Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Ordenar por: RelevânciaAutorTítuloAnoImprime registros no formato resumido
Registros recuperados: 33
Primeira ... 12 ... Última
Imagem não selecionada

Imprime registro no formato completo
A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Repositório Alice
LI, G.; LU, D.; DUTRA, L.; BATISTELLA, M..
This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected textural images and correlation coefficients between them were then used to determine the best combination of texture images for land-cover classification. Classification results based on different scenarios with maximum likelihood classifier were compared. Based on the identified best scenarios, different classification algorithms ? maximum likelihood classifier,...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: ALOS PALSAR; RADARSAT; Texture; Land-cover classification; Amazon.
Ano: 2012 URL: http://www.alice.cnptia.embrapa.br/handle/doc/924819
Imagem não selecionada

Imprime registro no formato completo
A Comparative analysis of satellite-based approaches for aboveground biomass estimation in the Brazilian Amazon. Repositório Alice
LU, D.; MORAN, E.; BATISTELLA, M..
The moist tropical forest in the Amazon has been regarded as an important part in global carbon budget. Deforestation since the 1970s has made it an important carbon source, but the rapid growth of secondary vegetation may compensate its negative role to a certain degree. In order to reduce the uncertainty in carbon estimation at regional or global scale, it is critical to timely provide the carbon spatial distribution with high accuracy. Remotely sensed data have become the primary source for mapping carbon storage at local or regional scale. Thanks to the NASA LBA-ECO funded projects (1998 - 2008), we have explored aboveground biomass (AGB) estimation in the eastern and western Brazilian Amazon with Landsat Thematic Mapper (TM) images. Different TM...
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Integração do fluxo de carbono; Observação de torres e aeronaves; Análise de imagens de satélite; Amazonas; Brasil.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31654
Imagem não selecionada

Imprime registro no formato completo
A comparative study of landsat TM and SPOT HRG images of vegetation classification in the brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M.; MIRANDA, E. E. de.
Complex forest structure and abundant tree species in the moist tropical regions often couse difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HBG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Comparative study; Landsat TM and SPOT HRG Images; Brazilian Amazon; Moist tropical regions; Machadinho d´Oeste.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31577
Imagem não selecionada

Imprime registro no formato completo
A comparative study of Terra ASTER, Landsat TM, and SPT HRG data for land cover classification in the Brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E. F.; MIRANDA, E. E. D..
2005
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Classificação vegetal; Vegetação; Bacia hidrográfica Amazonica; Amazonia; Amazonas; Sensoriamento Remoto.
Ano: 2005 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17473
Imagem não selecionada

Imprime registro no formato completo
A comparison of multisensor integration methods for land cover classification in the Brazilian Amazon. Repositório Alice
LU, D.; LI, G.; MORAN, E.; DUTRA, L.; BATISTELLA, M..
Many data fusion methods are available, but it is poorly understood which fusion method is suitable for integrating Landsat Thematic Mapper (TM) and radar data for land cover classification. This research explores the integration of Landsat TM and radar images (i.e., ALOS PALSAR L-band and RADARSAT-2 C-band) for land cover classification in a moist tropical region of the Brazilian Amazon. Different data fusion methods?principal component analysis (PCA), wavelet-merging technique (Wavelet), high-pass filter resolution-merging (HPF), and normalized multiplication (NMM)?were explored. Land cover classification was conducted with maximum likelihood classification based on different scenarios. This research indicates that individual radar data yield much poorer...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Landsat Thematic Mapper; Wavelet multisensor.
Ano: 2011 URL: http://www.alice.cnptia.embrapa.br/handle/doc/902113
Imagem não selecionada

Imprime registro no formato completo
Aboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates. Repositório Alice
LU, D.; CHEN, Q.; WANG, G.; MORAN, E.; BATISTELLA, M.; ZHANG, M.; LAURIN, G. V.; SAAH, D..
Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Biomassa.
Ano: 2012 URL: http://www.alice.cnptia.embrapa.br/handle/doc/922003
Imagem não selecionada

Imprime registro no formato completo
Application of spectral mixture analysis to Amazonian land-use and land-cover classification. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E.; MAUSEL, P..
Abundant vegetation species and associated complex forest stand structures in moist tropical regions often create difficulties in accurately classifying land-use and land-cover (LULC) features. This paper examines the value of spectral mixture analysis (SMA) using Landsat Thematic Mapper (TM) data for improving LULC classification accuracy in a moist tropical area in Rondbnia, Brazil. Different routines, such as constrained and unconstrained least-squares solutions, different numbers of endmembers, and minimum noise fraction transformation, were examined while implementing the SMA approach. A maximum likelihood classifier was also used to classify fraction images into seven LULC classes: mature forest, intermediate secondary succession, initial secondary...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Vegetation species; Landsat Thematic Mapper.
Ano: 2004 URL: http://www.alice.cnptia.embrapa.br/handle/doc/995070
Imagem não selecionada

