Ailton Luchiari

Mapping changes in coastline geomorphic features using Landsat TM and ETM+ imagery: examples in southeastern Brazil

Multitemporal Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery was used to assess coastline morphological changes in southeastern Brazil. A spectral linear mixing approach (SLMA) was used to estimate fraction imagery representing amounts of vegetation, clean water (a proxy for shade) and soil. Fraction abundances were related to erosive and depositional features. Shoreline, sandy banks (including emerged and submerged banks) and sand spits were highlighted mainly by clean water and soil fraction imagery. To evaluate changes in the coastline geomorphic features, the fraction imagery generated for each data set was classified in a contextual approach using a segmentation technique and ISOSEG, an unsupervised classification. Evaluation of the classifications was performed visually and by an error matrix relating ground-truth data to classification results. Comparison of the classification results revealed an intense transformation in the coastline, and that erosive and depositional features are extremely dynamic and subject to change in short periods of time.

Land-use and vegetation-cover mapping of an indigenous land area in the state of Mato Grosso (Brazil) based on spectral linear mixing model, segmentation and region classification

A spectral linear-mixing model using Landsat ETM+ imagery was undertaken to estimate fraction images of green vegetation, soil and shade in an indigenous land area in the state of Mato Grosso in the central-western region of Brazil. The fraction images were used to classify different types of land use and vegetation cover. The fraction images were classified by the following two methods: (a) application of a segmentation based on the region-growing technique; and (b) grouping of the regions segmented using the per-region unsupervised classifier named ISOSEG. Adopting a 75% threshold, ISOSEG generated 44 clusters that were grouped into eight land-use and vegetation-cover classes. The mapping achieved an average accuracy of 83%, showing that the methodology is efficient in mapping areas of great land-use and vegetation-cover diversity, such as that found in the Brazilian cerrado (savanna).

Use of fraction imagery, segmentation and masking techniques to classify land-use and land-cover types in the Brazilian Amazon

This work presents a procedure for classifying land-use and land-cover (LULC) types in the Brazilian Amazon. Fraction imagery representing proportions of green vegetation, soil, and shade was estimated using all six reflective bands of the Landsat-5 Thematic Mapper (TM1 to TM5 and TM7) through the linear spectral mixing model (LSMM). The fraction information registered at pixel level was then related to different types of land classes following three principal procedures: (1) selecting an image or image group as input for segmentation; (2) application of sequences of masking techniques to address the segmentation of preselected areas in order to obtain better image partitioning; and (3) application of an unsupervised classifier by region, named Isoseg, to group the segmented regions. Isoseg is a clustering algorithm that calculates the centre of each class using the covariance matrix and the average vector of the regions. An assessment of the classification was performed visually and by error matrix, relating reference data points to classification results. The results showed that fraction images were effective in highlighting the different types of LULC. Several tests were conducted to evaluate the efficacy of the masking technique in the process for extracting information. The results showed that the use of masks significantly improves the segmentation results. However, in the Isoseg classification process, the masking technique was not able to avoid omission and commission errors between classes of similar structures. On comparing the results obtained in this work with a Maximum Likelihood classification, it was found that adopting the procedures described resulted in increases of 10% in average and global accuracy, and 18% in average reliability. Furthermore, a reduction was observed in the variability of errors created in the classification.

Remote sensing and GIS applied to assessment of environmental fragility in the River Basin

Le bassin hydrographique de la haute riviere Coxim (BHC), d’une superficie d’environ 1375 km², est situe dans la partie nord de l’etat de Mato Grosso do Sud sur les municipalites de Sao Gabriel do Oeste-MS et de Camapua-MS. L’objectif de cette etude etait d’evaluer la vulnerabilite de l’environnement du BHC en utilisant la methode de logique floue dans un systeme d’information geographique (SIG) afin de proposer un modele d’amenagement territorial. Les donnees spatiales utilisees ont ete integrees dans un SIG. La generation du modele d’amenagement territorial ete realisee en fonction de la cartographie de la fragilite de l’environnement et de la legislation environnementale. Les resultats ont montre une relation significative entre les caracteristiques de l’espace (ex : topographie) et leurs usages: agriculture mecanisee dans la Chapada de Sao Gabriel et developpement de l’elevage dans les collines du Plateau du Taquari. Les lignes directrices etablies par le type de propositions d’amenagement etaient des secteurs prioritaires pour la conservation, secteur prioritaire pour la rehabilitation et les aires d’utilisation durable.The Upper Coxim River Basin (UCB) has an area of approximately 1375 km2 located in the municipalities of São Gabriel do Oeste and Camapuã in the state of Mato Grosso do Sul, Brazil. The aim of this work was to evaluate the environmental fragility of the UCB using fuzzy logic implemented at a Geographic Information System to propose a model of physical-territorial management. Spatial data used were arranged in a database implemented in a Geographic Information System (GIS). The generation of the physical-territorial management model was carried out considering preparation of UCB relief mapping, potential natural erosion, land-use and land-cover, environmental fragility and, environmental legislation. Results indicated a significant relationship between landforms and their uses: mechanized agriculture in the Chapada of the São Gabriel and livestock development on the Plateau Taquari hills. The guidelines set out by the type of land use proposals were: Priority areas for permanent preservation, priority area for rehabilitation and preservation and areas for sustainable use.

MAPEAMENTO DO DESMATAMENTO EM SÃO FÉLIX DO XINGÚ UTILIZANDO COMPOSIÇÃO COLORIDA MULTITEMPORAL DE IMAGENS FRAÇÕES SOMBRA

O objetivo deste trabalho consiste em mapear o avanco do desmatamento no municipio de Sao Felix do Xingu, Sul do Para (Amazonia Brasileira) usando imagens Landsat TM. A tecnica do modelo linear de mistura espectral (MLME) foi empregada para realcar as areas desmatadas. Tres imagens fracoes representando as proporcoes de solo exposto, vegetacao e sombra foram derivadas do MLME. O mapeamento do desmatamento foi feito utilizando os atributos da imagem-fracao sombra que e bem correlacionada com a estrutura do dossel florestal. Apos a segmentacao, as regioes foram agrupadas por um classificador nao-supervisionado por regioes ISOSEG. Palavras-chave: Desmatamento, modelo de mistura, imagem fracao-sombra, analise multitemporal. Abstract The aim of this work consists of mapping deforestation in Sao Felix do Xingu, Southern Para (Brazilian Amazon) using Landsat TM images. Three fraction images representing proportion of bare soil, vegetation, and shade were estimated from the Liner Spectral Mixture Model (LSMM). We choose in this study the shade fraction to discriminate cleared areas because it is well correlated with forest structure. While undisturbed tropical forests usually have medium proportion of shade, cleared areas have low shade content. After segmentation, the homogeneous regions were grouped using an unsupervised classifier named ISOSEG. Key words: Deforestation, Mixture model, Shade fraction image, Multi-temporal analysis. Resumen El objetivo del trabajo es mapear el progreso de la deforestacion en el municipio de Sao Felix do Xingu, Sur de Para (amazonia brasilena), utilizando imagenes Landsat TM. La tecnica del modelo lineal de mezcla espectral (MLME) fue empleada para reducir el volumen de datos y destacar las areas deforestadas. Tres imagenes-fraccion que representan las proporciones de suelo expuesto, vegetacion y sombra se derivaron del MLME. El mapeo de la deforestacion se ha hecho utilizando los atributos del imagen-fraccion sombra que se correlaciona bien con la estructura de la cubierta forestal: mientras que las zonas de bosques intactas tienen un medio coeficiente de sombra (en funcion de la rugosidad de la cubierta), el barbecho, las areas de pastizales y suelo desnudo poseen una baja proporcion en sus estructuras. Despues de la segmentacion, las regiones se combinaron con un clasificador no supervisado por regiones denominado como ISOSEG. Palabras clave: Deforestacion, Modelo de mezcla espectral, Imagenes-fraccion sombra.

AS MULHERES NO MERCADO DE TRABALHO: O SETOR TÊXTIL E DE CONFECÇÕES

Nos dias de hoje, o mundo do trabalho sofre reestruturacao, novas ocupacoes aparecem e individuos migram para novos empregos. Apesar disso, algumas formas de atividades ainda persistem neste âmbito. As mulheres trabalhadoras em atividades atreladas ao setor textil e de confeccoes ainda consiste em uma das ocupacoes que persistem nessas transformacoes. Baseando-se no tratamento e na analise das informacoes contidas nos recenseamentos gerais de 2000 e 2010, o objetivo deste artigo consiste em caracterizar as mulheres inseridas neste tipo de ocupacao laboral, no Oeste e no Sudoeste da Regiao Metropolitana de Sao Paulo.