Luis Marcelo Tavares de Carvalho

Universidade Federal de Lavras (UFLA), Lavras, Minas Gerais, Brazil

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Publications (40)7.42 Total impact

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    ABSTRACT: Este trabalho analisou a fragmentação florestal da Área de Proteção Ambiental Coqueiral, que está localizada no município de Coqueiral, região Sul do estado de Minas Gerais. O objetivo foi avaliar a fragmentação florestal da área de estudo, a partir de métricas da paisagem, bem como elaborar modelos de simulação da paisagem, no intuito de fornecer cenários futuros de restauração ecológica, e compará-los com a situação atual da paisagem. A análise do uso e ocupação da terra foi obtida por meio de técnicas de Sistemas de Informação Geográfica e Sensoriamento Remoto, a partir de uma imagem (SPOTMAP) do satélite SPOT 5. A análise da fragmentação florestal foi realizada utilizando o software FRAGSTATS, para calcular as métricas da paisagem mensurando parâmetros como: área, perímetro, forma, conectividade dos fragmentos. Para as simulações da paisagem foram criados buffers de 1 e 5 m no entorno de todos os remanescentes florestais da área de estudo, bem como a recuperação virtual das áreas de preservação permanente. A análise da fragmentação da paisagem mostrou que a vegetação natural está distribuída em 360 fragmentos, sendo 137 deles menores que 1 ha. Os modelos de simulação da paisagem mostraram que a área de vegetação aumentou de 1943,13 ha para 2299,02 ha na simulação em que as APPs foram reflorestadas (Vegetação natural/APPs restauradas = VA). O tamanho médio dos fragmentos nesta mesma simulação aumentou em relação à paisagem atual, passando de 7,66 m para 15,75 m. A paisagem VA mostrou um menor valor de forma (1,93), indicando que a forma dos fragmentos nesta simulação foi mais simples, o que é importante do ponto de vista da conservação, pois diminui o efeito de borda nos fragmentos. Os valores de isolamento não apresentaram diferença considerável nas simulações: 38,9 m (VN); 40,64 m (VB1); 42,89 m (VB5) e 39,75 m (VA), indicando um baixo isolamento dos fragmentos, mesmo na paisagem atual. O índice de conectividade foi alto (acima de 99%) para todas as simulações, indicando que as paisagens apresentam elevada conectividade estrutural. Estes dados são relevantes subsídios para a tomada de decisão e para gestão e planejamento da Área Proteção Ambiental Coqueiral, permitindo a indicação de áreas prioritárias para conservação.
    07/2014; 24(3):631-644.
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    ABSTRACT: Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities) of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ) of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops) is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level) the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C).
    Ciência e Agrotecnologia 12/2013; 37(6):538-549. · 0.73 Impact Factor
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    ABSTRACT: Characterizations of land-cover dynamics are among the most important applications of Earth observation data, providing insights into management, policy and science. Recent progress in remote sensing and associated digital image processing offers unprecedented opportunities to detect changes in land cover more accurately over increasingly large areas, with diminishing costs and processing time. The advent of high-spatial-resolution remote-sensing imagery further provides opportunities to apply change detection with object-based image analysis (OBIA), that is, object-based change detection (OBCD). When compared with the traditional pixel-based change paradigm, OBCD has the ability to improve the identification of changes for the geographic entities found over a given landscape. In this article, we present an overview of the main issues in change detection, followed by the motivations for using OBCD as compared to pixel-based approaches. We also discuss the challenges caused by the use of objects in change detection and provide a conceptual overview of solutions, which are followed by a detailed review of current OBCD algorithms. In particular, OBCD offers unique approaches and methods for exploiting high-spatial-resolution imagery, to capture meaningful detailed change information in a systematic and repeatable manner, corresponding to a wide range of information needs.
    International Journal of Remote Sensing 07/2012; 33(14):4434-4457. · 1.36 Impact Factor
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    ABSTRACT: Light Detection and Ranging, or LIDAR, has become an effective ancillary tool to extract forest inventory data and for use in other forest studies. This work was aimed at establishing an effective methodology for using LIDAR for tree count in a stand of Eucalyptus sp. located in southern Bahia state. Information provided includes in-flight gross data processing to final tree count. Intermediate processing steps are of critical importance to the quality of results and include the following stages: organizing point clouds, creating a canopy surface model (CSM) through TIN and IDW interpolation and final automated tree count with a local maximum algorithm with 5 x 5 and 3 x 3 windows. Results were checked against manual tree count using Quickbird images, for verification of accuracy. Tree count using IDW interpolation with a 5x5 window for the count algorithm was found to be accurate to 97.36%. This result demonstrates the effectiveness of the methodology and its use potential for future applications.
    Cerne 06/2012; 18(2):175-184. · 0.36 Impact Factor
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    Sustainable Forest Management - Case Studies, 04/2012; , ISBN: 978-953-51-0511-4
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    Phenology and Climate Change, 03/2012; , ISBN: 978-953-51-0336-3
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    ABSTRACT: This study analyzed the landscape structure of the Coqueiral Protected Area, located in southern Minas Gerais. We aimed to evaluate the landscape structure in the study area, based on landscape metrics and indicate priority areas for conservation. We use Geographic Information Systems and Remote Sensing tools to construct a land use map from a HCR SPOT 5 satellite image. Landscape structure analysis was carried out through Fragstats software and used landscape metrics. Results showed pasture class was considered as the landscape matrix and occupied almost half of the protected area. Landscape structure analysis showed the landscape is dominated by agropastoral activities. The landscape presented 704 units. Mean patch size area was higher for pasture than semideciduous forest, while semideciduous forest presented higher patch density. Land use classes showed complex shapes indicating higher edge effects. Pasture had the lower patch isolation. Data obtained in this study are relevant for decision making and environmental planning of the Coqueiral Protected Area, allowing suggest priority areas for conservation.
    Brazilian Journal of Ecology. 01/2012; 1:105-114.
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    ABSTRACT: Conservation Units are among the best methods found to secure biodiversity conservation. The physical and biotic characteristics of high altitude areas such as Serra de Carrancas and Luminárias, in Minas Gerais state, make these places a home to endemic species and to rich biodiversity. However, these environments are highly susceptible to fast advancing erosive processes that potentially lead to soil, habitat and species loss. This study aims to evaluate the physical and biotic characteristics of the Serra de Carrancas and Luminárias region using Natural Vulnerability indicators, and also to propose Conservation Unit implementation in areas which, as per this index, are considered environmentally critical and highly sensitive to anthropic actions. Biotic and abiotic indicators, as managed by a geographic information system, identifi ed the most vulnerable areas in the study site and, given the sensitivity and scope of Serra de Carrancas and Luminárias, a State Park was proposed. The natural vulnerability index proved to be an effective tool to pinpoint prospective conservation unit areas, gathering important environmental factors and thus improving the effi ciency of conservation strategies.
    Cerne 01/2011; 17(2):151-159. · 0.36 Impact Factor
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    ABSTRACT: Multi-temporal images are now of standard use in remote sensing of vegetation during monitoring and classification.Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated, poses many challenges, primarily due tosignal to noise-related issues. This study investigates which methods generate the most appropriate smoothed curves of vegetationsignatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm which is based on Fourieranalyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The study was conductedin four different regions of the Minas Gerais State. The smoothed data were used as input data vectors for vegetation classificationby means of artificial neural networks for comparison purpose. A comparison of the results was ultimately discussed in this workshowing encouraging results and similarity between the two filtering techniques used.
    Cerne 01/2010; · 0.36 Impact Factor
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    ABSTRACT: Temporal vegetation signatures (i. e., vegetation indices as functions of time) generated using the MODIS instrument poses many challenges, primarily due to signal to noise-related issues Bruce et al. (2006). This study investigates which methods best generate smoothed curves of vegetation signatures on MODIS NDVI time series. The filtering techniques compared were the HANTS algorithm, Verhoef (1996), which is based on Fourier analyses and Wavelet temporal algorithm which uses the wavelet analysis to generate the smoothed curves. The smoothed data were used as input data vectors for vegetation classification by means of Artificial neural networks. Statistics of the classifications reveal that the Wavelet filtering algorithm outperforms the original time series and the HANTS fft derived algorithms in all cases in all the classification algorithms.