Imprime registro no formato completo
Comparison of land-cover classification methods in the Brazilian Amazon Basin. Repositório Alice
LU, D.; MAUSEL, P.; BATISTELLA, M.; MORAN, E..
Numerous classifiers have been developed and different classifiers have their own characteristics. Controversial results often occurred depending on the landscape complexity of the study area and the data used. Therefore, this paper aims to find a suitable classifier for the tropical land cover classification. Five classifiers ? minimum distance classifier (MDC), maximum likelihood classifier (MLC), fisher linear discriminant (FLD), extraction and classification of homogeneous objects (ECHO), and linear spectral mixture analysis (LSMA) ? were tested using Landsat Thematic Mapper (TM) data in the Amazon basin using the same training sample data sets. Seven land cover classes ? mature forest, advanced succession forest, initial secondary succession forest,...
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Extraction and classification of homogeneous; Fisher linear discriminant; Minimum distance classifier.
Ano: 2003 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1022621
Imagem não selecionada

Imprime registro no formato completo
Comparison of land-cover classification methods in the Brazilian Amazon Basin. Repositório Alice
LU, D.; MAUSEL, P.; BATISTELLA, M.; MORAN, E..
Four distinctly different classifiers were used to analyze multispectral data. Which of these classifiers is most suitable for a specific study area is not always clear. This paper provides a comparison of minimum-distance classifier (MDC), maximumlikelihood classifier (MLC), extraction and classification of homogeneous objects (ECHO), and decision-tree classifier based on linear spectral mixture analysis (DTC-LSMA). Each of the classifiers used both Landsat Thematic Mapper data and identical field-based training sample datasets in a western Brazilian Amazon study area. Seven land-cover classes? mature forest, advanced secondary succession, initial secondary succession, pasture lands, agricultural lands, bare lands, and water?were classified....
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Mapeamento; Satélite; Floresta tropical úmida; Bacia hidrográfica; Amazonia brasileira; Amazonas.
Ano: 2004 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17039
Imagem não selecionada

Imprime registro no formato completo
Detecting Amazonian deforestation using multitemporal thematic mapper imageries and spectral mixture analysis. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
Linear spectral mixture analysis (LSMA) and multitemporal Thematic Mapper (TM) data were used to detect deforestation in Altamira and Machadinho, Brazilian Amazon. Standardized principal component analysis was used to transform TM data into uncorrelated principal components (PCs). Three endmembers were selected and an unconstrained least root-mean squared error solution was used to unmix the first four PCs into three fraction images. Mature forest classification was implemented using thresholds and deforestation detection using binary image overlay. This study indicates that LSMA is an effective method to identify mature forest and detect deforested areas with high accuracies.
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Mapeamento; Altamira; Machadinho d´Oeste; Rondônia; Amazonas; Brasil; Floresta; Satélite; Amazonia.
Ano: 2003 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/17038
Imagem não selecionada

Imprime registro no formato completo
Exploring approaches to improve the performance for separating successional vegetation stages in the Brazilian Amazon with remote sensing data. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
The rapid growth of successional vegetation has played an important role in reducing the carbon emission to atmosphere. However, lack of spatial data sets of successional vegetation with different stages has been regarded as an important source causing the uncertainty in carbon estimation in the Amazon. The complex vegetation stand structure and associated abundant tree species often induce difficulty in vegetation classification in the moist tropical regions with remotely sensed data. With the NASA LBA-ECO funding support (1998 - 2008), we have examined successional vegetation classification in Rondonia, Brazil, through comparative analyses of different image procedures. Different sensor data, i.e., Landsat TM/ETM+, Terra ASTER, and SPOT HRG, were used....
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Dinamica florestal; Pertubações naturais; Regeneração; Amazonas; Lba-Eco.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31673
Imagem não selecionada

Imprime registro no formato completo
Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M..
Muitas medidas de textura têm sido desenvolvidas e utilizadas para melhorar a acurácia de classificações de cobertura das terras, mas raramente têm-se avaliado a importância dessas medidas em estimativas de biomassa. O trabalho utilizou dados Landsat TM para explorar as relações entre texturas de imagens TM e biomassa em Rondônia, Amazônia.
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Textura; Biomassa; Imagens TM; Correlação; Amazônia.
Ano: 2005 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17497
Imagem não selecionada

Imprime registro no formato completo
Fractional forest cover mapping in the Brazilian Amazon with a combination of MODIS and TM images. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E.; HETRICK, S.; ALVES, D.; BRONDIZIO, E..
2011
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Deforestation.
Ano: 2011 URL: http://www.alice.cnptia.embrapa.br/handle/doc/899168
Imagem não selecionada

