Laurindo Antonio Guasselli

Variação do Índice de Vegetação por Diferença Normalizada na lagoa Itapeva, litoral norte do Rio Grande do Sul, Brasil, a partir de análise de séries temporais

O objetivo do trabalho foi analisar os padroes de comportamento espaco-temporal dos valores do Indice de Vegetacao por Diferenca Normalizada (NDVI) na lagoa Itapeva-RS, por meio de imagens Landsat TM5 e ETM+7, compreendendo o periodo de 1985 a 2010. Para a analise do comportamento espaco-temporal foram utilizadas classes de Indice de Vegetacao por Diferenca Normalizada (NDVI) e Analise por Series Temporais (TSA) de imagens. Para validacao dos padroes observados foram coletadas amostras de agua em seis pontos na lagoa Itapeva para clorofila_a, Totais de Solidos Suspensos e transparencia do disco Secchi. Estes resultados foram correlacionados com os valores de NDVI. Os mapas de classes de NDVI gerados apos a analise da TSA evidenciaram padroes de dinâmica espaciais e sazonais associados as variaveis ambientais atuantes, permitindo o estabelecimento de tres grandes compartimentos para a lagoa Itapeva: norte, centro e sul. A analise da serie temporal de imagens mostra que o aumento e o decrescimo dos valores de NDVI estao associados aos periodos de floracao do fitoplâncton. Concluiu-se que a analise da Serie Temporal de imagens Landsat foi satisfatoria no que se refere ao comportamento espaco-temporal da variacao das classes de NDVI.

Iterative K – Nearest Neighbors Algorithm (IKNN) for submeter spatial resolution image classification obtained by Unmanned Aerial Vehicle (UAV)

ABSTRACT This study proposes a classification technique named Iterative K – Nearest Neighbors algorithm (IKNN) for submeter spatial resolution images acquired by Unmanned Aerial Vehicles (UAV). The method is based on the development of simple solutions for some limitations found in the traditional K – Nearest Neighbors algorithm (KNN). The main changes with respect to the traditional one are: (i) handle the high dimensionality of the data and the overlapping of the features by computing Gini Importances (GI); and (ii) selecting the number of KNN through an iterative algorithm according each classification rate at each iteration. Considering the GI indices as features weights, the IKNN method achieved a reasonable reduction in dimensionality of the data and overlapping among features. Experiments using the proposed method with confidence threshold equal to 60% resulted in a proportion correct (PC) of 90%, which was superior comparing to Support Vector Machine (SVM) and simple KNN methods.

Quantificação da dinâmica dos remanescentes florestais no município de Jaquirana, RS, em imagens de satélite

Techniques of remote sensing and geoprocessing were used to evaluate the dynamics of the vegetal cover, more specifically in Mixed Ombrophile Forest (Araucaria Forest) and Forestry classes in the Jaquirana, northeastern Rio Grande do Sul, from 2002 to 2007. The results showed a significant increase of forestry in detriment to natural forest covering in this short time period. The loss of the natural wood belonging to Mixed Ombrophile Forest was of 5,643.37 ha in a five-year period of time. On the other hand, the forestry area which was 921.10 ha in 2002, increased to 4,814.37 ha in 2007. It was also observed that large areas along the banks of the rivers Antas, Tainhas, and Camisas are now occupied by Pinus sp. crops.

Delimitação de áreas inundáveis a partir de Modified Normalized Difference Water Index (MNDWI) no Município de Esteio (RS, Brasil)

One of the possibilities of analysis from satellite images is the spatial and temporal variation of flodplains. Among the indices developed for analysis of water resources highlights the Modified Normalized Difference Water Index (MNDWI), prepared in order to highlight flood areas with a higher power of discrimination of targets. This work aims to verify the spatial and temporal dynamics of floods, using Landsat images to observe the overflow of water from the Sinos River, from MNDWI index, as support for the delimitation of flooding in the city of Esteio, located in the Metropolitan Region of Porto Alegre, Rio Grande do Sul, Brazil. Therefore, we used four dates of selected images from the reading of accumulated rainfall of ten and thirty days: 08/30/1984 and 03/30/2004 (low rainfall), 11/19/1990 and 10/01/2007 (highest accumulated rainfall). The first two dates showed average accumulated rainfall of 113.6 mm and 61.5 mm, within 30 days and 19.7 mm and 11.9 mm, within 10 days preceding ten image acquisition. The dates of 11/19/1990 and 10/01/2007 presented, respectively, 201.7 mm and 200.1 mm accumulated in the period of 30 days and 28.1 and 126.6 mm accumulated in the previous 10 days of the image acquisition. Concerning the analysis of flood spots in images with low accumulation of precipitation, average MNDWI stood at -0.33, that is lower in relation to the date 10/01/2007, with a mean of -0.11. This data can be seen mainly in points where flood spot was separated from MNDWI composition and overlaps on the city’s image, allowing the study of the influence of this flood in the flow of the streams that cutting through the city of Esteio.

