Uso de imagens de satélite de alta resolução (GeoEye-1) para estimativa de acúmulo de carbono em alagados de Mata Atlântica em recuperação na Reserva Ecológica Guapiaçu (Cachoeiras de Macacu, Rio de Janeiro)

Áreas alagadas são importantes devido à grande biodiversidade que sustentam e aos serviços ambientais gerados pela sua conservação. Essas áreas, quando dominadas por macrófitas, tendem a suportar grande biodiversidade e assumir grande valor de conservação. Assim, o monitoramento do estabelecimento deste importante componente do ecossistema durante um projeto de recuperação de ecossistemas é importante para avaliar o sucesso da sua recuperação. Este trabalho teve como objetivo estimar aquantidade de biomassa por área acumulada em um ecossistema ao longo de um gradiente de recuperação. Através da classificação não supervisionada gerada a partir de de imagens de satélite de alta resolução (GeoEye-1) e amostragem destrutiva foram estimadas quantidades de biomassa por área em três alagados em recuperação na Reserva Ecológica Guapiaçú. A classificação não supervisionada se mostrou uma ferramenta acurada e eficiente no mapeamento de classes de vegetação. Os alagados estudados apresentam uma taxa de acúmulo de carbono anual estimada em 1,12 MgC.hec-1 atingindo um máximo de 5.55 MgC.hec-1 no terceiro ano. Adicionalmente, foi observada uma correlação negativa entre biomassa e profundidade.

基于项目驱动的藉河流域土地利用时空变化动态分析

根据1997年、2001年和2005年三期TM影像资料,运用遥感非监督分类的方法提取土地利用信息。利用地理信息系统空间分析和数据统计的方法,分析藉河流域1997~2005年间土地利用数量变化和空间变化特征,研究该地区主要土地利用类型数量变化、空间变化以及在不同坡度的动态变化特征。结果表明:耕地、林地和草地三种主要土地利用类型占该研究区土地利用面积的97%以上,是该研究区主要的土地利用类型。以1997年为基数,到2001年和2005年耕地减少幅度分别为1.2%和11.1%,因此1997~2001年的退耕程度小于2001~2005年;在不同坡度上,土地利用变化主要发生在5°~40°,而且在15°~25°之间变化最大。

Landscape change detection of the newly created wetland in Yellow River Delta

Four models are employed in the landscape change detection of the newly created wetland. The models include ones for patch connectivity. ecological diversity, human impact intensity and mean center of land cover. The landscape data of the newly created wetland in Yellow River Delta in 1984, 1991, and 1996 are produced from the unsupervised classification and the supervised classification on the basis of integrating Landsat TM images of the newly created wetland in the four seasons of the each year. The result from operating the models into the data shows that the newly created wetland landscape in Yellow River Delta had a great chance. The driving focus of the change are mainly from natural evolution of the newly created wetland and rapid population growth, especially non-peasant population growth in Yellow River Delta because a considerable amount of oil and gas fields have been found in the Yellow River Delta. For preventing the newly created wetland from more destruction and conserving benign Succession of the ecosystems in the newly created wetland, six measures are suggested on the basis of research results. (C) 2003 Elsevier Science B.V. All rights reserved.

淤泥质潮滩地貌的遥感研究－以苏北辐射沙洲海岸为例

本文以具有典型特征的苏北淤泥质潮滩海岸作为研究区，利用1975-2003年间14景覆盖该地区的Landsat和SPOT卫星影像作为主要数据源，结合地面调查和验证工作，在遥感影像处理和地理信息系统分析技术的支持下，对区内潮滩、岸线、水边线和盐沼植被等进行遥感解译，分析苏北辐射沙脊群和沿岸地貌的空间分布特征和动态演变趋势。研究结果表明：苏北辐射沙脊群海域的潮汐水位过程的不同步现象普遍存在，限制了常规遥感数据在苏北潮滩地貌研究中的适用范围和解译精度；在人工判别的辅助下，多光谱遥感的非监督分类方法可以有效解译淤泥质潮滩的水边线；利用修改型土壤调整植被指数（MSAVI）可以较好地提取潮滩上的盐沼植被信息；苏北沿岸潮滩的快速淤长促进了盐沼植被带向海侧快速扩展，近年来持续的潮滩围垦工程则不断从陆侧侵占盐沼植被带，使盐沼植被带宽度减小乃至消失；在大规模人类活动和自然条件的共同影响下，苏北辐射沙脊群海岸的岸线发育趋于平直化，无序的潮滩围垦项目使得可垦滩地资源被过度消耗；1975～2002年间，研究区北部和南部沿岸的高潮滩整体上处于淤长状态，中部沿岸潮滩和离岸沙洲高潮滩则被大面积侵蚀；1999年以来，研究区内低潮滩部位开始形成有序排列的滩面地物，并表现出逐年大面积蔓延的趋势，可能是滩涂紫菜养殖区扩展的结果。

Os Sistemas de Informação Geográfica e Detecção Remota na Determinação das Regiões de Risco por Malária na Guiné-Bissau

A malária é uma doença infecciosa complexa, que resulta do “vírus” plasmodium, e manifesta-se sob cinco tipos distintos de espécies protozoários (plasmodium vivax, plasmodium ovale, plasmodium falciparum, plasmodium malariae e plasmodium Knowlesi), atacando sobretudo os glóbulos vermelhos. Considerada a quinta maior causa de morte por doenças infecciosas em todo o mundo após doenças respiratórias, VIH/SIDA, doenças diarreicas e tuberculose, no continente africano, a malária é considerada a segunda causa do aumento da mortalidade, após VIH/SIDA. No caso particular da Guiné-Bissau, esta constitui a principal causa do incremento da morbilidade e da mortalidade naquele país, onde, em 2012 foram notificados 129.684 casos de paludismo, dos quais 370 resultaram em óbitos. Partindo da realidade acima constatada, em particular, da complexidade e o impacto global da doença associada a uma forte mortalidade e morbilidade, concluiu-se ser necessário abordar esta temática, utilizando os SIG e a DR no sentido de determinar as regiões de elevado risco. Entendeu-se serem necessárias novas abordagens e novas ferramentas de análise dos dados epidemiológicos e consequentemente novas metodologias que possibilitem a determinação de áreas de risco por malária. O presente estudo, pretende demonstrar o papel dos SIG e DR na determinação das regiões de risco por malária. A metodologia utilizada centrou-se numa abordagem quantitativa baseada na hierarquização das variáveis. Pretende-se, assim abordar os impactos da malária e simultaneamente demonstrar as potencialidades dos SIG e das ferramentas de Análise Espacial no estudo da disseminação da mesma na Guiné-Bissau.

Case study: object and ground point separation on a river bank using airborne based LIDAR data

In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the first task to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficient non-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithm needs to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR data in hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carried out. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigated and three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend the existing algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain.

Threshold-free object and ground point separation in LIDAR data

Light Detection And Ranging (LIDAR) is an important modality in terrain and land surveying for many environmental, engineering and civil applications. This paper presents the framework for a recently developed unsupervised classification algorithm called Skewness Balancing for object and ground point separation in airborne LIDAR data. The main advantages of the algorithm are threshold-freedom and independence from LIDAR data format and resolution, while preserving object and terrain details. The framework for Skewness Balancing has been built in this contribution with a prediction model in which unknown LIDAR tiles can be categorised as “hilly” or “moderate” terrains. Accuracy assessment of the model is carried out using cross-validation with an overall accuracy of 95%. An extension to the algorithm is developed to address the overclassification issue for hilly terrain. For moderate terrain, the results show that from the classified tiles detached objects (buildings and vegetation) and attached objects (bridges and motorway junctions) are separated from bare earth (ground, roads and yards) which makes Skewness Balancing ideal to be integrated into geographic information system (GIS) software packages.

Fuzzy c-means density based clustering using data induced metric

We propose a new data induced metric to perform un supervised data classification (clustering). Our goal is to automatically recognize clusters of non-convex shape. We present a new version of fuzzy c-means al gorithm, based on the data induced metric, which is capable to identify non-convex d-dimensional clusters.