Imprime registro no formato completo
From the Landscape to the region: scaling up approaches in human and physical dimensions of land-use and land-cover change in the Amazon. Repositório Alice
BATISTELLA, M.; ALVES, D.; LU, D.; MORAN, E. F.; BRONDIZIO, E. S.; D'ANTONA, A..
2006
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Land use and land cover change.
Ano: 2006 URL: http://www.alice.cnptia.embrapa.br/handle/doc/1008591
Imagem não selecionada

Imprime registro no formato completo
Integrating field data and remote sensing to identify secondary succession stages in the Amazon. Repositório Alice
BATISTELLA, M.; LU, D..
Secondary succession (SS) of tropical forest ecosystems follows disturbances such as deforestation. Sharp distinctions between SS stages are often artificial, but useful in Land-Use/Land-Cover (LULC) classifications. In this paper, results for vegetation structure in Rondônia, Brazilian Amazon, are presented as a basis for discussing the reflectance of SS stages when using Landsat TM imagery. Vegetation structure data were collected through 32 surveys encompassing initial SS (SS1), intermediate SS (SS2), advanced SS (SS3), and forest. The results informed the classification of a TM image acquired in 1998. Statistical analyses were performed. SS1, SS2, SS3, and forest were well separated when using solely the data for vegetation structure (p<0.001)....
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Floresta tropical umida; Desmatamento; Sensoriamento remoto; Amazonas.
Ano: 2002 URL: http://www.alice.cnptia.embrapa.br/handle/doc/16844
Imagem não selecionada

Imprime registro no formato completo
Integrating field data and remote sensing to study secondary forests in Amazonian rural settlements. Repositório Alice
BATISTELLA, M.; LU, D..
Secondary forests in the Amazon gained importance when attention was called to processes following landscape disturbances, such as deforestation. Sharp distinctions between successional stages are often artificial, but sometimes useful to characterize selected landscapes and to estimate their role in carbon sequestration.
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Amazon forests.
Ano: 2004 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17708
Imagem não selecionada

Imprime registro no formato completo
Integration of landsat TM and SPOT HRG Images for vegetation change detection in the Brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
Traditional change detection approaches have been proven to be difficult in detecting vegetation changes in the moist tropical regions with multitemporal images. This paper explores the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data for vegetation change detection in the Brazilian Amazon. A principal component analysis was used to integrate TM and HRG panchromatic data. Vegetation change/non-change was detected with the image differencing approach based on the TM and HRG fused image and the corresponding TM and HRG multispectral images into thematic maps with three coarse land-cover classes: forest, non-forest vegetation, and non-vegetation lands. A hybrid approach combining image differencing and...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Brazilian Amazon; Image collection and preprocessing; Vegetation Chance Detection.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31571
Imagem não selecionada

Imprime registro no formato completo
Integration of vegetation inventory data and thematic mapper image for Amazonian successional and mature forest classification. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E. F..
Successional and mature forest classification is often difficult in moist tropical regions. This paper explores vegetation stand structures of successional and mature forests and their spectral characteristics. Canonical discriminant analysis (CDA) was used to identify important stand parameters for secondary succession and mature forest classification. Correlation coefficient was used to analyze different stand parameter relationships and associated TM spectral signatures. Transformed divergence was used to analyze the separability of succession stages and mature forest based on the resultant images from CDA and principal component analysis (PCA), respectively. This study indicates that five vegetation categories, i.e., initial succession, intermediate...
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Mapeamento; Amazonas; Floresta; Vegetação.
Ano: 2003 URL: http://www.alice.cnptia.embrapa.br/alice/handle/doc/17037
Imagem não selecionada

Imprime registro no formato completo
Land use/cover classification in the Brazilian Amazon using satellite images. Repositório Alice
LU, D.; BATISTELLA, M.; LI, G.; MORAN, E.; HETRICK, S.; FREITAS, C. DA C.; SANT'ANNA, S. J..
Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation?based method are valuable ways to improve land use/cover...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Data fusion; Multiple sensor data; Nonparametric classifiers; Texture.
Ano: 2012 URL: http://www.alice.cnptia.embrapa.br/handle/doc/940299
Imagem não selecionada

Imprime registro no formato completo
Land-cover binary change detection methods for use in the moist tropical regiona of the Amazon: a comparative study. Repositório Alice
LU, D.; MAUSEL, P.; BATISTELLA, M.; MORAN, E..
Many land-cover change detection techniques have been developed; however, different conclusions about the value or appropriateness of each exist. This difference of opinion is often influenced by the landscape complexity of study areas and data used for analysis. Which method is most suitable for land-cover change detection in Amazon tropical regions remains unclear. ln this paper, 10 binary change detection methods were implemented and compared with respect to their capability to detect land-cover change and no change conditions in moist tropical regions. They are image differencing (ID), modified image differencing (MID), a combination of image differencing and principal component analysis (IDPCA), principal component differencing (PCD), multitemporal...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Vegetação; Monitoramento; Satélite; Região Amazônica; Amazonas.
Ano: 2005 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17488
Registros recuperados: 33
Primeira ... 12 ... Última
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional