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| Registros recuperados: 19 | |
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| Perea,Alberto Jesús; Meroño,José Emilio; Aguilera,María Jesús. |
| The objective of this paper was the development of a methodology for the classification of digital aerial images, which, with the aid of object-based classification and the Normalized Difference Vegetation Index (NDVI), can quantify agricultural areas, by using algorithms of expert classification, with the aim of improving the final results of thematic classifications. QuickBird satellite images and data of 2532 plots in Hinojosa del Duque, Spain, were used to validate the different classifications, obtaining an overall classification accuracy of 91.9% and an excellent Kappa statistic (87.6%) for the algorithm of expert classification. |
| Tipo: Journal article |
Palavras-chave: Expert classification; Vegetation index; Land cover; Object-based classification. |
| Ano: 2009 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392009000300013 |
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| Damian,Júnior Melo; Pias,Osmar Henrique de Castro; Cherubin,Maurício Roberto; Fonseca,Alencar Zachi da; Fornari,Ezequiel Zibetti; Santi,Antônio Luis. |
| ABSTRACT: The utilization of Normalized Difference Vegetation Index (NDVI) data obtained through satellite images can technically improve the process of delimiting management zones (MZ) for annual crops, resulting in socio-economic and environmental benefits. The aim of this study was to compare delimited MZ, using crop productivity data, with delimited MZ using the NDVI obtained from satellite images in areas under a no-tillage system. The study was carried out in three areas located in the state of Rio Grande do Sul, Brazil. Three crop productivity maps, from 2009 to 2015, were used for each area, whereby the NDVI was calculated for each crop productivity map using images from the Landsat series of satellites. Descriptive and geostatistical analysis were... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Fuzzy c-means clustering; Productivity data; Aerial images; Vegetation index. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162020000100101 |
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| Carvalho,Daniel C. De; Pessoa,Mayara M. De L.; Pereira,Marcos G.; Delgado,Rafael C.. |
| ABSTRACT This study aimed to assess vegetal cover evolution on a river island within the Ecological Station of (EEP), by remote sensing. For this purpose, Normalized Difference Vegetation Indexes were generated for Landsat 1 (1973) and Landsat 5 (1984, 1990, 2000 and 2011) images. Five landscape units were identified in the field: bare soil, Rough savanna, Typical savanna, Forested savanna and Evergreen dry woods. Only Forested savanna and Evergreen dry woods showed poor spectral splitting, being thus considered as a forestry complex. Changes throughout time have occurred in all units, with decreasing in bare soil areas (-2.56 ha year−1), Rough savanna (-0.66 ha year−1) and Typical savanna (-0.94 ha year−1) and with an increase in the Forested savanna... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Remote sensing; Environmental monitoring; Vegetation index. |
| Ano: 2016 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162016000601186 |
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| Ide,Andre Keiiti; Baptista,Gustavo Macedo de Mello. |
| Abstract: The objective of this work was to evaluate the applicability of time series of the enhanced vegetation index (EVI), from the moderate resolution imaging spectroradiometer (Modis), in the mapping of irrigated areas in the Northeastern region of Brazil. Annual time series from 2006 to 2015 were classified with the iterative self-organizing data analysis technique (Isodata) algorithm, generating a binary map of irrigated and nonirrigated areas for each year. In the Sertão region, the classification showed an average kappa coefficient of 0.66, underestimating the irrigated area by 7.6%, compared with data of the 2006 agricultural census. In regions more humid than the Sertão, such as Agreste and Zona da Mata Nordestina, the methodology showed... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Agricultural and environmental planning; EVI; Remote sensing; Semiarid; Vegetation index; Water resources management. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2018000100080 |
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| Carvalho,Daniel Fonseca de; Durigon,Valdemir Lucio; Antunes,Mauro Antonio Homem; Almeida,Wilk Sampaio de; Oliveira,Paulo Tarso Sanches de. |
| The objective of this work was to evaluate the seasonal variation of soil cover and rainfall erosivity, and their influences on the revised universal soil loss equation (Rusle), in order to estimate watershed soil losses in a temporal scale. Twenty-two TM Landsat 5 images from 1986 to 2009 were used to estimate soil use and management factor (C factor). A corresponding rainfall erosivity factor (R factor) was considered for each image, and the other factors were obtained using the standard Rusle method. Estimated soil losses were grouped into classes and ranged from 0.13 Mg ha-1 on May 24, 2009 (dry season) to 62.0 Mg ha-1 on March 11, 2007 (rainy season). In these dates, maximum losses in the watershed were 2.2 and 781.5 Mg ha-1 , respectively. Mean... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: C factor; Rainfall erosivity; Remote sensing; Soil loss; Vegetation index. |
| Ano: 2014 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2014000300215 |
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| Cattani,Carlos E. V.; Garcia,Murilo R.; Mercante,Erivelto; Johann,Jerry A.; Correa,Marcus M.; Oldoni,Lucas V.. |
| ABSTRACT Remote sensing applications in agriculture are presented as a very promising reality, but research is still needed for the correct use of spectral data. The objective of this study was to evaluate the spectral-temporal patterns of eleven wheat cultivars (Triticum aestivum L.). The experiment was conducted in Cascavel, PR, in the year 2014. With the help of the GreenSeeker and FieldSpec 4 terrestrial sensors, spectral signatures were determined and the temporal profiles of the Normalized Difference Vegetation Index (NDVI) were created. Statistical differences between wheat cultivars were analysed using analysis of variance (ANOVA) and Scott-Knott test. Grain yields obtained with INSEY (In-Season Estimate of Yield) factors were correlated. NDVI... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Vegetation index; Remote sensing; Growth stage. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017001100769 |
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| Espinosa Espinosa, José Luis. |
| La tarea de los sistemas de asesoramiento de riego suele ser costosa en recursos humanos y materiales por la necesidad de hacer un seguimiento intensivo en campo, en áreas extensas y se suele enfrentar al reto de transferir la información al usuario, agricultor o técnico, en la vía adecuada y en el momento oportuno. Asimismo, las nuevas tecnologías de observación de la tierra, ha contribuido a que millones de hectáreas sean monitoreadas mediante sensores a bordo de satélites siendo más eficaz el seguimiento en campo, ya que proporcionan imágenes de la superficie terrestre. De igual forma las tecnologías de la información, el internet y la telefonía móvil, permiten que la información generada por los sistemas de asesoramiento de riego, incluida la imagen... |
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Palavras-chave: Sensores remotos; Imágenes de satélite; Indice de vegetación; NDVI; Visor web; Remote sensing; Satellite imagery; Vegetation index; Web viewer; Hidrociencias; Maestría. |
| Ano: 2013 |
URL: http://hdl.handle.net/10521/2135 |
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| Beneduzzi,Humberto M.; Souza,Eduardo G.; Bazzi,Claudio L.; Schenatto,Kelyn. |
| ABSTRACT: Optimization of N management is one of the great challenges to be overcome in grain production, as it is directly related to productivity and can also cause environmental damage. Precision agriculture aims to solve this problem by applying nitrogen fertilizer at varying rates. Reflectance sensors are instruments capable of estimating N needs in various crops, including grain crops. However, it is not clear how these sensors perform under varying solar radiation and cloud cover, due to a lack of research on their temporal variability. Thus, this study examined the temporal variability of the NDVI (normalized difference vegetation index), as measured by an active reflectance sensor, in both soybean and wheat crops. The NDVI data were collected... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Precision agriculture; Remote sensing; Vegetation index; NDVI. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162017000400771 |
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| Registros recuperados: 19 | |
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