Connectivity among Wetlands of EPA of Banhado Grande, RS

The Environmental Protection Area (EPA) of Banhado Grande, located in the Metropolitan Region of Porto Alegre, comprises three areas of marshes, the Banhado Chico Lomã, the Banhado Grande and Banhado dos Pachecos. In periods of large flood pulses extensive flooded areas are formed between these wetlands and the river Gravataí floodplain, establishing a connectivity between the Wetlands of EPABG. This connectivity indicates that there is an interaction between these wetlands, such as exchange of nutrients, sediments and living organisms. Thus, this study aims to map extensive floodable areas associated with large flood pulses and to analyze the connectivity areas in EPABG. For this, the work is structured in three steps: i) choice of satellite images between the years 2000 to 2015 to identify largest flood pulses; ii) mapping of floodable areas in large flood pulses using images Normalized Difference Index Water (NDWI); and iii) analysis of the connectivity among wetlands. As the results, in large flood pulses, with precipitation greater than 247 mm, in the 30 days prior to the date of the image, establishing a large area of connectivity between the wetlands, forming on the polygon defined by elevation of 11 metres, two types of connectivity: wetlands-wetlands connectivity, allowing interactions among environments with turf and lagoon deposits; and wetlands-stream connectivity, linking the alluvial and floodplain of the Gravataí River deposits with the background lagoon and paludals deposits. Already, in flood pulses of flooding with rainfall less than or equal to 200 mm, in the last 30 days, the flooded area appears fragmented inside the polygon associated at an elevation of 11 metres, mainly in the corridor between the marshes Grande and the Pachecos, that does not connect by flood, forming just wetlands-stream connectivity. Thus, the characterization of the flood pulses and connectivity become fundamental to the understanding of the dynamic of wetlands, because, make aware of for the need to preserve these areas of importance for flood control, microclimate regulation and maintenance of biodiversity.

Temperature Surface of Guaíba Lake, RS, from time series of MODIS images

ABSTRACT The Guaiba lake is located in an area of complex weather variation and is influenced by many atmospheric circulation systems, bringing about violent occluded fronts, and, sometimes, intense precipitation. In Rio Grande do Sul, during El Nino, air temperatures and the precipitation index are higher, contrary to La Nina. Moreover, the Guaiba Lake receives water from the Guaiba’s Hydrographical Region, which corresponds to 1/3 of Rio Grande do Sul State, and is thus an important water body to the metropolitan region of Porto Alegre. Methods that seek to understand the behavior of Guaiba lake surface water temperature (LSWT) may lead to relevant information to identify periods of more or less water warming, as well as the relations between LSWT, water quality deterioration and risks to human health. This paper aims to comprehend the behavior of Guaiba LSWT during periods of climatic anomalies (El Nino/La Nina). Therefore, 418 sea surface temperature (SST) images from the MODIS sensor were processed with SeaDas 7.2 software. The quarterly averages of LSWT were obtained and compared to the climatological anomalies in Equatorial Pacific Ocean. LSWT behavior is more complex in El Nino/La Nina periods. The results show that during climatic abnormality periods there are no direct relationship between the warming/cooling of Guaiba LSWT and the warming/cooling of Equatorial Pacific Ocean’s SST. The precipitation indices were more significant to the behavior of LSWT during El Nino periods, but for all periods (of climatic normality and abnormality), air temperature is what most influences LSWT. This relation occurs with climatic factors of water retention time, water entry and precipitation, and air temperature. There is a major correspondence during La Nina periods with the cooling of Guaiba LSWT only for some years. On the other hand, during El Nino periods there are no correspondences of this phenomenon with the warming of Guaiba LSWT. There are only more intense oscillations in surface temperatures than during regular and La Nina periods, but with a tendency to LSWT warming.

Linear Spectral Mixing Model for estimating optically active components in estuarine waters of Patos Lagoon, Brazil

ABSTRACT Understanding about type and concentration of components in large continental waterbodies is of great value to environmental studies. The synoptic view of multispectral remote-sensing images has the potential to systematically estimate important parameters like suspended solids (SS) and chlorophyll (Chl). However, measures derived directly from radiometric image data usually retrieve inaccurate estimations, preventing discrimination of the spectra and amount of specific components. This work proposes the application of Linear Spectral Mixing Model to estimate concentrations of SS and Chl in the Patos Lagoon estuary, Brazil, through Landsat-8 Operational Land Imager sensor data. The linear mixing model was applied to produce fraction images of SS, sandy bottom, and dissolved organic matter. Simple and multiple linear regressions were performed in order to produce empirical models confronting parameters measured in situ with traditional radiometric data from spectral bands and with the resulting fraction images. The proposed empirical models estimates reached concentration of SS (coefficient of determination, R2 = 0.84) and Chl (R2 = 0.77) in comparison to the data collected in situ. These results showed great potential for using Spectral Mixing Models to indirectly estimate water components by remote-sensing data.

Influencia morfoestructural en la génesis de los procesos de arenización en Rio Grande do Sul, Brasil

La arenizacion es un proceso de degradacion del suelo derivado de la accion hidrica y eolica, que acarrea una dificultad de fijacion de la cobertura vegetal en areas con un substrato fragilizado. Por este motivo la region sudoeste del Rio Grande do Sul es identificada como area de especial atencion por el Ministerio de Medio Ambiente. Esta region se ubica en la Cuenca del Parana con embasamiento constituido por gran cantidad de zonas de flaqueza, separando este embasamiento en bloques de fallas. A traves de la investigacion de la genesis de esos procesos se constato la relacion entre alienaciones estructurales y la disposicion del drenaje, la orientacion de relieve y la ocurrencia de arenales, siendo uno de los procesos fundamentales de investigacion el tratamiento de la imagen SRTM