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.

Remote sensing analysis of depositional landforms in alluvial settings: Method development and application to the Taquari megafan, Pantanal (Brazil)

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

A study of habitat fragmentation in Southeastern Brazil using remote sensing and geographic information systems (GIS)

The purpose of this work was to study fragmentation of forest formations (mesophytic forest, riparian woodland and savannah vegetation (cerrado)) in a 15,774-ha study area located in the Municipal District of Botucatu in Southeastern Brazil (São Paulo State). A land use and land cover map was made from a color composition of a Landsat-5 thematic mapper (TM) image. The edge effect caused by habitat fragmentation was assessed by overlaying, on a geographic information system (GIS), the land use and land cover data with the spectral ratio. The degree of habitat fragmentation was analyzed by deriving: 1. mean patch area and perimeter; 2. patch number and density; 3. perimeter-area ratio, fractal dimension (D), and shape diversity index (SI); and 4. distance between patches and dispersion index (R). In addition, the following relationships were modeled: 1. distribution of natural vegetation patch sizes; 2. perimeter-area relationship and the number and area of natural vegetation patches; 3. edge effect caused by habitat fragmentation, the values of R indicated that savannah patches (R = 0.86) were aggregated while patches of natural vegetation as a whole (R = 1.02) were randomly dispersed in the landscape. There was a high frequency of small patches in the landscape whereas large patches were rare. In the perimeter-area relationship, there was no sign of scale distinction in the patch shapes, In the patch number-landscape area relationship, D, though apparently scale-dependent, tends to be constant as area increases. This phenomenon was correlated with the tendency to reach a constant density as the working scale was increased, on the edge effect analysis, the edge-center distance was properly estimated by a model in which the edge-center distance was considered a function of the to;al patch area and the SI. (C) 1997 Elsevier B.V. B.V.

Remote sensing techniques applied to slope failure analysis

The paper evaluates the applicability of products of remote sensing in studies related to the structural conditionings of slope stability in saprolites, usually conducted through field surveys. In this article we use a regional approach concentrating on an area of lane duplication of a major highway. In that area, resistance reduction to stress and the low cohesions of muscovite saprolites - schists and gneiss which are associated to geological discontinuities, all result in inumerous instabilities. The joints and foliations were extracted from satellite images as well as aerial photographs. Following that, the study area was divided into various sectors based on the directions and dips of the foliation. Different relationships between the structures and the slopes were analyzed in order to indicate the most feasible type of slope failure in each sector of analysis. The aim of the study is to subsidize further detailed future research.

An intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensing

Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field. (C) 2010 Elsevier B.V. All rights reserved.

Remote Sensing Detection of atmospheric pollutants using Lidar, Sodar and correlation with air quality data in an industrial area

Optical remote sensing techniques have obvious advantages for monitoring gas and aerosol emissions, since they enable the operation over large distances, far from hostile environments, and fast processing of the measured signal. In this study two remote sensing devices, namely a Lidar (Light Detection and Ranging) for monitoring the vertical profile of backscattered light intensity, and a Sodar (Acoustic Radar, Sound Detection and Ranging) for monitoring the vertical profile of the wind vector were operated during specific periods. The acquired data were processed and compared with data of air quality obtained from ground level monitoring stations, in order to verify the possibility of using the remote sensing techniques to monitor industrial emissions. The campaigns were carried out in the area of the Environmental Research Center (Cepema) of the University of São Paulo, in the city of Cubatão, Brazil, a large industrial site, where numerous different industries are located, including an oil refinery, a steel plant, as well as fertilizer, cement and chemical/petrochemical plants. The local environmental problems caused by the industrial activities are aggravated by the climate and topography of the site, unfavorable to pollutant dispersion. Results of a campaign are presented for a 24- hour period, showing data of a Lidar, an air quality monitoring station and a Sodar. © 2011 SPIE.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Rank Aggregation for Pattern Classifier Selection in Remote Sensing Images

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelling the surface circulation and thermal structure of a tropical reservoir using three-dimensional hydrodynamic lake model and remote-sensing data

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Determining large scale actual evapotranspiration using agro-meteorological and remote sensing data in the northwest of Sao Paulo State, Brazil

The best irrigation management depends on accurate estimation of reference evapotranspiration (ET0) and then selection of the appropriate crop coefficient for each phenological stage. However, the evaluation of water productivity on a large scale can be done by using actual evapotranspiration (ETa), determined by coupling agrometeorological and remote sensing data. This paper describes methodologies used for estimating ETa for 20 centerpivots using three different approaches: the traditional FAO crop coefficient (K-c) method and two remote sensing algorithms, one called SEBAL and other named TEIXEIRA. The methods were applied to one Landsat 5 Thematic Mapper image acquired in July 2010 over the Northwest portion of the Sao Paulo State, Brazil. The corn, bean and sugar cane crops are grown under center pivot sprinkler irrigation. ET0 was calculated by the Penman-Monteith method with data from one automated weather station close to the study site. The results showed that for the crops at effective full cover, SEBAL and TEIXEIRA's methods agreed well comparing with the traditional method. However, both remote sensing methods overestimated ETa according to the degree of exposed soil, with the TEIXEIRA method presenting closer ETa values with those resulted from the traditional FAO K-c method. This study showed that remote sensing algorithms can be useful tools for monitoring and establishing realistic K-c values to further determine ETa on a large scale. However, several images during the growing seasons must be used to establish the necessary adjustments to the traditional FAO crop coefficient method.

Coupling remote sensing bio-optical and three-dimensional hydrodynamic modeling to study the phytoplankton dynamics in a tropical hydroelectric reservoir

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

Application of landsat images for quantifying the energy balance under conditions of land use changes in the semi-arid region of Brazil

In the Nilo Coelho irrigation scheme, Brazil, the natural vegetation has been replaced by irrigated agriculture, bringing importance for the quantification of the effects on the energy exchanges between the mixed vegetated surfaces and the lower atmosphere. Landsat satellite images and agro-meteorological stations from 1992 to 2011 were used together, for modelling these exchanges. Surface albedo (α0), NDVI and surface temperature (T0) were the basic remote sensing retrieving parameters necessary to calculate the latent heat flux (λE) and the surface resistance to evapotranspiration (rs) on a large scale. The daily net radiation (Rn) was obtained from α0, air temperature (Ta) and short-wave transmissivity (τsw) throughout the slob equation, allowing the quantification of the daily sensible heat flux (H) by residual in the energy balance equation. With a threshold value for rs, it was possible to separate the energy fluxes from crops and natural vegetation. The averaged fractions of Rn partitioned as H and λE, were in average 39 and 67%, respectively. It was observed an increase of the energy used for the evapotranspiration process inside irrigated areas from 51% in 1992 to 80% in 2011, with the ratio λE/Rn presenting an increase of 3 % per year. The tools and models applied in the current research, can subsidize the monitoring of the coupled climate and land use changes effects in irrigation perimeters, being valuable when aiming the sustainability of the irrigated agriculture in the future, avoiding conflicts among different water users. © 2012 SPIE.