Bundle Block Adjustment of CBERS-2B HRC Imagery Combining Control Points and Lines

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

Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Orientação de imagens CBERS-2B usando o modelo rigoroso de colinearidade com dados orbitais

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

Geoestística e sensoriamento remoto na classificação de imagens em áreas cultivadas com citros

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)

Classificação de imagens em áreas cultivadas com citrus por técnicas de sensoriamento remoto e geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de transformações geométricas para o georreferenciamento de imagens do satélite CBERS-1

Neste trabalho serão descritos métodos e técnicas na análise de transformações geométricas para o georreferenciamento de imagens do satélite CBERS I, utilizando o sensor CCD na região de Porto Alegre, com a utilização das transformações afim e equações projetivas e com o uso de pontos de apoio coletados com receptor GPS. Os resultados experimentais obtidos com as transformações afim e equações projetivas são animadores, recomendando-se então continuar os estudos para as imagens do CBERS-I que pode ser um atalho importante para atualizar a cartografia regional brasileira, pois neste caso do sensor CCD se vislumbra a possibilidade de se gerarem cartas imagens nas escalas de 1:100.000 e 1:50.000.

Uso e ocupação do solo e monitoramento dos recursos hídricos na microbacia do Córrego do Ipê, Ilha Solteira, SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação do uso de técnicas digitais para caracterização de área degradada por empréstimo de solo: máxima verossimilhança x modelo linear de mistura espectral

Pós-graduação em Engenharia Civil - FEIS

Diagnóstico de conflitos em áreas de preservação permanente na bacia do Rio Capivara - Botucatu (SP)

The permanent preservation areas (PPA) established by Brazilian law are there to protect the natural environment. With the expansion of space occupied by man and development of economic activities in these areas were engaged in conflicts characterized PPA, where the use is other than the natural vegetation. According to these paradigms work aims to raise these conflict areas in the River Basin Capivara, Botucatu (SP) with the help of GIS Ilwis 3.4, topographic maps of IBGE and satellite images CBERS 2B. The map was generated from PPA in the GIS by distance calculation in relation to drainage, springs and break line on Cuesta de Botucatu. The classes of land use and natural vegetation were determined by interpretation of satellite images and field visits to check their veracity. With the cutting of the map of land use and natural vegetation in relation to PPA unit it was determined that the total 44,63% PPA is in conflict occupied by pasture, forest plantation, orange, annual crops, farms and irrigated rice project in lowland. This diagnostic characterizes the degradation of the environment and highlights the need to harmonize the economic and urban development with the preservation of the environment to ensure sustainability of the region.

Identificação de padrões de vegetação ciliar em imagens CBERS e respectivo estado de conservação.

A importância que a vegetação de margem de rios representa para o meio ambiente exercendo funções tais como proteção de mananciais e do solo e manutenção do equilíbrio ecológico do ecossistema, faz com que seja fundamental a sua conservação. Este trabalho tem por objetivo identificar padrões de vegetação ciliar em imagens CBERS do Mato Grosso do Sul e seu respectivo estado de conservação. Foram utilizadas imagens do sensor CCD do satélite CBERS-2B do ano de 2007 e informações de campo, coletadas em 368 pontos de imagem referentes a 14 desses 368 pontos que representam áreas de vegetação ciliar ocupadas por campos úmidos, vegetação arbustiva e vegetação arbórea, além de áreas impactadas por cultivo de arroz, desmatamentos, implantação de pasto exótico, erosão e assoreamento de cursos d'água. De maneira geral, a vegetação ciliar do Estado encontra-se impactada ou ausente na maior parte das áreas observadas.

Classificação de pastagens degradadas nos municípios de Corguinho e Rio Negro, MS, utilizando fusão de imagens CBERS.

A degradação das pastagens pode ser definida como um processo evolutivo de perda de vigor, produtividade e capacidade de recuperação natural, e é atualmente um dos maiores problemas para a pecuária brasileira. Estudos recentes com imagens de satélites de sensoriamento remoto apresentam resultados promissores para identificar e mapear diferentes níveis de degradação em pastagens. Estas imagens também permitem monitor ao longo dos anos o processo de degradação em escala local ou regional. O objetivo do presente estudo consiste em avaliar o uso de imagens fusionadas dos sensores HRC e CCD do satélite CBERS-2B, para identificar e caracterizar áreas com pastagens degradadas nos municípios de Corguinho e Rio Negro no Estado de Mato Grosso do Sul. As imagens foram processadas utilizando o aplicativo SPRING. A classificação foi baseada na segmentação, no MAXVER e na Bhattacharya gerando um mapa temático das áreas de pastagens degradadas na escala de 1:50.000.

Projections Onto Convex Sets through Particle Swarm Optimization and its application for remote sensing image restoration

Image restoration attempts to enhance images corrupted by noise and blurring effects. Iterative approaches can better control the restoration algorithm in order to find a compromise of restoring high details in smoothed regions without increasing the noise. Techniques based on Projections Onto Convex Sets (POCS) have been extensively used in the context of image restoration by projecting the solution onto hyperspaces until some convergence criteria be reached. It is expected that an enhanced image can be obtained at the final of an unknown number of projections. The number of convex sets and its combinations allow designing several image restoration algorithms based on POCS. Here, we address two convex sets: Row-Action Projections (RAP) and Limited Amplitude (LA). Although RAP and LA have already been used in image restoration domain, the former has a relaxation parameter (A) that strongly depends on the characteristics of the image that will be restored, i.e., wrong values of A can lead to poorly restoration results. In this paper, we proposed a hybrid Particle Swarm Optimization (PS0)-POCS image restoration algorithm, in which the A value is obtained by PSO to be further used to restore images by POCS approach. Results showed that the proposed PSO-based restoration algorithm outperformed the widely used Wiener and Richardson-Lucy image restoration algorithms. (C) 2010 Elsevier B.V. All rights reserved.

Unscented Kalman Filter Applied to the Spacecraft Attitude Estimation with Euler Angles

The aim of this work is to test an algorithm to estimate, in real time, the attitude of an artificial satellite using real data supplied by attitude sensors that are on board of the CBERS-2 satellite (China Brazil Earth Resources Satellite). The real-time estimator used in this work for attitude determination is the Unscented Kalman Filter. This filter is a new alternative to the extended Kalman filter usually applied to the estimation and control problems of attitude and orbit. This algorithm is capable of carrying out estimation of the states of nonlinear systems, without the necessity of linearization of the nonlinear functions present in the model. This estimation is possible due to a transformation that generates a set of vectors that, suffering a nonlinear transformation, preserves the same mean and covariance of the random variables before the transformation. The performance will be evaluated and analyzed through the comparison between the Unscented Kalman filter and the extended Kalman filter results, by using real onboard data.

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.