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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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Land-cover classification in the Brazilian Amazon with the integration of Landsat ETM + and Radarsat data. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
Land-cover classification with remotely sensed data in moist tropical regions in a challenge due to the complex biophysical conditions. This paper explores techniques to improve land-cover classification accuracy through a comparative analysis of different combinations of spectral signatures and textures from Landsat Enhanced Thematic Mapper Plus (ETM +) and Radarsat data. A wavelet-merging technique was used to integrate Landsat ETM + multispectral and panchromatic data or Radarsat data. Grey-level co-occurrence matrix (GLCM) textures based on Landsat ETM + panchromatic of Radarsat data and different sizes of moving windows were examined. A maximum-likelihood classifier was used to implement image classification for different combinations. This research...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Amazon; Landsat ETM+; Land-cover.
Ano: 2007 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17678
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Leaching of essential nutrient cations and anions from undisturbed lowland forests across the Brazilian Amazon Basin. Repositório Alice
MCGRODDY, M.; HEDIN, L.; MORAN, E.; BATISTELLA, M..
2005
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Balanço de carbono; Ecossistema florestal; Floresta Amazonica; Amazonia.
Ano: 2005 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17511
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Linear mixture model applied to Amazonian vegetation classification. Repositório Alice
LU, D.; MORAN, E.; BATISTELLA, M..
2003
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Vegetação; Classificação; Cartografia; Modelo linear de mistura; Modelagem de dado; Sucessão secundária; Imagem de satélite; Mapa temático.
Ano: 2003 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17097
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Linear spectral mixture analysis of TM data for land-use and land-cover classification in Rondônia, Brazilian Amazon. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
2002
Tipo: Artigo em anais de congresso (ALICE) Palavras-chave: Linear spectral mixture analysis; Land cover; Classification; Thematic Mapper; Brazilian Amazon.
Ano: 2002 URL: http://www.alice.cnptia.embrapa.br/handle/doc/16752
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Mappig and monitoring land degradation risks in the western Brazilian Amazon using multitemporal landsat TM/ETM + IMAGES. Repositório Alice
LU, D.; BATISTELLA, M.; MAUSEL, P.; MORAN, E..
Mapping and monitoring land degradation in areas under human-induced stresses have urgent tasks in remote sensing whose importance has not yet been fully appreciated. In this study, a surface cover index (SCI) is developed to evaluate and map potential land degradation risks associated with deforestation and accompanying soil erosion in a Western Brazilian Amazon rural settlement study area. The relationships between land-use and land-cover (LULC) types and land degradation risks as well as the impacts of LULC change on land degradation are examined. This research indicates that remotely sensed data can be effectively used for identification and mapping of land degradation risks and monitoring of land degradation changes in the study area. Sites covered by...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Land degradation risk; Surface cover index; Spectral mixture analysis; Landsat TM/ETM+; Amazon; Brazil.
Ano: 2007 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17677
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Mapping of Fractional Forest Cover in Rondonia, Brazil with a Combination of Terra MODIS and Landsat TM Images. Repositório Alice
LU, D.; BATISTELLA, M.; ALVES, D. HETRICK, S.; MORAN, E..
High deforstation rates in Amazonia have motivated considerable efforts to monitor land-cover changes based on satellite images and image porcesssing techniques. Most commonly, MODIS images are used to provide low-cost region-wide coverage at nearly monthly frequencies, but they offer offer only coarse resolution, Lsndsat TM has been used in a majority of studies for nearly two decades, but these, but these data are expensive, and provide, at best, yearly coverage because of clouds. Here, a new approach to estimate forest change is proposed based on the integration of TM and MODIS images. TM images are processed using a hybrid approach including spectral mixture, expert rules, and usupervised classification, to generate a reference forest image. Three...
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Amazonia; MODIS images; Terra; Forest; Rondônia.
Ano: 2007 URL: http://www.alice.cnptia.embrapa.br/handle/doc/17602
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Multitemporal spectral mixture analysis for Amazonian land-cover change detection. Repositório Alice
LU, D.; BATISTELLA, M.; MORAN, E..
The complex landscape and environmental conditions in the moist tropical region often result in poor land-cover change detection accuracy using traditional change detection methods. This paper explores linear spectral mixture analysis (LSMA) of multitemporal thematic mapper (TM) images to detect land-cover change in Rondônia, Brazilian Amazon basin. Three image endmembers (shade, green vegetation, and soil) were developed based on a combination of field data and image scatterplots. An unconstrained least-squares solution was used to unmix the multitemporal TM images into three fractions. Then, fraction image differencing results were used to analyze land-cover change/non-change detection. The detailed ?from-to? change detection was implemented using a...
Tipo: Artigo em periódico indexado (ALICE) Palavras-chave: Tropical region; Remote sensing.
Ano: 2004 URL: http://www.alice.cnptia.embrapa.br/handle/doc/994980
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Pesquisas Interdisciplinares sobre a Transformação da Natureza e da Sociedade: um caminho para o entendimento das Mudanças de uso e cobertura das terras na Amazônia Repositório Alice
BATISTELLA, M.; MORAN, E.; ALVES, D..
Nesse trabalho discutimos a longa e tortuosa trajetória da interdisciplinaridade envolvendo ciências naturais e humanas no LBA, como amadurecimento do que foi chamado de pesquisa sobre as dimensões humanas da biosfera e atmosfera na Amazônia. Muitos colegas fizeram parte dessa discussão, contribuindo para uma leitura multifacetada apresentada pelos autores. Nosso fio condutor começa por uma critica do papel das ciências sociais no LBA, encarando um desafio que não havia sido formulado na concepção do programa, mas que se tornou imprescindível na busca do dialogo interdisciplinar, visto que as transformações relativamente recentes observadas na Amazônia são causa e consequência das transformações da própria sociedade. A contribuição de varias disciplinas...
Tipo: Resumo em anais de congresso (ALICE) Palavras-chave: Causas econômicas; Mudanças do uso; Cobertura da terra; Amazônia.
Ano: 2008 URL: http://www.alice.cnptia.embrapa.br/handle/doc/31675
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