Yaringa and French Island Marine National Park habitat mapping

Deakin University and the Department of Primary Industries were commissioned by ParksVictoria (PV) to create two updated habitat maps for Yaringa and French Island MarineNational Parks. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from World-View-2 imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. In addition, the team applied an unsupervised classification approach to an aerial photograph to assess the differences between the two remote sensors. This report describes the results of the mapping as well as the methodology used to produce these habitat maps.This study has provided mapping of intertidal and subtidal habitats of Yaringa and FrenchIsland MNPs at a 2 m resolution with fair to good accuracies (Kappa 0.40-0.75). These were combined with mangrove and saltmarsh habitats recently mapped by Boon et al. (2011) to provide compete-coverage habitat maps of Yaringa and French Island MNPs.The mapping showed that Yaringa MNP was dominated by mangroves, wet saltmarsh and dense Zostereaceae, covering 33%, 29% and 19%, respectively. Similarly, intertidalvegetation and subtidal vegetation (dominated by Zosteraceae) covered 26% and 25% ofFrench Island MNP. However, as a result of turbidity and missing satellite imagery 27% ofFrench Island MNP remains unmapped.The coupling of WV-2 and LiDAR reduced potential artefacts (e.g. sun glint causing whiteand black pixels known as the “salt and pepper effect”). The satellite classification appeared to provide better results than the aerial photography classification. However, since there is a two-year difference between the capture of the aerial photography and the collection of the ground-truth data this comparison is potentially temporally confounded. It must also be noted that there are differences in costs of the data,the spatial resolution between the two datasets (i.e. WV-2 = 2 m and the Aerial = 0.5 m) and the amount spectral information contained in the data (i.e. WV-2 = 8 bands and the aerial = 4 bands), which may ultimately determine its utility for a particular project.The spatial assessment using FRAGSTATs of habitat patches within Yaringa MNP provides a viable and cost effect way to assess habitat condition (i.e. shape, size and arrangement).This spatial assessment determined that dense Zosteraceae and NVSG habitat classeswere generally larger in patch size and continuity than the medium/sparse Zosteraceaehabitat. The application spatial techniques to time-series mapping may provide a way toremotely monitor the change in the spatial characteristics of marine habitats.This work was successful in providing new baseline habitat maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, fisheries and catchment management, and contribute toward infrastructure planning to limit impacts on Western Port.

Aplicação do Sensoriamento Remoto e do Sistema de Informações Geográficas na Detecção de Manchas de Óleo na Região do Pólo de Exploração de Guamaré, R.N.

Objective to establish a methodology for the oil spill monitoring on the sea surface, located at the Submerged Exploration Area of the Polo Region of Guamaré, in the State of Rio Grande do Norte, using orbital images of Synthetic Aperture Radar (SAR integrated with meteoceanographycs products. This methodology was applied in the following stages: (1) the creation of a base map of the Exploration Area; (2) the processing of NOAA/AVHRR and ERS-2 images for generation of meteoceanographycs products; (3) the processing of RADARSAT-1 images for monitoring of oil spills; (4) the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products; and (5) the structuring of a data base. The Integration of RADARSAT-1 image of the Potiguar Basin of day 21.05.99 with the base map of the Exploration Area of the Polo Region of Guamaré for the identification of the probable sources of the oil spots, was used successfully in the detention of the probable spot of oil detected next to the exit to the submarine emissary in the Exploration Area of the Polo Region of Guamaré. To support the integration of RADARSAT-1 images with NOAA/AVHRR and ERS-2 image products, a methodology was developed for the classification of oil spills identified by RADARSAT-1 images. For this, the following algorithms of classification not supervised were tested: K-means, Fuzzy k-means and Isodata. These algorithms are part of the PCI Geomatics software, which was used for the filtering of RADARSAT-1 images. For validation of the results, the oil spills submitted to the unsupervised classification were compared to the results of the Semivariogram Textural Classifier (STC). The mentioned classifier was developed especially for oil spill classification purposes and requires PCI software for the whole processing of RADARSAT-1 images. After all, the results of the classifications were analyzed through Visual Analysis; Calculation of Proportionality of Largeness and Analysis Statistics. Amongst the three algorithms of classifications tested, it was noted that there were no significant alterations in relation to the spills classified with the STC, in all of the analyses taken into consideration. Therefore, considering all the procedures, it has been shown that the described methodology can be successfully applied using the unsupervised classifiers tested, resulting in a decrease of time in the identification and classification processing of oil spills, if compared with the utilization of the STC classifier

