Classificação de padrões de savana usando assinaturas temporais NDVI do sensor MODLS no Parque Nacional Chapada dos Veadeiros
暂无分享,去创建一个
Nilton Correia da Silva | Osmar Abílio de Carvalho Júnior | Roberto Arnaldo Trancoso Gomes | Ana Paula Ferreira de Carvalho | Cárita da Silva Sampaio | Yosio Edemir Shimabukuro | O. Junior | A. F. C. Júnior | R. A. T. Gomes | N. Silva | A. Carvalho | Antônio Felipe Couto Júnior | Carita da Silva Sampaio
[1] L. Richardson,et al. Remote Sensing of Algal Bloom DynamicsNew research fuses remote sensing of aquatic ecosystems with algal accessory pigment analysis , 1996 .
[2] Gregory Asner,et al. Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis , 2000, IEEE Trans. Geosci. Remote. Sens..
[3] P. Switzer,et al. A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .
[4] O. Junior,et al. UTILIZAÇÃO DO CLASSIFICADOR SPECTRAL CORRELATION MAPPER EM IMAGENS TM-LANDSAT , 2002 .
[5] P. R. Meneses,et al. Spectral Correlation Mapper ( SCM ) : An Improvement on the Spectral Angle Mapper ( SAM ) , 2000 .
[6] M. C. Hansena,et al. Development of a MODIS tree cover validation data set for Western Province , Zambia , 2002 .
[7] Jesslyn F. Brown,et al. Measuring phenological variability from satellite imagery , 1994 .
[8] G. Eiten,et al. The cerrado vegetation of Brazil , 1972, The Botanical Review.
[9] Andreas T. Ernst,et al. ICE: a statistical approach to identifying endmembers in hyperspectral images , 2004, IEEE Transactions on Geoscience and Remote Sensing.
[10] John F. Mustard,et al. Optimization of Endmembers Mixture Analysis for Spectral , 2002 .
[11] S. Sader,et al. Remote sensing of tropical forests : an overview of research and applications using non-photographic sensors , 1990 .
[12] Brian Curtiss,et al. A method for manual endmember selection and spectral unmixing , 1996 .
[13] J. B. Lee,et al. Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform , 1990 .
[14] J. Townshend,et al. Global discrimination of land cover types from metrics derived from AVHRR pathfinder data , 1995 .
[15] R. F. Guimarães,et al. Análise comparativa do processo de identificação automatizada de membros finais a partir de imagens com diferentes resoluções espectrais para a região de Niquelândia (AVIRIS, ETM+ e ASTER) , 2005 .
[16] Hui Qing Liu,et al. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise , 1995, IEEE Transactions on Geoscience and Remote Sensing.
[17] J. A. Schell,et al. Monitoring vegetation systems in the great plains with ERTS , 1973 .
[18] A. Huete,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .
[19] Paul E. Johnson,et al. Quantitative determination of mineral types and abundances from reflectance spectra using principal components analysis , 1985 .
[20] A. Huete,et al. Optical characterization of the Brazilian Savanna physiognomies for improved land cover monitoring of the cerrado biome: preliminary assessments from an airborne campaign over an LBA core site , 2004 .
[21] Yosio Edemir Shimabukuro,et al. Integração de dados de sensoriamento remoto multi resoluções para a representação da cobertura da terra utilizando campos contínuos de vegetação e classificação por árvores de decisão , 2007 .
[22] E. E. Sano,et al. Assessing the spatial distribution of cultivated pastures in the Brazilian savanna. , 2000 .
[23] Renato Fontes Guimarães,et al. IDENTIFICAÇÃO REGIONAL DA FLORESTA ESTACIONAL DECIDUAL NA BACIA DO RIO PARANÃ A PARTIR DA ANÁLISE MULTITEMPORAL DE IMAGENS MODIS , 2006 .
[24] Alba Valéria Rezende,et al. Estudo fenológico de Stryphnodendron adstringens (Mart.) Coville no cerrado sensu stricto da Fazenda Água Limpa no Distrito Federal, Brasil , 1999 .
[25] C. E. Doll,et al. Overview of TDRSS , 1995 .
[26] J. C. Price. Estimating vegetation amount from visible and near infrared reflectances , 1992 .
[27] G. Woodwell,et al. Map of the vegetation of South America based on satellite imagery , 1994 .
[28] G. Asner. Biophysical and Biochemical Sources of Variability in Canopy Reflectance , 1998 .
[29] Bruce Dickson,et al. Noise reduction of aerial gamma-ray surveys , 1998 .
[30] F. G.,et al. DISCRIMINATION AND BIOPHYSICAL CHARACTERIZATION OF CERRADO PHYSIOGNOMIES WITH EO-1 HYPERSPECTRAL HYPERION , 2003 .
[31] D. Roy,et al. Achieving sub-pixel geolocation accuracy in support of MODIS land science , 2002 .
[32] V. Ambrosia,et al. The detection of algal photosynthetic accessory pigments using airborne visible-infrared imaging spectrometer (AVIRIS) spectral data , 1994 .
[33] J. W. Boardman,et al. FIFTEEN YEARS OF HYPERSPECTRAL DATA: NORTHERN GRAPEVINE MOUNTAINS, NEVADA , 1999 .
[34] R. F. Guimarães,et al. Classificação e eliminação dos ruídos em imagens hiperespectrais pela análise seqüencial da transformação por Fração de Ruído Mínima , 2002 .
[35] J. Townshend,et al. NDVI-derived land cover classifications at a global scale , 1994 .
[36] D. Roy,et al. An overview of MODIS Land data processing and product status , 2002 .
[37] P. J. Curran,et al. Multispectral remote sensing for the estimation of green leaf area index , 1983, Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences.