粗差检测分析为了提高生态建模的精度，模拟和提取该区的地面特征至关重要。在已建立的森林资源与环境空间数据库的支持下，利用Arcinfo和ERDAS，建立了新疆阜康地区的1：5万数字高程模型(DEM)。通过提取地形的海拔、坡度、坡向特征因子，分析森林植被的垂直分布。通过对DEM的粗差检测分析，分析阜康地区的数字高程模型精度。 3、新疆阜康地区景观格局变化分析在1977年、1987年、1999年森林资源与环境空间数据库的支持下，利用景观分析软件编制三个时段的新疆阜康地区植被景观类型图，并分析了近30年来新疆阜康地区景观动态与景观格局变化。结果表明：①在此期间整个研究区的斑块数减少，斑块平均面积扩大，景观中面积在不同景观要素类型之间的分配更加不均衡，景观面积向少数几种类型聚集。说明了在这期间阜康地区的景观类型有向单一化方向发展的趋势;②农耕地分布呈破碎化的趋势，斑块平均面积变小，斑块间离散程度也更高：这些变化说明人为的经济活动在阜康地区的加剧，③天然林面积减少较多，水域的面积却呈现上升的趋势，冰川及永久积雪的面积呈下降趋势， 4、新疆阜康地区森林生态效益的初步分析从广义森林生态效益定义出发，针对12种森林生态效益因变量不完全独立、且各自的自变量集不完全相同，引入具有多对多特征且整体上相容的似乎不相关广义线性模型。通过构造12种森林生态效益的“有效面积系数”和“市场逼近系数”，在森林资源与环境空间数据库的支持下，对新疆阜康地区两期的森林生态效益进行科学的计量。结果表明：新疆阜康地区的森林生态效益货币量1987年是90673.8万元，1999年是84134.4万元，总体上呈下降趋势。 5、利用新疆气象站资料研究年降雨量的空间分布规律利用ArcGIS地统计学模块，在2000年新疆气候信息空间数据库和新疆DEM模型的支持下，做出了新疆地区的年降水量空间分布图。根据新疆气候资料建立趋势而分析模型、模拟了新疆降水量空间分布的趋势值。采用3种算法（距离权重法、普通Kriging法、协同Kriging方法）计算并比较分析了研究区多年的平均降水量的时空变化。利用模拟产生的精度最优的栅格降水空间数据库，建立的多年平均降水资源信息系统，可快速计算研究区内任一地域单元中降水的总量及其空间变化，可以生成高精度的气候要素空间分布图。

Responses to seasonal changes in nutrient quality and patchiness of food in a multigroup community of Tibetan macaques at Mt. Emei

Provisioning along pedestrian trails by tourists much increased the nutrient quality and patchiness of food (NqPF)for Tibetan macaques (Macaca thibetana) at Mt Emei in spring and summer. In the habitat at a temperate-subtropical transition zone, the mncaque's NqPF could be ordered in a decreasing rank from spring summer to autumn to winter With the aid of a radio-tracking system, I collected ranging data on a multigroup community in three 70-day periods representing the different seasons in 1991-92, Rank-order correlation on the data show that with the decline of NqPF; the groups tended to increase days away from the trail, their effective range size (ERS) their exclusive area (EA) and the number of days spent in the EA, and reduced their group/community density and the ratio of the overlapped range to the seasonal range (ROR). In icy/snowy winter; the macaques searched for mature leaves slowly and carefully in the largest seasonal range with a considerable portion that was nor used in other seasons. Of the responses, the ROR decreased with the reduction in group/community density; and the ERS was the function of both group size (+) and intergroup rank (-) when favorite food was highly clumped. All above responses were clearly bound to maximize foraging effectiveness and minimize energy expenditure, and their integration in term of changes in time and space leads to better understanding macaque ecological adaptability. Based on this study and previous work on behavioral and physiological factors, I suggest a unifying theory of intergroup interactions. Ir! addition, as the rate of behavioral interactions,was also related to the group density, I Waser's (1976) gas model probably applies to behavioral, as well as spatial, data on intergroup interactions.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Progressive 3D reconstruction of infrastructure with videogrammetry

A number of methods are commonly used today to collect infrastructure's spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic, and cost-efficient at the same time. This paper presents a videogrammetric framework for acquiring spatial data of infrastructure which holds the promise to address this limitation. It uses a calibrated set of low-cost high resolution video cameras that is progressively traversed around the scene and aims to produce a dense 3D point cloud which is updated in each frame. It allows for progressive reconstruction as opposed to point-and-shoot followed by point cloud stitching. The feasibility of the framework is studied in this paper. Required steps through this process are presented and the unique challenges of each step are identified. Results specific to each step are also presented.

Automated sparse 3D point cloud generation of infrastructure using its distinctive visual features

The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.

Progressive Site Modelling with Videogrammetry

A number of methods are commonly used today to collect as-built spatial data (time-of-flight, visual triangulation, etc.). However, current practice lacks a solution that is accurate, automatic and cost-efficient at the same time. LiDARmethods generate high resolution depth information, but the significant cost of the equipment counteracts their benefits for the majority of construction projects. This is true especially for small projects, where projected savings hardly justify adopting this technology. Vision-based technologies, such as videogrammetry, is potentially able to address the existing limitations.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Comparison of Image-Based and Time-of-Flight-Based Technologies for 3D Reconstruction of Infrastructure

Image-based (i.e., photo/videogrammetry) and time-of-flight-based (i.e., laser scanning) technologies are typically used to collect spatial data of infrastructure. In order to help architecture, engineering, and construction (AEC) industries make cost-effective decisions in selecting between these two technologies with respect to their settings, this paper makes an attempt to measure the accuracy, quality, time efficiency, and cost of applying image-based and time-of-flight-based technologies to conduct as-built 3D reconstruction of infrastructure. In this paper, a novel comparison method is proposed, and preliminary experiments are conducted. The results reveal that if the accuracy and quality level desired for a particular application is not high (i.e., error < 10 cm, and completeness rate > 80%), image-based technologies constitute a good alternative for time-of-flight-based technologies and significantly reduce the time and cost needed for collecting the data on site.