Detecção de áreas degradadas na sub-bacia hidrográfica do rio taperoá/pb, utilizando parâmetros físicos dos sensores modis/terra e tm/landsat

This study includes the results of the analysis of areas susceptible to degradation by remote sensing in semi-arid region, which is a matter of concern and affects the whole population and the catalyst of this process occurs by the deforestation of the savanna and improper practices by the use of soil. The objective of this research is to use biophysical parameters of the MODIS / Terra and images TM/Landsat-5 to determine areas susceptible to degradation in semi-arid Paraiba. The study area is located in the central interior of Paraíba, in the sub-basin of the River Taperoá, with average annual rainfall below 400 mm and average annual temperature of 28 ° C. To draw up the map of vegetation were used TM/Landsat-5 images, specifically, the composition 5R4G3B colored, commonly used for mapping land use. This map was produced by unsupervised classification by maximum likelihood. The legend corresponds to the following targets: savanna vegetation sparse and dense, riparian vegetation and exposed soil. The biophysical parameters used in the MODIS were emissivity, albedo and vegetation index for NDVI (NDVI). The GIS computer programs used were Modis Reprojections Tools and System Information Processing Georeferenced (SPRING), which was set up and worked the bank of information from sensors MODIS and TM and ArcGIS software for making maps more customizable. Initially, we evaluated the behavior of the vegetation emissivity by adapting equation Bastiaanssen on NDVI for spatialize emissivity and observe changes during the year 2006. The albedo was used to view your percentage of increase in the periods December 2003 and 2004. The image sensor of Landsat TM were used for the month of December 2005, according to the availability of images and in periods of low emissivity. For these applications were made in language programs for GIS Algebraic Space (LEGAL), which is a routine programming SPRING, which allows you to perform various types of algebras of spatial data and maps. For the detection of areas susceptible to environmental degradation took into account the behavior of the emissivity of the savanna that showed seasonal coinciding with the rainy season, reaching a maximum emissivity in the months April to July and in the remaining months of a low emissivity . With the images of the albedo of December 2003 and 2004, it was verified the percentage increase, which allowed the generation of two distinct classes: areas with increased variation percentage of 1 to 11.6% and the percentage change in areas with less than 1 % albedo. It was then possible to generate the map of susceptibility to environmental degradation, with the intersection of the class of exposed soil with varying percentage of the albedo, resulting in classes susceptibility to environmental degradation

An environment for knowledge discovery in biology

This paper describes a data mining environment for knowledge discovery in bioinformatics applications. The system has a generic kernel that implements the mining functions to be applied to input primary databases, with a warehouse architecture, of biomedical information. Both supervised and unsupervised classification can be implemented within the kernel and applied to data extracted from the primary database, with the results being suitably stored in a complex object database for knowledge discovery. The kernel also includes a specific high-performance library that allows designing and applying the mining functions in parallel machines. The experimental results obtained by the application of the kernel functions are reported. © 2003 Elsevier Ltd. All rights reserved.

Processamento digital de fotografias aéreas para análise do uso do solo

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Sensoriamento remoto e geoprocessamento aplicado ao estudo temporal do uso da terra e na comparação entre classificação não supervisionada e análise visual

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Dinâmica no uso da terra de 1991 a 2010 da região semiárida do estado do Piauí: cajucultura e apicultura

Pós-graduação em Agronomia (Produção Vegetal) - FCAV