Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Object-Space Road Extraction in Rural Areas Using Stereoscopic Aerial Images

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Three-Dimensional Semiautomatic Road Extraction From a High-Resolution Aerial Image by Dynamic-Programming Optimization in the Object Space

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mapping Macrophyte Species in the Amazon Floodplain Wetlands Using Fully Polarimetric ALOS/PALSAR Data

The purpose of this paper was to evaluate attributes derived from fully polarimetric PALSAR data to discriminate and map macrophyte species in the Amazon floodplain wetlands. Fieldwork was carried out almost simultaneously to the radar acquisition, and macrophyte biomass and morphological variables were measured in the field. Attributes were calculated from the covariance matrix [C] derived from the single-look complex data. Image attributes and macrophyte variables were compared and analyzed to investigate the sensitivity of the attributes for discriminating among species. Based on these analyses, a rule-based classification was applied to map macrophyte species. Other classification approaches were tested and compared to the rule-based method: a classification based on the Freeman-Durden and Cloude-Pottier decomposition models, a hybrid classification (Wishart classifier with the input classes based on the H/a plane), and a statistical-based classification (supervised classification using Wishart distance measures). The findings show that attributes derived from fully polarimetric L-band data have good potential for discriminating herbaceous plant species based on morphology and that estimation of plant biomass and productivity could be improved by using these polarimetric attributes.

Deciphering the weathering processes using environmental mineralogy and geochemistry: Towards an integrated model of laterite and podzol genesis in the Upper Amazon Basin

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Rainfall representativeness at TRMM & GPM PR resolution

Precipitation radar on board the TRMM satellite was a milestone in the rainfall observation capability in the large scale. Stemming from TRMM the new mission GPM (Global Precipitation Measurement) is to overcome some TRMM shortcomings like the high level of the PR MDZ. However, for major problems like the PR horizontal resolution, significant improvements are not foreseeable. This papers investigates the impact of TRMM PR resolution on the structure of tropical rainfall. The issue is approached by both gradient analysis and texture verification. Results indicate that the impact maybe significant, affecting important applications like in NWP. © 2005 IEEE.

Investigations on the full polarimetric PALSAR data to discriminate macrophytes species in the Amazon floodplain wetland

The purpose of this work is to evaluate the capacity of full polarimetric L band data to discriminate macrophyte species in Amazon wetland. Fieldwork was carried out almost simultaneously to the acquisition of the full polarimetric PALSAR data. Coherent and incoherent attributes were extracted from the image, and macrophyte morphological variables were measured on the ground. The image attributes and the macrophyte variables were compared in order to evaluate their application for discriminating macrophytes species. The findings suggest that polarimetric information could be adopted to discriminate plant species based on morphology, and that estimation of plant biomass and productivity could be improved by using the polarimetric information. © 2010 IEEE.

Land use image classification through optimum-path forest clustering

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Is it possible to make pixel-based radar image classification user-friendly?

In this paper we would like to shed light the problem of efficiency and effectiveness of image classification in large datasets. As the amount of data to be processed and further classified has increased in the last years, there is a need for faster and more precise pattern recognition algorithms in order to perform online and offline training and classification procedures. We deal here with the problem of moist area classification in radar image in a fast manner. Experimental results using Optimum-Path Forest and its training set pruning algorithm also provided and discussed. © 2011 IEEE.

Submerged macrophytes height estimation by echosounder data sample

Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.

Automatic landslide recognition through Optimum-Path Forest

In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach. © 2012 IEEE.

O processo de construção de objetos de aprendizagem em cálculo diferencial e integral durante uma atividade de design

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Proposição de índice de qualidade ambiental de vida municipal

Pós-graduação em Geociências e Meio Ambiente - IGCE

Nature-Inspired Framework for Hyperspectral Band Selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Geoparks in Brazil-strategy of Geoconservation and Development

Within the framework of the potential of geopark development and the interest of the geological community in creating new areas for geoconservation in Brazil, the aim of this contribution is to show the importance of geoscience education as a strategy for both geoconservation and development, and for the success and maintenance of new geoparks. A historical and evolutionary approach to the theme reveals the current status of geoscience education in Brazil and offers a panorama of the challenges inherent in preparing for the creation of new geoconservation areas. Proposals that aim to promote geoconservation and sustainability in Brazil include projects that capitalize on geological heritage and its relationship with local communities, proposals that form partnerships between the government, universities, businesses, and non-governmental organizations for the development of education, and changes in the law specifically aimed at geoconservation. Improvement in the educational system, including Earth science education, is undoubtedly one of the best strategies to promote the preservation of our natural heritage, and a cultural change in education will certainly promote changes in other areas.