Home Itens selecionados Provedores de dados OAI Créditos Sobre Ajuda

			Busca avançada
	Provedor de dados Ciências Agrárias (3) Anais da ABC (AABC) (2) Rev. Ciênc. Agron. (1) AgEcon (1) Colegio de Postgraduados (1) Acta Amazonica (1) BABT (1) REA (1) Mais... Autor HUDAK,ANDREW T. (2) KLAUBERG,CARINE (2) VIERLING,LEE A. (2) ADAMI,Marcos (1) ALMEIDA,Cláudio Aparecido de (1) Alves,Marcelo Rodrigo (1) Alves,Marcelo de C. (1) BERNETT,LUIZ G. (1) Batista, Getulio (1) Batista, Getulio Teixeira (1) CORTE,ANA PAULA D. (1) COUTINHO,Alexandre Camargo (1) Caballero Luis, Josafat (1) Carvalho,Luiz G. de (1) Catelani, Celso de Souza (1) Coltri,Priscila P. (1) DESSAY,Nadine (1) DINIZ,Cesar Guerreiro (1) DURIEUX,Laurent (1) Demattê,José A. M. (1) Mais... Palavra-chave Remote Sensing (11) Geographic Information System (2) LiDAR metrics (2) Sensoriamento Remoto (2) Agribusiness (1) Agricultura de Precisión (1) Agrometeorology (1) China (1) Comportamento espectral (1) Crop Monitoring (1) Detecção de Feições (1) Distritos de Riego (1) Dynamic change of the green land (1) Espectroscopia (1) Features of detection (1) Forest Inventory (1) Forest inventory (1) Geo-information tupu (1) Hidrociencias (1) Image Analysis (1) Mais... Tipo do documento Info:eu-repo/semantics/article (6) Article (3) Journal Article (1) Ano 2020 (1) 2018 (1) 2017 (1) 2016 (2) 2015 (1) 2013 (1) 2011 (1) 2007 (1) 2006 (1) 2004 (1) Mais... País Brazil (9) Mexico (1) United States (1) Idioma Inglês (8) Português (2) Espanhol (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 11 Primeira ... 1 ... Última A SPECTRAL AGROMETEOROLOGICAL MODEL FOR ESTIMATING SOYBEAN GRAIN PRODUCTIVITY IN MATO GROSSO, BRAZIL REA Sarmiento,Christiany M.; Coltri,Priscila P.; Alves,Marcelo de C.; Carvalho,Luiz G. de. ABSTRACT This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to... Tipo: Info:eu-repo/semantics/article Palavras-chave: Geographic Information System; Mathematical Modeling; Remote Sensing; Agrometeorology; Crop Monitoring. Ano: 2020 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000300405 Aplicação de rotinas morfológicas para detecção de redes de drenagem Ciências Agrárias Leonardi, Fernando; Silva, Erivaldo Antônio da. Brazil presents great deficiency in cartographic updating area. Many products are outdated around in 30 years in the several scales. A country that has the continental dimensions as Brazil needs have a solid cartographic base to take important decisions about urban planning and consequenting to administration of the territory. One way of updating the cartographic products is the combined use of remote sensing products and techniques of Digital Processing Images (DPI). Among many DPI tools, the Mathematical Morphology allied to the remote sensing data, is one alternative method used to minimize this problem. For the development of this work three images taken with the Landsat sensor was used, having draining net, as the interest features. In this paper was... Tipo: Article Palavras-chave: Sensoriamento Remoto; Remote Sensing; PDI; Detecção de Feições; Morfologia Matemática; Mathematical Morphology; Features of detection. Ano: 2007 URL: http://hdl.handle.net/2315/97 Dynamic Change Analysis of Urban Green Land in Jinan City Based RS and Geo-information Tupu AgEcon Xu, Qiu-xiao. The three-period (1995, 1998 and 2003) remote sensing images in Jinan City, China are selected. And the information of green land, construction land, woodland and water body is extracted by using the image processing module of remote-sensing software and computerized interpretation module. Both the change table and transfer matrix table of land use area are analyzed by modeling module of remote-sensing software. Then, the Geo-information Tupu is obtained; and the temporal and spatial variation of land use in Jinan City is monitored and analyzed by Geo-information Tupu and transfer matrix. Result shows that land use structure change of Jinan City in the years 1995-1998 shows a transformation from green land to construction land. Area of green land... Tipo: Journal Article Palavras-chave: Remote Sensing; Geo-information tupu; Dynamic change of the green land; Jinan; China; Agribusiness. Ano: 