Paulo Roberto Meneses

Avaliação dos processamentos de crosstalk e de correção atmosférica em dados ASTER para identificação da relação mineralógica caulinita/(caulinita + gibbsita) em solos no município de São João d'Aliança (GO)

The aim of this study was to analyze the influence of atmospheric correction and crosstalk in the spatial relationship of kaolinite/(kaolinite + gibbsite) in tropical soils through the application of the spectral index RCGb scale, in ASTER-SWIR L1A and L1B images, and in products on-demand AST_07 and AST_07XT, acquired on October 24, 2001. Atmospheric correction routines FLAASH and QUAC and the CRSTK30 software were used to correct for the crosstalk effect. The results were analyzed according to four approaches: comparing the behavior of RCGb scale and RCGbATG transects, analysis of the RCGb scale image of sliced values and analysis of the RCGb scale image and statistical analysis of the similarity between the values of the RCGb scale and RCGbATG transects through the Mann-Whitney statistical test. The routines FLAASH and QUAC hampered the identification of environments and mineralogical relationship. The combination CRSTK30-FLAASH impaired the identification of environments, as well as the relationship mineralogical and the behavior of the RCGb scale transect. The combination CRSTK30-QUAC provided better results in terms of the statistical similarity in relation to the results of the processing without corrections. The results indicated that the products on-demand AST_07 and images L1B converted to reflectance with crosstalk correction and atmospheric correction (QUAC) are the most appropriate, in this order.

Classificação e eliminação dos ruídos em imagens hiperespectrais pela análise seqüencial da transformação por Fração de Ruído Mínima

Hyperspectral images are extremely susceptible to noise interferences which hinder mineral identification and quantification. Therefore, it is fundamental the use of techniques to minimize them. An efficient mathematical noise reducing procedure employs the Minimum Noise Fraction (MNF). The MNF procedure is derived from and similar to the Principal Component Analysis (APC). The main difference between them is that the MNF considers the noise while the PCA considers the data variation. It results in an ordering that reflects the image quality. The MNF transformation can be subdivided in four stages: a) obtaining a noise sample; b) formulation of a noise fraction index; c) implementation of a linear transformation function as PCA; and d) inversion of MNF considering only signs information. In the present work a methodology of MNF sequential steps is proposed using internal and external references of the image. As external reference it was used the dark reference collected during a flight simultaneously to the image acquisition. The internal reference was obtained by statistical techniques for the segmentation of the noise fraction in relation to the sign. Three types of noises can be defined by variance and correlation: a) uncorrelated noises with equal variance in all bands, b) highly correlated noises, and c) Noises with Unknown Covariance. Matrix. For the AVIRIS images, a sequential procedure of MNF can be accomplished with two stages: the first one eliminates the noises of intern reference and the second the relative external reference to the instrumental noise. That procedure allows to distinguish different types of noises and to eliminate them sequentially and efficiently.

The use of ALOS PALSAR imagery for Cerrado's land use and land cover mapping

In Brazil, land use and land cover (LULC) mappings are obtained mainly from optical images. Radar data are also promising since they are independent of solar illumination and the microwave radiation can penetrate clouds and depict differences in canopy structures. This study analyzed the potential of ALOS PALSAR data for LULC mapping of Federal District of Brazil (FD). L-band, HH-, HV- and VV-polarized amplitude images from the end of wet season were processed through the image segmentation technique by growing region. The segments were exported into a geographical information system software package as shapefile format and then visually interpreted in the computer screen. The folloowing classes were discriminated: consolidate urban areas; urban areas in consolidation; natural grasslands; Cerrado shrubland; croplands; gallery forest; indiscriminated forests: pasturelands; reforestations; and water reservoirs. Cerrado shrubland was the most representative mapping class of the study area, followed by consolidated urban areas and natural grasslands.

Abordagem metodológica baseada em imagens do SAR-R99B para identificar prováveis pistas de pouso não-homologadas na Amazônia

This study presents a methodological approach based on radar images and on gray level, size and geometric pattern to identify potential unofficial airplane strips in Amazonia. The following procedures were conducted: georeferencing of a L-band, HH polarization, 3-meter spatial resolution image obtained by the SAR-R99B system over the Itaituba municipality, State of Para; subtraction of speckle noise with a median filter; image classification with the ISODATA unsupervised technique; conversion of selected targets of interest into vector format; and calculation and automatic selection of targets of interest by the circularity and tortuosity indices. Among the 10 previously identified targets, two were considered as potential unofficial airplane strips by the above mentioned indices.

Análise de dados hiperespectrais em mina de manganês laterítico, São João da Aliança (GO)

The aim this paper is to develop a methodology of lateritic manganese identification using imaging spectroscopy. In this study was used the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) image. The AVIRIS is an imaging sensor that measures the solar reflected spectrum from 400 nm to 2500 nm at 10 nm intervals. The study area is located at Goias State and enclosed the Fazenda Extrema mine that presents lateritic manganese deposits developed on Paranoa Group rocks. Laboratory spectrometry studies conjugated with mineralogical analysis by diffractometry of X-ray demonstrated that the ore spectrum is opaque and spectrally featureless, due to the conduction band of MnO3 extending throughout this spectral range. The digital image processing can be subdivided in the following steps: (a) atmospheric correction using Green method, (b) areas selection with opaque behavior from the integral spectra calculation, and (c) lateritic manganese individualization using the Minimum Noise Fraction transformation. The method is efficient to classify areas of abandoned manganese mine that consist of priority areas for implementation of environmental recovery.