    01/2009;
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    ABSTRACT: This paper describes the methodology used for monitoring changes in forest and natural vegetation cover in Minas Gerais, Brazil. The state of Minas Gerais is characterized by a large geographical extent and an intense fragmentation history. Both characteristics limit the application of traditional change detection algorithms demanding a large number of trained inpterpreters to separate noise from real land cover changes. Hence, the objective of this work was to develop and implement a procedure for digital change detection which is less sensitive to erros cause by misregistration, phonological state of the vegetation and atmospheric conditions. Landsat images form circa 2005 and circa 2007 acquired over Minas Gerais, as well as a land cover map produced in 2005 were used for change detection. The methodology is based on multiresolution wavelet analysis and local maxima detection in order to pinpoint multscale change objects. The change objects were recursively segmented from coarse to fine scale levels. The results showed that the method is less sensitive to radiometric and geometric misregistration. A new data base relative to vegetation cover classes for the year 2007 was produced and the change statistics were presented for the state of Minas Gerais Palavras-chave: remote sensing, image processing, forest monitoring, sensoriamento remoto, processamento de imagens, monitoramento florestal.
    01/2009;
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    ABSTRACT: O objetivo deste trabalho foi caracterizar a dinâmica sazonal do cerrado, floresta estacional semidecidual e decidual nonorte do estado de Minas Gerais, Brasil. Séries multitemporais dos índices de vegetação NDVI (índice de vegetação da diferençanormalizada) e EVI (índice de vegetação melhorado) derivados do sensor MODIS, foram comparadas analisando o perfil temporale os resultados de classificação das imagens. Os resultados mostraram que: (1) Os índices de vegetação estudados refletiram opadrão sazonal das fisionomias, diferenciando os períodos chuvosos e os períodos de seca; (2) a fisionomia floresta estacionaldecidual apresentou menores valores dos índices e maior variação; (3) as fisionomias cerrado e floresta estacional semidecidualapresentaram alto valores dos índices e baixa variação; (4) de acordo com os resultados das classificações o melhor índice para omapeamento das fisionomias na área de estudo foi o NDVI, porém ambos podem ser usados para avaliar a dinâmica sazonal davegetação; e (5) estudos precisam ser realizados explorando algoritmos de extração de feições para melhorar a acuracidade domapeamento das fisionomias cerrado, floresta decídua e semidecidua na área de estudo.
    Cerne. 01/2008;
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    ABSTRACT: The objectives of this work were to characterize seasonal dynamics of cerrado, deciduous and semideciduous forests in the north of Minas Gerais, Brazil. Time series of NDVI (Normalized Difference Vegetation Index) and EVI (Enhanced Vegetation Index) derived from MODIS (MODerate-resolution Imaging Spectroradiometer) sensor, were compared by analyzing temporal profiles and image classification results. The results showed that: (1) there is an agreement between vegetation indices and the monthly precipitation pattern; (2) deciduous forest showed the lowest values and the highest variation; (3) cerrado and the semideciduous forest presented higher values and lower variation; (4) according to the paired Student's test there was a significant difference between the NDVI and EVI values (5) the NDVI showed higher values than the EVI; (6) based on the classification accuracies the best vegetation index for mapping the vegetation classes in the study area was the NDVI, however both indices might be used to assess the vegetation seasonal dynamic; and (7) further research need to be carried out exploring the use of feature extraction algorithms to improve classification accuracy of cerrado, semideciduous and deciduous forests in Minas Gerais, Brazil.
    Analysis of Multi-temporal Remote Sensing Images, 2007. MultiTemp 2007. International Workshop on the; 08/2007
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    ABSTRACT: Our objective was to develop a procedure for change detection which is less sensitive to problems caused by misregistration, atmospheric effects and variations in vegetation phenology. The procedure is based on redundant wavelet transforms. Wavelet correlation was explored by taking point wise products of adjacent scales in order to enhance coefficients due to changes and smooth out noises. Local maxima were detected on the product spaces at varying spatial resolutions. The detected maxima were used as seeds for a multiscale region growing algorithm. The results showed that the method is not sensitive to geometric and radiometric misregistrations because of the multiresolution approach to feature extraction.
    Analysis of Multi-temporal Remote Sensing Images, 2007. MultiTemp 2007. International Workshop on the; 08/2007
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    07/2007: pages 237-270;
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    Frederico Pereira Reis, Luciano T. de Oliveira, Luis Marcelo T. de Carvalho
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    ABSTRACT: The present work aims at performing automatic tree crown counting in planted Eucalypt forests. High resolution remote sensing imagery and digital image processing using Lee Filters and the unsupervised classification algorithm ISODATA were used. The classification result that best extracted tree crowns was exported to a GIS for tree counting. The resulting number of trees was compared to the number obtained by visual interpretation. Resumo. O presente trabalho objetiva, através da utilização de imagens de sensoriamento remoto de alta resolução e processamento digital de imagens, realizar a contagem automática de copas individuais em um povoamento plantado de Eucalyptus spp., através da técnica que associa o filtro de Lee com o classificador não-supervisionado ISODATA. Após as etapas de processamento, o resultado da classificação que mais representou as copas das árvores foi exportado para ambiente SIG (Sistema de Informações Geográficas), onde foi realizada a contagem automática dos polígonos que representaram melhor as copas. Os resultados foram comparados com o parâmetro, que foi obtido através da interpretação visual da imagem.
    IX Brazilian Symposium on Geoinformatics, 25-28 November, Campos do Jordão, São Paulo, Brazil; 01/2007
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    ABSTRACT: This paper describes the research carried out within the framework of the Ecological Economical,Zoning of Minas Gerais (ZEE-MG) to model vegetation vulnerability derived by a number,of spatial inference methods. Methods based on weighted overlay, fuzzy logic, and neural networks were compared in terms of visual similarity between maps, the degree of restrictiveness concerning vulnerability, and the easiness of implementation. It was concluded,that weighted,overlay is the best approach,to be used within the ZEE-MG. Resumo. Este artigo descreve os estudos realizados durante os trabalhos do
    IX Brazilian Symposium on Geoinformatics, 25-28 November, Campos do Jordão, São Paulo, Brazil; 01/2007
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    Gleyce Campos Dutra, Luis Marcelo Tavares de Carvalho, Ary Teixeira de Oliveira Filho
    IX Brazilian Symposium on Geoinformatics, 25-28 November, Campos do Jordão, São Paulo, Brazil; 01/2007
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    ABSTRACT: This present work describes the classification of the Phytophysiognomies present in the Brazilian Cerrado biome through the means Artificial Intelligence; data from remote sensing images and other sources served as input for these algorithms to generate the vegetation maps. The data acquired was of many types so that it fully described the various Phytophysiognomies present in biome and served as training data for the machine learning algorithms. Various statistical and neuro-computation based algorithms were used for pattern recognition in the data so that we could build a good generalization model for the biome. A vegetation map was successfully generated with each algorithm. Finally a comparison among these algorithms was made so that we could find the best algorithm that fitted the problem of mapping this biome.
    IX Brazilian Symposium on Geoinformatics, 25-28 November, Campos do Jordão, São Paulo, Brazil; 01/2007
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    ABSTRACT: This meta paper is the thematic map accuracy assessment of "Mapeamento da Flora Nativa e dos Reflorestamentos de Minas Gerais". It will enclose the Minas Gerais State all and it will use, for attainment of points you show that they portray the truth terrestrial the procedure of random estratified sampling. In this sampling design will be placed 250 points in the thematic class with bigger area of covering in the State and, excessively, divided proportionally in the too much class. One expects to get with this study an assesment of the thematic classification of the "Mapeamento da Flora Nativa e dos Reflorestamentos de Minas Gerais" to assure the trustworthiness of the information for it generated. Moreover, to more establish a strategy of adjusted sampling for this evaluation, guaranteeing efficiency of costs and statistical severity.
    01/2007;

Publication Stats

102 Citations
7.42 Total Impact Points

Institutions

  • 2007–2014
    • Universidade Federal de Lavras (UFLA)
      • • Departamento de Ciência do Solo
      • • Departamento de Ciências Florestais
      Lavras, Minas Gerais, Brazil
    • Centro Universitário de Lavras
      Lavras, Minas Gerais, Brazil
  • 2004
    • Wageningen University
      Wageningen, Gelderland, Netherlands