2011 URL: http://purl.umn.edu/108419 Estimating Stand Height and Tree Density in Pinus taeda plantations using in-situ data, airborne LiDAR and k-Nearest Neighbor Imputation Anais da ABC (AABC) SILVA,CARLOS ALBERTO; KLAUBERG,CARINE; HUDAK,ANDREW T.; VIERLING,LEE A.; LIESENBERG,VERALDO; BERNETT,LUIZ G.; SCHERAIBER,CLEWERSON F.; SCHOENINGER,EMERSON R.. ABSTRACT Accurate forest inventory is of great economic importance to optimize the entire supply chain management in pulp and paper companies. The aim of this study was to estimate stand dominate and mean heights (HD and HM) and tree density (TD) of Pinus taeda plantations located in South Brazil using in-situ measurements, airborne Light Detection and Ranging (LiDAR) data and the non- k-nearest neighbor (k-NN) imputation. Forest inventory attributes and LiDAR derived metrics were calculated at 53 regular sample plots and we used imputation models to retrieve the forest attributes at plot and landscape-levels. The best LiDAR-derived metrics to predict HD, HM and TD were H99TH, HSD, SKE and HMIN. The Imputation model using the selected metrics was more... Tipo: Info:eu-repo/semantics/article Palavras-chave: Forest inventory; LiDAR metrics; K-NN Imputation; Remote Sensing. Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652018000100295 Estudo do Comportamento Espectral das Principais Classes de Cobertura d Solo do Vale do Paraíba e Relação com o Índice de Área Foliar Ciências Agrárias Batista, Getulio. Proposta de pesquisa para suporte à Iniciação Científica. Tipo: Article Palavras-chave: Sensoriamento Remoto; Remote Sensing; Espectroscopia; Comportamento espectral; Radiometria de campo; Radiometer. Ano: 2006 URL: http://hdl.handle.net/2315/45 Fusion of High Spatial Resolution with Extended Spectral Resolution Bands of CBERS Satellite Sensors for Land Use Survey Ciências Agrárias Batista, Getulio Teixeira; Catelani, Celso de Souza. Trabalho aceito para apresentação no 2nd. International Conference on Computing, Communication and Control Technologies: CCCT'04 Tipo: Article Palavras-chave: Image Analysis; Remote Sensing. Ano: 2004 URL: http://hdl.handle.net/2315/147 High spatial resolution land use and land cover mapping of the Brazilian Legal Amazon in 2008 using Landsat-5/TM and MODIS data Acta Amazonica ALMEIDA,Cláudio Aparecido de; COUTINHO,Alexandre Camargo; ESQUERDO,Júlio César Dalla Mora; ADAMI,Marcos; VENTURIERI,Adriano; DINIZ,Cesar Guerreiro; DESSAY,Nadine; DURIEUX,Laurent; GOMES,Alessandra Rodrigues. ABSTRACT Understanding spatial patterns of land use and land cover is essential for studies addressing biodiversity, climate change and environmental modeling as well as for the design and monitoring of land use policies. The aim of this study was to create a detailed map of land use land cover of the deforested areas of the Brazilian Legal Amazon up to 2008. Deforestation data from and uses were mapped with Landsat-5/TM images analysed with techniques, such as linear spectral mixture model, threshold slicing and visual interpretation, aided by temporal information extracted from NDVI MODIS time series. The result is a high spatial resolution of land use and land cover map of the entire Brazilian Legal Amazon for the year 2008 and corresponding calculation... Tipo: Info:eu-repo/semantics/article Palavras-chave: Remote Sensing; Tropical Deforestation; TerraClass; Image Processing. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0044-59672016000300291 Hyperspectral remote sensing as an alternative to estimate soil attributes Rev. Ciênc. Agron. Demattê,José A. M.; Alves,Marcelo Rodrigo; Gallo,Bruna Cristina; Fongaro,Caio T.; Souza,Arnaldo Barros e; Romero,Danilo Jefferson; Sato,Marcus Vinicius. Minimizing environmental impacts and increasing crop productivity depend mainly on the knowledge of chemical, physical and mineralogical characteristics of the soil attributes. However, traditional methods are timeconsuming and costly. The objective of this study was to determine and validate a method to quantify soil attributes using UV-Vis-NIR Spectroscopy as an alternative to conventional methods of soil analyses. The work comprised two main phases: (1) creation and calibration of statistical models to determine the soil attributes derived from spectral data extracted from soil samples collected in area 1, (2) validation of statistical models in area 2 and correlations between the estimated and observed values (conventional method) for each soil... Tipo: Info:eu-repo/semantics/article Palavras-chave: Reflectance; Soil analysis; Remote Sensing. Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1806-66902015000200223 Modeling and mapping basal area of Pinus taeda L. plantation using airborne LiDAR data Anais da ABC (AABC) SILVA,CARLOS A.; KLAUBERG,CARINE; HUDAK,ANDREW T.; VIERLING,LEE A.; FENNEMA,SCOTT J.; CORTE,ANA PAULA D.. ABSTRACT Basal area (BA) is a good predictor of timber stand volume and forest growth. This study developed predictive models using field and airborne LiDAR (Light Detection and Ranging) data for estimation of basal area in Pinus taeda plantation in south Brazil. In the field, BA was collected from conventional forest inventory plots. Multiple linear regression models for predicting BA from LiDAR-derived metrics were developed and evaluated for predictive power and parsimony. The best model to predict BA from a family of six models was selected based on corrected Akaike Information Criterion (AICc) and assessed by the adjusted coefficient of determination (adj. R²) and root mean square error (RMSE). The best model revealed an adj. R²=0.93 and RMSE=7.74%.... Tipo: Info:eu-repo/semantics/article Palavras-chave: Forest Inventory; LiDAR metrics; Multiple Linear Regression; Remote Sensing. Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017000401895 Novel Image Classification technique using Particle Filter Framework optimised by Multikernel Sparse Representation BABT N. R,Bhuvaneswari; V.G,Sivakumar. ABSTRACT The robustness and speed of image classification is still a challenging task in satellite image processing. This paper introduces a novel image classification technique that uses the particle filter framework (PFF)-based optimisation technique for satellite image classification. The framework uses a template-matching algorithm, comprising fast marching algorithm (FMA) and level set method (LSM)-based segmentation which assists in creating the initial templates for comparison with other test images. The created templates are trained and used as inputs for the optimisation. The optimisation technique used in this proposed work is multikernel sparse representation (MKSR). The combined execution of FMA, LSM, PFF and MKSR approaches has resulted in a... Tipo: Info:eu-repo/semantics/article Palavras-chave: Multikernel Sparse Representation; Image Classification; Sparse Learning; Level Set Method; Particle Filter Framework; Remote Sensing. Ano: 2016 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-89132016000300606 Uso de técnicas de la información para estimar parámetros estratégicos en la operación de los distritos de riego. Colegio de Postgraduados Caballero Luis, Josafat. Mediante el presente trabajo se propone el uso de técnicas de la información para estimar parámetros estratégicos en la operación de los distritos de riego a través del uso de sistemas de información geográfica y técnicas de percepción remota, debido a que la CONAGUA cada vez dispone de poco personal técnico y requiere la toma de decisiones oportunas en la administración del agua disponible. Para esto, se analizaron algunos estudios de casos en donde éstos sistemas ya fueron aplicados en ciertos distritos de riego como el manejo y actualización del padrón de usuarios, el inventario de infraestructura, la caracterización de suelos agrícolas, la estimación de superficie sembrada, de la producción agrícola y de la evapotranspiración. Los avances obtenidos... Palavras-chave: Distritos de Riego; Sistema de Información Geográfica; Percepción Remota; Agricultura de Precisión; Indices de Vegetación; Irrigation Districts; Geographic Information System; Remote Sensing; Precision Agriculture; Vegetation Index; Hidrociencias; Maestría Tecnológica. Ano: 2013 URL: http://hdl.handle.net/10521/2057 Registros recuperados: 11 Primeira ... 1 ... 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